Patent Publication Number: US-2020276444-A1

Title: Methods of sensing cross-frequency coupling and neuromodulation

Description:
RELATED APPLICATIONS 
     The present application is a continuation of U.S. patent application Ser. No. 15/197,333, filed Jun. 29, 2016, which claims the benefit of U.S. Provisional Patent Application Ser. No. 62/188,176 filed Jul. 2, 2015, entitled “SENSING CROSS-FREQUENCY CORRELATION,” which are incorporated herein by reference. 
    
    
     BACKGROUND 
     Neurostimulation (NS) systems are devices that generate electrical pulses and deliver the pulses to nervous tissue to treat a variety of disorders. For example, spinal cord stimulation (SCS) has been used to treat chronic and intractable pain. Another example is deep brain stimulation (DBS), which has been used to treat movement disorders such as Parkinson&#39;s disease and affective disorders such as depression. SCS therapy, delivered via epidurally implanted electrodes, is a widely used treatment for chronic intractable neuropathic pain of different origins. Traditional tonic therapy evokes paresthesia covering painful areas of a patient. During SCS therapy calibration, the paresthesia is identified and localized to the painful areas by the patient in connection with determining correct electrode placement. 
     Recently, new stimulation therapies such as burst stimulation and high frequency stimulation, have been developed, in which closely spaced high frequency pulses are delivered. In general, conventional neurostimulation systems seek to manage pain and other pathologic or physiologic disorders through stimulation of select nerve fibers that carry pain related signals. However, nerve fibers and brain tissue carry other types of signals, not simply pain related signals. 
     Although some neurological disorders have been treated through known neurostimulation methods, many other neurological disorders exhibit physiological complexity, functional complexity, or other complexity and have not been adequately treated through known neurostimulation methods. 
     SUMMARY 
     In accordance with embodiments disclosed herein, optimal targets within the nervous system are selected for neuromodulation. The optimal targets are selected according to network connectivity within the nervous system of a patient according to selected embodiments. For example, the brain of a patient may be modeled as a complex adaptive system of one or more neural networks. The brain may be viewed as exhibiting small world topology characteristics. That is, the brain functions as a modular scale free hierarchical network (e.g., fractal in organization). Also, the brain functions in the presence of noise (equivalently variability in neural activity). In a noisy, hierarchical organization, the brain functions as a complex adaptive network of interconnected modules. 
     Certain connectivity between neural populations in the brain may be defined by structural connectivity. The structural connectivity may be determined using diffusion tensor imaging (DTI), diffusion spectrum imaging (DSI) or diffusion kurtosis imaging (DKI) as examples. Connectivity may also be the result of functional connectivity in a network. The functional connectivity may be determined by correlation in neural activity in one or more respective brain areas or brain networks. Also, connectivity may be related to effective connectivity, which can be considered directional functional connectivity, through the result of information transfer between neural nodes and networks. 
     Functional connectivity between respective neural networks is detected using detection of cross-frequency coupling according to some representative embodiments. Neural activity in nodes of respective networks is measured using suitable sensors and the neural activity is suitably processed. Specifically, neural activity in the respective nodes is analyzed to identify activity within specific frequency bands or in specific discrete frequencies. The activity in the respective frequency bands or discrete frequencies is analyzed to determine whether cross-frequency coupling or nesting is present. Also, it is determined whether any cross-frequency coupling or nesting in the respective nodes is physiological or pathological. If pathological activity is detected, appropriate stimulation is provided to address the pathological activity. 
     In some embodiments, frequency analysis is performed to determine the lower neural frequency that exhibits correlation to the higher neural frequency in the cross-frequency coupling relationship. For example, a neurological disorder of a patient may cause a first frequency (that is cross coupled to a second frequency in one or more locations in the brain) to be lowered. For example, a healthy or physiological cross-frequency coupling may exhibit correlation between activity within the alpha frequency band and activity within the gamma frequency band. A neurological disorder may cause the cross-frequency relationship to change whereby the cross-frequency coupling is exhibited between activity within the theta frequency band and activity within the gamma frequency band. By sensing pathological cross-frequency coupling, suitable stimulation may be provided to one or more locations in the brain to address the pathological neural activity. Tonic, burst, noise, and/or nested stimulation patterns may be applied as examples. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1A  illustrates an example neurological stimulation (NS) system for electrically stimulating a predetermined site area to treat one or more neurological disorders or conditions in accordance with embodiments herein. 
         FIG. 1B  illustrates an example neurological stimulation (NS) systems for electrically stimulating a predetermined site area to treat one or more neurological disorders or conditions in accordance with embodiments herein. 
         FIG. 1C  depicts an NS system that delivers stimulation therapies in accordance with embodiments herein. 
         FIG. 2A  illustrates example stimulation leads that may be used for electrically stimulating the predetermined site to treat one or more neurological disorders or conditions in accordance with embodiments herein. 
         FIG. 2B  illustrates example stimulation leads that may be used for electrically stimulating the predetermined site to treat one or more neurological disorders or conditions in accordance with embodiments herein. 
         FIG. 2C  illustrates example stimulation leads that may be used for electrically stimulating the predetermined site to treat one or more neurological disorders or conditions in accordance with embodiments herein. 
         FIG. 2D  illustrates example stimulation leads that may be used for electrically stimulating the predetermined site to treat one or more neurological disorders or conditions in accordance with embodiments herein. 
         FIG. 2E  illustrates example stimulation leads that may be used for electrically stimulating the predetermined site to treat one or more neurological disorders or conditions in accordance with embodiments herein. 
         FIG. 2F  illustrates example stimulation leads that may be used for electrically stimulating the predetermined site to treat one or more neurological disorders or conditions in accordance with embodiments herein. 
         FIG. 2G  illustrates example stimulation leads that may be used for electrically stimulating the predetermined site to treat one or more neurological disorders or conditions in accordance with embodiments herein. 
         FIG. 2H  illustrates example stimulation leads that may be used for electrically stimulating the predetermined site to treat one or more neurological disorders or conditions in accordance with embodiments herein. 
         FIG. 2I  illustrates example stimulation leads that may be used for electrically stimulating the predetermined site to treat one or more neurological disorders or conditions in accordance with embodiments herein. 
         FIG. 3  illustrates an example of the various brainwave frequency bands in accordance with embodiments herein. 
         FIGS. 4A-4G  illustrate examples of cross-frequency coupling variations that may be used in accordance with embodiments herein. 
         FIG. 5  illustrates a model of a portion of the brain with interest directed to neural modules in accordance with embodiments herein. 
         FIG. 6  illustrates a model reflecting the memory functionality of a brain in accordance with embodiments herein. 
         FIG. 7A  illustrates models proposed, in the 2007 Jensen paper, regarding computational roles for cross-frequency interactions between theta and gamma oscillations by means of phase coding in accordance with embodiments herein. 
         FIG. 7B  illustrates models proposed, in the 2007 Jensen paper, regarding computational roles for cross-frequency interactions between theta and gamma oscillations by means of phase coding in accordance with embodiments herein. 
         FIG. 8A  illustrates an example of a nested stimulation waveform that may be delivered in connection with nested therapies to brain tissue (or brain tissue) of interest in accordance with embodiments herein. 
         FIG. 8B  illustrates an example of a nested stimulation waveform that may be delivered in connection with nested therapies to brain tissue (or brain tissue) of interest in accordance with embodiments herein. 
         FIG. 8C  illustrates an alternative example of a nested stimulation waveform that may be delivered in connection with nested therapies to brain tissue (or brain tissue) of interest in accordance with embodiments herein. 
         FIGS. 9A-9F  illustrate alternative nested stimulation waveforms that may be utilized in accordance with embodiments herein. 
         FIG. 10  illustrates leads implanted for stimulation of neural networks in response to analysis of cross-coupling or nesting activity in a patient according to embodiments herein. 
         FIG. 11  illustrates a flowchart for providing neurostimulation in response to detection of cross-frequency coupling activity in a patient according to embodiments herein. 
