# Patent

## Title
Neurological prosthesis

## Abstract

A method improving or restoring neural function in a mammalian subject in need thereof, the method including: using an input receiver to record an input signal generated by a first set of nerve cells; using an a encoder unit including a set of encoders to generate a set of coded outputs in response to the input signal; using the encoded outputs to drive an output generator; and using an output generator to activate a second set of nerve cells wherein the second set of nerve cells is separated from the first set of nerve cells by impaired set of signaling cells. In some embodiments, the second set of nerve cells produces a response that is substantially the same as the response in an unimpaired subject.

## Background
CROSS REFERENCE TO RELATED APPLICATION
This application claims the benefit under 35 U.S.C. §119(e) of U.S. Provisional Application No. 61/381,646 (filed on Sep. 10, 2010). The subject matter of this application is also related to U.S. Provisional Application Nos. 61/378,793 (filed on Aug. 31, 2010), 61/308,681 (filed on Feb. 26, 2010), 61/359,188 (filed on Jun. 28, 2010), 61/378,793 (filed on Aug. 31, 2010), and 61/382,280 (filed on Sep. 13, 2010), and International Patent Application Nos. PCT/US2011/26526 (filed Feb. 28, 2011) and PCT/US2011/026525 (filed Feb. 28, 2011). The contents of each of the forgoing applications are incorporated by reference in their entirety.


STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
This invention was made with U.S. Government support under R01 EY12978 from National Institute of Health (NIH). The U.S. Government has certain rights in the invention.


FIELD
The present invention relates to methods and devices for restoring or improving function, such as nerve function, in a subject. In particular, the present invention relates to methods and devices for restoring or improving motor, auditory, or other function using a set of encoders that closely mimic the input/output transformation of nerve cells to produce near-normal, normal or even super-normal function in a subject.
BACKGROUND
A number of neurological disorders including, e.g., motor neuron disorders (e.g., damage from stroke, injury, diseases such as ALS and MS), psychiatric disorders, memory disorders, and auditory disorders involve thempairment of a set of nerve cells. In many cases, the malfunction of these cells prevents or degrades communication between healthy sets of cells.
Various neural prosthetics have been developed to bypass malfunctioning cells to restore communication between the healthy cells. However, in typical cases, the bypassed impaired cells do not simply operate as signal pass-throughs, but instead provide processing of signals. In cases where a neural prosthetic does not accurately mimic the processing of the bypassed cells, the subject will exhibit degraded function in comparison to an unimpaired subject.
Thus, there exists a need to develop a neural prosthesis that bypasses or “jumps” impaired signaling cells, while providing a close proxy of the processing of the bypassed impaired signaling cells (i.e., such that the input to output transfer function of the prosthesis is well matched to that which would have been exhibited by the bypassed signaling cells in an unimpaired subject).
SUMMARY
As described in PCT/US2011/026525 (filed Feb. 28, 2011) (henceforth the “Retinal Application”), the applicants have developed a method and device for restoring or improving vision, increasing visual acuity, or treating blindness or visual impairment, or activating retinal cells. The method includes capturing a stimulus, encoding the stimulus, transforming the code into transducer instructions at an interface, and transducing the instructions to retinal cells. The device includes a way to capture a stimulus, a processing device executing a set of encoders, an interface, and a set of transducers, where each transducer targets a single cell or a small number of cells; the set of transducers is referred to as a high resolution transducer. In one embodiment, each encoder executes a preprocessing step, a spatiotemporal transforming step as well as an output-generating step. The method can be used for a retinal prosthesis to generate representations for a broad range of stimuli, including artificial and natural stimuli.
The stimulus is converted or transformed into a proxy of normal retinal output, that is, a form of output the brain can readily interpret and make use of as a representation of an image. The conversion occurs on about the same time scale as that carried out by the normal or near-normal retina, i.e., the initial retinal ganglion cell response to a stimulus occurs in a time interval ranging from about 5-300 ms. The methods and devices described in the Retinal Application can help restore near-normal to normal vision, or can improve vision, including both grayscale vision and color vision, in a patient or affected mammal with any type of retinal degenerative disease where retinal ganglion cells (which may also be referred to herein as “ganglion cells”) remain intact.
The retina prosthesis, like the normal retina, is an image processor—it extracts essential information from the stimuli it receives, and reformats the information into patterns of action potentials the brain can understand. The patterns of action potentials produced by the normal retinal are in what is referred to as the retina's code or the ganglion cell's code. The retina prosthesis converts visual stimuli into this same code, or a close proxy of it, so that the damaged or degenerated retina can produce normal or near-normal output. Because the retina prosthesis uses the same code as the normal retina or a close proxy of it, the firing patterns of the ganglion cells in the damaged or degenerated retina, that is, their patterns of action potentials are the same, or substantially similar, to those produced by normal ganglion cells. A subject treated with such devices will have visual recognition ability closely matching the ability of a normal or near-normal subject.
The applicants have realized that this approach may be applied more generally to provide methods and devices for restoring or improving function, such as neurological, motor, or auditory function in a human patient or other mammalian subject. As in the retinal case, a device including a processor which implements a set of encoders is provided which receives an input signal and generates an output signal, such that the input/output transformation operates as a close proxy of the signal processing that would occur in a normal patient.
In some embodiments, the input signal comes from a first set of healthy cells (e.g., supplementary motor area neurons), and the output signal drives a response in second set of healthy cells (e.g., spinal motor neurons) that are separated from the first set by an impaired set of signaling cells (e.g., damaged primary motor cortex neurons). The encoders provide a close proxy of the processing that would occur in the set of signaling cells in an unimpaired subject, allowing the impaired cells to be bypassed or jumped while reducing or eliminating degradation in function.
In some embodiments, the input signal is an external stimulus (e.g., sound waves), which are detected by the device (e.g., using a microphone). The input signal is processed using a set of encoders to generate a coded output used to drive healthy cells (e.g., spiral ganglion cells in the inner ear) which are associated with an impaired set of signaling cells (e.g., cochlear hair cells used to detect sound in the inner ear). The encoders provide a close proxy of the processing that would occur in the set of signaling cells in an unimpaired subject, allowing the impaired cells to be bypassed or jumped over, reducing or eliminating degradation in function.
To ensure that the encoders provide a close proxy of the processing that would occur in the signaling cells of a normal subject, a strategy may be employed of using experimental data (e.g., collected in vivo or in vitro from unimpaired cells) to generate a model of the signaling cells' processing. Accordingly, a data-driven phenomenological model is provided, directly analogous to those developed to model retinal processing in the Retinal Application.
Because this approach leverages experimental data, the generated encoders can accurately simulate the signaling cell processing, without requiring a detailed abstract understanding of the signaling cells' underlying processing schemes. For example, it is believed that retinal processing in primates and humans highlights features in the visual stimulus useful for pattern recognition tasks (e.g., facial recognition) while de-emphasizing or eliminating other features (e.g., redundant information or noise) to allow for efficient processing in the brain. Similar processing occurs in many other types of cells or neural networks (e.g., spinal motor neurons or motor neuron networks or spiral ganglion cells in the ear, etc.). As of yet, there is no complete abstract understanding of the details of these natural processing schemes, which developed as the result natural selection over the course of eons. However, despite this lack of abstract understanding, the devices and techniques described herein can capture the benefit of this processing, by accurately mimicking the response of unimpaired cells
A method improving or restoring neural function in a mammalian subject in need thereof is disclosed, the method including: using an input receiver to record an input signal generated by a first set of nerve cells; using an a encoder unit including a set of encoders to generate a set of coded outputs in response to the input signal; using the encoded outputs to drive an output generator; and using an output generator to activate a second set of nerve cells where the second set of nerve cells is separated from the first set of nerve cells by impaired set of signaling cells; where the second set of nerve cells produces a response that is substantially the same as the response in an unimpaired subject.
In some embodiments, the first set of nerve cells includes supplementary motor area neurons; the second set of nerve cells includes spinal motor neurons; and the impaired set of signaling cells includes primary motor cortex neurons.
Some embodiments include generating the input signal as a time resolved series of values {right arrow over (a)} corresponding to the pattern of neural activity generated in the first set of nerve cells; and transforming the values {right arrow over (a)} to a time resolved series of output values {right arrow over (c)} by applying a transformation.
In some embodiments, {right arrow over (c)} is a vector valued function, where each element of the vector is a value corresponding to a firing rate of a single cell or small group of cells from the second set of nerve cells.
In some embodiments, {right arrow over (c)} is a vector valued function, where each element of the vector is a value corresponding to the total firing rate of second set of nerve cells.
In some embodiments, {right arrow over (c)} is a vector valued function, where each element of the vector is a value corresponding to the total firing rate of a respective subpopulation of the second set of nerve cells.
In some embodiments, the second set of nerve cells includes motor neurons, and each subpopulation innervates a different respective muscle.
In some embodiments, the transformation includes: a set of spatiotemporal linear filters; and a nonlinear function.
In some embodiments, the transformation is characterized by a set of parameters; and where the set of parameters corresponds to a result of fitting the transformation to experimental data obtained by: exposing an unimpaired subject to a broad range of reference stimuli; recording a first response in the unimpaired subject corresponding to the first set of nerve cells; recording a second response in the unimpaired subject corresponding to the second set of nerve cells.
In some embodiments, the second response includes the firing rate of individual nerve cells.
In some embodiments, the spatiotemporal filters are parameterized by a set of K weights.
In some embodiments, the method of claim 11, where K is in the range of 1-100 or any subrange thereof, e.g., in the range of 5-20.
In some embodiments, the nonlinear function is parameterized as a cubic spline function with M knots.
In some embodiments, M is in the range of 1-100 or any subrange thereof, e.g., in the range of 2-20.
In some embodiments, the spatiotemporal linear filters operate over P time bins, each having a duration Q.
In some embodiments, P is in the range of 1-100, or any subrange thereof, e.g., in the range of 5-20.
In some embodiments, Q is in the range of 10 ms-100 ms. In some embodiments, Q is in the range of 1 ms-1000 ms or any subrange thereof.
In some embodiments, the broad range of reference stimuli includes at least one chosen from the list consisting of: motion in an environment including one or more obstacles; manipulation of objects having different weights; and moving a cursor to one of several locations on a display.
In some embodiments, the second set of nerve cells are light sensitized; and the step of using an output generator to activate a second set of nerve cells includes: generating a time resolved optical signal; and directing the optical signal to the second set of nerve cells to stimulate a response.
Some embodiments include sensitizing the second set of nerve cells to light
In some embodiments, the optical signal includes a spatially and temporally modulated pattern of light.
In some embodiments, the modulated pattern of light includes an array of pixels having an average pixel size of less than 0.1 mm and a pixel modulation rate of greater than 100 Hz.
In some embodiments, the step of using an output generator to activate a second set of nerve cells includes: generating a set of electrical pulses; and directing the electrical pulses the second set of nerve cells to stimulate a response.
In another aspect, a device improving or restoring neural function in a mammalian subject in need thereof is disclosed, the device including: an input receiver configured to record an input signal generated by a first set of nerve cells; an output generator configured to activate a second set of nerve cells, where the second set of nerve cells is separated from the first set of nerve cells by an impaired set of signaling cells; and an encoder unit including a set of encoders that generate a set of coded outputs in response to the input signal, where the set of coded outputs control the output generator to activate the second set of nerve cells to produce a response to the input signal that is substantially the same as the response in an unimpaired subject.
In some embodiments, the input receiver includes an electrode.
In some embodiments, the input receiver includes an array of electrodes.
In some embodiments, the array of electrodes records the response of at least 100 neurons in the first set of neurons.
In some embodiments, the encoder unit includes at least one processor.
In some embodiments, the at least one processor includes a digital signal processor.
In some embodiments, the at least one processor includes multiple processors configured to operate in parallel.
In some embodiments, the output generator includes a set of electrodes.
In some embodiments, the output generator includes an optical signal generator. In some embodiments, the optical signal generator includes a digital light processor.
In some embodiments, the optical signal generator includes an array of light emitting diodes.
In another aspect, a non-transitory computer readable media is disclosed having computer-executable instruction including instruction for executing steps including: recording an input signal generated by a first set of nerve cells; using an a encoder unit including a set of set of encoders to generate a set of coded outputs in response to the input signal, and using the coded outputs to control an output generator to activate a second set of nerve cells where the second set of nerve cells is separated from the first set of neurons by an impaired set of signaling cells; where the second set of nerve cells produces a response to the input signal that is substantially the same as the response in an unimpaired subject.
In another embodiments, a method of improving or restoring auditory function in a mammalian subject in need thereof, is disclosed the method including: using an audio receiver to generate an input signal in response to an audio stimulus; using an a encoder unit including a set of set of encoders to generate a set of coded outputs in response to the input signal; using the encoded outputs to drive an output generator; and using an output generator to activate a set of auditory neurons, where the set of auditory neurons are associated with a set of impaired signaling cells; where the auditory neurons produce a response that is substantially the same as the response to the stimuli in an unimpaired subject.
In some embodiments, the set of auditory neurons include spiral ganglion cells; and the impaired set of signaling cells includes cochlear hair cells.
Some embodiments include generating the input signal as a time resolved series of values {right arrow over (a)} corresponding to the audio stimulus; transforming the values {right arrow over (a)} to a time resolved series of output values {right arrow over (c)} by applying a transformation.
In some embodiments, {right arrow over (c)} is a vector valued function, where each element of the vector is a value corresponding the firing rate of a single spiral ganglion cell or small group of spiral ganglion cells from the set of auditory neurons.
In some embodiments, {right arrow over (c)} is a vector valued function, where each element of the vector is a value corresponding to the total firing rate of a respective subpopulation of the auditory set of neurons.
In some embodiments, the transformation includes: a set of spatiotemporal linear filters; and a nonlinear function.
In some embodiments, the transformation is characterized by a set of parameters; and where the set of parameters corresponds to a result of fitting the transformation to experimental data obtained by: exposing an unimpaired subject to a broad range of reference audio stimuli; and recording a response in the unimpaired subject corresponding to the set of auditory neurons.
In some embodiments, the response includes the firing rate of individual neurons.
In some embodiments, the spatiotemporal filters are parameterized by a set of K weights.
In some embodiments, K is in the range of 1-100 or any subrange thereof, e.g., in the range of 5-20.
In some embodiments, the nonlinear function is parameterized as a cubic spline function with M knots.
In some embodiments, M is in the range of 1-100 or any subrange thereof, e.g., in the range of 2-20.
In some embodiments, the spatiotemporal linear filters operate over P time bins, each having a duration Q.
In some embodiments, P is in the range of 1-100 or any subrange thereof, e.g., in the range of 5-20.
In some embodiments, Q is in the range of 1 ms-1000 ms, or any subrange thereof, e.g., in the range of 10 ms-100 ms.
In some embodiments, the broad range of reference stimuli includes natural sound and white noise stimuli.
In some embodiments, the set of auditory neurons are light sensitized; and the step of using an output generator to activate the set of auditory neurons includes: generating a time resolved optical signal; and directing the optical signal to the second set of neurons to stimulate a response.
Some embodiments include sensitizing the second set of neurons to light
In some embodiments, the optical signal includes a spatially and temporally modulated pattern of light.
In some embodiments, the modulated pattern of light includes an array of pixels having an average pixel size of less than 0.1 mm and a pixel modulation rate of greater than 100 Hz.
In some embodiments, the step of using an output generator to activate the set of auditory neurons includes: generating a set of electrical pulses; and directing the electrical pulses to the set of auditory neurons to stimulate a response.
In another aspect, a device for improving or restoring auditory function in a mammalian subject in need thereof is disclosed, the device including: an audio receiver configured to generate an input signal in response to an audio stimulus; an encoder unit including a set of set of encoders configured to generate a set of coded outputs in response to the input signal; and an output generator configured to, in response to the set of coded outputs, activate a set of auditory neurons, where the set of auditory neurons are associated with a set of impaired signaling cells; where the second set of cells produces a response to a broad range of stimuli that is substantially the same as the response to the stimuli in an unimpaired subject.
In some embodiments, the input receiver includes an audio transducer configured to convert an audio signal to a digital signal.
In some embodiments, the encoder unit includes at least one processor.
In some embodiments, the at least one processor includes a digital signal processor.
In some embodiments, the at least one processor includes multiple processors configured to operate in parallel.
In some embodiments, the output generator includes a set of electrodes.
In some embodiments, the output generator includes an optical signal generator.
In some embodiments, the optical signal generator includes a light emitting diode array or a digital light processor.
In another aspect, a non-transitory computer readable media is disclosed having computer-executable instruction including instruction for executing steps including: generating an input signal in response to an audio stimulus; controlling an encoder unit including a set of set of encoders to generate a set of coded outputs in response to the input signal; and controlling an output generator to, in response to the set of coded outputs, activate a set of auditory neurons, where the set of auditory neurons are associated with a set of impaired signaling cells; where the set of coded outputs control the output generator to activate the set of auditory neurons to produce a response that is substantially the same as the response to the stimuli in an unimpaired subject.
Various embodiments may feature any of the elements, steps, devices, techniques, etc. described above, either alone or in any suitable combination.
The terms prosthetic, prosthesis, prosthetic device, and prosthesis device are used interchangeably herein.



BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1A is a schematic illustrating neural activity in a neural system, where signals from a set of cells labeled A are communicated through a set of cells labeled B to generate a response in a set of cells C.
FIG. 1B is a schematic illustrating the use of a neural prosthesis to treat impairment in the neural system of FIG. 1A.
FIG. 2 is a block diagram of a neural prosthesis.
FIG. 3 is a schematic diagram of a neural prosthesis.
FIG. 4 is a schematic diagram of a neural prosthesis featuring multiple encoders.
FIG. 5 is a functional block diagram of a processor for a neural prosthesis.
FIG. 6A is a plot of a time dependent firing rate generated by an encoder of a neural prosthesis.
FIG. 6B is a plot of a digital pulse train generated based on the time dependent firing rate shown in FIG. 6A.
FIG. 6C is a plot of the pulsed output of a neural prosthesis train generated based on the digital pulse train of FIG. 6B.
FIG. 7 is a functional block diagram of a processor featuring a parallel processing architecture.
FIG. 8A is an illustration of a neural prosthesis deployed in and on a human subject.
FIG. 8B is an x-ray snapshot of an implanted portion of the neural prosthesis of FIG. 8A.
FIG. 9 is functional block diagram of an auditory prosthesis.
FIG. 10A is a schematic of an auditory prosthesis featuring multiple output electrodes.
FIG. 10B is a schematic of an auditory prosthesis featuring multiple output light emitting diodes (LEDs).
FIG. 11A is a schematic illustration of a flexible LED array implanted in the cochlea of a subject.
FIG. 11B is a top down view of the a flexible LED array of FIG. 12A prior to implantation.