         FIG. 12  illustrates how multiple frequencies may be coupled leading to hierarchical cross-frequency coupling. 
     
    
    
     DETAILED DESCRIPTION 
     While multiple embodiments are described, still other embodiments of the described subject matter will become apparent to those skilled in the art from the following detailed description and drawings, which show and describe illustrative embodiments of disclosed inventive subject matter. As will be realized, the inventive subject matter is capable of modifications in various aspects, all without departing from the spirit and scope of the described subject matter. Accordingly, the drawings and detailed description are to be regarded as illustrative in nature and not restrictive. 
     I. Definitions 
     Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. For purposes of the description, the following terms are defined below. Further, additional terms are used herein that shall have definitions consistent with the definitions set forth in U.S. Pat. No. 8,401,655, which is expressly incorporated herein by reference in its entirety. 
     As used herein, the use of the word “a” or “an” when used in conjunction with the term “comprising” in the claims and/or the specification may mean “one,” but it is also consistent with the meaning of “one or more,” “at least one,” and “one or more than one.” Still further, the terms “having”, “including”, “containing” and “comprising” are interchangeable and one of skill in the art is cognizant that these terms are open ended terms. 
     As used herein, the term “burst firing” or “burst mode” refers to an action potential that is a burst of high frequency spikes/pulses (e.g. 400-1000 Hz) (Beurrier et al., 1999). Burst firing acts in a non-linear fashion with a summation effect of each spike/pulse. One skilled in the art is also aware that burst firing can also be referred to as phasic firing, rhythmic firing (Lee 2001), pulse train firing, oscillatory firing and spike train firing, all of these terms used herein are interchangeable. 
     As used herein, the term “tonic firing” or “tonic mode” refers to an action potential that occurs in a linear fashion. 
     As used herein, the term “burst” refers to a period in a spike train that has a much higher discharge rate than surrounding periods in the spike train (N. Urbain et al., 2002). Thus, burst can refer to a plurality of groups of spike pulses. A burst is a train of action potentials that, possibly, occurs during a ‘plateau’ or ‘active phase’, followed by a period of relative quiescence called the ‘silent phase’ (Nunemaker, Cellscience Reviews Vol 2 No. 1, 2005.) Thus, a burst comprises spikes having an inter-spike interval in which the spikes are separated by 0.5 milliseconds to about 100 milliseconds. Those of skill in the art realize that the inter-spike interval can be longer or shorter. Yet further, those of skill in the art also realize that the spike rate within the burst does not necessarily occur at a fixed rate; this rate can be variable. 
     The terms “pulse” and “spike” are used interchangeably to refer to an action potential. Yet further, a “burst spike” refers to a spike that is preceded or followed by another spike within a short time interval (Matveev, 2000), in other words, there is an inter-spike interval, in which this interval is generally about 100 ms but can be shorter or longer, for example 0.5 milliseconds. 
     II. Cross-Frequency Coupling and Nesting Activity 
     It has been proposed that activity between respective neural networks or modules occurs through intrinsic coupling modes (“ICMs”). The ICMs are reflected in cross-frequency coupling activity and are discussed in the article “Intrinsic Coupling Modes: Multiscale Interactions in Ongoing Brain Activity,” by Engel et al., Neuron, Volume 80, Issue 4, 20 Nov. 2013, pages 867-886, which is incorporated herein by reference. Through analysis of recordings of neural activity in respective networks in the brain, ICMs were shown to have relevance for the characterization of functional networks in ongoing activity. ICMs can be exhibited in phase-ICMs and envelope ICMs. Phase ICMs exhibit coupling in phase relationships (coherence or imaginary coherence). Envelope ICMs exhibit coupling in envelope correlation (amplitude or power correlation). Most commonly, power to phase cross-frequency coupling (e.g., gamma activity nested on theta activity) is exhibited in a number of physiological neural activities.  FIG. 12  depicts graph  1200  including multiple neural modules in which multiple frequencies are coupled leading to hierarchical cross-frequency coupling. 
     For example, it has been reported that transient coherence of phase synchronization binds distributed neural assemblies with long range connections (such as those shown in  FIG. 5 ). Local activity within modules is in high frequency bands (beta and gamma neural activity bands) while long distance communication between modules occurs in low frequency bands (infraslow (0-1 Hz), delta, theta, and alpha neural activity bands). Communication between modules occurs via nesting or cross-frequency coupling. 
       FIGS. 3, 4A-4G, 5, 6, and 7A-7B  depict various frequency and waveform characteristics associated with neural activity including cross-frequency coupling.  FIG. 3  illustrates an example of the various brainwave frequency bands which include infraslow waves  302  (from 0 to 1 Hz); delta waves  304  (1-4 Hz); theta waves  306  (4-8 Hz); alpha waves  308  (8-12 Hz), beta waves  310  (12-30 Hz), gamma waves  312  (greater than 30 Hz), and sigma waves (not shown) (greater than 500 Hz). Individual brainwave frequency bands and combinations of brainwave frequency bands are associated with various mental, physical and emotional characteristics. It should be recognized that the cutoff frequencies for the frequency bands for the various types of brain waves are approximations. Instead, the cutoff frequencies for each frequency band may be slightly higher or lower than the examples provided herein. 
     Neural oscillations from various combinations of the brainwave frequency bands have been shown to exhibit coupling with one another, wherein one or more characteristics of one type of brainwave effect (or are affected by) one or more characteristics of another type of brainwave. In general, the coupling phenomenon is referred to as cross-frequency coupling, various aspects of which are described in the papers referenced herein. Combinations of frequency bands couple with one another to different degrees, while the coupling of various types of brainwaves may occur in connection with physiologic behavior or pathologic behavior. For example, theta and gamma frequency coupling has been identified at the hippocampalcortical in connection with physiologic behavior, but in thalamocortical activity this same theta-gamma coupling should be considered pathological, as normal activity consists of alpha-gamma coupling, except in sleep stages. Delta-gamma and delta-beta frequency coupling have been identified in connection with physiological reward system activity as well as in autonomic nervous system activity. As another example, alpha-gamma frequency coupling has been identified at the pulvinar region in connection with physiological processes mediating attention. 
       FIGS. 4A-4G  illustrate examples of cross-frequency coupling variations that may be used and/or detected in accordance with embodiments herein. There are different principles of cross-frequency interactions.  FIGS. 4A-4G  illustrate various example brain waves  402 - 408 . As one example, a carrier wave  402  may correspond to a slow oscillatory signal in the theta band (e.g. 8 Hz). Although the frequency remains fairly constant, the power (as denoted by line  440 ) of the signal fluctuates over time. The gamma oscillations can interact in different ways with other signal oscillations. 
     The brain waves  403 - 408  illustrate examples of how the carrier and secondary waves  402  and  403  may be combined. For example, the wave  403  as illustrated, has been frequency coupled to the carrier wave  402  in a power to power matter such that the amplitude of the secondary wave  402  reduces (as denoted at intermediate region  410 ) as the amplitude of the carrier wave  402  reduces (as denoted in region  412 ). The amplitude of the secondary wave  403  is at a maximum in the regions  414  and  416  corresponding to the maximum amplitudes of the carrier wave  402 . The fluctuations in power of the faster gamma oscillations are correlated with power changes in the lower frequency band. This interaction is independent of the phases of the signals. 
     The brainwave  404  represents the carrier and secondary waves  402  and  403 , as frequency coupled in a phase to phase manner. Given that the carrier and secondary waves  402  and  403  are aligned in phase with one another, the brainwave  404  exhibits a relatively even signal with little notable phase shift. Phase-locking occurs between oscillations at different frequencies. In each slow cycle, there are four faster cycles and their phase relationship remains fixed. 
     The brainwave  405  represents the carrier and secondary waves  402  and  403 , as frequency coupled in a phase to power manner. For example, the amplitude of the resulting brainwave  405  is modulated based on the phase of the carrier wave  402 . Accordingly, the brainwave  405  exhibits a maximum in amplitude in regions  418  which correspond to the positive 90° phase shift point (at reference numerals  420 ) in the carrier wave  402 . The brainwave  405  exhibits a minimum amplitude in regions  422  which correspond to the negative 90° phase shift point (at reference numerals  424 ) in the carrier wave  402 . Hence, in the example of brainwave  405 , the amplitude of the higher frequency brainwave is modulated/determined by the phase of the lower frequency carrier wave. 
     The brain waves  406 - 408  reflect the carrier and secondary waves  402  and  403  when coupled in different manners, namely phase to frequency (brainwave  406 ), power to frequency (brainwave  407 ) and frequency to frequency (brainwave  408 ). It is recognized that the brain waves illustrated in  FIGS. 4A-4G  represent non-limiting examples and may be shaped in the numerous other manners. The different types of cross-frequency interaction are not mutually exclusive. For instance, the phase of theta oscillations might modulate both frequency and power of the gamma oscillations. 
     Hierarchical cross-frequency coupling (as shown in  FIG. 12 ) is a cross-frequency coupling between more than two discrete frequencies or frequency bands. For example, gamma may be nested on alpha or theta which itself may be nested on delta and this may be nested on infraslow oscillations. It is clear that from a practical point of view this also means that for simplification infraslow-gamma nesting (or cross-frequency coupling) may be the result of more complex hierarchical cross-frequency coupling. 
     The brain organization is shaped by an economic trade-off between minimizing costs and allowing efficiency in connection with adaptive structural and functional topological connectivity patterns. For example, a low-cost, but low efficiency, organization would represent a regular lattice type topology. At an opposite end of the spectrum, a random topology would be highly efficient, but be more economically costly. 
     In accordance with embodiments disclosed herein, the brain of a patient is modeled as a complex adaptive system of one or more neural networks. The brain may be viewed as exhibiting small world topology characteristics. That is, the brain functions as a modular scale free hierarchical network (e.g., fractal in organization). Also, the brain functions in the presence of noise (equivalently variability in neural activity)—see, for example, U.S. Pat. No. 8,682,441 by De Ridder, which is incorporated herein by reference. In a noisy, hierarchical organization, the brain functions as a complex adaptive network of interconnected modules. 
     In a network connectivity framework, the centrality of a node refers to how many of the shortest paths between all other node pairs in a network pass through the respective node. As discussed herein, a hub refers to a network node in a neurological network which exhibits a high degree of centrality. Neurological hubs connect to may other brain areas. “Rich club” neurological sites refer to neurological sites that are hubs and are connected to many other hubs. Rich club sites integrate neurological activity from different networks and different neurological modules. According to some embodiments, sites for neuromodulation are selected according to identified hubs (for example feeder hubs or hubs of the rich club or core). 
     Certain connectivity between neural populations in the brain may be defined by structural connectivity. The structural connectivity may be determined using diffusion tensor imaging (DTI), diffusion spectrum imaging (DSI) or diffusion kurtosis imaging as examples. 
     Connectivity may also be the result of functional connectivity in a network. The functional connectivity may be determined by correlation in activity in one or more respective networks using multiple electrodes to detect neural activity in relevant brain locations. Any number of suitable mechanisms may be employed to measure neuronal activity for suitable processing. 
     For example, EEG (or electroencephalogram) is a digital recording of brainwave activity. QEEG (Quantitative EEG), popularly known as brain mapping, refers to a comprehensive analysis of brainwave frequency bandwidths that make up the raw EEG. QEEG is recorded the same way as EEG, but the data acquired in the recording are used to create topographic color-coded maps that show electrical activity of the cerebral cortex. 
     In an QEEG analysis, the electrical activity of the brain is measured by placing a number of electrodes or sensors about the head of a patient and the sensors are connected to a recording device. Electrical activity is recorded using the sensors for typically five to thirty minutes. 
     The data representing the recorded electrical activity is suitably processed. The processing provides complex analysis of brainwave characteristics such as symmetry, phase, coherence, amplitude, power and dominant frequency. Suitable processing enables the correlation, coherence or phase synchronization (total coherence, instantaneous coherence, lagged phase coherence with total coherence=instantaneous+lagged phase coherence), and relevant activity metrics indicative of functional connection between brain locations to be identified. 
     The analysis enables activity falling above or below a statistical norm to be identified for locations within the brain. Also, the activity may identify activity above or below the norm for relevant brainwave frequency bands (infraslow, delta, theta, alpha, beta, gamma and sigma bands as examples). The activity variance from the norm can be expressed relative to a calculated standard deviation of activity data. 
     Further, the QEEG analysis further enables functional connectivity to be identified by coherence analysis of activity between different neural sites. The functional connectivity can be likewise expressed in terms of above or below the norm relative to a standard deviation calculation. 
     Additional and/or alternative processing of recordings of electrical activity in the brain of a patient may be employed to assist identification of variations in functional connectivity related to a neurological disorder according to some embodiments. For example, QEEG combined with LORETA (Low Resolution Electromagnetic Tomography) enables examining of deep structures of the brain slice by slice, as well as viewing 3-dimensional models of the brain and may provide a suitable analysis to identify functional connectivity resulting from a neurological disorder to be treated according to representative embodiments. 
     Also, the BrainWave software application (available from the Department of Clinical Neurophysiology, VU University Medical Center, Amsterdam, The Netherlands) is an application for the analysis of multivariate neurophysiological data sets (such as EEG data sets). The BrainWave application provides several measures of functional connectivity (coherence, phase coherence, imaginary coherence, PLI and synchronization likelihood) among other relevant neural activity metrics. The functional connectivity mapping of the BrainWave application may be employed to assist identification of variations in functional connectivity related to a neurological disorder in a patient according to some embodiments. 
     In some embodiments, a network representation of neural activity is created using graph and network concepts. The graph representation may be patterned according to a mathematical representation of a neural network composed of interconnected elements or sites. The representation may involve construction and processing according to Graph Theory (mathematical study of graphs/networks). From the representation, the network topology of the neural activity may be analyzed according to mathematical analysis of shapes and spaces, concerned with the invariant properties of space that are preserved under continuous deformations (bending, stretching). Also, topological distance does not necessarily imply close physical distances. Thus, physical distances between nodes, transmission rates, and/or signal types may differ in two networks and yet their topologies may be identical. 
       FIG. 5  illustrates a model of a portion of the brain with interest directed to neural modules  502  and  504 . Local activity within modules  502  and  504  generally exhibits high frequency brain waves/oscillations (as generally denoted by the links  506  and  508 ). For example, the high-frequency brain waves/oscillations may represent beta and gamma waves. The neural modules  502  and  504  communicate with one another over long-distance communications links (as denoted at  510  and  512 ). The communications links  510 ,  512  between distributed neural modules  502 ,  504  occur through the use of low frequency brain waves (e.g. infraslow, Delta, Theta and Alpha waves). The communication between modules  502 ,  504  utilizes nesting or cross-frequency coupling between the low frequency brain waves (traveling between distributed neural modules) and the high frequency brain waves (within corresponding neural modules). In this manner, transient coherence or phase synchronization binds distributed neural assemblies/modules within the brain through dynamic (and potentially long-range) connections. Nested therapy may be utilized to facilitate long-distance communication links. 
     Hubs are nodes with high degree (or high centrality). The degree of a node is the number of connections that link it to the rest of the network. Degrees of all the network&#39;s nodes form a degree distribution. Assortativity is the correlation between the degrees of connected nodes. Positive assortativity indicates that high-degree nodes tend to connect to each other (rich club). Clustering coefficient quantifies the number of connections that exist between the nearest neighbors of a node as a proportion of the maximum number of possible connections. Path length is the minimum number of edges that must be traversed to go from one node to another. Each module contains several densely interconnected nodes, and there are relatively few connections between nodes in different modules. Connection density is the actual number of edges in the graph as a proportion of the total number of possible edges and is the simplest estimator of the physical cost. Connection density is an indirect measure of global efficiency. Centrality of a node measures how many of the shortest paths between all other node pairs in the network pass through it. 