DETAILED DESCRIPTION
FIGS. 1A and 1B illustrate the operation of a neural prosthetic 100. FIG. 1A, illustrates the function of an unimpaired subject. A first set of neurons (A) sends signals to another set of neurons (B) and they, in turn, send signals to a third set (C). FIG. 1B illustrates the function in an impaired subject, e.g., where the subject has suffered a stroke that damages set B. The neural prosthetic 100, bypasses or jumps (the terms are used interchangeably herein) the impaired nerves of set B. Using experimentally derived information about the transformation implemented by the unimpaired set B in communicating signals from set A to C, one can build the device 100 such that it mimics the transformation. That is, the device 100 can produce a response in set C (e.g., a neural or nerve firing pattern) that closely mimics that which would normally occur when A sends out its signals to set C through an unimpaired set B. C can then send on normal signals to its downstream neurons, and the patient can regain normal functioning. The encoder essentially jumps over B. (If the transformation is well modeled based on experimental data, then this can be done for arbitrary signals from A). To drive the neurons in C, several techniques are possible such as driving optogenetic transducers (e.g., channelrhodopsin-2 or one of its derivatives) or electrode based stimulation, as described in greater detail below.
In some embodiments, the signal from set A may be replaced by an external stimulus. This was the case in the Retinal Application, where set B corresponded to damaged retinal cells (e.g., photoreceptors), set C corresponded to retinal ganglion cells, and the prosthesis 100 received a visual stimulus (e.g., using a camera), processed the stimulus with encoders in a way that mimicked the processing of the damaged retinal cells and circuitry (which would be analogous to B in FIG. 1B) and used a high resolution transducer to drive the retinal ganglion cells to produce a response that closely matched that produced in an unimpaired subject. A similar approach may be used for restoring or improving auditory function, as detailed below.
As noted above, in some embodiments, a data-based phenomenological approach is used in building the encoders for the prosthetic 100: In typical cases, to build the encoder, one needs to finds the transformation between the outside world (e.g., an external visual or audio stimulus) and a set of neurons or between two sets of neurons. Below are three examples.
In the case of the prosthetic device for the retina, described in the Retinal Application, the encoder mimics the transformation between visual stimuli (the outside world) and the retina's output cells—that is, it jumps over the damaged sensory cells in the retina (the photoreceptors) and interacts directly with the healthy cells (e.g., ganglion cells), the retina's output cells, so that normal signals can be sent to the brain.
In the case of an auditory prosthetic, the encoder mimics the transformation between auditory stimuli (the outside world) and the cells in the auditory nerve—that is, it bypasses the damaged sensory cells (the hair cells of the inner ear) and interacts directly with the auditory nerve cells, the spiral ganglion cells, so normal sound information can be sent to the brain.
In the case of a motor prosthetic (the specific embodiment given below), the encoder mimics the transformation between Supplementary Motor Area (SMA) and spinal motor neurons (SMN)—that is, it jumps over the damaged primary motor cortex (a area commonly damaged by strokes) and interacts directly with the healthy cells, the SMN (or the muscles they synapse on), so that normal muscle contractions/relaxations can be made.
This approach may be extended to a wide variety of other applications. A non limiting list of such applications is provided in Tables 2-6 found toward the end of this document.
To generate the data based model, the transformations performed by the encoders are worked out a priori (e.g., in an animal model or, using human patients, i.e., using electrode implants and electromyography (EMG)). It's worked out by causing a large variety of patterns of activity to occur in the system and recording from the healthy neurons.
For example, to develop the encoder for the visual prosthetic, recordings were made from retina's output neurons, the ganglion cells, while the retina was presented with a wide variety of stimuli: this allowed us to determine the transformation from visual stimuli to retinal ganglion cell firing spike patterns.
Likewise, in the case of the auditory prosthetic, recordings are made in the spiral ganglion cells in the presence of a wide variety of auditory stimuli (e.g., including white noise and natural noise), so the transformation between sound stimuli and the spiral ganglion cell spike patterns can be determined.
In the case of the motor prosthetic, one may use two sets of recordings: one from neurons in the SMA and one from the spinal motor neurons that correspond to them (e.g. to generate a set of encoders useful for arm prosthetics, one may record from SMA neurons that affect arm movements and from spinal motor neurons that control arm muscles), so one can obtain the transformation between the two sets of neurons (in this case, in FIG. 1B, set A would correspond to the SMA neurons that affect arm movements, and set C would correspond to the spinal motor neurons that control arm muscles).
In each of these example and other cases, visual, auditory, motor, or other, the approach is phenomenological: One parameterizes the relationship between the external stimuli and a set of neural signals or between two sets of neural signals, and one finds the parameter values using an optimization procedure, such as maximum likelihood.
In many applications, an advantage of this approach is that it has the capacity to generalize, that is, to mimic the processing of the impaired cells across a broad range of activity, because the approach uses a mathematical transformation to capture the relation between the outside world and a set of neurons or between two sets of neurons, rather than, for example, a look up table. As indicated schematically in FIG. 1B, the prosthesis 100 is designed to take activity patterns of arbitrary complexity in set A and produce the outputs that normally occur in set C as a result—that is, for most or all patterns that occur in A, the method will be able to make C produce its normal output (e.g., nerve firing patterns). This is advantageous because normal brain activity is complex and variable and cannot be accurately characterized into a small number of categories, as would be necessary for the more standard look up table approach.
Note, in some examples presented herein the prosthesis device is described as jumping or bypassing impaired cells. It is to be understood that in typical embodiments, the prosthetic does not simply reproduce the processing of specific impaired cells, but provides an accurate proxy of the input/output transformation that occurs in a normal subject which converts a given input stimulus or neural activity at A into an output at C. That is, the prosthetic not only mimics the behavior of a subset of impaired cells in B, but instead acts as a proxy for the entire signally chain (potentially including both healthy and/or impaired cells with various interactions) from A to C.
Motor Prosthesis
In one embodiment, the prosthesis 100 is employed to restore motor function in an impaired subject. Restoration of motor system function as is important for a number of reasons, including: a) damage to the motor system is the major source of disability in stroke and other neurological disease (e.g., MS, primary lateral sclerosis (a form of ALS), cancers of the nervous system), b) major features of the motor system's anatomy map on to the A to B to C scheme described above in reference to FIGS. 1A and 1B, and c) the motor system is readily accessible to the required studies in animals and for implants in humans. Thus, using the techniques described herein building a set of encoders for applications is straightforward, and the return on the effort is large—it can provide a remedy for a very broad range of disorders—that is, motor damage due to many different underlying causes can all be treated with the same set of encoders.
Normally, during voluntary movement, signals are transmitted from the Supplementary Motor Area (SMA) to Primary Motor Cortex (PMC) to Spinal Motor Neurons (SMN) to Muscle (M). The SMA corresponds to A in FIGS. 1A and 1B, the PMC and its descending fibers correspond to B, and the SMN (and their axons) correspond to C. In some embodiments, the SMN can be jumped also (i.e., included as part of B), and stimulation can go directly to muscle, which would then correspond to C.
In some cases, B is a particularly vulnerable part of the motor system because the pathway from PMC to the SMN is long—that is, the cell bodies of the neurons lie in the cortex, but their axons descend through the thalamus, brain stem, and spinal cord. Thus strokes or other damage to any area along the pathway will interrupt their signals and cause motor deficits or outright paralysis.
Referring to FIG. 2, in some embodiments, the prosthesis 100 is a device that carries out the transformation of signals from A to C that is normally carried out by interactions from A to B to C. The prosthesis 100 includes an input receiver 101 (e.g., one or more electrodes) which record an input signal generated by set of neurons in A (e.g., in response to a decision by the patient to make a movement, a motor command). A processor 102 (sometimes referred to herein as an encoder unit) processes the input signal using a set of encoders to generate a set of coded outputs. An output generator 103 (e.g. an electrode or optical device of the types described herein), in response to the coded outputs, activates the second set of neurons (neurons in C) to produce a response to the input signal, e.g., a response that is substantially the same as the response in an unimpaired subject.
In some embodiments, an encoder implemented by the prosthesis 100 operates using a model for the transformation, {right arrow over (c)}={right arrow over (f)}({right arrow over (a)}), where {right arrow over (a)} is the pattern of neural activity (expressed here as a n firing rate as a function of time) in region A, and {right arrow over (c)} is the pattern of neural activity in region C. Both {right arrow over (a)} and {right arrow over (c)} are multivariate (they represent the activity of a population of neurons), so we represent them here as vector-valued functions of time. (Note that it's not critical to understand B at a mechanistic level, just to capture its input/output relation, as in the retinal prosthetic approach described in the Retinal Application.)
Some embodiments employ a strategy adapted from those found to be effective in the retina—that is, we choose the following parametric form, and we determine the parameters of the form by optimizing a cost function separately for each output neuron (or small groups of output neurons, e.g., containing less than 2, less than 3, less than 5, less than 10, less than 20, less than 30, less than 50, or less than 100 neurons, e.g., in the range of 1-1000 neurons or any subrange thereof).
For example, for each output neuron, ci, we determine weight functions, {right arrow over (w)}i, and a nonlinearity, Ni, so that the modeled transformation

cifit=Ni({right arrow over (a)}·{right arrow over (w)})  (1)

is an optimal match to the actual transformation, ci=fi({right arrow over (a)}), measured experimentally using the techniques described herein. Ni is a pointwise nonlinearity, i.e., a function y=Ni(x), where x and y are both real-valued quantities (in the case of the retinal encoders, Ni was a cubic spline with 7 knots, but any other suitable number may be used), and {right arrow over (w)} is a vector of weights, specific to the output neuron i. {right arrow over (w)}i consists of an array of quantities wi,j(t), where i labels a neuron in the population C, j labels a neuron in the population A, and t is time. The ith component of the dot product {right arrow over (a)} is calculated as follows:

Σj,taj(t)wi,j(t)

As was the case for the encoders for the retina, the optimization is performed to maximize the expected log likelihood over the entire output population, namely,





  L
  =
  
    〈
    
      
        ∑
        i
      
      ⁢
      
        ll
        ⁡
        
          (
          
            
              c
              i
              fit
            
            ,
            
              a
              →
            
          
          )
        
      
    
    〉
  




ll(cifit, {right arrow over (a)}) denotes the log likelihood that cifit accounts for the observed activity of the ith neuron in C, when {right arrow over (a)} is the pattern of neural activity in region A, and the brackets denote an average over all patterns of activity produced in A. This likelihood is calculated from Poisson statistics based on the model firing rates (i.e., cifit).

The parametric form in eq. 1 builds on what we used for the retinal transformation: the weights {right arrow over (w)}i, i.e., the arrays wi,j(t) correspond to a set of spatiotemporal linear filters, because the subscripts i and j correspond to the positions of the neurons in C and A, respectively, and Ni is an adjustable nonlinearity.
This overall strategy has several advantages—the linear-nonlinear cascade (LNC) can be used as a universal building block for any transformation (Cybenko, 1989), it is a reasonable caricature of the input/output transformation carried out by single neurons (or small groups of neurons), and there are optimization techniques that work well with complex, natural inputs, such as are present in area A. In the retina, the inputs were white noise and complex natural scenes. In the motor case, the inputs are the activity patterns that occur in A under freely-moving behavior.
Constructing Encoders from Experimental Motor Activity Data
In some embodiments, the encoders implemented by the processor 102 are constructed from data collected in two locations: the SMA and the targeted muscles. Briefly, e.g., one may implant an array of extracellular electrodes in SMA (e.g., as described in Hochberg et al, 2006). This allows one to obtain firing patterns from one or more SMA neurons (e.g. in the range of 1-10,000 neurons, or any subrange thereof). At the same time, one may apply surface electrodes to the targeted muscles to obtain electromyography signals (EMGs), as mentioned above (see, e.g., Cescon et al, 2006), as this allows us to obtain the array of activity patterns, ci.
Note, in various embodiments, one can use the EMG from each muscle to determine the activity pattern in at least two ways: the EMG can be processed to count spikes (to obtain a total firing rate), or it can be rectified and low pass filtered. In many applications, the first approach is the simplest and corresponds directly to the population firing rate, but there are practical advantages to using the second. Specifically, the rectified, low pass filtered signal will be dominated by the larger motor units in the population, and since larger motor unit produce more force by the muscle, this low pass filtered signal correlates more closely with the force command, and, therefore, is considered the more relevant quantity when aiming to control force.
Note that for a given ci, some SMA neurons may not be relevant for its control, and the model described herein accounts for this (the weights of these neurons will be zero or negligible). This is analogous to the situation with ganglion cells in the retina, where some regions of an image (some pixels) are not relevant for a given ganglion cell's control, and these pixels are given negligible weights.
To generate generalizable encoders, one adapt the strategy as was used for generating the retinal encoders: one may provoke the system with a broad range of stimuli. In the case of the retinal encoders, we presented the retinas from normal subjects with two classes of stimuli-artificial (white noise) and natural scenes—and recorded ganglion cell responses. We then modeled the transformation from stimulus to response. The “training” stimuli (the white noise and natural scenes) were broad enough to produce a general model, one that was effective on any stimulus. In other words, given the training stimuli, we obtained a model that faithfully reproduced ganglion cell responses to essentially any stimuli (stimuli of arbitrary complexity).
In the case of the motor system, one may adapt the same approach. The normal subject (e.g., a human, a non-human primate, a mouse, etc.) carries out a variety of artificial and natural movements, such as walking on a wide variety of different and irregular terrains and grades, and manipulating objects of different masses, and we record responses from SMA and from the muscles (e.g., using the surface electrode EMG recordings). The irregular terrains and unpredictable loads are an example of a motor equivalent of white noise, and the movements on naturally changing terrain with predictable loads are an example of a motor equivalent of natural scenes. In typical applications, the two together are the key elements for obtaining generalizable encoders. In various embodiments, other suitable activities may be used.
Using the experimental the data sets generated in the previous step, one may model the transformation between SMA recordings and EMG recordings using eq. 1. This gives a set of encoders, e.g., one for each muscle.
An alternative strategy to the one described above is to treat ci as the total firing rate of a subpopulation of neurons, rather than a single neuron. This makes sense in the case of muscle activation because each muscle is activated by a subpopulation of neurons, rather than a single neuron, and the relevant variable for the subpopulation is total firing rate (at each moment in time). This firing rate can be obtained from the branch of the peripheral nerve that innervates the muscle. Experimentally, the firing rate can be measured noninvasively using surface electrodes that are placed on the skin over the muscle; the surface electrodes record an electromyography signal (EMG), from which the firing rate of the branch can be measured. (The EMG basically a surrogate for the total firing rate in the peripheral nerve branch that innervates the muscle.)
In this alternate strategy, each subpopulation ci corresponds to the population that innervates a different muscle. Thus, the transformation modeled is the transformation from the activity is SMA to {right arrow over (c)}, the pattern of activity in the array of subpopulations.
Note that despite the apparent challenges of providing a transformation that can cover the jump from supplementary motor area to spinal motor neurons (or muscle), experimental results obtained in the case of retinal prosthetic techniques indicate that these challenges can be readily overcome with the techniques described herein. In the case of the retinal prosthesis, the transformation jumped at least two synapses and captured the output almost exactly (for both mouse and primate subjects), as shown in the Retinal Application. Specifically, the transformation was from image to ganglion cell output which required jumping all the operations from photoreceptors to bipolar cells to ganglion cells, including the lateral actions of the horizontal cells and the many types of amacrine cells. The jump in the motor system would be, e.g., Supplementary Motor Layer 5→Motor Layer 4→Motor Layer 2/3→Motor Layer 5→spinal motoneuron or muscle. A second related point is that the approach might appear to be challenging due to the apparent high dimensionality in the motor context—that is, the motor cortex is signaling activity for movements related to many extremities—e.g., for the legs, it's covering the hips, knees, ankles, feet, toes, etc. But the dimensionality is not as high as it seems because we treat the cells as independent, a reasonable approximation as shown by Lee et al., 1998, Variability and Correlated Noise in the Discharge of Neurons in Motor and Parietal Areas of the Primate Cortex J. Neurosci, 18:1161; Averback and Lee (2006) Effects of Noise Correlations on Information Encoding and Decoding, J Neurophysiol 95: 3633-3644, and because many (or all) transformations are carried out locally—that is, the transformation required for knee movements are laterally displaced in the tissue from those involved in ankle movements, etc, just as they are in the retina. (In the retina, transformations for different parts of visual space are carried out locally, and the transformations can be carried out very effectively assuming conditional independence among the cells. For example, in some typical cases, each location in visual space is handled by about 10-30 cells—thus one doesn't have to perform an optimization over thousands or even hundreds of neurons to obtain a good representation. Comparison of optimizations using large populations with those using local populations pieced together as independent groups indicates that local optimization provides satisfactory results.
It should be noted that the number of degrees of freedom for a movement is far, far less than in an image, and the motor system is much more redundant. For example, in some typical situations: there are about 2×10^6 optic nerve fibers (including both eyes), but roughly about 1/10 that number of descending motor neurons (roughly 10^4 per spinal segment, 30 spinal segments.) And on a per-cell basis, in typical cases, the motor system is also more redundant: there are about 1000, at least, motor neurons per muscle, even though only one time series (the force generated by that muscle) must be specified. In some cases, for a complete comparison one needs to compare contrast sensitivity and bandwidth for vision, with motor control precision and bandwidth, but in typical case these are comparable as well (1 part in 300 for visual contrast sensitivity, motor control is, in many cases, not finer than that; e.g., corresponding to a  ̃30-60 Hz bandwidth for both vision and motor.)
The greater redundancy of the motor system is also indicated by clinical and electromyographic results showing that about an 80% loss of motor neurons is typically required to have a clinical (functional) motor deficit.
Exemplary Implementation of Motor Prosthetic
Referring again to FIG. 2, the motor prosthetic 100, may incorporate encoders built using the techniques described here, e.g., implemented by the processor 102. The encoders are used in conjunction with an input receiver 101 and an output generator 103.
As described herein, in various embodiments, the strategy is to first develop encoders that capture the transformation from SMA activity to nerve branch activity (for arbitrary activity patterns), and, second, to use these encoders as an interface between SMA and the muscles (in patients in which the connections have been severed or otherwise impaired (anywhere along the pathway from SMA to muscle).
In some embodiments, what the encoders do is jump over the damaged area (bridge the gap) in real time or near real time; the muscle receives the signals or a close proxy of the signals it would normally receive—but it receives them through the device instead of the normal biological circuitry. Because the encoders mimic the normal transformations from SMA all the way down to the branches of the nerves that directly command the muscle, they can restore normal or near-normal movements.
Referring to FIG. 3, in some embodiments the input receiver 101 includes a plurality of electrodes 301 embedded in the SMA (although three electrodes are shown, any suitable number may be used).
For example, in some embodiments, electrodes may be implanted in human SMA using techniques of the type described in Hochberg et al, 2006: Action potentials (e.g., of individual neurons or small groups of neurons) may be recorded, e.g., using a 10×10 array of silicon microelectrodes (e.g., of the type known in the art as a Utah array). In one embodiment, electrodes 1 mm in length protrude from a 4 mm×4 mm platform. Signals from the electrodes then pass through a titanium percutaneous connector to reach the outside environment. The connector is then connected to a recording system, which carries out amplification and unit identification on the signals from the electrodes, e.g., using the techniques described in Chestek et al, 2009. Note that in some embodiments, one may use single unit (e.g., single cell) activity as the relevant quantity in determining SMA activity. Additional or alternatively local field potential or multi-unit activity as recorded by each electrode in the array could play this role.
The measured SMA activity signals are then fed into the processor 102 that performs the operations of the encoders. In some embodiments, the electrodes and a battery pack are positioned subcutaneously, as in deep brain stimulation (DBS) methods familiar in the art, e.g., as used for Parkinson's patients. For this, a battery pack to drive the recording system is put in subcutaneously in the anterior chest wall with leads tunneled up to a site in the scalp to supply power to the recording system. An example of such a system is described in greater detail below.
The output of the encoders is then sent to muscle via the output generator 103. As shown, the generator includes an array of output electrodes 302. Again, although three output electrodes are shown, any number may be used. In various embodiments, and suitable technique for stimulating the muscle may be used. In some embodiments, the generator may be implemented using the techniques described in Moritz et al, 2008 and/or Guiraud et al, 2006.
For example, in some embodiments, each encoder output, determines the amplitude of the current pulse during a given time bin. In some embodiments, the time bins are typically 20 ms, following standard practice for stimulating muscles at 50 Hz, however, any suitable time bin duration may be used. In some embodiments, the maximum current (peak of the current pulse) will follow standard practice (i.e., about 10 mA), however, any suitable value may be used.
In some embodiments, after device implantation, the encoder must be optimized for the specific patient. For example, in the case of encoders used in prosthetics for humans, but based on experimental data from non-human primate subjects (e.g., monkeys) the optimization makes the necessary correction, e.g., it takes into account the fact that the encoder was determined for monkey, and the SMA of a monkey and a human are not the same size. Tuning may be accomplished in software in the encoder. In some embodiments, one may add a set of additional parameters to each encoder. These parameters determine the overall location and size of the patch of input neurons corresponding to aj, as used in eq. 1. These parameters may be determined as follows for each target muscle: the patient is asked to attempt to execute a movement that normally results in contraction, isolated as well as possible to that muscle (note that because the patient cannot move the muscle because of neurologic damage, no movement will occur, but SMA will be activated because of the intent to move). The intent activates the neurons in the portion of the SMA that will provide the correct inputs to the encoder for that muscle. The tuning parameters are systematically varied until the muscle is in fact activated. Note that this tuning process can be expedited by functional MRI prior to implantation; this will narrow down the relevant region of SMA for each muscle.
In some embodiments, after device implantation, a gain factor that converts the encoder's output to the amplitude of the current pulse may be adjusted. This will be determined by asking the patient to make isolated movements as in the previous step, and adjusting the gain to produce the patient's desired output.
Exemplary Motor Prosthesis Device
FIG. 4 is a schematic diagram of an exemplary embodiments of the motor prosthesis 100. As shown the input receiver includes nine input devices 401 (e.g., electrodes) for measuring the activity of single neurons or groups of neurons in the SMA. The input signal measured by each input device 401 is sent to a corresponding encoder in the processor 102 (each encoder is represented as a vertical column).
The output of each processor is used to control a corresponding output generator element (e.g., an electrode, digital micromirror device element, or LED, as detailed below) 403 of the output generator 103. The output of the output generator elements drive a response in corresponding muscle or SMN cells.
Execution of the encoders proceeds in a series of steps, indicated in the figure as modules 402a-c: preprocessing 402a, spatiotemporal transformation 402b, and spike generation 402c. The output of the spike generation step may be nontransiently stored in a storage module 402d in preparation for conversion to a format suitable output, which may include a burst elimination step (not shown). The output is generated by the output generator 103. Note that output may be in the form of current pulses delivered as in as in either Moritz et al, 2008 or Guiraud et al, 2006 as is standard practice for stimulating muscles. Arrows show the flow of signals from specific regions of the SMA through the modules of the encoders, through output generator 103, which drives muscles or SMN.
Input Receiver
As noted above, in some embodiments, electrodes may be implanted in human SMA using techniques of the type described in Hochberg et al, 2006: Action potentials (e.g., of individual neurons or small groups of neurons) may be recorded, e.g., using a 10×10 array of silicon microelectrodes (e.g., of the type know in the art as a Utah array). In one embodiment, electrodes 1 mm in length protrude from a 4 mm×4 mm platform. Signals from the electrodes then pass through a titanium percutaneous connector to reach the outside environment. The connector is then connected to a recording system, which carries out amplification and unit identification on the signals from the electrodes, e.g., using the techniques described in Chestek et al, 2009. Note that in some embodiments, one may use single unit (e.g., single cell) activity as the relevant quantity in determining SMA activity. Additional or alternatively local field potential or multi-unit activity as recorded by each electrode in the array could play this role.
In other embodiments, any other suitable technique for measuring SMA activity may be used.
Processor/Encoder
As noted above, in the case of a motor prosthetic (the specific embodiment given below), the encoder mimics the transformation between Supplementary Motor Area (SMA) and spinal motor neurons (SMN)—that is, it jumps over the damaged primary motor cortex (a area commonly damaged by strokes) and interacts directly with the healthy cells, the SMN (or the muscles they synapse on), so that normal muscle contractions/relaxations can be made. These encoders use an algorithm that converts input signal from the SMA into patterns of electrical signals that are the same, or substantially similar, to that would be output in a normal subject. That is, the encoders jump all cells and circuitry between the input cells (corresponding to A in FIG. 1B) and the output cells (corresponding to C in FIG. 1B).
The prosthetic can use multiple encoders which can be assembled in a parallel manner as shown, for example, in FIG. 4, where different segments of the SMA activity are run through separate encoders, which, in turn, control different, specified output generator elements 403. In this embodiment, each encoder may have parameters suited for its operation, which may, for example, take into account the location and/or type of signaling cells being emulated by the encoder or being driven by the encoder's output. The term “code” can refer to a pattern of electrical pulses that corresponds to a pattern of action potentials (also referred to as spike trains) that the output cells produces in response to a stimulus or signals from upstream neurons. The term “code” may refer to bit streams corresponding to a pattern of spike trains. Each bit may correspond to the activity of one neuron (e.g., 1 means the neuron fires; 0 means the neuron does not fire). In other embodiments the bits correspond to other information (e.g., the firing rate of a population of neurons). The code may also be a continuous wave. Any type of waveform may be encompassed by the present invention, including nonperiodic waveforms and periodic waveforms, including but not limited to, sinusoidal waveforms, square waveforms, triangle waveforms, or sawtooth waveforms.
FIG. 5 shows a functional block diagram illustrating an exemplary embodiment of an encoder in the processor 102. As shown, the processor 102 includes a number of processing modules corresponding to the encoder, each operatively connected with one, several, or all other modules. The modules may be implemented on one or more processing devices (e.g., as described in detail below). As used herein, a module is considered to be substantially implemented on a given processor if substantially all essential computations associated with the function of the module are carried out on the processor.
The processor 102 includes a preprocessing module 501 which receives an input signal from the input receiver 101 and, e.g., rescales the signal for processing. In some embodiments, the preprocessing module implements processing analogous to that described in the Retinal Application subsection entitled “Preprocessing Step.”
A spatiotemporal transformation module 502 receives the output of the preprocessing module and applies a spatiotemporal transformation (e.g., analogous to that described in the subsection of the Retinal Application entitled “Spatiotemporal Transformation Step”) to generate, e.g., a set of firing rates corresponding to those that would have been generated by the output cells, e.g., to a digital pulse generator. In some embodiments, the spatiotemporal transformation module 502 includes a spatial transformation module 502a that convolves the input signal with a spatial kernel and a temporal transformation module 502b that convolves the output of the spatial transformation module 502b with a temporal kernel to generate a temporal transformation output. In other embodiments, e.g., where the processing involves an encoder with a non-separable spatiotemporal transformation, separate spatial and temporal transformation modules are not used.
In some embodiments, the processor 102 includes a nonlinear transformation module which 503 applies a nonlinear function to the spatiotemporal transformation output to generate the set of firing rates (e.g., as described in reference to Eq. 1 above). In some embodiments the nonlinear function is implemented using a look-up table.
A digital pulse generator module 505 generates digital pulse trains corresponding to the firing rates output from one or more of the other modules and generates a digital pulse train (i.e., a series of digital pulses) corresponding to each firing rate. These pulse trains are then output to the output generator 103. In some embodiments, the digital pulse generator module 505 implements processing of the type described in the subsection of the Retinal Application entitled “Spike Generation Step.”
FIGS. 6A-6C show an example of the generation of a spike train output based on a calculated firing rate. FIG. 6A shows the time dependent firing rate calculated by the encoder. FIG. 6B shows the corresponding spike train generated by the pulse generator module 505. FIG. 6C shows the corresponding output of the output generator 103.
Referring back to FIG. 5, in some embodiments, an interpolation module 506 is used to generate data having temporal resolution higher than the measurement rate of the input receiver 101. In one embodiment, the interpolation module 506 receives output from the spatiotemporal transformation module 502, applies interpolation, and passes the results on to the nonlinear transformation module 503. In other embodiments, the interpolation may be applied after the nonlinear transformation, e.g., to directly interpolate firing rates prior to input into the digital pulse generator 506. In some embodiments, the interpolated information has a temporal resolution corresponding to at least 2, at least 5, at least 10, at least 20, or at least 50 times or more the measurement rate of input receiver 101.
In some embodiments, a burst elimination module 507 is provided which operates on the output of the digital pulse generator module 505 to reduce or eliminate the presence of bursts. In some embodiments, the burst elimination module 507 implements burst elimination processing analogous to the type described in the subsection of the Retinal Application entitled “Spike Generation Step.”
FIG. 7 shows an exemplary embodiment of the processor 102 featuring a dual processor architecture. As shown, the processor 102 includes a general purpose processor (GPP) and a digital signal processor (DSP), e.g., integrated onto a single chip. The GPP and DSP are connected to a shared memory (MEM). The processor 102 receives data from input receiver 101, e.g., via the shared memory. The processor 102 outputs data, e.g., to the output generator 103.
In one embodiment, the DSP is a Texas Instrument TMS320C64 series processor. The GPP is an ARM Cortex A8 processor, and the shared memory is an SDRAM (e.g., with 512 MB of memory). In various embodiments, other suitable processors known in the art may be used. Some embodiments may feature more than two parallel processors and more than one shared memory.
The platform shown in FIG. 7 is capable of highly-parallel computation. The processing flow may be pipelined, as described above, with the implementation of various processing steps or modules divided between the processors. In general, the more computationally expensive processing tasks (e.g., tasks involving complicated matrix operations, convolutions, interpolation etc.) may be assigned to the DSP, with less expensive tasks (e.g., scaling operations, pulse generation, process synchronization and other “housekeeping” tasks, etc.) may be assigned to the GPP.
The table below shows an exemplary assignment of the processing steps. However, in other embodiments, different assignments may be made.