     Most brain disorders are hub disorders. For example, lesions in neural hubs are linked to amyotrophic lateral sclerosis, dystonia, developmental dyslexia, anorexia nervosa, obsessive-compulsive disorder, Parkinson&#39;s disease, hereditary ataxia, dementia in Parkinson&#39;s, chronic pain, panic disorder, attention deficit hyperactivity disorder, bipolar affective disorder, multiple sclerosis, frontotemporal dementia, obstructive sleep apnea, Autism, schizophrenia, Alzheimer&#39;s disease, Asperger syndrome, Huntington&#39;s disease, depressive disorder, right temporal lobe epilepsy, post traumatic stress disorder, progressive supranuclear palsy, left temporal lobe epilepsy, and juvenile myodonlc epilepsy. Accordingly, representative embodiments employ neurostimulation of one or more hubs (possibly rich club sites or feeder hubs) to treat any of the neurological disorders discussed herein. 
     One or more hubs and/or rich club sites associated with a respective neurological disorder in a patient may be identified from the representation of neural activity generated by the measurement and processing operations discussed herein. The activity and cross-coupling between nodes, hubs, and/or rich club sites may be identified and compared to activity and coupling exhibited by healthy controls. Relevant deviations from the healthy controls are used to identify neural hubs and/or rich club sites for neuromodulation to treat the respective neurological disorder. 
     Improper neural connectivity (associated with neural hubs and rich club or core sites) as detected using the operations discussed herein is addressed using neuromodulation of identified sites. As previously discussed, various EEG, MEG or functional MRI measurements and processing may be employed to analyze coupling associated with respective hubs. Coupling between respective sites may be identified, for example, in reference to envelope correlation of neural activity at the various neural sites. 
       FIG. 6  illustrates a model reflecting the memory functionality of a brain. Memory has spatial and temporal characteristics  602  and  604 . Memories are encoded through low frequency coupling between parahippocampal area  606 , frontal area  608  and parietal (PFC) area  610 . The spatial and temporal characteristics  602 ,  604  of memory are multiplexed along common pathways through different frequencies. For example, the spatial characteristics  602  of memory are carried within the Delta wave frequency band, while the temporal characteristics  604  of memory are carried within the theta wave frequency band. Nested therapy may be utilized to facilitate spatial and/or temporal characteristics for memories. 
       FIGS. 7A and 7B  illustrate models proposed, in the 2007 Jensen paper, regarding computational roles for cross-frequency interactions between theta and gamma oscillations by means of phase coding.  FIG. 7A  illustrates a model for working memory, in which individual memory representations are activated repeatedly in theta cycles. Each memory representation is represented by a subset of neurons in the network firing synchronously. Because different representations are activated in different gamma cycles, the gamma rhythm serves to keep the individual memories segmented in time. As reported by Jensen, the number of gamma cycles per theta cycle determines the span of the working memory.  FIG. 7B  illustrates a model accounting for theta phase precession in rats. Positional information is passed to the hippocampus, which activates the respective place cell representations and provokes the prospective recall of upcoming positions. In each theta cycle, time-compressed sequences are recalled at the rate of one representation per gamma cycle. 
     While certain cross-frequency coupling is exhibited in physiological or normal activity as reported by Engel, other types of cross-frequency coupling may be developed in selected brain locations as a result of one or more neurological disorders. Also, cross-frequency coupling caused by one or more neurological disorders may occur intermittently. Representative embodiments detect persistent or intermittent pathological cross-frequency coupling and provide neurostimulation to address the detected cross-frequency coupling to treat the one or more neurological disorders in a patient. 
     When pathological cross-frequency coupling is identified in a patient, an implantable stimulation pulse generator and implantable leads may be implanted in the patient to provide therapeutic stimulation. According to some embodiments, electrodes using one or more deep brain or cortical leads are implanted in or adjacent to two different sites associated with the pathological cross-frequency coupling. Respective electrodes may be employed to analyze neural activity to detect when pathological neural activity or connectivity is present. Respective electrodes may be employed to provide suitable electrical stimulation when pathological activity is detected. 
       FIG. 10  depicts a patient with implanted cortical leads  1001  and  1002 . Lead  1001  is disposed over region  1011  and lead  1002  is disposed over region  1012 . One or both of regions  1011  and  1012  may be a hub and/or a rich club neural site within a neurological network. Electrodes of leads  1001  and  1002  may be employed to measure neural activity (e.g., local field potential) in regions  1011  and  1012 . The measured neural activity may be suitably processed (e.g., by performing the operations discussed in  FIG. 11 ) to identify cross-frequency coupling in activity in regions  1011  and  1012 . If the identified cross-frequency coupling is determined to be pathological, suitable stimulation may be provided using one or more electrodes of leads  1001  and  1002 . Specifically, the various electrodes of leads  1001  and  1002  may be employed to deliver electrical pulses to appropriate sites within regions  1011  and  1012 . 
     Referring to  FIG. 11 , neurostimulation may be provided to a patient to treat a neurological disorder by detecting cross-frequency coupling or nesting activity in a patient according to embodiments described herein. In  1101 , an implantable stimulation system samples neuronal activity (e.g., local field potential (LFP)) using multiple electrodes or sensors and sampling electronic circuitry (including one or more analog-to-digital converters, for example). The sampled neuronal activity is suitably processed. The processing and analysis of neuronal activity may be performed by the processor of an implantable pulse generator and/or an external processor-based device in wireless communication with implantable components according to some embodiments 
     In  1102 , suitable processing such as bandpass filtering may be applied using one or more analog and/or digital filters to separate neural activity associated with respective frequency bands. For example, neural activity may be processed to identify activity in respective neural activity bands (sigma, gamma, beta, alpha, theta, delta, infraslow bands). 
     In  1103 , the instantaneous amplitude and/or phase in respective activity bands are determined. The instantaneous amplitude and/or phase in the respective activity bands may be determined using Fast Fourier Transform (FFT), Hilbert transforms, wavelet analysis, waveform-based estimation (via identification of intra-band waveform maxima, minima, and zero crossings), and suitable techniques as described in the journal article “Cross-frequency coupling between neuronal oscillations,” by Jensen, Trends Cogn. Sci. 11: 267-269 (2007) and other references. Phase orthogonalization of signals may be employed before analyzing power envelope correlations (equivalently removing, after Fourier transformation, components of the same phase for the two respective signals). 
     In  1104 , frequency relationships may be determined (such as the cross-frequency coupling relationships shown in  FIGS. 4A-4G ). The determination of frequency relationships may include determination of the frequency of a low frequency carrier component of cross-frequency coupling or neural activity nesting. Also, the determination frequency relationships may include determination of frequency of high frequency information processing related activity. The determination of frequency relationships may include determining an amount or percentage of time that identified coupling or nesting activity with identified frequency characteristics have occurred. 
     In  1105 , a logical determination is made whether pathological cross-frequency coupling or nesting activity is detected. If so, suitable neurostimulation is applied to one or more neural sites (in  1106 ). 
     In some embodiments, pathological neuronal coupling is detected by examining a lower frequency carrier component of the neuronal activity. If the lower frequency carrier component in a physiological or healthy state is in a theta neural activity band at one or more identified site(s), detection of neuronal coupling within an alpha neural activity band carrier component is indicative of pathological activity. In certain embodiments, the change in the low frequency carrier component from theta to alpha is measured in one or more thalamocortical sites. Suitable stimulation may be applied to one or more sites when pathological neuronal coupling is detected. 
     In other embodiments, the physiological neuronal activity exhibits a lower frequency carrier component in the alpha frequency band. Pathological activity is detected when the lower frequency carrier deviates from the theta frequency band into the alpha frequency band. In certain cases, deviation of the lower frequency carrier component is associated with a distress or maladaptive coping response in patients due to a neurological disorder. A pathological change of the lower frequency carrier from alpha to theta may be observed in thalamo-cortical sites (e.g., Pulvinar-cortex) for information processing. Also, a pathological change of the lower frequency carrier from alpha to theta may be observed in Accumbens-cortical sites for reward-based information processing. Suitable stimulation may be applied to one or more sites when pathological neuronal coupling is detected. 
     In other embodiments, the physiological neuronal activity exhibits a higher frequency information component in the gamma frequency band. However, physiological neuronal activity in the gamma frequency band is transient in a physiological or healthy state. The activity is typically related to information processing (bottom-up prediction error by respective neuronal assemblies or modules). The activity waxes and wanes as information processing occurs and, hence, gamma activity in a healthy state is intermittent. However, persistent activity detected in the gamma band is indicative of pathological activity. Suitable stimulation may be applied to one or more sites when pathological neuronal activity is detected. 
     In some embodiments, analysis of cross-frequency coupling is employed to treat tinnitus in patients. Tinnitus is a noise in the ears, often described as ringing, buzzing, roaring, or clicking. Subjective and objective forms of tinnitus exist, with objective tinnitus often caused by muscle contractions or other internal noise sources in the area proximal to auditory structures. In subjective forms, tinnitus is a neurological condition and is only audible only to the subject. Tinnitus varies in perceived amplitude, with some subjects reporting barely audible forms and others essentially deaf to external sounds and/or incapacitated by the intensity of the perceived noise. 
     Tinnitus is usually constantly present, e.g., a non-rational valence is attached to the internally generated sound, and there is no auditory habituation to this specific sound, at this specific frequency. Thus, tinnitus is the result of hyperactivity of lesion-edge frequencies, and auditory mismatch negativity in tinnitus patients is specific for frequencies located at the audiometrically normal lesion edge (Weisz 2004). 
     As pathological valence of the tinnitus sound is mediated by burst firing, burst firing is increased in tinnitus in the extralemniscal system (Chen and Jastreboff 1995; Eggermont and Kenmochi 1998; Eggermont 2003), in the inner hair cells (Puel 1995; Puel et al., 2002), the auditory nerve (Moller 1984), the dorsal and external inferior colliculus (Chen and Jastreboff 1995), the thalamus (Jeanmonod, Magnin et al., 1996) and the secondary auditory cortex (Eggermont and Kenmochi 1998; Eggermont 2003). 
     According to some embodiments, the severity or loudness of tinnitus is correlated with functional connectivity in theta between the left parrahippocampal cortex (PHC) and the left secondary auditory cortex (A2). Specifically, the tinnitus loudness is correlated to the percentage of time that theta-gamma nesting is present in functional connectivity between these sites. Detection of theta-gamma nesting in tinnitus patients that exceeds a threshold amount of percentage of time may be employed to trigger application of electrical stimulation by an implantable neurostimulation system to treat tinnitus in a patient according to some embodiments. 
     In some embodiments, nested stimulation may be applied to one or more neural network sites in response to detection of pathological cross-frequency coupling or nesting activity. Nested stimulation according to respective embodiments stimulate neuronal sites according to different types of physiological neural oscillations or “brain waves” across the cortex. The different types of neural oscillation or brain wave activity can be decomposed into distinct frequency bands that are associated with particular physiologic and pathologic characteristics. 
     As explained herein, nested stimulation may be applied such that two, three or more frequency bands are coupled to one another to achieve various results. As noted above, the lower band represents a carrier wave with higher frequency bands nested on the lower carrier wave. The higher frequency bands carry content to be utilized by the targeted neural modules. For example, the high-frequency content may be superimposed into the phase of the lower carrier wave, such as in connection with external information transmission. Alternatively, the high-frequency content may be added while maintaining phase synchronization. Optionally, the high-frequency content may be added through amplitude or frequency modulation to the lower carrier wave. It is recognized that the high-frequency content may be added in other manners as well, based on the particular neural region of interest and desired effect that is being sought. 
     Nested stimulation according to some embodiments applies multiple frequency bands to form a stimulation waveform or pattern. The waveform may be analog waveform. Alternatively, the stimulation pattern may include discontinuous pulses in other embodiments. The frequency bands may include respective bands from infra-slow frequencies to sigma frequencies. 
       FIG. 8A  illustrates an example of a nested stimulation waveform that may be delivered in connection with nested therapies to brain tissue (or brain tissue) of interest in accordance with embodiments herein. In  FIG. 8A , the nested stimulation waveform  802  includes multiple pulse bursts  804  that are separated from one another by an inter-burst delay  808 . Each of the pulse bursts  804  includes a series of individual pulses or spikes  810 . The pulses  810  are delivered over a burst length  816  in connection with an individual pulse bursts  804 . The rate at which the individual pulses  810  are delivered within a pulse bursts  804  is determined based on a pulse rate  812  (denoted as a bracket extending between successive positive peaks of adjacent successive pulses  810 ). 
       FIG. 8A  also illustrates a timeline extending along a horizontal axis with various points in time noted along the nested stimulation waveform  802 . Each of the successive pulse bursts  804  are initiated at start times T 10 , T 20  and T 30 , respectively. The interval between successive start times (e.g. T 10  and T- 20 ) represents the burst to burst period  814 . The timeline also illustrates examples of the timing between pulses  810  within an individual pulse burst (e.g.  804 ). For example, pulse peak times T 1 -T 5  are illustrated as aligned with the peak positive point of each pulse  810 . The pulse rate  812  corresponds to the pulse to pulse period  814 . 
     The nested stimulation waveform may be decomposed into at least two primary waveform components, generally denoted as a carrier waveform  820  and a high-frequency waveform  830 . In accordance with embodiments herein, the high frequency waveform is defined to correspond to high frequency physiologic neural oscillations associated with the brain tissue of interest, while the low frequency waveform is defined to correspond to low frequency physiologic neural oscillations associated with the brain tissue of interest. Optionally, one of the carrier and high frequency waveforms may be defined to differ from the low and high frequency physiologic neural oscillations. For example, the high frequency waveform may be defined to correspond to a physiologic beta or gamma wave, while the carrier waveform is defined to be independent of a physiologic infraslow, delta, theta or alpha wave. Alternatively, the high frequency waveform may be defined to be independent of a physiologic beta or gamma wave or sigma wave, while the carrier waveform is defined to correspond to a physiologic delta, theta or alpha wave. 
     The carrier wave  820  may represent a non-sinusoidal waveform similar to a square wave, but with only positive or only negative wave segments  822 . In the example of  FIG. 8A , the carrier wave  820  includes a series of positive wave segments  822  that are defined by parameters, such as a predetermined amplitude  824 , segment width  826 , inter segment delay  828 , among other parameters. The segment width  826  corresponds to the burst length  816 , while the inter segment delay  828  corresponds to the interburst delay  808 . The segment amplitude  824  defines an average amplitude for each pulse burst  804 . 
     The high-frequency waveform  830  includes a series of bursts  832 . Within each burst  832 , the waveform  830  oscillates periodically by switching between positive and negative amplitudes  834  and  835  at a select frequency  838 . The high-frequency waveform  830  represents an intermittent waveform in that successive adjacent bursts  832  are separated by an interburst delay  836  which corresponds to the interburst delay  808  and inter segment delay  828 . The high-frequency waveform  830  is defined by various parameters such as the frequency  138 , amplitudes  834 ,  835 , interburst delay  836 . 