TABLE 1







Dual Processor Assignments










Processing Step
Processor Assigned







Preprocessing
GPP or DSP



Spatial Transformation
DSP



Temporal Transformation 
DSP



Interpolation
DSP



Nonlinearity
GPP



Digital Pulse Generation
GPP



Burst Elimination
GPP



Output
GPP










In some embodiments, one, several, or all of the preprocessing module, the spatiotemporal transformation module, and the interpolation module are all substantially or entirely implemented of the DSP. In some embodiments, one, several, or all of the scaling module, nonlinear transformation module, the digital pulse generation module, and the burst elimination module may be substantially or entirely implemented of the GPP. This implementation of the modules may lead to a particularly advantageous processing throughput and reduced processing time. However, in various embodiments, other suitable implementations may be used.
Although some exemplary embodiments of a processor for the prosthetic device 100 are set out above, it is to be understood that in various embodiments, other processing devices may be used. The processing device, e.g., hand-held computer, can be implemented using any device capable of receiving a data and transforming them into output with acceptable speed and accuracy for the application at hand. This includes, but is not limited to, a combination general purpose processor (GPP)/digital signal processor (DSP); a standard personal computer, or a portable computer such as a laptop; a graphical processing unit (GPU); a field-programmable gate array (FPGA) (or a field-programmable analog array (FPAA), if the input signals are analog); an application-specific integrated circuit (ASIC) (if an update is needed, the ASIC chip would need to be replaced); an application-specific standard product (ASSP); a stand-alone DSP; a stand-alone GPP; and the combinations thereof.
In one embodiment, the processing device is a hand-held computer (Gumstix Overo, Gumstix, San Jose, Calif.), based around a dual-core processor (OMAP 3530, Texas Instruments, Dallas, Tex.) that integrates a general purpose processor (GPP) and a digital signal processor (DSP) onto a single chip. This platform is capable of highly-parallel computation and requires much less power than a typical portable computer ( ̃2 Watts or less, compared to 26 Watts for a standard laptop computer). This allows the transformation to be computed in real-time, on a device that is portable and can be powered on a single battery for long periods of time. For example, typical laptop batteries, with charge capacities in the range of 40-60 Watt-hours, could run the processor continuously for about 20-30 hours. In another embodiment, all or a portion the processing device is small in size so that it can be worn by a patient (as detailed below). In other embodiments, other suitable computing devices may be used, e.g., a Beagleboard device available from Texas Instruments of Dallas, Tex.
Output Generator
As described in the device component of the Retinal Application, the encoder or encoders could drive many output elements. Several output generator interfaces for driving target cells are possible.
For example, in some embodiments, the cells to be driven by the output of the prosthetic 100 (i.e., the set C shown in FIG. 1A) may be sensitized to light, e.g., using a light-activated transducer (such as Channelrhodopsin-2). The output generator 103 could be an LED array, a set of fiber optics driven by an LED, a digital light processing (DLP) device, among others.
These optical devices would output pulses of light that correspond to the activity patterns of the cells in C. The pulses of light would drive the light-activated transducer, causing the cells in C to fire as the encoder specifies. For example, the encoder would send signals to a general purpose input/output (GPIO), which would signal the LEDs.
For example, in some embodiments, an encoder's output is a set of spike times (times at which an action potential should be produced in the downstream neuron). Because the output is in a sense binary (at each moment in time, a spike does or does not occur), this can be naturally converted into a program that sends high/low information to the GPIO. The GPIO then outputs voltage that is “high” and turns the LED on, or “low” and does not turn it on. In other words, the encoder produces a set of spike times, which get converted into TTL pulses through the software and the GPIO, and pulses current then goes down a wire from the GPIO to the LED. The temporal resolution of the spike times produced by the encoder may be sub-millisecond or any other suitable value.
The TTL pulses are the length of the neural signal (e.g., about 1 ms for an action potential.) In this example, the LEDs are separately addressable (one for each encoder); however, other methods that allow better use of interface materials (data compression), such as multiplexing or making use of correlations in the pulse patterns of the encoders to get many signals through to many LEDs rapidly, may be used. Finally, the addition of an amplifier to drive up signals to the LEDs may be built in as well (to allow the neurons receiving the light pulses to fire in a one-to-one manner or a near one-to-one manner with the pulses they receive).
For output generators based on electrodes, the output generator could consist of any device capable of driving current into the electrodes.
In general, as will be apparent to one skilled in the art, for various applications, any of the output generation techniques described in the Retinal Application may be adapted for use in the devices described herein.
Exemplary Deployment of the Motor Prosthesis on a Human Subject
Referring to FIG. 8A, in one embodiment of the motor prosthetic 100, electrodes of the input receiver 101 are implanted in SMA. The electrodes and a battery pack are all subcutaneous, as in deep brain stimulation (DBS) methods used for Parkinson's patients. The battery pack to drive input receiver 101 is put in subcutaneously in the anterior chest wall; it has leads that are tunneled up to a site in the scalp so it can supply the needed power to the recording system.
The signals from the input receiver are sent wirelessly to the processor 102, implemented in a unit worn on a belt with its battery pack.
The processor then drives output generator 103, as shown implemented as an implanted muscle stimulator system which is also completely internal to the human subjected including a power source. In some embodiments, the stimulator system may be of the type described in Guiraud et al, 2006. In some embodiments, the dimensions of the stimulator are comparable to the battery pack used for pacemakers (e.g., about 6 cm×6 cm). In one embodiment, including the connectors to muscle, the width of the stimulator is about 10 cm. FIG. 8B shows an X-ray snapshot from Guiraud et al, 2006, showing actual size of an exemplary stimulating device inside a human.
Procedures for Measuring Motor Prosthetic Performance
The following describes exemplary procedures for measuring the performance of the prosthetic 100 and its encoders. Performance of the encoders can be measured on a forced choice activity discrimination task or performance on an error pattern test. The term “test stimulus” that will be used herein, refers to pattern of muscle activity, measured using EMG.
To evaluate performance on a forced choice discrimination task, a known test in the art, a confusion matrix is used (Hand D J. 1981). A confusion matrix shows the probability that a pattern of nerve branch activity ({right arrow over (c)}, the population comprising the individual activities of each subpopulation ci) corresponds to its appropriate pattern of SMA activity, {right arrow over (c)}[k]. To generate different patterns of SMA activity, the animal (or human) is required to carry out an array of stereotyped movements (e.g., moving a cursor to one of several locations on a computer monitor). Each kind of movement (for example, the movement to each location) is repeated for many trials, thus giving a set of SMA activities. For each movement type k, the set of SMA activities is denoted {right arrow over (a)}[m], and the set of resulting nerve branch activities is denoted {right arrow over (c)}[k].
With respect to the matrix, the vertical axis gives the movement type k. The horizontal axis gives the movement type predicted by decoding the pattern of nerve branch activity {right arrow over (c)}[k]; the decoded movement type is denoted m. The matrix element at position (k,m) thus gives the probability that nerve branch activity {right arrow over (c)}[k] is decoded as movement type m. If m=k, the nerve branch activity pattern is decoded correctly, otherwise, it is decoded incorrectly. Put simply, elements on the diagonal indicate correct decoding; elements off the diagonal indicate confusion.
To generate the confusion matrices, we divide the data into two sets: a training and a testing set. The training set is obtained in order to build response distributions, and the testing set is obtained for decoding.
To decode each pattern in the test set, {right arrow over (c)}[k], we determine the pattern of SMA activity that was the most likely to have produced it. That is, we determine the pattern {right arrow over (a)}[m] for which




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  ,




where p ({right arrow over (a)}[m]|{right arrow over (c)}[k]) is the probability that the pattern {right arrow over (a)}[m] in the SMA was present, given that the particular {right arrow over (c)}[k] was present in the nerve branches. p({right arrow over (c)}[k]|{right arrow over (a)}[m]) is the probability that a particular {right arrow over (c)}[k] occurred given a particular {right arrow over (a)}[m], and p({right arrow over (a)}[m]) is the prior probability of {right arrow over (a)}[m]. p({right arrow over (a)}[m]) is set uniform in this experiment and so, by Bayes Theorem, p({right arrow over (a)}[m]|{right arrow over (c)}[k]) is maximized when p({right arrow over (c)}[k]|{right arrow over (a)}[m]) is maximized. When p({right arrow over (a)}[m]) is uniform, as it is here, this method of finding the most likely pattern {right arrow over (a)}[m] given a pattern {right arrow over (c)}[k] is referred to as maximum likelihood decoding (Kass et al. 2005; Pandarinath et al. 2010; Jacobs et al. 2009). For each occurrence of a movement type k that that was decoded as m, the entry at position (m,k) in the confusion matrix is incremented.

To build the distributions needed for the decoding calculations used to make the confusion matrices (i.e., to specify p({right arrow over (c)}[k]|{right arrow over (a)}[k])), the procedure is as follows. As mentioned above, the subject makes N types of movements (where N is typically 8), and each is repeated many times (e.g., >20 times). For each movement, we obtain a pattern of SMA activity {right arrow over (a)}[k], which we record via the implanted electrodes, and we obtain a pattern {right arrow over (c)}. Each pattern {right arrow over (a)}[k] is taken as the spike train spanning from  ̃1 sec prior to movement onset to  ̃200 ms following movement onset, and binned with 10-100 ms bins. Each pattern {right arrow over (c)}[k] is taken as the nerve branch activity over the same period and binned in the same way. In both cases, the spike generation process is assumed to be an inhomogeneous Poisson process, and the probability of any given pattern of activity for the entire period is calculated as the product of the probabilities for each bin. The probability assigned to each bin is determined by Poisson statistics, based on the training set response in this bin. Note that this can be done by averaging over all trials for a given type of movement pattern, or by considering each trial individually.
Once the confusion matrices are calculated, overall performance in the forced choice activity discrimination task is quantified by “fraction correct”, which is the fraction of times over the whole task that the decoded movement type m was correctly matched to the movement type k.
Given this procedure, at least 3 sets of analyses may be performed. For each one, the activity patterns from the normal subject are used for the training set and a different set of activity patterns is used for the test set, as outlined below:
(1) The first set should consist of the test sets described above, i.e., out-of-sample activity patterns from the normal subject. (These are recordings of activity patterns in SMA and the nerve branches that were not used to make the training set.) We use the fraction correct produced by the activity patterns from normal subjects as the baseline correct performance.
(2) The second set should consist of the responses from the encoders. These are the responses {right arrow over (a)}[k] calculated from eq. 1, from the recorded SMA activity patterns {right arrow over (a)}[k]. Responses from this test set yield a measure of how well the encoders perform, given the training set response distributions used for analysis (1). The reason for performing the analysis this way is that we want to compare the encoder's performance against the normal baseline condition.
When responses from the encoder are used as a test set, one obtains a measure of how well the motor system would do with our proxy of the transformation from SMA to the peripheral nerve branch activity (our proxy of the motor system code).
(3) The third set, which is carried out only in subjects in which the normal pathway from SMA to muscle has been damaged, is to determine the confusion matrix that relates the movement actually made, to the movement that was intended. Since the normal pathways are damaged, the movement results from applying the prosthetic's encoder signals, determined as in analysis (2), to the muscles via the output generated (in this example, output uses electrodes, see above). The movement intended is determined from the subject's verbal responses, and can be verified by decoding the patterns of activity in SMA that are produced at the time of intention. This analysis provides a measure of how well the prosthetic performs after its output has been passed through the to real tissue. This is a bottom-line measure of the prosthetic's performance in patients.
The encoder's performance and prosthetics performance in the forced choice discrimination task, as measured by “fraction correct”, will be at least about 35%, 50%, 60%, 70%, 80%, 90%, 95%, 99%, or 100% of the performance of the normal system, or better than the normal system, measured as described above. Moreover, these performance levels may be obtained with response time for the prosthetic 100 which is substantially the same as those found in an unimpaired subject. That is, in some embodiments, the prosthetic 100 in jumping impaired signaling cells introduces a lag time of which is of suitably short duration. For example, in some embodiments the lag time is less than a factor of 5, 4, 3, 2, 1, 0.5, 0.1, (e.g., a factor in the range of 0.1-5 or any subrange thereof) or less times the signaling time exhibited by a normal subject.
Although a number of examples of neural prosthetic devices and techniques have been presented above, it is to be understood that numerous modifications are possible.
For example, the above description of the strategy to find the transformation to be implemented by the encoders; there are a number of variations that may be used.
In various embodiments, there are options for how spike trains (either input from A or output to C) are represented. For example, they can be represented as a point process in continuous time; they can be smoothed into continuous rate functions, and they can be binned. In typical embodiments, the data collected at both A and C is in the form of a point process, but under some conditions it is easier to perform optimizations with smooth representations.
The smooth representations, then, can be reconverted to spike trains by assuming, for example, Poisson spike generation. Related to this, note that some embodiments can also use a non-spiking measure to capture the neural activity in area A, such as a local field potential or optically recorded signal. These represent a local average of neural activity, and (e.g., in circumstances that do not require resolution at the single neuron level), may provide a more stable measurement. In these cases, the smooth representation of activity in A is used directly for determining the transformation.)
In various embodiments, there are options for the cost function to be used in optimization of the encoder transformation model. The examples presented above use the likelihood, because it is well principled, but under many circumstances, a mean-squared-error is an excellent approximation and the optimization is faster to perform. Note, in regard to the previous paragraph, that in order to use mean-squared-error, some form of binning or smoothing is required.
In various embodiments, while the choice of a linear-nonlinear cascade is a natural and principled one, other functional forms may also be applicable, such as models with dynamic gain controls or neural network models, or any transformation that can be expressed, explicitly or implicitly, as a solution of a system of integral, differential, or ordinary algebraic equations, whose form and coefficients are determined by experimental data. This also includes models in which activity among the neurons in region C is correlated, e.g., via recurrent feedback.
Further, while in may cases it is most straightforward to fit the model parameters for each neuron in A independently, in some applications these parameters may have a systematic dependence on the neuron's location. Identification of this dependence will reduce the number of independent parameters that must be fit, and, potentially, allow for generalization of the model to neurons not actually recorded.
Also, it is notable that in embodiments where the prosthesis device performs a jump to muscle, an involved extra transformation (e.g., from SMA output to muscle response) is likely linear, so the cascade becomes linear nonlinear linear (LNL) transformation to go from SMA to muscle.
Auditory Prosthesis
In several of the examples above, a prosthesis 100 is described which is used to restore or improve communication from one set of healthy cells A to another set of health cells C by jumping a set of impaired signally cells B that separate the sets of healthy cells.
As noted above, in some embodiments, the input signal to the prosthesis is an external stimulus instead of the activity of the set of healthy cells A. For example, FIG. 9 shows an auditory prosthetic 200. The prosthetic 200 is a device to bypass damaged hair cells in the inner ear, that is, to jump from sound stimuli directly to the output of the cochlea (the output of the spiral ganglion cells).
The prosthesis 200 includes an input receiver 201 for detecting an audio signal (e.g., a microphone or other sound transducer) an converting the audio signal to, e.g., a digital format. A processor 202 (sometimes referred to herein as an encoder unit) processes the input signal from the input receiver 201 using a set of encoders to generate a set of coded outputs. An output generator 203 (e.g. an electrode or optical device of the types described herein), in response to the coded outputs, activates auditory nerve cells (e.g., spiral ganglion cells) to produce a response to the audio stimulus, e.g., a response that is substantially the same as the response in an unimpaired subject.
A well functioning auditory prosthesis, e.g., one that can provide near normal or normal function in an impaired subject is advantageous because the incidence of hearing loss as the population ages is very high.
As in the examples presented above, an important aspect of the prosthetic 200 is the functioning of the encoders implemented by the processor 202. These are the components that carry out the transformation from sound to cochlear output. As discussed above for the motor prosthetic and for the visual prosthetic described in the Retinal Application, an advantage of this approach is that it has the capacity to generalize. it does this by using a mathematical transformation that captures the relation between the outside world (in this case, audio stimuli) and the activity of a set of neurons. The techniques used here are directly analogous to those used to generate the motor encoders described above and visual encoders described in the Retinal Application. The following discussion uses the notation developed herein for the motor encoders for convenience. However, one skilled in the art will recognize that the formalism and techniques used in the Retinal Application may be readily adapted to the present case of an auditory prosthesis.
Again the approach for building the encoders is phenomenological: One may parameterize the relationship between the external stimuli and a set of neural signals or between two sets of neural signals, and find the parameter values using an optimization procedure, such as maximum likelihood.
Note that in various embodiments, the prosthetic 200 uses signaling that is not limited to frequency coding or intensity coding, but uses natural coding derived directly from data. That is, each encoder is essentially a complete model for the input/output relations for a class of SG cell, where the input is the sound stimului (such that the hair cells are being jumped). This means it has the capability to transform any sound stimulus into the normal auditory output for that class of cell. The encoders of the prosthesis 200 thus carry much more information that simple frequency detectors and transmitters (e.g., of the type described in Boyden, 2010, U.S. Pat. Pub. No. 2010 0234273).
Constructing Auditory Encoders Using Experimental Data:
In some embodiments, encoders are constructed from data collected from spiral ganglion (SG) neurons in an unimpaired subject while sound stimuli are presented. In some embodiments, one may implant an array of extracellular electrodes e.g., using the techniques described in Sellick 1982. Accordingly one obtain firing patterns from an array of SG neurons. At the same time, one may present sound stimuli. One may formalize the relation between the sound stimuli and the SG responses as {right arrow over (c)}={right arrow over (f)}({right arrow over (a)}), where {right arrow over (a)} is vector representing the sound (as a time series), and {right arrow over (c)} is the pattern of neural activity in the SG neurons. Note that {right arrow over (a)} is univariate (it's a vector where the components are sound (pressure) as a function of time) and {right arrow over (c)} is multivariate (as above, it represents the activity of a population of neurons, the SG neurons). In some embodiments, the transformation may instead operate on the frequency spectrum of the sound. As will be readily understood by one skilled in the art, such a frequency spectrum may easily be obtained from {right arrow over (a)} via a Fourier transform (e.g., performed by processor 202 implementing an algorithm such as the well known Fast Fourier Transform).
To generate generalizable encoders, one may use the same strategy discussed herein for generating the retinal encoders and the motor encoders. One may provoke the system with a broad range of stimuli. In the case of the retinal encoders, we presented the retinas from normal subjects with two classes of stimuli—artificial (white noise) and natural scenes—and recorded ganglion cell responses. We then modeled the transformation from stimulus to response. The “training” stimuli (the white noise and natural scenes) were broad enough to produce a general model, one that was effective on any stimulus. In other words, given the training stimuli, we obtained a model that faithfully reproduced ganglion cell responses to essentially any stimuli (stimuli of arbitrary complexity).
Here, with the auditory system, one may take the same approach. On may present white noise (WN) and natural sound (NS) stimuli, where the latter falls into two categories, environmental sound and sound relevant to language (both described in, for example, Lewicki, 2002.
Given the data sets generated in the previous step, one may model the transformation between the sound stimuli and the SG responses. This provides a set of encoders, e.g., one for each SG cell or corresponding to a small group of SG cells (e.g., containing less than 2, less than 3, less than 5, less than 10, less than 20, less than 30, less than 50, or less than 100 cells, e.g., in the range of 1-1000 cells or any subrange thereof).
As for the motor prosthetic, one may use the following parametric form, and determine the parameters of the form by optimizing a cost function separately for each SG neuron: for each SG neuron, ci determine weight functions, {right arrow over (w)}i, and a nonlinearity, Ni, so that the modeled transformation cifit=Ni({right arrow over (a)}·{right arrow over (w)}) is an optimal match to the actual transformation, ci=fi({right arrow over (a)}). Ni is a pointwise nonlinearity, i.e., a function y=Ni(x), where x and y are both real-valued quantities (in the case of the retinal encoders, Ni was a cubic spline with 7 knots, but any suitable choice may be used), and {right arrow over (w)} is a vector of weights, specific to the output each SG neuron i. {right arrow over (w)}i consists of an array of quantities wj(t), where i labels a neuron in the SG population, and t is time. The ith component of the dot product  is calculated as follows:

Σa(t)wi(t)

Note that this differs slightly from the parallel equation for the motor prosthetic in that it has no subscript j; this is because the quantity a here is a one-dimensional function of time (or frequency in the case where an Fourier transform has been applied). As was the case for the encoders for the retina and motor systems, the optimization is performed to maximize the expected log likelihood over the entire output population, namely,





  L
  =
  
    〈
    
      
        ∑
        i
      
      ⁢
      
        ll
        ⁡
        
          (
          
            
              c
              i
              fit
            
            ,
            
              a
              →
            
          
          )
        
      
    
    〉
  




ll(cifit, {right arrow over (a)}) denotes the log likelihood that cifit accounts for the observed activity of the ith neuron in SG, when {right arrow over (a)} is the sound input, and the brackets denote an average over all inputs. This likelihood is calculated from Poisson statistics based on the model firing rates (i.e., cifit).

The weights {right arrow over (w)}i, i.e., the arrays wi,j(t) correspond to a set of linear filters, one for each neuron i in the SG, and Ni is an adjustable nonlinearity for neuron i.
Exemplary Implementation of Auditory Prosthesis
Referring again to FIG. 9, the auditory prosthesis 200 may incorporate encoders built using the techniques described here, e.g., implemented by the processor 202. The encoders are used in conjunction with an input receiver 201 (e.g., a microphone) and an output generator 203 which stimulates a response in the SG cells.
As described herein, in various embodiments, the strategy is to first develop encoders that capture the transformation from audio stimulus to SG activity (for arbitrary activity patterns), and, second, to use the coded output these encoders to jump impaired cochlear hair cells and directly stimulate the SG cells to restore normal or near normal function.
In various embodiments, the output generator 203 may include any suitable technology for stimulating SG neurons, such as that of they type describe in Zeirhofer et al., 1995 or Zeng et al, 2009. For example, in the embodiment shown in FIG. 10A the prosthesis 200 works as follows: 1) a microphone included in the input receiver 201 sends signals to a processor 202, 2) the signal processor 202 converts the signals from the microphone to signals to drive an array of electrodes in output generator 203, and 3) the signals from processor 202 control the electrodes that stimulate the SG neurons.
As shown, the microphone and a signal processing portion 202a of the processor 202 are located outside of the subject. The signal processing portion 202a generated coded outputs, and transfers them, e.g., via a radio frequency (RF) or other wireless link to a subcutaneously implanted portion 202a of the processor 202. The implanted portion receiver the signal and controls the electrodes to stimulate the SG cells.
In other embodiments, all of the processing may occur externally, with an RF signal being used to directly drive implanted electrodes. In various embodiments other implementation schemed may be used. In some embodiments, an external power supply provides power to the subcutaneous elements, e.g., via an RF or inductive power coupling, or any other power transmission technique known in the art.
FIG. 10B shows a variant of the device of FIG. 10A, where the output of the encoders is sent not to electrodes, but to light emitting diodes (LEDs) included in the output generator 203 (or another light sources) to drive alternate transducers, e.g., channelrhodopsin-2 (ChR2) used to sensitive the SG cells. Pulses from the LEDs are used to drive a response in the sensitized SG cells.
In various embodiments, expression of ChR2 or other transducer genes in SG neurons can be achieved using the gene promoters described in Table 1 of Liu et al, 2007. Examples include EF-1\alpha, NSE, CMV, CAG; these all express in SG neurons. In various embodiments, any other suitable promoters may be used.
With respect to delivery of the gene, any of the same gene therapy approaches described in the Retinal Application can be used for delivery to SG cells. Lentivirus (LV), adenovirus-5 (Ad-5) and adeno-associated virus-2 (AAV-2) have been shown to penetrate, although (Ad-5) was found to be the most effective (under conditions where the round window of the cochlea, one of the openings to the inner ear, was left intact (Lei et al, 2010). If the round window is partially digested, then AAV-2 becomes effective (Wang et al, 2011); this is valuable in some applications, as AAV-2 is one of the more promising gene therapy vectors in terms of safety (Simonelli et al, 2010). In various embodiments, any other suitable delivery technique may be used.
Referring to FIGS. 11A and 11B, in some embodiments, the output generator 203 includes a thin flexible LED array 1201 implanted in the cochlea 1202 of a subject. The flexible array is able to conform to the spiral shape of the cochlea, such that the LEDs may be positioned to stimulate SG cells. Note that although one possible configuration of the array 1201 is shown, and other suitable positioning, array size, etc.
In some embodiments, the array 1201 includes an arrays of interconnected, ultrathin LEDs 1203 that are built into a flexible waterproof material. In various embodiments, the device can be placed into the inner ear to stimulate the ChR2-expressing SG cells. In one embodiment, each LED is 100 by 100 microns, which would stimulate multiple cells; however, one can narrow its light path to target fewer cells by masking a portion of the LED. In some embodiments, the size of the masking may be optimized to allow sufficient intensity to reach the ChR2; “sufficient intensity” is defined as that which produces action potentials that follow the output of the encoder in a one-to-one or near one-to one manner.
In some embodiments, the flexibility of the array 1201 matches well with the curvature of the cochlea 1201: For example, in humans the radius of curvature of the cochlea ranges from 4 mm at the high frequency end to 0.7 mm at the low frequency end, while in some embodiments, the radius of curvature of the flexible device is e.g., 0.4 mm or less.
In some embodiments, the array 1201 may be of the type described in Kim et al, 2010. In various embodiments, the array 1201 may be operatively connected to the processor 202 using any suitable technique including, e.g., a wired or wireless connection.
In some embodiments, after device implantation, the encoder may be optimized for the specific patient. Two examples of optimization are the following. First, in some cases, different encoders capture different information (e.g., frequencies, intensity), so they need to be positioned on the SG neuron array to stimulate the appropriate SG cells (the SG cells that carry the same information). Second, in some embodiments, threshold levels and maximum levels have to be determined. This can be achieved using extracellular electrodes (e.g., using pure tones to drive a small number of cells at a time).
Methods for Measuring Auditory Prosthesis Performance
The following describes exemplary procedures for measuring the performance of the prosthetic 200 and its encoders. In some embodiments, the procedure for measuring the performance of the encoders and the prosthetic will follow directly from that used to test the retinal prosthetic or motor prosthetic, focusing specifically on performance on a forced choice discrimination task. The term “test stimulus” that will be used herein, refers to a stimulus or a stimuli, which is presented to an animal for evaluation of performance of the encoders or encoders and output generator (e.g., the auditory prosthesis 200).
In various embodiments, it is important that the task used to measure prosthetic performance falls into a range of difficulty that allows meaningful information to be obtained. Briefly, the task must be difficult enough (i.e. must use a stimulus set rich enough) that the normal retinal responses provide information about the stimuli, but do not perform perfectly on the task. For example, in the task shown in Example 8 in the Retinal Application, the fraction correct using the responses from the normal retina, was 80%, satisfying this criterion. If the task used had been too hard, such that the normal retina's performance were near chance, then matching would have been of limited use to a performance analysis. Conversely, if the task chosen had been too easy (e.g., requiring just gross discriminations, such as black versus white, and where the fraction correct for the responses from the normal is near 100%), then prosthetic methods that are far from approximating the natural code and provide nothing close to normal vision would appear to do well. The same applies to the auditory tests: it is critical to use an appropriately challenging test, as was used in the examples in the Retinal Application. The use of a challenging test also allows one to determine if the prosthesis is performing better than the auditory system (i.e., entering into the domain of “bionic hearing”).
Various methods for the forced choice task follow directly from those analogous used in the Retinal Application, converting to auditory stimuli. Two types of natural stimuli may be used—natural environment sound stimuli and speech-sound stimuli, as described in, for example, Lewicki, 2002. To evaluate performance on a forced choice discrimination task, a known test in the art, a confusion matrix is used (Hand D J. 1981). A confusion matrix shows the probability that a response to a presented stimulus will be decoded as that stimulus. The vertical axis of the matrix gives the presented stimulus (i), and the horizontal axis gives the decoded stimulus (j). The matrix element at position (i,j) gives the probability that stimulus i is decoded as stimulus j. If j=i, the stimulus is decoded correctly, otherwise, the stimulus is decoded incorrectly. Put simply, elements on the diagonal indicate correct decoding; elements off the diagonal indicate confusion.
In this task, an array of stimuli is presented, specifically, stimuli containing natural sounds, and the extent to which the stimuli can be distinguished from each other, based on the responses of the SG cells and/or encoders, is measured.
A training set is obtained in order to build response distributions (the “training set”), and another set is obtained to be decoded to calculate the confusion matrix (the “test set”).
To decode the responses in the test set, one determines which of the stimuli sj was the most likely to produce it. That is, one determines the stimulus sj for which p(r|sj) was maximal. Bayes theorem is used, which states that p(sj|r)=p(r|sj)p(sj)/p(r), where p(sj|r) is the probability that the stimulus sj was present, given a particular response r; p(r|sj) is the probability of obtaining a particular response r given the stimulus sj; and p(sj) is the probability that the stimulus sj was present. p(sj) is set equal for all stimuli in this experiment and so, by Bayes Theorem, p(s|rj) is maximized when p(r|sj) is maximized. When p(sj) is uniform, as it is here, this method of finding the most likely stimulus given a response is referred to as maximum likelihood decoding (Kass et al. 2005; Pandarinath et al. 2010; Jacobs et al. 2009). For each presentation of stimulus si that resulted in a response r that was decoded as the stimulus sj, the entry at position (i,j) in the confusion matrix is incremented.
To build the response distributions needed for the decoding calculations used to make the confusion matrices (i.e., to specify p(r|sj) for any response r), the procedure is as follows. The response r is taken to be the spike train spanning 100 ms after stimulus onset and binned with 5 ms bins; this is the appropriate timescale in particular for speech sounds. The spike generation process is assumed to be an inhomogeneous Poisson process, and the probability p(r|sj) for the entire 100 ms response is calculated as the product of the probabilities for each 5 ms bin. The probability assigned to each bin is determined by Poisson statistics, based on the average training set response in this bin to the stimulus sj. Specifically, if the number of spikes of the response r in this bin is n, and the average number of spikes in the training set responses in this bin is h, then the probability assigned to this bin is (hn/n!)exp(−h). The product of these probabilities, one for each bin, specifies the response distributions for the decoding calculations used to make the confusion matrices.
Once the confusion matrices are calculated, overall performance in the forced choice visual discrimination task is quantified by “fraction correct”, which is the fraction of times over the whole task that the decoded responses correctly identified the stimuli. The fraction correct is the mean of the diagonal of the confusion matrix.
Given this procedure, at east sets of analyses may be performed. For each one, the responses from the normal SG cells are used for the training set and a different set of responses is used for the test set, as outlined below.
(1) The first set may include or consist of responses from normal SG cells. This is done to obtain the fraction correct produced by normal SG cells.
(2) The second set may include or consist of the responses from the encoders (in various embodiments, the responses from the encoders, as indicated throughout this document and that of the original application, may be streams of electrical pulses, e.g., spanning 100 ms after stimulus presentation, and binned with 5 ms, as are the normal SG responses). In other embodiments, other suitable durations and bin times may be used.
Responses from this test set yield a measure of how well the encoders perform, given the response distributions of the normal SG cells. The basis for this is that the brain is built to interpret the responses of the normal SG cells (i.e., the naturally encoded responses.) When responses from the encoder are used as a test set, one obtains a measure of how well the brain would do with our proxy of the normal SG responses (our proxy of the SG code).
(3) The third set may include or consist of responses from the SG cells of a deaf animal or human driven by the encoders and output generator (e.g., driving a ChR2 based transducer), where the responses are of the same duration and bin size as above. This set provides a measure of how well the encoder performs after its output has been passed through to real tissue.
As shown in Example 8 of the Retinal Application, the encoder's performance in the forced choice discrimination task was 98.75% of the normal retina's performance, and complete system's performance, that is, the performance of an embodiment of the encoder, output generator, and related transducer was 80% of the normal retina's performance. Thus, for various embodiments, when tested in vitro or in an animal or human model, the performance of the auditory prosthesis in the forced choice discrimination task, as measured by “fraction correct”, should be similar, that is at least about 35%, 50%, 60%, 70%, 80%, 90%, 95%, 99%, or 100% of the performance of the normal SG cells, or better than the normal SG cells, measured as described above. Moreover, these performance levels may be obtained with response time scales for the prosthetic 200 which are substantially the same as those found in an unimpaired subject. That is, in some embodiments, the prosthetic 200 in jumping impaired cochlear hair cells introduces a lag time of which is of suitably short duration. For example, in some embodiments the lag time is less than a factor of 5, 4, 3, 2, 1, 0.5, 0.1, (e.g., a factor in the range of 0.1-5 or any subrange thereof) or less times the signaling time exhibited by a normal subject.
Other Embodiments
Although several examples have been provided, it is to be understood that numerous variations are within the scope of the present disclosure. For example, although prostheses for auditory and motor applications have been provided, it is to be understood that the devices and techniques may be applied in a variety of additional settings. Further, although various examples of cell and tissue types have been provided (e.g. jumping from SMA to SMN or muscle, or jumping from an audio stimulus to SG), it is to be understood that other types of cells, tissue, etc. may be used. In general, the devices and techniques described herein may be adapted to a wide variety of cases where a prosthetic is required which operates as a proxy for signaling cells which have suffered some form of gap or impairment.
Tables 2-6 summarize a number of applications where the devices and techniques described herein may be used to restore or improve function. For each application, the tables set forth a region of the nervous system that is impaired, the resulting body parts that have diminished function, the cause of the injury or impairment, the region from which activity is read (corresponding to A in FIG. 1B), the region which is stimulated (corresponding to C in FIG. 1B), and the connection that us bypassed or “jumped.” It is to be understood that the examples provided in the tables are in no way exhaustive.