     The high-frequency waveform  830  is combined with the carrier waveform  820  to form the nested stimulation waveform  802 . The parameters of the high-frequency and carrier waveforms  830  and  820  may be adjusted to achieve various effects. As one example, the parameters may be adjusted to achieve cross-frequency coupling with neural oscillations of interest. As one example, the parameters may be adjusted to entrain neural oscillations of interest. For example, the frequency, phase and amplitude of the carrier waveform  820  may be managed to entrain neural oscillations associated with brain tissue of interest, such as tissue associated with sensory, motor or cognitive processing. The carrier waveform  820  may entrain neural oscillations to the temporal structure defined by the carrier waveform  820  such as to facilitate selective attention in connection with certain psychiatric disorders (e.g. schizophrenia, dyslexia, attention deficit/hyperactivity disorder). Additionally or alternatively, the high-frequency waveform  830  may be managed to entrain neural oscillations associated with the brain region of interest. For example, the frequency, phase, amplitude as well as other parameters may be adjusted for the high-frequency waveform  830  to obtain entrainment of the neural oscillations of interest. 
     The characteristics discussed herein in connection with  FIG. 8A  represent non-limiting examples of therapy parameters that may be varied to define different nested therapies (e.g., different carrier waveforms and different high frequency waveforms). For example, a nonlimiting list of potential therapy parameters include pulse amplitude, pulse frequency, pulse to pulse period, the number of pulses in each burst, burst length, interburst delay, the number of pulse bursts in each nested stimulation waveform and the like. The pulse bursts may include pulses having a frequency corresponding to high frequency intrinsic neural oscillations exhibited by normal/physiologic brain tissue of interest. The pulse bursts are separated from one another with a burst to burst period that corresponds to a frequency of the low-frequency intrinsic neural oscillations exhibited by normal/physiologic brain tissue of interest. 
     The nested stimulation waveform combines the carrier waveform and high frequency waveform in a predetermined manner. For example, the carrier and high-frequency waveforms may be combined utilizing one of the following types of cross-frequency coupling: power to power; phase to power; phase to phase; phase to frequency; power to frequency and frequency to frequency. Optionally, the carrier and high-frequency waveforms are combined through phase to power cross-frequency coupling, in which the phase of the carrier waveform modulates the power of the high-frequency waveform. For example, the waveforms  820  and  830  may be combined in the manners discussed herein in connection with  FIGS. 4A-4G . 
     As one example, first parameters may be set to define the carrier waveform to correspond to physiologic neural oscillations in the theta wave frequency band, while second parameters may be set to define the high-frequency waveform to correspond to physiologic neural oscillations in the gamma wave frequency band. As explained herein, the nested stimulation waveform may be defined to entrain and modulate the neural oscillations in the gamma wave frequency band in connection with at least one of sensory, motor, and cognitive events. Optionally, the nested stimulation waveform may be managed in connection with a pattern of interest in neural oscillations through cross-frequency coupling between theta and gamma waves associated with the brain tissue of interest. 
     As explained herein, the brain tissue of interest may correspond to one brain region or comprise distributed neural modules located in separate regions of the brain. In accordance with embodiments herein methods and systems may manage the nested stimulation waveform in connection with cross-frequency coupling between neural oscillations associated with one or distributed neural modules that exhibit long-distance communication over neural oscillations within at least one of delta, theta and alpha wave frequency bands. 
     In accordance with embodiments herein, methods and system measure intrinsic neural oscillations, determine whether the nested stimulation waveform is achieving a desired modulation (e.g., entrainment) of the intrinsic neural oscillations, and adjust at least one of the first and second parameters to maintain the desired modulation (e.g., entrainment) of the intrinsic neural oscillations. The intrinsic neural oscillations may exhibit pathologic behavior or patterns. The nested stimulation waveform is adjusted until the intrinsic neural oscillation exhibits a physiologic behavior or pattern. 
       FIG. 8B  illustrates an example of a nested stimulation waveform that may be delivered in connection with nested therapies to brain tissue (or brain stem or spinal cord tissue) of interest in accordance with embodiments herein. In  FIG. 8B , the nested stimulation waveform  842  includes multiple pulse bursts  844  that are separated from one another by an inter-burst delay  848 . Each of the pulse burst  844  includes a series of individual pulses or spikes  850 . The pulses  850  are delivered over a burst length  856  in connection with an individual pulse burst  844 . The rate at which the individual pulses  850  are delivered within a pulse burst  844  is determined based on a pulse rate  862  (denoted as a bracket extending between successive positive peaks of adjacent successive pulses  810 . The nested stimulation waveform  842  includes a low frequency carrier waveform  853  and a high frequency waveform that defines the characteristics of the pulses  850 . 
       FIG. 8C  illustrates an alternative example of a nested stimulation waveform that may be delivered in connection with nested therapies to brain tissue (or brain stem or spinal cord tissue) of interest in accordance with embodiments herein. In  FIG. 8C , the nested stimulation waveform  852  includes multiple pulse bursts  854  that are separated from one another by an inter-burst delay  858 . Each of the pulse burst  854  includes a series of individual pulses or spikes  860 . The pulses  810  are delivered over a burst length  866  in connection with an individual pulse burst  854 . The rate at which the individual pulses  860  are delivered within a pulse burst  854  is determined based on a pulse rate  862  (denoted as a bracket extending between successive positive peaks of adjacent successive pulses  860 ). 
     The nested stimulation waveform  852  is decomposed into a carrier waveform  870  and a high-frequency waveform  880 . The carrier wave  870  may represent a sinusoidal waveform having positive and negative wave segments  872 . The positive and negative wave segments  822  are defined by a predetermined amplitude  874  and segment width  876  among other parameters. 
     The high-frequency waveform  880  includes a series of bursts  882 . Within each burst  882 , the waveform  880  oscillates periodically by switching between positive and negative amplitudes  884  and  885  at a select frequency  888 . The high-frequency waveform  880  represents an intermittent waveform in that successive adjacent bursts  882  are separated by an interburst delay  886  which corresponds to the interburst delay  858 . 
     The high-frequency waveform  880  is combined with the carrier waveform  870  to form the nested stimulation waveform  852 . The parameters of the high-frequency and carrier waveforms  880  and  870  are adjusted to entrain and/or achieve cross-frequency coupling with neural oscillations of interest. For example, the frequency, phase and amplitude of the carrier waveform  870  may be managed to entrain neural oscillations associated with a brain region of interest, such as a brain region associated with sensory, motor or cognitive processing. The carrier waveform  870  may entrain neural oscillations to the temporal structure defined by the carrier waveform  870  such as to facilitate selective attention in connection with certain psychiatric disorders (e.g. schizophrenia, dyslexia, attention deficit/hyperactivity disorder). Additionally or alternatively, the high-frequency waveform  880  may be managed to entrain neural oscillations associated with the brain region of interest. For example, the frequency, phase, amplitude as well as other parameters may be adjusted for the high-frequency waveform  880  to obtain entrainment of the neural oscillations of interest. 
     The carrier and high-frequency waveforms  870  and  880  may be combined utilizing one of the following types of cross-frequency coupling: power to power; phase to power; phase to phase; phase to frequency; power to frequency and frequency to frequency. For example, the waveforms  870  and  880  may be combined in the manner discussed herein in connection with  FIGS. 4A-4G . As one example, the carrier and high-frequency waveforms  870  and  880  are combined through phase to power cross-frequency coupling (as illustrated in connection with the waveform  405  in  FIGS. 4A-4G ), in which the phase of the carrier waveform modulates the power of the high-frequency waveform. 
       FIGS. 9A-9F  illustrate alternative nested stimulation waveforms that may be utilized in accordance with embodiments herein. The nested stimulation waveforms  902 - 912  may be delivered from multiple electrode combinations along the lead. The nested stimulation waveform  902  includes a carrier waveform that is cross-frequency coupled to a high frequency waveform to form multiple (e.g. three) pulse bursts  922  separated by an inter-burst interval  924 . The pulse burst  922  include a series of pulses  926  having a common polarity (e.g. all positive pulses or all negative pulses). 
     The nested stimulation waveform  904  includes a pair of pulse bursts  932  separated by an interburst interval  934 . Each pulse burst  932  includes a series of pulses  936  (e.g. three) that have a common polarity. The nested stimulation waveform  906  includes a single pulse burst  942  having a series of pulses  946 , each of which is bipolar (e.g. extends between positive and negative polarities). The pulses  946  have one of two states/voltage levels, namely a positive pulse amplitude and a negative pulse amplitude that are common. 
     The stimulation waveform  908  includes a pair of pulse bursts  952  separated by an inter-burst interval  954 . Each pulse burst  952  includes multiple pulses  956  that are bipolar (extending between positive and negative polarities). The pulses  956  vary between more than two states or voltage levels, namely first and second positive voltages  957 - 958  and first and second negative voltages  959  and  960 . Optionally, additional voltage levels/states may be utilized and the positive and negative voltage levels need not be common. 
     The nested stimulation waveform  910  includes pulse burst  962 A- 962 D that are separated by an interburst interval  964 . The interburst intervals  964  may differ from one another or be common. The pulse bursts  962 A and  962 C have similar positive and negative amplitudes, while the pulse bursts  962 B (positive) and  962 D (negative) are monopolar and different from one another. The nested stimulation waveform  912  illustrates a single pulse burst  972  that has a carrier wave component (as denoted by envelope  973  in dashed lines) that is modulated by a higher frequency component (as denoted by solid lines  975 ). Optionally, the nested stimulation waveform may be varied from the foregoing examples. Additionally, separate and distinct nested stimulation waveforms may be delivered from different electrode combinations at non-overlapping distinct points in time. 
     In some embodiments, network stimulation may include stimulation of one or more peripheral nerves, autonomic nerves (vagal, sympathetic nerves), sensory nerves, auditory nerves, and/or the spinal cord, in addition to stimulation of sites in the brain. 
     Electrical Stimulation Devices 
       FIGS. 1A-1B  illustrate example neurological stimulation (NS) systems  10  for electrically stimulating a predetermined site area to treat one or more neurological disorders or conditions. NS system  10  may perform one, multiple, or all of the operations discussed herein related to cross-frequency coupling. In general terms, stimulation system  10  includes an implantable pulse generating source or electrical IMD  12  (generally referred to as an “implantable medical device” or “IMD”) and one or more implantable electrodes or electrical stimulation leads  14  for applying stimulation pulses to a predetermined site. In operation, both of these primary components are implanted in the person&#39;s body, as discussed below. In certain embodiments, IMD  12  is coupled directly to a connecting portion  16  of stimulation lead  14 . In some embodiments, IMD  12  is incorporated into the stimulation lead  14  and IMD  12  instead is embedded within stimulation lead  14 . Whether IMD  12  is coupled directly to or embedded within the stimulation lead  14 , IMD  12  controls the stimulation pulses transmitted to one or more stimulation electrodes  18  located on a stimulating portion  20  of stimulation lead  14 , positioned in communication with a predetermined site, according to suitable therapy parameters (e.g., duration, amplitude or intensity, frequency, pulse width, firing delay, etc.). 
     A doctor, the patient, or another user of IMD  12  may directly or in directly input therapy parameters to specify or modify the nature of the stimulation provided. 
     In  FIG. 1B , the IMD  12  includes an implantable wireless receiver. In another embodiment, the IMD can be optimized for high frequency operation as described in U.S. Provisional Application Ser. No. 60/685,036, filed May 26, 2005, entitled “SYSTEMS AND METHODS FOR USE IN PULSE GENERATION,” which is incorporated herein by reference. The wireless receiver is capable of receiving wireless signals from a wireless transmitter  22  located external to the person&#39;s body. The wireless signals are represented in  FIG. 1B  by wireless link symbol  24 . A doctor, the patient, or another user of IMD  12  may use a controller  26  located external to the person&#39;s body to provide control signals for operation of IMD  12 . Controller  26  provides the control signals to wireless transmitter  22 , wireless transmitter  22  transmits the control signals and power to the wireless receiver of IMD  12 , and IMD  12  uses the control signals to vary the signal parameters of electrical signals transmitted through electrical stimulation lead  14  to the stimulation site. Thus, the external controller  26  can be for example, a handheld programmer, to provide a means for programming the IMD. 
     The IMD  12  applies tonic, burst, nested, noise, and other suitable electrical stimulation to tissue of the nervous system of a patient. Specifically, the IMD includes a microprocessor and a pulse generation module. The pulse generation module generates the electrical pulses according to a defined pulse width and pulse amplitude and applies the electrical pulses to defined electrodes. The microprocessor controls the operations of the pulse generation module according to software instructions stored in the device. 
     For example, for burst stimulation, the IMD  12  can be adapted by programming the microprocessor to deliver a number of spikes (relatively short pulse width pulses) that are separated by an appropriate interspike interval. Thereafter, the programming of the microprocessor causes the pulse generation module to cease pulse generation operations for an interburst interval. The programming of the microprocessor also causes a repetition of the spike generation and cessation of operations for a predetermined number of times. After the predetermined number of repetitions has been completed within a stimulation waveform, the microprocessor can cause burst stimulation to cease for an amount of time (and resume thereafter). Also, in some embodiments, the microprocessor could be programmed to cause the pulse generation module to deliver a hyperpolarizing pulse before the first spike of each group of multiple spikes. 
     The microprocessor can be programmed to allow the various characteristics of the electrical stimulation to be set by a physician to allow the stimulation to be optimized for a particular pathology of a patient. For example, the spike amplitude, the interspike interval, the interburst interval, the number of bursts to be repeated in succession, the electrode combinations, the firing delay between stimulation waveforms delivered to different electrode combinations, the amplitude of the hyperpolarizing pulse, and other such characteristics could be controlled using respective parameters accessed by the microprocessor during burst stimulus operations. These parameters could be set to desired values by an external programming device via wireless communication with the implantable neuromodulation device. 
     In representative embodiments, IMD  12  applies electrical stimulation according to a suitable noise signal (white noise, pink noise, brown noise, etc.). Details regarding implementation of a suitable noise signal can be found in U.S. Pat. No. 8,682,441, which is incorporated herein by reference 
     In another embodiment, the IMD  12  can be implemented to apply burst stimulation using a digital signal processor and one or several digital-to-analog converters. The burst stimulus waveform could be defined in memory and applied to the digital-to-analog converter(s) for application through electrodes of the medical lead. The digital signal processor could scale the various portions of the waveform in amplitude and within the time domain (e.g., for the various intervals) according to the various burst parameters. 
       FIG. 1C  depicts an NS system  100  that delivers stimulation therapies in accordance with embodiments herein. For example, the NS system  100  may be adapted to stimulate spinal cord tissue, peripheral nervous tissue, deep brain tissue, or any other suitable nervous/brain tissue of interest within a patient&#39;s body. 
     The NS system  100  may be programmed or controlled to deliver various types of stimulation therapy, such as tonic stimulation, high frequency stimulation, burst stimulation, noise stimulation, and nested stimulation therapies and the like. High frequency neurostimulation includes a continuous series of monophasic or biphasic pulses that are delivered at a predetermined frequency. Burst neurostimulation includes short sequences of monophasic or biphasic pulses, where each sequence is separated by a quiescent period. In general, nested therapies include a continuous, repeating or intermittent pulse sequence delivered at a frequency and amplitude with multiple frequency components. 
     The NS system  100  may deliver stimulation therapy based on preprogrammed therapy parameters. The therapy parameters may include, among other things, pulse amplitude, pulse polarity, pulse width, pulse frequency, interpulse interval, inter burst interval, electrode combinations, firing delay and the like. Optionally, the NS system  100  may represent a closed loop neurostimulation device that is configured to provide real-time sensing functions from a lead. The configuration of the lead sensing electrodes may be varied depending on the neuronal anatomy of the sensing site(s) of interest. The size and shape of electrodes is varied based on the implant location. The electronic components within the NS system  100  are designed with both stimulation and sensing capabilities. 