TABLE 2






Body Part(s)






Region of CNS
That Have






That is
Diminished
Cause of





Impaired
Function
Impairment
Input Region
Output Region
Connection







dorsal column
impairment of
tabes dorsalis
dorsal root
(medial
primary somatic


tract aka
procrioception,
(sensory ataxia);
or: right before
lemniscus) VPL
sensory cortex


posterior/dorsal
vibratory
stereoanethesia
lesioned part of
thalamus
(postcentral


horn (dorsal
sensation/loss
(impaired
tract;
or: right after
gyrus);


white column)
of deep tendon
graphesia and
Adams' and
lesioned part of
Waxman, 56;


fibers
reflex (skin,
tactile
Victor's
tract;
http://www.ncbi



joints,tendons);i 
localization);
Neurology Ch 9
Waxman 57;
.nlm.nih.gov/bo



mpaired two-
multiple

http://www.ncbi
oks/NBK11142/



point
sclerosis,

.nlm.nih.gov/bo
;; Brazis 287



discrimination;
vitamin B12

oks/NBK11142/




figure writing;
deficiency, HIV






detection of
and human T-






size, shape,
lymphotropic






weight, and
virus infection;






texture of
Waxman 68;






objects; ability
Ropper and






to detect the
Samuels ch 9;






direction and







speed of a







moving stimulus







on the skin;







Waxman







68,55,56,57;







Ropper and







Samuels Ch 9






Spinothalamic
(skin) loss of
Syringomyelia;
posterior root
(medial
primary somatic


Tract
pain/temp
stroke; trauma;
ganglion axons
lemniscus) VPL
sensory cortex


(ventrolateral
sensation
Waxman 66, 68;
aka dorsal root
thalamus
(postcentral


column fibers)
below/opposite
Kierman 77;
or: right before
or: right after
gyrus);



side of lesion
http://www.ncbi
lesioned part of
lesioned part of
Waxman 57;



(ipsilateral lower
.nlm.nih.gov/pm
tract;
tract;
http://www.ncbi



extremities)
c/articles/PMC2
Snell 142;
Waxman 56;
.nlm.nih.gov/bo



;motor
170182/?tool=p
Waxman Ch 5
http://www.ncbi
oks/NBK10967/;



weakness same
ubmed;
Sec III;
.nlm.nih.gov/bo
Brazis 287



side of lesion;
http://www.ncbi

oks/NBK10967/;




ipsilateral side
.nlm.nih.gov/pu

Brazis 287




of face;
bmed/14663044






neuronal







hyperexcitability







at injury/above







the injury; pain







below the injury







level (central







pain);







Waxman







56;http://www.







ncbi.nlm.nih.gov







/books/NBK109







67/ ; Brazis 370;







http://www.ncbi







.nlm.nih.gov/pm







c/articles/PMC2







170182/?tool=p







ubmed;www.nc







bi.nlm.nih.gov/p







ubmed/1466304







4






Dorsal
muscle
X-Chromosome
posterior root
precerebellar
inferior


Spinocerebellar
spindles/Golgi
Linked Copper
aka dorsal root
nuclei
cerebellar


tract aka
tendon
Malabsorption ;
(posterior gray
or: right after
peduncle;


posterior
organs,touch+pr
Hereditory
column)
lesioned part of
Kierman 72,167;


spinocerebellar
essure receptors
Spastic
or: right before
tract;
2)


tract (lateral
via nucleus
Paresis;spinocer
lesioned part of
Kierman 93;
http://www.acc


column fibers)
dorsalis;
ebellar ataxia
tract;
http://www.dart
essmedicine.co



ipsilateral lower
(atrophy +
Snell 147
mouth.edu/~rsw
m/content.aspx



extremities
demyelinization

enson/NeuroSci
?alD=5272458&



(vibration/positi
of fibers); Miller

/chapter_7A.ht
searchStr=cereb



onal sensory
Fisher-Guillain

ml
ellar+peduncle#



functions)
Barre Overlap


5272458



;severe
Syndrome;






ophthalmoplegi
http://onlinelibr






a (paralysis of
ary.wiley.com/d






eye muscles),
oi/10.1002/ana.






bilateral
410050609/a bst






ptosis(eyelid),
ract;






areflexia,
http://www.scie






and moderate
ncedirect.com/s






cerebellar
cience/article/pi






ataxia;
i/0022510X9490






irresponsive
037X; (SCA 2)






pupils; facial
http://www.ncbi






nerve palsy;
.nlm.nih.gov/pu






Waxman 56;
bmed/14507334






Brazis 370 ;
;






http://cornell.w
http://www.ncbi






orldcat.org/title/ 
.nlm.nih.gov/pu






position-and-
bmed/7876862






vibration-







sensations-







functions-of-







the-dorsal-







spinocerebellar-







tracts/ocic/1147







67304&referer=







brief_results;







http://www.ncbi







.nlm.nih.gov/pu







bmed/7876862






Ventral
1)muscle
a) Miller Fisher- 
dorsal root
precerebellar
superior


Spinocerebellar
spindles/Golgi
Guillain Barre
ganglion axons
nuclei
cerebellar


tract aka
tendon organs
Overlap
(posterior gray
or: right after
peduncle ((to


anterior
(sensory input
Syndrome;
column)
lesioned part of
cerebellar


spinocerebellar
from skeletal
b) Friedrich's
or: right before
tract;
cortex) ;


tract
muscle)
Syndrome
lesioned part of
Kierman 93
Kierman 72;



,touch+pressure
(heredo-ataxia);
tract;
;http://www.dar
http://www.acc



receptors; 2)
a)
Snell 146
tmouth.edu/~rs
essmedicine.co



severe
http://www.ncbi

wenson/NeuroS
m/content.aspx



ophthalmoplegi
.nlm.nih.gov/pu

ci/chapter_7A.ht
?alD=5272458&



a (paralysis of
bmed/7876862;

ml
searchStr=cereb



eye muscles),
b)


ellar+peduncle#



bilateral
http://www.ncbi


5272458



ptosis(eyelid),
.nlm.nih.gov/pu






areflexia,
bmed?term=%2






and moderate
2ventral%20spin






cerebellar
ocerebellar%20t






ataxia;
ract%22%20atax






irresponsive
ia






pupils; 3) facial 







nerve palsy;







optic nerve







degeneration;







1) Waxman 56;







http://www.blac







kwellpublishing.







com/patestas/c







hapters/10.pdf;







2)







http://www.ncbi







.nlm.nih.gov/pu







bmed/7876862;







3)







http://www.ncbi







.nlm.nih.gov/pu







bmed?term=%2







2ventral%20spin







ocerebellar%20t







ract%22%20atax







ia






Spinoreticular
deep somatic
Wallenberg's
posterior root
reticular
Thalamus;


Tract (lateral
structures ; lack 
Syndrome;
ganglion axons
formation
cerebral cortex;


column)
of triggering of
http://www.ncbi
or: right before 
(precerebellar
http://www.blac



noxious
.nlm.nih.gov/pu
lesioned part of
nucleus)
kwellpublishing.



inhibitory
bmed?term=Diff
tract;
or: right after
com/patestas/c



controls
use%20noxious
Snell 150
lesioned part of
hapters/10.pdf ;



(nonpainful but
%20inhibitory%

tract;
Latash 171



noxious stimuli)
20controls%20in

http://www.acc
(Neurophysiolog



; hemianalgesia;
%20man.%20Inv

essmedicine.co
ical basis of



Waxman 56;
olvement%20of

m/content.aspx
movement)



http://www.ncbi
%20the%20spin

alD=5271956&




.nlm.nih.gov/pu
oreticular%20tra

searchStr=spino




bmed?term=Diff
ct

cerebellar+tract




use%20noxious


s#5271956.




%20inhibitory%


Kierman 72;




20controls%20in


http://www.scie




%20man.%201nv


ncedirect.com/s




olvement%20of


cience/article/pi




%20the%20spin


i/S03010082980




oreticular%20tra


00483




ct






Corticopontocer
myelin decay
ataxic
nerve cells in
pontine nuclei
cerebellar


ebellar Pathway
(white matter
neurodegerenati 
frontal/parietal/
or: right after
cortex;


(pontocerebellar
tracts);
ve diseases
temporal/occipit
lesioned part of 
Snell 226-229


tract; pontine
dysarthria
(hereditary
al lobes of
tract;



nuclei; part of
(mouth),
spinocerebellar
cerebral cortex
Snell 226-229



cerebellum)
hemiparesis of
ataxia); multiple
or: right before





one side,
system atrophy
lesioned part of





nystagmus
(MSA); late-
tract;





(involuntary eye
onset cerebellar 
Snell 226-227





twitching);
cortical atrophy






http://www.ncbi
(LCCA); stroke;






.nlm.nih.gov/pu
http://www.ncbi






bmed/18172629
.nlm.nih.gov/pu







bmed/18172629







http://www.ncbi







.nlm.nih.gov/pu







bmed/8342190





cerebro-
involuntary eye
olivocerebellar
nerve cells in
inferior olivary 
cerebellar


olivocerebellar
twitching
atrophy;
frontal/parietal/ 
nuclei
cortex;


tract fibers
(rebound
cerebellar
temporal/occipit
or: right after
Snell 229



nystagmus),
ataxia;
al lobes of
lesioned part of




wasting of small
http://www.ncbi
cerebral cortex
tract;




muscles of both
.nlm.nih.gov/pu
or: right before
Snell 229




hands, spastic
bmed/7931442;
lesioned part of





paralysis of both

tract;





legs,

Snell 226





dysdiadochokine







sia (lack of







coordination)of







upper limbs,







ocular







dysmetria;







http://www.ncbi







.nlm.nih.gov/pu







bmed/7931442;





















TABLE 3






Body Part(s)






Region of CNS
That Have






That is
Diminished
Cause of





Impaired
Function
Impairment
Input Region
Output Region
Connection







Ventromedial
ipsilateral
Kierman
1) dorsomedial
medial
inferior


medulla
hypoglossal
108,109;
hypothalamus
lemniscus;
cerebellar



palsy (tongue
Head and neck
neurons
Waxman 86
peduncle



paralysis);
surgery--
2) midbrain

(cerebral



contralateral
otolaryngology
periaqueductal

cortex);



hemiplegia/hem
By Byron J.
gray (for rostral

Waxman 86;



iparesis; loss of
Bailey p119;
ventromedial

Smith et al 45



sense of
Jonas T.
medulla);





temp/pain
Johnson, Shawn
1)





(skin);
D. Newlands;
http://www.ncbi





Kierman 108;
http://stroke.ah
.nlm.nih.gov/pu





http://www.scie
ajournals.org/co
bmed/21196160





ncedirect.com/s
ntent/26/4/702.
2)





cience/article/pi
full;
http://www.ann





i/S10523057988
http://www.scie
ualreviews.org/





0027X;
ncedirect.com/s
doi/abs/10.1146





http://www.nej
cience/article/pi
/annurev.ne.14.





m.org/doi/full/1
i/S03064522060
030191.001251





0.1056/ENEJMic
03836;






m020058;
http://www.scie






http://www.scie
ncedirect.com/s






ncedirect.com/s
cience/article/pi






cience/article/pi
i/S10523057988






i/S10523057988
0027X






0027X;







http://archneur.







ama-







assn.org/cgi/rep







rint/57/4/478






Lateral Medulla
1. ipsilateral
Wallenberg's
solitary tract
medial
inferior



palate paralysis
syndrome
nucleus (NTS) ;
lemniscus;
cerebellar



(roof of mouth);
“Lateral
http://www.scie
Waxman 86
peduncle



vocal cord
Medullary
ncedirect.com/s

(cerebral



paralysis; loss of 
Syndrome”
cience/article/pi

cortex);



pain/heat
(vertigo, ataxia); 
i/S10538119080

Waxman 86;



sensation on
caused by
1001X;

Smith et al 45



same side of
inferior artery
http://onlinelibr





face/opposite of
occlusion;
ary.wiley.com/d





body (skin?);
trauma; stroke;
oi/10.1002/cne.





loss of facial
Kierman 107,
21105/abstract





sweating (skin);
108,109;






2. diminishment
http://www.spri






pf pharyngeal
ngerlink.com/co






reflex (pharynx); 
ntent/p7662218






limb weakness;
4414hr60/ ;






Kierman
Waxman Ch 7






108,110;
Clinical






http://keur.eldo
Illustration 7-1






c.ub.rug.nl/FILES







/wetenschapper







s/1/478/478.pdf







;







http://stroke.ah







ajournals.org/co







ntent/28/4/809.







abstract;







Brazis 369;







http://www.spri







ngerlink.com/co







ntent/f3488893







72351m38/






Lateral Medulla
ipsilateral plate 
Avellis'
solitary tract
medial
inferior



paralysis; vocal
syndrome;
nucleus (NTS);
lemniscus;
cerebellar



cord paralysis;
dysphagia; acute
http://www.scie
Waxman 86
peduncle



loss of pain/heat stroke;
Kierman 108;
ncedirect.com/s

(cerebral



on ipsilateral
http://www.ncbi
cience/article/pi

cortex);



side of
.nlm.nih.gov/pu
i/S10538119080

Waxman 86;



face/contralater
bmed/8821503;
1001X;

Smith et al 45



al side of body
http://www.ncbi
http://onlinelibr





(face-arm-trunk-
.nlm.nih.gov/pu
ary.wiley.com/d





legs);
bmed/21576937
oi/10.1002/cne.





Kierman 108;

21105/abstract





http://www.ncbi







.nlm.nih.gov/pm







c/articles/PMC2







170182/pdf/v06







5p00255.pdf ;







http://jnnp.bmj.







com/content/65







/2/255.abstract






pons
ipsilateral LMN
Millard Gubler's
midbrain basis
pontine nuclei;
middle


(corticospinal
paralysis
syndrome;
pedunculi
Kierman 101;
cerebellar


fibers/descendin
(face);contralate
trauma;
or: undamaged
Smith 56
peduncle


g fibers)
ral hemiplesia;
Kierman
part of fibers

(cerebellum);



or: undamaged
108;localization
right after

Kierrman 101



fibers before the
in clinical
lesion;

Wxman 89;



lesion;
neurology by
Kierman 101

Brazis et al 357



Kierman 108 ;
braxis/masdeu/






localization in
biller 291;






clinical
http://content.k






neurology by
arger.com/Prod






braxis/masdeu/
ukteDB/produkt






biller 291,553 ;
e.asp?Aktion=Sh






http://content.k
owPDF&ArtikelN






arger.com/Prod
r=000116965&A






ukteDB/produkt
usgabe=234289






e.asp?Aktion=Sh
&ProduktNr=22






owPDF&ArtikelN
3840&filename=






r=000116965&A
000116965.pdf






usgabe=234289







&ProduktNr=22







3840&filename=







000116965.pdf






dorsal pons
ipsilateral LMN
Foville's
pontine nuclei;
middle



(pontine
facial paralysis
Syndrome
Kierman 101;
cerebellar



tegmentum)
(face); ipsilateral 
(lower dorsal
Smith 56
peduncle




conjugate gaze
pontine

(cerebellum);




paralysis (eyes);
syndrome) ;

Kierrman 101;




contralateral
Wall-Eyed

Waxman 89;




hemiparesis;
Internuclear

Brazis et al 357




blepharospasm
Ohtalmoplegia






(eyelid closing);
WEBINO






motor tract
syndrome






damage; facial
(caused by






nerve damage;
stroke; multiple






failure to abduct
schlerosis;






eye;
infections);






Kierman
stroke ;






108,110;
Kierman






http://keur.eldo
108,110,111,121






c.ub.rug.nl/FILES
;






/wetenschapper
http://stroke.ah






s/1/478/478.pdf
ajournals.org/co






;
ntent/11/1/84.a






http://stroke.ah 
bstract; Brazis et






ajournals.org/co al 359;
http://www.spri






ntent/28/4/809.
ngerlink.com/co






abstract;
ntent/f3488893






Brazis 369;
72351m38/ ;






http://www.spri
http://www.ncbi






ngerlink.com/co
.nlm.nih.gov/pu






ntent/f3488893
bmed/21729278






72351m38/






ventral pons
ipsilateral
Raymond's
pontine nuclei
middle



(pontocerebellar 
abducens nerve
Syndrome;
neurons' axons
cerebellar



fibers)
palsy (VI nerve, 
Locked in
(cerebral cortex)
peduncle




lateral rectus
Syndrome
or: undamaged
(cerebellum)




muscle of eye);
(caused by
portion of
or: undamaged




contralateral
Stroke or
pontocerebellar
portion of




hemiparesis (1/2
traumatic brain
fibers right
pontocerebellar




of body);upper
injury due to
before the
fibers right after




motor neuron
obstructed
the lesion;
Kierman 101




quadriplegia,
basilar artery); lesion;
Kierman 101;
Waxman 89;




paralysis of
anarthria
Smith 56
Brazis et al. 357




lower cranial
(speech loss);






nerves,
quadriplegia;






bilateral paresis
Kierman 108;






of horizontal
http://www.spri






gaze;
ngerlink.com.pr






Kierman 108 ;
oxy.library.corne






http://stroke.ah 
II.edu/content/7






ajournals.org/co 
4n878271705ru






ntent/28/4/809.
11/;






abstract;
http://www.ncbi






http://www.ncbi
.nlm.nih.gov/pu






.nlm.nih.gov/pu
bmed/12119076






bmed/12119076






cerebral
ipsilateral
Benedikt's
lenticular
Pontine Nuclei;
medulla


peduncle (
oculomotor
Syndrome;
nucleus aka
Kahle and
oblongata;


pyramidal
abducens nerve
Weber's
corpus striatum
Frotscher 166;
Morris and


fibers/fascicle of
palsy (pupil of
syndrome (i.e.
externus
Morris and
McMurrich 876


cranial nerve 3 ) 
eyes);
Ventral
(olfactory lobe
McMurich 871




contralateral
Midbrain
fasciculi)





hemiparesis;con
Syndrome);
or: unlesioned





tralateral
peduncular
part





hemiplegia
hallucinosis (for
Stricker 416





(face); tremor +
vascular






involuntary
lesions); stroke ; 






movements (red
Dysarthia






nucleus
(Clumsy Hand






destruction);
Syndrome);






heaviness of
Kierman 108;






limbs/difficulty
http://www.harr






using
isonspractice.co






hand/slurred
m/practice/ub/v






speech (disorder
iew/Harrisons%






of articulatory
20Practice/1416






movements of
11/all/Double+30V






tongue + oris
ision;http://ww






muscles);
w.ncbi.nlm.nih.g






unwanted hand
ov/pubmed/188






activity ;
26349






Kierman 108;
http://www.brig






http://onlinelibr
hamandwomens






ary.wiley.com/d
.org/Departmen






oi/10.1002/mds.
is and Services






10084/full;
/neurology/servi






http://www.ncbi
ces/NeuroOphth






.nlm.nih.gov/pu
amology/Images






bmed/18826349
/SelectedPublica






;
tions/Strabismu






http://www.brig
s.pdf ;






hamandwomens
Brazis 361, 362;






.org/Departmen
http://www.ncbi






ts_and_Services
.nlm.nih.gov/pu






/neurology/servi
bmed?term=Gel






ces/NeuroOphth
ler%20TJ%2C%2






amology/Images
OBellur%20SN.%






/SelectedPublica
20Peduncular%2






tions/Strabismu
Ohallucinosis%3






s.pdf;
A%20magnetic%






http://www.scie
20resonance%2






ncedirect.com/s
Oimaging%20co






cience/article/pi
nfirmation%20of






i/S08872171019
%20mesenceph






00034 ;
alic%20infarctio






Brazis 361, 362;
n%20during%20l






Theime's
ife.%20Ann%20






Anatomic Basis
Neurol%201987






of Neurologic
%3B21%3A602%






Diagnosis Atlas
E2%80%93604;






226;
http://www.ncbi






http://www.ncbi
.nlm.nih.gov/pu






.nlm.nih.gov/pm
bmed/17621531






c/articles/PMC1
http://www.scie






073816/
ncedirect.com/s







cience/article/pi







i/S10523057080







01535;http://w







ww.ncbi.nlm.nih







.gov/pmc/article







s/PMC1073816/





dorsal midbrain
conjugate
Parinaud's
occipital cortex 
a) caudal
a) Thalamus;


(superior
upward gaze
syndrome (aka
(corticotectal
nucleus ;
b) primary visual


colliculus,
paralysis w-o
dorsal midbrain
fibers);
b) lateral
cortex;


pretectal area,
paralysis of
syndrome,
Kierman 102-
geniculate
Westerlain 248;


posterior
convergence;
pretectal
103
nucleus (LGN);
http://www.ncbi


commisure etc)
abnormalities of
syndrome,

http://www.ncbi
.nlm.nih.gov/pu



pupil response
Sylvian

.nlm.nih.gov/pu
bmed/21344403



(eyes); paralysis 
aqueduct

bmed/21344403




of vertical gaze; 
syndrome) ;






ipsilateral head
tumor pressure






tilt; vertical
on posterior






diplopia
commissure/pre






(downwards/co
tectal






ntralesional
area/superior






gaze);
colliculi ;






Kierman 108,
trauma; stroke;






121;
Horner's






http://www.ncbi
Syndrome;






.nlm.nih.gov/pu
miningitis/herpe






bmed/20182210
s zoster/syphilis






;
(connective






http://www.scie
tissue






ncedirect.com/s
infections);






cience/article/pi 
Kierman






i/S03038467090
108,121;






02406;
http://stroke.ah







ajournals.org/co







ntent/12/2/251.







abstract;







http://www.ncbi







.nlm.nih.gov/pu







bmed/20182210







;







http://www.scie







ncedirect.com/s







cience/article/pi







i/S03038467090







02406





Middle
ipsilateral facial 
anterior inferior
pontocerebellar
Cerebellum;



cerebellar
paralysis (face),
cerebellar artery
fibers (from
Young et al 105



peduncle aka
impaired facial
(AICA) injury;
pontine nuclei




branchial pontis
sensation (skin);
lateral inferior
neurons' axons);





paralysis of
pontine
Kierman 101





conjugate gaze
syndrome;






to the side of
ataxia;






the lesion
aneurysm;






(eyes);
stroke ; cardiac






contralateral
embolism;






sense loss of
trauma;






temp/pain;
localization in






deafness (ears) ;
clinical






tinnitus (ears);
neurology by






middle
braxis/masdeu/






cerebellar
biller 553;






peduncle
http://www.ncbi






infarction
.nlm.nih.gov/pu






(nystagmus,
bmed/21748288






speech
;






difficulty, ataxia
http://www.ncbi






of limbs/trunk);
.nlm.nih.gov/pu






inner ear
bmed/20572906






dysfunction
;http://www.nc






(vertigo/tinnitus
bi.nlm.nih.gov/p






/bilateral
ubmed/1983486






hearing loss);
5;






(anterior inferior
http://www.ncbi






cerebellar
.nlm.nih.gov/pu






artery-related)
bmed/21631321






localization in







clinical







neurology by







braxis/masdeu/







biller 553;







http://stroke.ah







ajournals.org/co







ntent/33/12/28







07.full;







http://brain.oxf







ordjournals.org/







content/113/1/1







39.abstract?ijke







y=60f163a9bdc3







3efe496746bc1e







ffc8f9c4e1dd9c







&keytype2=tf_ip







secsha;







http://www.ncbi







.nlm.nih.gov/pu







bmed/20572906







;http://www.nc







bi.nlm.nih.gov/p







ubmed/1983486







5;http://www.n







cbi.nlm.nih.gov/







pubmed/197971







77





















TABLE 4






Body Part(s)






Region of CNS
That Have






That is
Diminished
Cause of





Impaired
Function
Impairment
Input Region
Output Region
Connection







C2 root
impairment of
tumors ;
dorsal
spinothalamic
periaquaductal



respiratory
http://www.ncbi
rami/afferent
tract,
grey (midbrain);



function;
.nlm.nih.gov/pu
fibers from
spinomesenceph
thalamus;



Currrent
bmed/21123996
dorsal root
alic tract;
http://www.ncbi



Treatment and

ganglion
http://www.ncbi
.nlm.nih.gov/pu



Diagnostic in

or: right before
.nlm.nih.gov/pu
bmed/2358537



Orthopedics ch

the lesioned part
bmed/2358537
(for cervical



13

of the root;
(for cervical
enlargement





Kierman 62;
enlargement
projections in





Waxman 48-49
projections in
general);






general);
Thieme Color






Thieme Color
Atlas of the






Atlas of the
Human Body,






Human Body,
p558-






p558-
559(reference






559(reference
for cervical






for cervical
enlargement






enlargement
components)






components)



C3 root
jaw/neck;
sensory
dorsal
1) Ventral
1) cerebellum



infrahyoids,
disturbances;
rami/afferent
Spinocerebellar
2)



semispinalis
muscle paresis;
fibers from
Tract;
periaquaductal



capitis and
(trauma)
dorsal root
2) spinothalamic
grey (midbrain);



cervicis,
subluxation of
ganglion
tract,
thalamus;



longissimus
spinal axis;
or: right before
spinomesenceph
1)



capitis and
degenerative
the lesioned part
alic tract;
http://www.ncbi



cervicis,
motor root C3
of the root;
1)
.nlm.nih.gov/pu



intertransversarii 
compression
Kierman 62;
http://www.ncbi
bmed/14337566



, rotatores,
(ventral osseus
Waxman 48-49
.nlm.nih.gov/pu
?dopt=Abstract&



multifidi muscle
compression);

bmed/14337566
holding=npg ;



paresis;diapragm
Brazis et al 93;

?dopt=Abstract&
http://www.ncbi



weakness
http://www.ncbi

holding=npg;
.nlm.nih.gov/pu



/anterior trunk;
.nlm.nih.gov/pu

2)http://www.nc
bmed/2358537



Brazis et al 93;
bmed/21120549

bi.nlm.nih.gov/p
(for cervical



waxman 51


ubmed/2358537
enlargement






(for cervical
projections in






enlargement
general);






projections in
Thieme Color






general);
Atlas of the






Thieme Color
Human Body,






Atlas of the
p558-






Human Body,
559(reference






p558-
for cervical






559(reference
enlargement






for cervical
components);






enlargement
2)






components)
http://www.scie







ncedirect.com/s







cience/article/pii







/S000689939800







4120 (for







cuneate nucleus







in general);







Thieme Color







Atlas of Human







Anatomy Vol III -







Nervous System







and Sensory







Organs 341 (for







cuneate nucleus-







thalamus-cortex







connection)







Thieme Color







Atlas of the







Human Body,







p558-







559(reference







for cervical







enlargement







components)


C4 root
scalene/levator
muscle paresis;
dorsal
spinothalamic
1)



scapulae/trapez
degenerative
rami/afferent
tract,
periaquaductal



oid
motor root C4
fibers from
spinomesenceph
grey (midbrain);



(shoulder)/rhom
compression
dorsal root
alic tract;
thalamus



boid muscles
(ventral osseus
ganglion
1)
2) postcentral



paresis;
compression);
or: right before
http://www.ncbi
cyrus (from



diaphragmic
trauma/birth
the lesioned part
.nlm.nih.gov/pu
cuneate nucleus



paresis +
injury;trauma;
of the root;
bmed/14337566
to thalamus);



pulmonary
compression by
Kierman 62;
?dopt=Abstract&
1)



difficulty;diaphra 
a ganglion;
Waxman 48-49
holding=npg;
http://www.ncbi



gm
Brazis et al 93;

2)http://www.nc
.nlm.nih.gov/pu



weakness/anteri
http://www.ncbi

bi.nlm.nih.gov/p
bmed/14337566



or trunk;
.nlm.nih.gov/pu

ubmed/2358537
?dopt=Abstract&



Brazis et al 93;
bmed/21120549

(for cervical
holding=npg ;



waxman 51


enlargement
http://www.ncbi






projections in
.nlm.nih.gov/pu






general);
bmed/2358537






Thieme Color
(for cervical






Atlas of the
enlargement






Human Body,
projections in






p558-
general);






559(reference 
Thieme Color






for cervical
Atlas of the






enlargement
Human Body,






components)
p558-







559(reference







for cervical







enlargement







components);







2)







http://www.scie







ncedirect.com/s







cience/article/pii







/S000689939800







4120 (for







cuneate nucleus







in general);







Thieme Color







Atlas of Human







Anatomy Vol III -







Nervous System







and Sensory







Organs 341 (for







cuneate nucleus-







thalamus-cortex







connection)







Thieme Color







Atlas of the







Human Body,







p558-







559(reference







for cervical







enlargement







components)


C5 root
neck/shoulder/u
depressed bicets
dorsal
spinothalamic
1)



pper anterior
reflex;
rami/afferent
tract,
periaquaductal



arm pain;
depressed
fibers from
spinomesenceph
grey (midbrain);



sensory
brachioradialis
dorsal root
alic tract;
thalamus



disturbances on
reflex;cervical
ganglion
http://www.ncbi
2) postcentral



lateral arm;
spondylosis(deg
or: right before
.nlm.nih.gov/pu
cyrus (from



muscle paresis
enerative tissue
the lesioned part 
bmed/2358537
cuneate nucleus



for levator
of cervical
of the root;
(for cervical
to thalamus);



scapulae,
vertebrae);
Kierman 62;
enlargement
http://www.ncbi



rhomboids,
cervical
Waxman 48-49
projections in
.nlm.nih.gov/pu



serratus
radiculopathy;

general);
bmed/2358537



anterior,
post-operative

Thieme Color
(for cervical



supraspinatus,
(decompression/

Atlas of the
enlargement



infraspinatus,
spinal cord

Human Body,
projections in



deltoid, biceps,
fusion) C5 palsy

p558-
general);



brachioradialis;
following

559(reference
Thieme Color



diaphragmatic
anterior

for cervical
Atlas of the



paresis (if
decompression

enlargement
Human Body,



damaged C5
and spinal fusion

components);
p558-



fibers reach
for cervical

http://www.scie
559(reference



phrenic nerve);
degenerative

ncedirect.com/s
for cervical



biceps/brachiora
diseases;

cience/article/pii
enlargement



dialis (poor
contributing pre-

/S000689939800
components)



reflex);
existing

4120




hemidiaphragmi
asymptomatic






c paresis +30
damage of the






pulmonary
anterior horn






difficulty;
cells at C3-C4






radicular pain
and C4-C5 levels






(suprascaular
(motor






region of
weakness);






root);deltoid
upper brachial






weakness;
plexus palsies;






Brazis et al 93;
high velocity






http://www.joso
impact (like






nline.org/abstrac 
football) causing






ts/v18n3/356.ht
nerve avulsion;






ml; Waxman 51
trauma;







compression by







a ganglion;







Brazis et al 93;







Frank 1031;







http://www.joso







nline.org/abstrac







ts/v18n3/356.ht







ml;







http://www.ncbi







.nlm.nih.gov/pu







bmed/20461418







;







http://www.scie







ncedirect.com/s







cience/article/pii







/S036350231000







5101;







http://www.ncbi







.nlm.nih.gov/pm







c/articles/PMC2







504282/ ;







Theime Atlas of







Neurology 767-







768





C6 root
lateral/dorsal
hyperflexia (if
dorsal
1) n/a
1) Ventrolateral



forearm pain;
corticalspinal
rami/afferent
2) Spinothalamic
Medulla (VLM)



paresis of
tract is damage);
fibers from
tract (dorsal
Nuclei; Solitary



muscles (erratus
depressed
dorsal root
column);
tract nucleus



anterior, biceps, 
biceps/brachiora
ganglion
1) n/a
(NTS), lateral



pronator teres,
dialis reflex (due
or: right before
2)
reticular nucleus



flexor carpi
to compression
the lesioned part
http://www.scie
(LRt),



radialis,
of C5-6 vertebral
of the root;
ncedirect.com/s
caudal/rostral



brachioradialis,
level); cervical
Kierman 62;
cience/article/pii 
ventrolateral



extensor carpi
spondylosis(deg
Waxman 48-49
/S000689939800
medulla;



radialis longus,
enerative tissue

4120
2) postcentral



supinator, and
of cervical


cyrus (from



extensor carpi
vertebrae);


cuneate nucleus



radialis brevis); 
cervical


to thalamus);



depressed
radiculopathy;up


1)



biceps/brachiora
per brachial


http://www.scie



dialis reflex;
plexus palsies;


ncedirect.com/s



radicular pain
ipsilateral root


cience/article/pii



(posterior
injury;C5-C6


/S156607020200



deltoid
unilateral facet


0346;



region);biceps
dislocation


2)



weakness;
(vertebrae injury


http://www.scie



Brazis et al 93;
due to trauma


ncedirect.com/s



http://www.joso
like car


cience/article/pii



nline.org/abstrac 
accident); high


/S000689939800



ts/v18n3/356.ht
velocity impact


4120 (for



ml;
(football)


cuneate nucleus



Waxman 51
causing nerve


in general);




avulsion;


Thieme Color




trauma;


Atlas of Human




compression by


Anatomy Vol III -




a ganglion;


Nervous System




Brazis et al 93;


and Sensory




Frank 1031;


Organs 341 (for




http://www.joso


cuneate nucleus-




nline.org/abstrac


thalamus-cortex




ts/v18n3/356.ht


connection)




ml;







http://www.scie







ncedirect.com/s







cience/article/pii







/S036350231000







5101;







Johnson Ch 29







(Principles of







Critical Care);







http://www.ncbi







.nlm.nih.gov/pm







c/articles/PMC2







504282/





C7 root
pain in dorsal
compression due
dorsal
1) n/a
1) Ventrolateral



forearm/deep
to disc
rami/afferent

Medulla (VLM)



breast; sensory
herniation at C6-
fibers from

Nuclei; Solitary



disturbances on
7 vertebral level; 
dorsal root

tract nucleus



3rd/4th digits;
cervical
ganglion

(NTS), lateral



paresis of
osteoarthritis;ce
or: right before

reticular nucleus



muscles (
rvical
the lesioned part

(LRt),



serratus
spondylosis
of the root;

caudal/rostral



anterior,
(degenerative
Kierman 62;

ventrolateral



pectoralis major,
tissue of cervical
Waxman 48-49

medulla;



latissimus dorsi,
vertebrae);


1)



pronator teres,
cervical


http://www.scie



flexor carpi
radiculopathy


ncedirect.com/s



radialis, triceps, 
;upper brachial


cience/article/pii



extensor carpi
plexus palsies;


/S156607020200



radialis longus,
trauma;


0346;



extensor carpi
Brazis et al 94;






brevis,extensor
Frank 1031;






digitorum);
http://www.joso






triceps reflex
nline.org/abstrac






depressed;
ts/v18n3/356.ht






pseudomyotonia
ml;






of hand
http://www.scie






(difficulty in
ncedirect.com/s






opening b/c of
cience/article/pii






cervical
/S036350231000






osteoarthritis);
5101 ;






radicular pain
Thieme Atlas of






(interscapular
Neurology 768






region) ;triceps







weakness;







Brazis et al 94;







http://www.joso







nline.org/abstrac







ts/v18n3/356.ht







ml;







Waxman 51






C8 root
pain in the
compression due
dorsal
1) n/a
1) Ventrolateral



medial
to disc
rami/afferent

Medulla (VLM)



arm/forearm;
herniation at C7-
fibers from

Nuclei; Solitary



fifth digit; medial
T1 vertebral
dorsal root

tract nucleus



forearm/hand;
level; ipsilateral
ganglion

(NTS), lateral



paresis of
Horner
or: right before

reticular nucleus



muscles (flexor
Syndrome;
the lesioned part

(LRt),



digitorum
cervical
of the root;

caudal/rostral



superficialis,
radiculopathy;
Kierman 62;

ventrolateral



flexor pollicis
nerve root
Waxman 48-49

medulla;



longus, flexor
blockage ;


1)



digitorum
trauma/birth


http://www.scie



profundus Ito
trauma; tumor


ncedirect.com/s



IV, pronator
of lung apex;


cience/article/pii



quadratus,
ly,phomatous


/S156607020200



abductor pollicis
infiltration;


0346



brevis, opponens
pressure lesion






pollicis, flexor
at elbow;






pollicis brevis, 
all traumatic palsy






lumbricals,
(from a






flexor carpi
blow/knife/glass






ulnaris, abductor
at the wrist or






digiti minimi,
elbow fractures);






opponens digiti
delayed nerve






minimi, flexor
palsy (ages after






digiti minimi, all
an elbow






interossei,
fracture/dislocat






adductor pollicis,
ion etc +vagus






extensor digiti
deformity) ;






minimi, extensor
arthrosis;






carpi ulnaris,
Brazis et al 94;






abductor pollicis
http://www.joso






longus, extensor
nline.org/abstrac






pollicis longus
ts/v18n3/356.ht






and brevis, and
ml;






extensor indicis); 
Thieme Atlas of






depressed finger
Neurology 753,






flexor reflex;
759, 776






razis et al 94;







http://www.joso







nline.org/abstrac







ts/v18n3/356.ht







ml; Thieme Atlas







of Neurology







779







radicular pain







(interscapular/sc







apular region of







nerve root) ;







motor deficit in







hand muscles






T3 root
decreased
arachnoid
dorsal
Dorsal
cerebellum



sensation of skin
calcifications
rami/afferent
Spinocerebellar
(cerebellar



(dermatome);
(caused by
fibers from
Tract;
cortex);



radicular
trauma);
dorsal root
http://www.ncbi
http://www.ncbi



pain/low back
myelography,
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



pain/paralysis;
subarachnoid
or: right before
bmed/14337566
bmed/14337566



Brazis et al 94;
hemorrhage,
the lesioned part
?dopt=Abstract&
?dopt=Abstract&



http://www.ncbi
spinal
of the root;
holding=npg
holding=npg



.nlm.nih.gov/pu
anesthesia;
Kierman 62;





bmed/17149734
http://www.ncbi
Waxman 48-49






.nlm.nih.gov/pu







bmed/17149734





T4 root
decreased
intramecdullary
dorsal
Dorsal
cerebellum



sensation of skin
tumor (spinal
rami/afferent
Spinocerebellar
(cerebellar



(dermatome);nu
metastasis);
fibers from
Tract;
cortex);



mbness in
arachnoid
dorsal root
http://www.ncbi
http://www.ncbi



body/both legs;
calcifications
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



bladder/bowel
(caused by
or: right before
bmed/14337566
bmed/14337566



dysfunction;
trauma);
the lesioned part
?dopt=Abstract&
?dopt=Abstract&



progressive
subarachnoid
of the root;
holding=npg
holding=npg



weakness of
hemorrhage;
Kierman 62;





bilateral lower
http://www.ncbi
Waxman 48-49





extremities;
.nlm.nih.gov/pu






radicular
bmed/19398862






pain/low back
;






pain/paralysis;
http://www.ncbi






Brazis et al 94;
.nlm.nih.gov/pu






http://www.ncbi
bmed/17149734






.nlm.nih.gov/pu







bmed/19398862







;







http://www.ncbi







.nlm.nih.gov/pu







bmed/17149734







;







http://www.ncbi







.nlm.nih.gov/pu







bmed/17149734






T5 root
decreased
T5 nerve root
dorsal
Dorsal
cerebellum



sensation of skin
fistula; trauma
rami/afferent
Spinocerebellar
(cerebellar



(dermatome);
(particularly
fibers from
Tract;
cortex);



Brazis et al 94;
head injuries or
dorsal root
http://www.ncbi
http://www.ncbi



http://www.ncbi
penetrating
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



.nlm.nih.gov/pu
damage to the
or: right before
bmed/14337566
bmed/14337566



bmed/8133999
spine) ;
the lesioned part
?dopt=Abstract&
?dopt=Abstract&




http://www.ncbi
of the root;
holding=npg
holding=npg




.nlm.nih.gov/pu
Kierman 62;






bmed/8133999
Waxman 48-49




T6 root
decreased
schwannoma
dorsal
Dorsal
cerebellum



sensation of skin
(nerve sheath
rami/afferent
Spinocerebellar
(cerebellar



(dermatome);
tumor);
fibers from
Tract;
cortex);



gait control
http://www.scie
dorsal root
http://www.ncbi
http://www.ncbi



difficulty; tactile 
ncedirect.com/s
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



hypaethesia
cience/article/pii 
or: right before
bmed/14337566
bmed/14337566



below T6;
/S096758680600
the lesioned part
?dopt=Abstract&
?dopt=Abstract&



Brazis et al 94;
2384
of the root;
holding=npg
holding=npg



http://www.scie

Kierman 62;





ncedirect.com/s

Waxman 48-49





cience/article/pii







/S096758680600







2384






T7 root
no movement in
T6-T7 injury
dorsal
Dorsal
cerebellum



lower
(trauma);
rami/afferent
Spinocerebellar
(cerebellar



extremities; gait
schwannoma
fibers from
Tract;
cortex);



control difficulty; 
(tumor of nerve
dorsal root
http://www.ncbi
http://www.ncbi



thermic/algic
sheath);
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



hypaethesia
arachnoid
or: right before
bmed/14337566
bmed/14337566



below T7;
calcifications w/
the lesioned part
?dopt=Abstract&
?dopt=Abstract&



http://www.ncbi
possible
of the root;
holding=npg
holding=npg



.nlm.nih.gov/pu
arachnoid
Kierman 62;





bmed/18662744
ossification +
Waxman 48-49





;
nerve root






http://www.scie
compression






ncedirect.com/s
(caused by






cience/article/pii 
trauma or






/S096758680600
interspinal






2384
tumor);







myelography,







subarachnoid







hemorrhage,







spinal anethesia;







http://www.ncbi







.nlm.nih.gov/pu







bmed/18662744







;







O'Rahilly et al ch







41;







http://www.scie







ncedirect.com/s







cience/article/pii







/S096758680600







2384 ;







http://www.ncbi







.nlm.nih.gov/pu







bmed/17149734





T8 root
no movement in
T6-T7 injury
dorsal
Dorsal
cerebellum



lower
(trauma) ; T7-T8
rami/afferent
Spinocerebellar
(cerebellar



extremities;
injury (trauma);
fibers from
Tract;
cortex);



complete
T7 level injury
dorsal root
http://www.ncbi
http://www.ncbi



motor/sensory
(trauma);
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



deficit; lack of
http://www.ncbi
or: right before
bmed/14337566
bmed/14337566



sphincter/sexual
.nlm.nih.gov/pu
the lesioned part
?dopt=Abstract&
?dopt=Abstract&



function and
bmed/18662744
of the root;
holding=npg
holding=npg



control;radicular
;
Kierman 62;





pain/low back
O'Rahilly et al ch 
Waxman 48-49





pain/paralysis;
41.






http://www.ncbi







.nlm.nih.gov/pu







bmed/18662744







;







http://www.ncbi







.nlm.nih.gov/pu







bmed/17149734






T9 root
lack of
T7-T8
dorsal
Dorsal
cerebellum



sphincter/sexual
injury(trauma);
rami/afferent
Spinocerebellar
(cerebellar



function and
arachnoid
fibers from
Tract;
cortex);



control;
calcifications w/
dorsal root
http://www.ncbi
http://www.ncbi



http://www.ncbi
possible
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



.nlm.nih.gov/pu
arachnoid
or: right before
bmed/14337566
bmed/14337566



bmed/18662745
ossification +
the lesioned part
?dopt=Abstract&
?dopt=Abstract&




nerve root
of the root;
holding=npg
holding=npg




compression
Kierman 62;






(caused by
Waxman 48-49






trauma);







myelography,







subarachnoid







hemorrhage,







spinal







anesthesia;







http://www.ncbi







.nlm.nih.gov/pu







bmed/18662744







;







http://www.ncbi







.nlm.nih.gov/pu







bmed/17149734







;







O'Rahilly et al ch







41





T10 root
bilateral
T9 Injury
dorsal
Dorsal
cerebellum



abdominal
(trauma); tumor
rami/afferent
Spinocerebellar
(cerebellar



muscle paresis;
pressure;
fibers from
Tract;
cortex);



trace
http://www.ncbi
dorsal root
http://www.ncbi
http://www.ncbi



movements/hyp
.nlm.nih.gov/pu
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



oethesia (partial
bmed/18662744
or: right before
bmed/14337566
bmed/14337566



loss of
;
the lesioned part
?dopt=Abstract&
?dopt=Abstract&



sensation) in
O'Rahilly et al ch
of the root;
holding=npg
holding=npg



lower
41.
Kierman 62;





extremities; lack

Waxman 48-49





of







sphincter/sexual







function or







control; muscle







spasms;







Brazis et al 94;







http://www.ncbi







.nlm.nih.gov/pu







bmed/18662745






T11 root
excessive
lateral disc
dorsal
Dorsal
cerebellum



protrusion of
herniation
rami/afferent
Spinocerebellar
(cerebellar



abdomen (when
causing
fibers from
Tract;
cortex);



inspiring);
compression on
dorsal root
http://www.ncbi
http://www.ncbi



bilateral
root;
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



abdominal
http://www.ncbi
or: right before
bmed/14337566
bmed/14337566



muscle paresis;
.nlm.nih.gov/pu
the lesioned part
?dopt=Abstract&
?dopt=Abstract&



Brazis et al 94
bmed/18090072
of the root;
holding=npg
holding=npg





Kierman 62;







Waxman 48-49




T12 root
excessive
trauma; nerve
dorsal
Dorsal
cerebellum



protrusion of
root avulsion;
rami/afferent
Spinocerebellar
(cerebellar



abdomen (when
associated
fibers from
Tract;
cortex);



inspiring);
syringomyelia;
dorsal root
http://www.ncbi
http://www.ncbi



bilateral
tumor pressure ;
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



abdominal
lateral disc
or: right before
bmed/14337566
bmed/14337566



muscle paresis;
herniation
the lesioned part
?dopt=Abstract&
?dopt=Abstract&



motor weakness
causing
of the root;
holding=npg
holding=npg



in lower
compression on
Kierman 62;





extremity;
root;
Waxman 48-49





hyperalgesia
http://www.ncbi






below L1;
.nlm.nih.gov/pu






Brazis et al 94;
bmed/19350043






http://www.ncbi
;






.nlm.nih.gov/pu
http://www.ncbi






bmed/19350043
.nlm.nih.gov/pu







bmed/18090072





L1 root
tibial nerve;
herniation of
dorsal
Dorsal
cerebellum



cremasteric
L5/51 disc;
rami/afferent
Spinocerebellar
(cerebellar



reflex; inguinal
lateral disc
fibers from
Tract ;
cortex);



region
herniation
dorsal root
Waxman Ch 5;
Waxman Ch 5;



(groin/lower
causing
ganglion
http://www.ncbi
http://www.ncbi



lateral regions of 
compression on
or: right before
.nlm.nih.gov/pu
.nlm.nih.gov/pu



abdomen); lower
root;
the lesioned part
bmed/14337566
bmed/14337566



abdominal
(L5/S1)
of the root;
?dopt=Abstract&
?dopt=Abstract&



paresis (internal
http://www.neu
Kierman 62;
holding=npg
holding=npg



oblique,
roanatomy.wisc.
Waxman 48-49





transversus
edu/SClinic/Radi






abdominis);
culo/Radiculopat






Waxman 62;
hy.htm;






Brazis et al 95
http://www.ncbi







.nlm.nih.gov/pu







bmed/18090072





L2 root
anterior thigh
meralgia
dorsal
Dorsal
cerebellum



sensory
parethetica due
rami/afferent
Spinocerebellar
(cerebellar



disturbances;
to compression
fibers from
Tract;
cortex);



paresis of body
of nerve; lumbar
dorsal root
Waxman Ch 5;
Waxman Ch 5;



parts:pectineus
radiculopathy;
ganglion
http://www.ncbi
http://www.ncbi



(thigh adduction, 
lumbar disc
or: right before
.nlm.nih.gov/pu
.nlm.nih.gov/pu



flexion, and
herniation into
the lesioned part 
bmed/14337566
bmed/14337566



eversion),
preganglionic
of the root;
?dopt=Abstract&
?dopt=Abstract&



iliopsoas (thigh
region of the
Kierman 62;
holding=npg
holding=npg



flexion),
nerve root;
Waxman 48-49





sartorius (thigh
spinal stetosis;






flexion and
trauma;






eversion),
(meralgia






quadriceps (leg
parethetica/lum






extension), and
bar)http://www.






thigh adductors;
ncbi.nlm.nih.gov






depression of
/pubmed/21294






cremasteric
431;






reflex (of L2) ;







Brazis et al 95;







http://www.ncbi







.nlm.nih.gov/pu







bmed/20431433







;






L3 root
lower anterior
arachnoidal/dur
dorsal
Dorsal
cerebellum



thigh,medial
al defect;
rami/afferent
Spinocerebellar
(cerebellar



knee; paresis in
physical trauma
fibers from
Tract;
cortex);



pectineus (thigh
leading to
dorsal root
http://www.ncbi
http://www.ncbi



adduction,
herniation of
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



flexion, and
nerve root;
or: right before
bmed/14337566
bmed/14337566



eversion),
nerve root
the lesioned part 
?dopt=Abstract&
?dopt=Abstract&



iliopsoas (thigh
entrapment in
of the root;
holding=npg
holding=npg



flexion),
pseudominingoc
Kierman 62;





sartorius (thigh
ele; lumbar
Waxman 48-49





flexion and
spondylolysis;






eversion),
(archnoidal/dura






quadriceps (leg
l/pseudominingo






extension), and
cele/lumbar






thigh adductors;
spondylolysis)






depressed reflex
http://www.joso






of L2-L4 (patellar
nline.org/pdf/v1






reflex) ; S1 root
8i3p367.pdf;






@dorsal lateral







portion of L3







level;quadricepts







femoris







weakness







(knee);







Brazis et al 95;







http://www.joso







nline.org/pdf/v1







8i3p367.pdf;







Waxman 51






L4 root
pain in lower
lumbar
dorsal
Dorsal
cerebellum



back/buttock/an
spondylolysis;inv
rami/afferent
Spinocerebellar
(cerebellar



terlateral
ading tumors
fibers from
Tract;
cortex);



thigh/anterior
involving ala of
dorsal root
http://www.ncbi
http://www.ncbi



leg; sensory
sacrum
ganglion
.nlm.nih.gov/pu
.nlm.nih.gov/pu



disturbances of
infringing on
or: right before
bmed/14337566
bmed/14337566



knee/medial leg;
nerve root;
the lesioned part 
?dopt=Abstract&
?dopt=Abstract&



paresis in
tumor excision;
of the root;
holding=npg
holding=npg



muscles of
neurogenic
Kierman 62;





leg/feet -
hypertrophy
Waxman 48-49





quadriceps (leg
(tibialis anterior 






extension)sartori
muscle) due to






us (thigh flexion
excessive






and
activity;






eversion),tibialis
Brazis et al 95;






anterior (foot
http://www.joso






dorsiflexion and
nline.org/pdf/v1






inversion);
8i3p367.pdf;






depressed
http://www.joso






patellar reflex;
nline.org/abstrac






quadriceps
ts/v18n3/352.ht






femoris
ml;






weakness







(knee);







Brazis et al 95;







http://www.joso







nline.org/pdf/v1







8i3p367.pdf;







http://www.joso







nline.org/abstrac







ts/v18n3/352.ht







ml;







Waxman 51






S1 root
pain in lower
post-osteotomy
dorsal
VPL Thalamus ;
Primary Sensory



back, buttock,
surgery
rami/afferent
Young et al 142
Cortex



lateral thigh,calf; 
complications;
fibers from

(postcentral



sensory
post-dissection
dorsal root

gyrus);



disturbance of
joining of S1,S2
ganglion

Young et al 138-



little toe, lateral 
leaving nerve
or: right before

142; Ropper and



foot, most of the
roots at risk of
the lesioned part

Samuels Ch 9



sole of the foot;
tumor invasion;
of the root;





paresis in
clear cell
Kierman 62;





knee/hip/feet -
sarcoma (tumor
Waxman 48-49





gluteus maximus
arising from S1






(hip extension),
nerve root);






biceps femoris
http://www.joso






(knee flexion),
nline.org/abstrac






gastrocnemius +
ts/v18n3/352.ht






soleus (plantar
ml






flexion of foot),







flexor hallucis







longus (plantar







flexion of foot







and terminal







phalanx of great







toe), flexor







digitorum longus







(plantar flexion







of foot and all







toes except the







large toe), all of







the small







muscles of the







foot, extensor







digitorum brevis







(extension of







large toe + three







medial toes); S1-







S2 (depressed







achilles reflex)







;gastrocnemius







weakness; lower







extremity







parethesia ;







Brazis et al 96;







Waxman 51;







http://www.ncbi







.nlm.nih.gov/pu







bmed/17341045







;






S2 root
lower
iatrogenic injury 
dorsal
VPL Thalamus;
Primary Sensory



limb/bowel/blad
during surgery;
rami/afferent
Young et al 142
Cortex



der functions;
post-dissection
fibers from

(postcentral



Sensory
joining of S1,S2
dorsal root

gyrus);



disturbances for
leaving nerve
ganglion

Young et al 138-



calf, posterior
roots at risk of
or: right before

142; Ropper and



thigh, buttock,
tumor invasion;
the lesioned part

Samuels Ch 9



perianal region;
(surgery/tumors)
of the root;





Brazis et al 96;
http://www.joso
Kierman 62;





http://www.ioso
nline.org/abstrac
Waxman 48-49





nline.org/abstrac
ts/v18n3/352.ht






ts/v18n3/352.ht
ml;






ml
http://www.ncbi







.nlm.nih.gov/pu







bmed/21500136





S3 root
Chronic lower
invasion by
dorsal
VPL Thalamus ;
Primary Sensory



back pain;
tumor; sciatica
rami/afferent
Young et al 142
Cortex



impaired
(nerve root
fibers from

(cerebrum) ;



Sphincter
compression);
dorsal root

Young et al 138-



activity; Sensory 
Tarlov Cysts;
ganglion

142



disturbances for
Cauda Equina
or: right before





calf, posterior
Syndrome(due
the lesioned part





thigh, buttock,
to spinal cord
of the root;





perianal region;
compression by
Kierman 62;





Brazis et al 96;
drug-induced
Waxman 48-49





http://www.ncbi
loculation);






.nlm.nih.gov/pu
(Invasion by






bmed/21286446
tumor)http://w






;
ww.josonline.org






http://www.ncbi
/abstracts/v18n3






.nlm.nih.gov/pu
/352.html;






bmed/18034793
http://www.ncbi






;
.nlm.nih.gov/pu







bmed/21500136







;http://www.ncb







i.nlm.nih.gov/pu







bmed/21286446





















TABLE 5





Region 
Body Part(s)






of CNS
That Have






That is
Diminished
Cause of
Input 
Output



Impaired
Function
Impairment
Region
Region
Connection







small center
i)loss of
a) Syringomyelia
posterior root
ventral posterior
cerebral cortex


lesions
pain/temp
b) Chiari Type
ganglion axons
nucleus of
(primary sensory


(spinothalamic
sensibilities in
I, II,Dandy
aka dorsal root
thalamus
cortex or SI


tract
the segment
Walker
or: right before
or: right after
area) ;


decussating
w/lesion
Malformations,t
lesioned part of
lesioned part of
Young et al 149-


fibers)
(Decussating
raumatic
tract;
tract;
150;



fibers in the
paraplegia,
Snell 142;
Kierman 292;




ventral white
spinal trauma,
Waxman Ch 5
Waxman




commisure) -
spinal cord
Sec III;
56,57,58




anethesia for
tumors,






shoulders/upper
arachnoiditis,my






limbs;muscle
elitis;






wasting in upper
a) Waxman 66,






limbs; ii)anterior
68;






horn
Kierman 77






atrophy/paresis/
b)Brazis et al






areflexia;
105






i)Waxman 68;







ii) Brazis et al







105






posterior/lateral
cervical cord;
a) Posterolateral
dorsal root
dorsal column
primary sensory


columns in
thoratic cord;
Column Disease
or: right before
nuclei (cuneate
cortex (SI area);


upper spinal
lumbar cord
(lack of B12);
lesioned part of
nuclei)
Kierman 292;


cord (dorsal
degeneration;
AIDS; HTLV-1;
tract;
or: right after
Young et al 149-


column-medial
parethesia in
tropical spastix 
Adams' and
lesioned part of
150;


lemniscus
feet/hands;
paraperesis;
Victor's
tract;
http://www.ncbi


pathway) aka
Dorsal column
cervical
Neurology Ch 9
http://www.goo
.nlm.nih.gov/pu


dorsal cornu or
dysfunction
spondylosis

gle.com/url?sa=t 
bmed/3096488 ;


lateral
(spine/skin
(chronic disk

&source=web&c
http://www.ncbi


cornu/horn
sensation);
degeneration) ;

d=1&ved=OCBo
.nlm.nih.gov/pu



Brazis et al 106;
b)sensory

QFjAA&url=http
bmed/8899636;



Tsementzis 208
ataxia/loss of

%3A%2F%2Fww
http://www.goo




proprioception

w.biomed.cas.cz
gle.com/url?sa=t




and vibration

%2Fphysiolres%
&source=web&c




sense/bilateral

2Fpdf%2F53%25
d=1&ved=OCBo




spasticity/hyper

20Suppl%25201
QFjAA&url=http




reflexia

%2F53_5125.pdf
%3A%2F%2Fww




c) trauma;

&ei=etY2TuP9Llr
w.biomed.cas.cz




a)Bravis 106;

ZgQf_sdnsDA&u
%2Fphysiolres%




http://www.acc

sg=AFQjCNG_02
2Fpdf%2F53%25




essmedicine.co

zJSpiKjPhNyxivc- 
20Suppl%25201




m/content.aspx

VBjOpWww
%2F53_5125.pdf




?alD=2319519&


&ei=etY2TuP9Llr




searchStr=cervic


ZgQf_sdnsDA&u




al+spine+diseas


sg=AFQjCNG_02




e; b) Differential


zJSpiKjPhNyxivc-




diagnosis in


VBjOpWww




neurology and







neurosurgery: a







clinician's







pocket guide







By S. A.







Tsementzis 208







c)







http://www.ncbi







.nlm.nih.gov/pu







bmed/3096488





complete
a) Vertebral
1) traumatic
undamaged
undamaged
neocortex


transection of
Tenderness
spine injuries
parts of all
parts of all
(cingulate gyrus)


spinal cord
(percussion?) b)
(stabbing/gunfir
ascending tracts
ascending tracts
for sensory


(transverse
inhibition of
e/diving into a
from below the
from above the
ascending tracts;


myelopathy)
reflex anywhere
shallow pool),
lesion; all
lesion; all
Kierman 289



in the cord
tumor (e.g.,
descending
descending




below the
metastatic
tracts from
tracts from




lesion; Spincter
carcinoma,
above the lesion
below the lesion




disturbance;
lymphoma),
;
;




back/radicular
multiple
Brazis et al 103
Brazis et al 103




pain c)Tactile
sclerosis,






stimulus above
,vascular






lesion
disorders,spinal






d) all
epidural






motor/sensory
hematoma






functions below
(usually






the level of
secondary to






lesion;
anticoagulants)






a) Current
or abscess,






Diagnosis and
paraneoplastic






Treatment
myelopathy,






(Keith Stone) ch
autoimmune






35
disorders,






b)Total
herniated






Transverse
intervertebral






Lesions of the
disc, and






Spinal Cord
parainfectious






c)Adam's and
or postvaccinal






Victor's
syndromes






Neurology,
2) herpes






ch44:
simplex,






http://www.acc
influenza,






essmedicine.co
Epstein-Barr






m/content.aspx
virus),






?alD=3640629&
immunisations






searchStr=transv
(smallpox,






erse+myelitis
influenza) and






d) Brazis et al
intoxication






103
(baclofen,







penicillins, lead);







; Systemic







Lupus;







3)tetraplegia (if







upper cervical







cord







transection);







paraplegia iif







transection







between the







cervical and







lumbosacral







enlargements;







1. Brazis et al







103;







Jeffrey et al Arch







Neurol. 1993







May;50(5):532-







5. ;







2)http://ard. bmj







.com/content/5







9/2/120.abstrac







t







3) Kierman 76





Dorsal Root
elecated touch-
ALS, HIV/AIDS,
peripheral
dorsal
medulla


ganglion (aka
pressure
tumor
nervous
(posterior) horn
oblongata;


posterior root
sensation
(particularly
system's
cells
cerebellum;


ganglion)
thresholds
Small Cell Lung
afferent/sensory
or: part of the
Color Atlas of



(dorsal
Cancer SCLC);
fibers
dorsal root right
Textboom of



column/spinoce
Vitamin B6
or: part of dorsal
after the
Anatomy:



rebellar tract
intoxication (ex:
Human
lesioned
Nervous system



dysfunction due
body building
root right before 
ganglion;
and Sensory



to
regimen,PMS
the lesioned
Color Atlas of
Organs 50-56



demyelination);i
treatment);
ganglion ;
Textboom of




ncreased sense
chemotherapy
Brazis et al 89
Human




of
drugs especially

Anatomy:




pain(hyperalgesi
platinum based

Nervous system




a)/pain due to
agents (ex:

and Sensory




negligible
Ciplatin,

Organs 50-56




stimulus(allodyn
carboplatin,






ia) ; gait
oxaliplatin etc) ;






impairment,
Guillian Barre,






autonomic
Miller Fisher






system
Sundrome,






impairment;
opthalmoplegia;






(vitamin
rheumatoid






overdose) loss
arthritis,






of tendon reflex, 
Sjogren's






progressive
syndrome,






sensory ataxia;
Epstein-barr,






bilnk reflex
measles,






abnormalities;
varicella zoster;






(ALS)
(ALS)






http://www.ncbi
http://www.ncbi






.nlm.nih.gov/pu
.nlm.nih.gov/pu






bmed/17929040
bmed/17929040






;
;






http://www.ncbi
http://www.ncbi






.nlm.nih.gov/pu
.nlm.nih.gov/pu






bmed/20628092
bmed/20628092






;
;






http://jn.physiol
http://pn.bmj.co






ogy.org/content
m/content/10/6






/84/2/798.full;
/326.full






http://pn.bmj.co







m/content/10/6







/326.full






Anterior horn
upper motor
Spinal muscular
ventral root
dorsal
Color Atlas of


(aka anterior
neurons (any
Atrophies; ALS
(sensory
horn/columns;
Textboom of


column/ventral
striated muscle);
(degeneration of
nerves);
Bonica's
Human


horn)
progressive
upper motor
Bonica's
Management of
Anatomy:



weakness of the
neurons/Charco
Management of
Pain 1497;
Nervous system



bulbar,
is Lou Gehrig's); 
Pain 1497;
http://onlinelibr
and Sensory



limb/thoracic/
progressive
http://onlinelibr 
ary.wiley.com/d
Organs 50



abdominal
bulbar palsy,
ary.wiley.com/d
oi/10.1002/cne.




musculature;
progressive
oi/10.1002/cne.
901790304/pdf




upper motor
muscular
901790304/pdf





neuron
atrophy (lower






spasticity/paresi 
motor






s;
syndrome),






Brazis et al 107- 
primary lateral






109;
sclerosis (upper






http://jnnp.bmj.
motor






com/content/74
syndrome),astro






/9/1250.abstrac
cytosis; trauma;






t;
stroke






Tsementzis 209
(ipsilateral







cerebral







peduncular







atrophy); non-







traumatic







cardiac arrest







(due to spinal







cord ischemia) ;







Brazis et al 109,







http://jnnp.bmj.







com/content/74







/9/1250.abstrac







t;







http://www.ncbi







.nlm.nih.gov/pu







bmed/18024577







;







http://www.ncbi







.nlm.nih.gov/pu







bmed/7884198





Upper Cervical
contralateral
Cruciate

medial
cerebral


Cord
upper extremity
Paralysis

lemniscus ;
hemisphere


(cervicomedullar
paresis and
(caused by

Smith et al 34- 
(sensory-motor


y junction
ipsilateral lower
traumatic

35
cortex) ;


injuries or
extremity
injuries mostly);


cerebellum;


malformations)
paresis; lower
http://www.upt


Smith et al 34-



extremity
odate.com/cont


35;



weakness
ents/anatomy-


http://www.ncbi



(muscles
and-localization-


.nlm.nih.gov/pu



proximal to the
of-spinal-cord-


bmed/19793979



lesion) ;
disorders/a bstra






facial/limb
ct/18






hypethesia;







Brazis et al 112;







http://www.upt







odate.com/cont







ents/anatomy-







and-localization-







of-spinal-cord-







disorders/abstra







ct/18






Complete
ipsilateral zone
Brown-Sequard
below the lesion
dorsal column
cerebral cortex


hemisection of
of cutaneous
Syndrome
in dorsal
nuclei (cuneate
(primary sensory


spinal cord
anethesia in the
(stab/gunshot
column; below
nuclei);
cortex or SI


(dorsal column)
segment of the
wounds)
the lesion in

area) ;



lesion (due to
;syringomelia
spinothalamic
http://www.goo




undecussated
(loss of
tract; below the
gle.com/url?sa=t 
Kierman 292;



afferent fibers
pain/temperatur 
lesion for any
&source=web&c
Young et al 149-



that had already
e sensation at
afferent fibers;
d=1&ved=0CBo
150;



entered the
multiple levels);
Waxman 68
QFjAA&url=http
http://www.ncbi



spinal cord); loss
spinal cord

%3A%2F%2Fww
.nlm.nih.gov/pu



of
tumor;

w.biomed.cas.cz
bmed/3096488 ;



propioceptive/vi
hematomyelia

%2Fphysiolres%
http://www.ncbi



bratory/2-pt
(hemorrhage

2Fpdf%2F53%25
.nlm.nih.gov/pu



discrimination
into the spinal

20Suppl%25201
bmed/8899636;



sense below the
cord) ;

%2F53_5125.pdf
http://www.goo



lesion (dorsal
Waxman 68 ;

&ei=etY2TuP9Llr
gle.com/url?sa=t



column
Brazis et al 105

ZgQf_sdnsDA&u
&source=web&c



damage); spastic


sg=AFQjCNG_02
d=1&ved=OCBo



weakness at


zJSpiKjPhNyxivc-
QFjAA&url=http



level of lesion;


VBjOpWww
%3A%2F%2Fww



loss of



w.biomed.cas.cz



temperature/pai



%2Fphysiolres%



n sensation



2Fpdf%2F53%25



below the level



20Suppl%25201



(decussated



%2F53_5125.pdf



spinothalamic



&ei=etY2TuP9Llr



tract fibers



ZgQf_sdnsDA&u



damage);



sg=AFQjCNG_02



Waxman 68;



zJSpiKjPh Nyxivc-



Brazis et al 105



VBjOpWww


myelin sheaths
axon
Multiple
node of ranvier
next node of



of axons (PNS +
degeneration;
Sclerosis; Acute
before the
ranvier after the



CNS)
failure of signal
inflammatory
lesion;
lesion in the




transmission;
demyelinating
Waxman 25
direction of the




slowing of nerve
polyneuropathy

action potential




conduction;
(AIDP), Guillain

pathway;




motor
Barre; traumatic

Waxman 25




weakness,
brain injury (for






paraparesis,
oligodendrite






paresthesia
injuries)+






(numbing of
subsequent






skin) , diplopia
degeneration of






(double vision),
white matter






nystagmus
tracts; Miller-






(involuntary eye
Fischer






movement),
Syndrome;






tremor, ataxia,
copper






impairment of
deficiency ;






deep sensation,
Waxman 302;






and bladder
DeLisa et al 899;






dysfunction;
Adams and






blindness,
Victor's






tremor;
Neurology Ch 36






Young et al 13;
;






Waxman
http://www.ncbi






24,38,302;
.nlm.nih.gov/pu






Adams and
bmed/21669255






Victor's
;






Neurology Ch 36
http://www.ncbi







.nlm.nih.gov/pu







bmed/21631649







;







http://www.ncbi







.nlm.nih.gov/pu







bmed/20685220



















TABLE 6





Region of CNS





That is





Impaired
Input Region
Output Region
Connection







I Olfactory
bipolar cells in
Olfactory Bulb
Olfactory


Nerve
olfactory
(glomeruli)
association



epithelium
or: part of
cortex (frontal



(cilia at surface 
normal nerve
lobe);



of epithelium in
right after the
Kierman 262-



superior nasal
lesion;
263



concha + upper
Young et al 262;




1⁄3 of nasal
http://www.ncbi




septum)
.nlm.nih.gov/pu




or: part of
bmed/21704681




normal nerve





before lesion;





Young et al 270;





http://www.blac





kwellpublishing.





com/patestas/c





hapters/15.pdf




VIII Vestibular
vestibular
Vestibular nuclei
Vestibulocerebel


(Vestibulocochle
ganglion aka
or: part of
lum aka


ar Nerve)
scarpa's
normal nerve
flocculonodar



ganglion
right after the
lobe of



(hair cells of
lesion;
cerebellum;



ampullary crests
Young et al 262;
Kierman 335



in semicircular
Kierman 335;




ducts/maculae
Shumway-Cook




of saccule and
69




utricle)





or: part of





normal nerve





Young et al 272;





Shumway-Cook





69




VIII Cochlear
otic ganglion
Cochlear nuclei 
primary auditory


(Vestibulocochle
(auriculotempor
(second-order
area of cerebral


ar Nerve)
al nerve
neurons)
cortex (aka



supplying
or: part of
superior



paratoid gland)
normal nerve
temporal gyrus);



or: part of
right after the 
Kierman 326



normal nerve
lesion;




before lesion;
Young et al 262,




Schuenke et al
161




150;





Young et al 272;




V Trigeminal
trigeminal
spinal trigeminal
VPM Thalamus


Nerve
ganglion aka
nucleus
(then to primary



sublingual/Langl 
(caudal);
sensory cortex);



ey's ganglion (
principal
Waxman ch 8



free nerve ends
trigeminal




in muscous
nucleus




mouth
or: part of




membrane aka
normal nerve




oral mucosa;
right after the




anterior
lesion;




scalp/face; free 
Young et al 270;




nerve endings in





tympanic





membrane,





supratentorial





meninges);





submandibular





ganglion





or: part of





normal nerve





before lesion;





Young et al 270;





http://www.ncbi





.nlm.nih.gov/pu





bmed/13886632





;





http://www.scie





ncedirect.com/s





cience/article/pi





i/S03043940100





03423




VII Facial Nerve 
Pterygopaline
Solitary Nucleus
ipsilateral



ganglion;
or: part of
cerebral cortex



submandibular
normal nerve
(primary



ganglion;
right after the
gustatory



geniculate
lesion;
cortex) ;



ganglion (taste
Waxman 113-
Kierman 131;



buds in anterior
115
Young et al 193-



2⁄3 of mouth)

194



or: part of





normal nerve





(chorda tympani





fibers) before





lesion;





Young et al





237,271;





Waxman 113




IX
otic ganglion
Solitary Nucleus
cerebral cortex


Glossopharynge
(auriculotempor
(taste +
(post central


al Nerve
al nerve
chemoreceptor
gyrus) ;



supplying
and
Kierman



paratoid gland)
baroreceptor
214,215



or: part of
reflexes)/Spinal 




normal nerve
Trigeminal




before lesion;
Nucleus (general




Young et al. 237;
sensations)




Waxman 257;
or: part of




Snell 403,405
normal nerve





right after the





lesion;





Young et al 269;





Brazis et al 325



X Vagus Nerve
cardiac ganglion;
Solitary nucleus
cerebral cortex;



bronchial
(inferior
Young et al 253



ganglion;
ganglion)/Spinal




pulmonary
trigeminal




ganglion; enteric
nucleus(superior




ganglion;intestin
)




al ganglion;
or: part of




proximal colon
normal nerve




ganglion
right after the




or: part of
lesion;




normal nerve
Young et al 273;




before lesion;





Young et al 237;





http://www.ncbi





.nlm.nih.gov/pu





bmed/2435865;





http://www.ncbi





.nlm.nih.gov/pu





bmed/8946336









Although in the examples above we describe and build encoders in a modular fashion with a specific set of algorithmic steps, it is evident that algorithms or devices with substantially similar input/output relationships can be built with different steps, or in a non-modular fashion, for example, by combining any two or three of the steps in to a single computational unit, such as an artificial neural network.
Given the encoders of the present disclosure, it is possible to generate data sets, without the collection of physiological data, that can be used, for example, to develop parameters for alternate spatiotemporal transformations, or to train a neural net, to produce identical or similar output using methods that are well known in the art. The explicit description of the encoders thus enables the development of prosthetics, as well as other devices, such as, but not limited to, bionics (e.g., devices providing supranormal capability) and robotics (e.g., artificial sensing systems).
The scope of the present invention is not limited by what has been specifically shown and described herein. Those skilled in the art will recognize that there are suitable alternatives to the depicted examples of materials, configurations, constructions and dimensions. Numerous references, including patents and various publications, are cited and discussed in the description of this invention. The citation and discussion of such references is provided merely to clarify the description of the present invention and is not an admission that any reference is prior art to the invention described herein. All references cited and discussed in this specification are incorporated herein by reference in their entirety.
While various inventive embodiments have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein, and each of such variations and/or modifications is deemed to be within the scope of the inventive embodiments described herein. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the inventive teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific inventive embodiments described herein. It is, therefore, to be understood that the foregoing embodiments are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, inventive embodiments may be practiced otherwise than as specifically described and claimed. Inventive embodiments of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the inventive scope of the present disclosure. The above-described embodiments can be implemented in any of numerous ways. For example, the embodiments may be implemented using hardware, software or a combination thereof. When implemented in software, the software code can be executed on any suitable processor or collection of processors, whether provided in a single computer or distributed among multiple computers.
Further, it should be appreciated that a computer may be embodied in any of a number of forms, such as a rack-mounted computer, a desktop computer, a laptop computer, or a tablet computer. Additionally, a computer may be embedded in a device not generally regarded as a computer but with suitable processing capabilities, including a Personal Digital Assistant (PDA), a smart phone or any other suitable portable or fixed electronic device.
Also, a computer may have one or more input and output devices. These devices can be used, among other things, to present a user interface. Examples of output devices that can be used to provide a user interface include printers or display screens for visual presentation of output and speakers or other sound generating devices for audible presentation of output. Examples of input devices that can be used for a user interface include keyboards, and pointing devices, such as mice, touch pads, and digitizing tablets. As another example, a computer may receive input information through speech recognition or in other audible format.
Such computers may be interconnected by one or more networks in any suitable form, including a local area network or a wide area network, such as an enterprise network, and intelligent network (IN) or the Internet. Such networks may be based on any suitable technology and may operate according to any suitable protocol and may include wireless networks, wired networks or fiber optic networks.
A computer employed to implement at least a portion of the functionality described herein may comprise a memory, one or more processing units (also referred to herein simply as “processors”), one or more communication interfaces, one or more display units, and one or more user input devices. The memory may comprise any computer-readable media, and may store computer instructions (also referred to herein as “processor-executable instructions”) for implementing the various functionalities described herein. The processing unit(s) may be used to execute the instructions. The communication interface(s) may be coupled to a wired or wireless network, bus, or other communication means and may therefore allow the computer to transmit communications to and/or receive communications from other devices. The display unit(s) may be provided, for example, to allow a user to view various information in connection with execution of the instructions. The user input device(s) may be provided, for example, to allow the user to make manual adjustments, make selections, enter data or various other information, and/or interact in any of a variety of manners with the processor during execution of the instructions.
The various methods or processes outlined herein may be coded as software that is executable on one or more processors that employ any one of a variety of operating systems or platforms. Additionally, such software may be written using any of a number of suitable programming languages and/or programming or scripting tools, and also may be compiled as executable machine language code or intermediate code that is executed on a framework or virtual machine.
In this respect, various inventive concepts may be embodied as a computer readable storage medium (or multiple computer readable storage media) (e.g., a computer memory, one or more floppy discs, compact discs, optical discs, magnetic tapes, flash memories, circuit configurations in Field Programmable Gate Arrays or other semiconductor devices, or other non-transitory medium or tangible computer storage medium) encoded with one or more programs that, when executed on one or more computers or other processors, perform methods that implement the various embodiments of the invention discussed above. The computer readable medium or media can be transportable, such that the program or programs stored thereon can be loaded onto one or more different computers or other processors to implement various aspects of the present invention as discussed above.
The terms “program” or “software” are used herein in a generic sense to refer to any type of computer code or set of computer-executable instructions that can be employed to program a computer or other processor to implement various aspects of embodiments as discussed above. Additionally, it should be appreciated that according to one aspect, one or more computer programs that when executed perform methods of the present invention need not reside on a single computer or processor, but may be distributed in a modular fashion amongst a number of different computers or processors to implement various aspects of the present invention.
Computer-executable instructions may be in many forms, such as program modules, executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Typically the functionality of the program modules may be combined or distributed as desired in various embodiments.
Also, data structures may be stored in computer-readable media in any suitable form (e.g., non-transitory media). For simplicity of illustration, data structures may be shown to have fields that are related through location in the data structure. Such relationships may likewise be achieved by assigning storage for the fields with locations in a computer-readable medium that convey relationship between the fields. However, any suitable mechanism may be used to establish a relationship between information in fields of a data structure, including through the use of pointers, tags or other mechanisms that establish relationship between data elements.
Also, various inventive concepts may be embodied as one or more methods, of which an example has been provided. The acts performed as part of the method may be ordered in any suitable way. Accordingly, embodiments may be constructed in which acts are performed in an order different than illustrated, which may include performing some acts simultaneously, even though shown as sequential acts in illustrative embodiments.
As used herein the term “light” and related terms (e.g. “optical”) are to be understood to include electromagnetic radiation both within and outside of the visible spectrum, including, for example, ultraviolet and infrared radiation.
As used herein the term “sound” and related terms (e.g. “audio”) are to be understood to include vibratory waves in any medium (e.g., gas, fluid, liquid, solid, etc.) both within and outside of the spectrum audible to humans, including, for example, ultrasonic frequencies.
All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms.
Variations, modifications and other implementations of what is described herein will occur to those of ordinary skill in the art without departing from the spirit and scope of the invention. While certain embodiments of the present invention have been shown and described, it will be obvious to those skilled in the art that changes and modifications may be made without departing from the spirit and scope of the invention. The matter set forth in the foregoing description and accompanying drawings is offered by way of illustration only and not as a limitation.
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## Claims

1. A method improving or restoring neural function in a mammalian subject in need thereof, the method comprising:
using an input receiver to record an input signal generated by a first set of nerve cells;
using an encoder unit comprising a set of encoders to generate a set of coded outputs in response to the input signal, wherein:
generating the set of coded outputs comprises transforming the input signal based on experimental neural function data of an unimpaired subject; and
the experimental neural function data comprises:
a first response in the unimpaired subject corresponding to the first set of nerve cells, and
a second response in the unimpaired subject corresponding to a second set of nerve cells;


using the coded outputs to drive an output generator; and
using the output generator to activate the second set of nerve cells wherein the second set of nerve cells is separated from the first set of nerve cells by an impaired set of signaling cells;
wherein the second set of nerve cells produces a response that is substantially the same as the second response in the unimpaired subject; and
wherein said generating the set of coded outputs further comprises tuning the input signal based on a gain factor corresponding to:
a magnitude difference between the first response in the unimpaired subject and the input signal generated by the first set of nerve cells; or
a size difference between the unimpaired subject and the mammalian subject.

2. The method of claim 1, wherein:
the first set of nerve cells comprises supplementary motor area neurons;
the second set of nerve cells comprises spinal motor neurons; and
the impaired set of signaling cells comprises primary motor cortex neurons.

3. The method of claim 1, wherein the transformation further comprises:
generating the input signal as a time resolved series of values {right arrow over (a)} corresponding to the pattern of neural activity generated in the first set of nerve cells; and
transforming the values {right arrow over (a)} to a time resolved series of output values {right arrow over (c)} by applying a transformation.

4. The method of claim 3, wherein {right arrow over (c)} is a vector valued function, wherein each element of the vector is a value corresponding to a firing rate of a single cell or small group of cells from the second set of nerve cells.

5. The method of claim 4, wherein {right arrow over (c)} is a vector valued function, wherein each element of the vector is a value corresponding to the total firing rate of the second set of nerve cells.

6. The method of claim 4, wherein {right arrow over (c)} is a vector valued function, wherein each element of the vector is a value corresponding to the total firing rate of a respective subpopulation of the second set of nerve cells, and wherein the second set of nerve cells comprises motor neurons, and each subpopulation innervates a different respective muscle.

7. The method of claim 3, wherein the transformation further comprises:
a set of spatiotemporal linear filters; and
a nonlinear function.

8. The method of claim 7, wherein the spatiotemporal linear filters are parameterized by a set of K weights, and wherein K is in the range of 5-20.

9. The method of claim 7, wherein the nonlinear function is parameterized as a cubic spline function with M knots.

10. The method of claim 9, wherein M is in the range of 2-20.

11. The method of claim 7, wherein the spatiotemporal linear filters operate over P time bins, each having a duration Q.

12. The method of claim 11, wherein P is in the range of 5-20.

13. The method of claim 12, wherein Q is in the range of 10 ms-100 ms.

14. The method of claim 1, wherein the transformation is characterized by a set of parameters; and wherein the set of parameters corresponds to a result of fitting the transformation to the experimental neural function data obtained by:
exposing the unimpaired subject to a broad range of reference stimuli;
recording the first response in the unimpaired subject corresponding to the first set of nerve cells;
recording the second response in the unimpaired subject corresponding to the second set of nerve cells.

15. The method of claim 14, wherein the second response comprises the firing rate of individual nerve cells.

16. The method of claim 14, wherein the broad range of reference stimuli comprises at least one chosen from the list consisting of:
motion in an environment comprising one or more obstacles;
manipulation of objects having different weights; and
moving a cursor to one of several locations on a display.

17. The method of claim 14, wherein the reference stimuli comprises an unpredictable load, and wherein the unpredictable load comprises an irregular terrain, grade, or load.

18. A device improving or restoring neural function in a mammalian subject in need thereof, the device comprising:
an input receiver configured to record an input signal generated by a first set of nerve cells;
an output generator configured to activate a second set of nerve cells, wherein the second set of nerve cells is separated from the first set of nerve cells by an impaired set of signaling cells; and
an encoder unit comprising a set of encoders that generate a set of coded outputs in response to the input signal, wherein:
the encoder unit is configured to generate the set of coded outputs by transforming the input signal based on experimental neural function data of an unimpaired subject;
the experimental neural function data comprises:
a first response in the unimpaired subject corresponding to the first set of nerve cells, and
a second response in the unimpaired subject corresponding to the second set of nerve cells; and


the set of coded outputs control the output generator to activate the second set of nerve cells to produce a response to the input signal that is substantially the same as the second response in the unimpaired subject; and
wherein the encoder unit is configured to generate the set of coded outputs by, at least in part, tuning the input signal based on a gain factor corresponding to:
a magnitude difference between the first response in the unimpaired subject and the input signal generated by the first set of nerve cells; or
a size difference between the unimpaired subject and the mammalian subject.

19. The device of claim 18, wherein the output generator comprises a light outputting device configured to selectively apply light to a light-activated transducer to activate the second set of nerve cells.

20. A non-transitory computer readable media having computer-executable instruction comprising instruction for executing steps comprising:
recording an input signal generated by a first set of nerve cells;
using an encoder unit comprising a set of encoders to generate a set of coded outputs in response to the input signal, wherein:
generating the set of coded outputs comprises transforming the input signal based on experimental neural function data of an unimpaired subject; and
the experimental neural function data comprises:
a first response in the unimpaired subject corresponding to the first set of nerve cells, and
a second response in the unimpaired subject corresponding to the second set of nerve cells; and


using the coded outputs to control an output generator to activate the second set of nerve cells wherein the second set of nerve cells is separated from the first set of neurons by an impaired set of signaling cells;
wherein the second set of nerve cells produces a response to the input signal that is substantially the same as the second response in the unimpaired subject; and
wherein said generating the set of coded outputs further comprises tuning the input signal based on a gain factor corresponding to:
a magnitude difference between the first response in the unimpaired subject and the input signal generated by the first set of nerve cells; or
a size difference between the unimpaired subject and the mammalian subject.