     The NS system  100  includes an implantable medical device (IMD)  150  that is adapted to generate electrical pulses for application to tissue of a patient. The IMD  150  typically comprises a metallic housing or can  158  that encloses a controller  151 , pulse generating circuitry  152 , a battery  154 , a far-field and/or near field communication circuitry  155 , battery charging circuitry  156 , switching circuitry  157 , memory  158  and the like. The switching circuitry  157  connects select combinations of the electrodes  121   a - d  to the pulse generating circuitry  152  thereby directing the stimulation waveform to a desired electrode combination. As explained herein, the switching circuitry  157  successively connects the pulse generating circuitry  152  to successive electrode combinations  123  and  125 . The components  151 - 158  are also within the IMD  12  ( FIGS. 1A and 1B ). IMD  150  may include sensing circuitry  153  (e.g., analog-to-digital converters) to sense neuronal signals of interest (e.g., local field potentials, neuronal spike activity, etc.). 
     The controller  151  typically includes one or more processors, such as a microcontroller, for controlling the various other components of the device. Software code is typically stored in memory of the IMD  150  for execution by the microcontroller or processor to control the various components of the device. 
     The IMD  150  may comprise a separate or an attached extension component  170 . If the extension component  170  is a separate component, the extension component  170  may connect with the “header” portion of the IMD  150  as is known in the art. If the extension component  170  is integrated with the IMD  150 , internal electrical connections may be made through respective conductive components. Within the IMD  150 , electrical pulses are generated by the pulse generating circuitry  152  and are provided to the switching circuitry  157 . The switching circuitry  157  connects to outputs of the IMD  150 . Electrical connectors (e.g., “Bal-Seal” connectors) within the connector portion  171  of the extension component  170  or within the IMD header may be employed to conduct various stimulation pulses. The terminals of one or more leads  110  are inserted within connector portion  171  or within the IMD header for electrical connection with respective connectors. Thereby, the pulses originating from the IMD  150  are provided to the lead  110 . The pulses are then conducted through the conductors of the lead  110  and applied to tissue of a patient via stimulation electrodes  121   a - d  that are coupled to blocking capacitors. Any suitable known or later developed design may be employed for connector portion  171 . 
     The stimulation electrodes  121   a - d  may be positioned along a horizontal axis  102  of the lead  110 , and are angularly positioned about the horizontal axis  102  so the stimulation electrodes  121   a - d  do not overlap. The stimulation electrodes  121   a - d  may be in the shape of a ring such that each stimulation electrode  121   a - d  continuously covers the circumference of the exterior surface of the lead  110 . Adjacent stimulation electrodes  121   a - d  are separated from one another by non-conducting rings  112 , which electrically isolate each stimulation electrode  121   a - d  from an adjacent stimulation electrode  121   a - d . The non-conducting rings  112  may include one or more insulative materials and/or biocompatible materials to allow the lead  110  to be implantable within the patient. Non-limiting examples of such materials include polyimide, polyetheretherketone (PEEK), polyethylene terephthalate (PET) film (also known as polyester or Mylar), polytetrafluoroethylene (PTFE) (e.g., Teflon), or parylene coating, polyether bloc amides, polyurethane. The stimulation electrodes  121   a - d  may be configured to emit the pulses in an outward radial direction proximate to or within a stimulation target. Additionally or alternatively, the stimulation electrodes  121   a - d  may be in the shape of a split or non-continuous ring such that the pulse may be directed in an outward radial direction adjacent to the stimulation electrodes  121   a - d . The stimulation electrodes  121   a - d  deliver tonic, high frequency and/or burst nested stimulation waveforms as described herein. Optionally, the electrodes  121   a - d  may also sense neural oscillations and/or sensory action potential (neural oscillation signals) for a data collection window. 
     The lead  110  may comprise a lead body  172  of insulative material about a plurality of conductors within the material that extend from a proximal end of lead  110 , proximate to the IMD  150 , to its distal end. The conductors electrically couple a plurality of the stimulation electrodes  121  to a plurality of terminals (not shown) of the lead  110 . The terminals are adapted to receive electrical pulses and the stimulation electrodes  121   a - d  are adapted to apply the pulses to the stimulation target of the patient. Also, sensing of physiological signals may occur through the stimulation electrodes  121   a - d , the conductors, and the terminals. It should be noted that although the lead  110  is depicted with four stimulation electrodes  121   a - d , the lead  110  may include any suitable number of stimulation electrodes  121   a - d  (e.g., less than four, more than four) as well as terminals, and internal conductors. Additionally or alternatively, various sensors may be located near the distal end of the lead  110  and electrically coupled to terminals through conductors within the lead body  172 . 
     Although not required for any embodiments, the lead body  172  of the lead  110  may be fabricated to flex and elongate upon implantation or advancing within the tissue (e.g., nervous tissue) of the patient towards the stimulation target and movements of the patient during or after implantation. By fabricating the lead body  172 , according to some embodiments, the lead body  172  or a portion thereof is capable of elastic elongation under relatively low stretching forces. Also, after removal of the stretching force, the lead body  172  may be capable of resuming its original length and profile. 
     By way of example, the IMD  12 ,  150  may include a processor and associated charge control circuitry as described in U.S. Pat. No. 7,571,007, entitled “SYSTEMS AND METHODS FOR USE IN PULSE GENERATION,” which is expressly incorporated herein by reference. Circuitry for recharging a rechargeable battery (e.g., battery charging circuitry  156 ) of an IMD using inductive coupling and external charging circuits are described in U.S. Pat. No. 7,212,110, entitled “IMPLANTABLE DEVICE AND SYSTEM FOR WIRELESS COMMUNICATION,” which is expressly incorporated herein by reference. An example and discussion of “constant current” pulse generating circuitry (e.g., pulse generating circuitry  152 ) is provided in U.S. Patent Publication No. 2006/0170486 entitled “PULSE GENERATOR HAVING AN EFFICIENT FRACTIONAL VOLTAGE CONVERTER AND METHOD OF USE,” which is expressly incorporated herein by reference. One or multiple sets of such circuitry may be provided within the IMD  12 ,  150 . Different burst and/or high frequency pulses on different stimulation electrodes may be generated using a single set of the pulse generating circuitry using consecutively generated pulses according to a “multi-stimset program” as is known in the art. Complex pulse parameters may be employed such as those described in U.S. Pat. No. 7,228,179, entitled “Method and apparatus for providing complex tissue stimulation patterns,” and International Patent Publication Number WO 2001/093953 A1, entitled “NEUROMODULATION THERAPY SYSTEM,” which are expressly incorporated herein by reference. Alternatively, multiple sets of such circuitry may be employed to provide pulse patterns (e.g., tonic stimulation waveform, burst stimulation waveform) that include generated and delivered stimulation pulses through various stimulation electrodes of one or more leads as is also known in the art. Various sets of parameters may define the pulse characteristics and pulse timing for the pulses applied to the various stimulation electrodes. Although constant current pulse generating circuitry is contemplated for some embodiments, any other suitable type of pulse generating circuitry may be employed such as constant voltage pulse generating circuitry. 
     The controller  151  delivers stimulation pulses to at least one electrode combination located proximate to nervous tissue of interest. The controller  151  may deliver the sitmulation pulses based on preprogrammed therapy parameters. The preprogrammed therapy parameters may be set based on information collected from numerous past patients and/or test performed upon an individual patient during initial implant and/or during periodic checkups. 
     Optionally, the controller  151  senses intrinsic neural oscillations from at least one electrode on the lead. Optionally, the controller  151  analyzes the intrinsic neural oscillations signals to obtain brain activity data. The controller  151  determines whether the activity data satisfies a criteria of interest. The controller  151  adjusts at least one of the therapy parameters to change the nested stimulation waveform when the activity data does not satisfy the criteria of interest. The controller  151  iteratively repeats the delivering operations for a group of TPS. The IMD selects a candidate TPS from the group of TPS based on a criteria of interest. The therapy parameters define at least one of a burst stimulation waveform or a high frequency stimulation waveform. The controller  151  may repeat the delivering, sensing and adjusting operations to optimize the nested stimulation waveform. The analyzing operation may include analyzing a feature of interest from a morphology of the neural oscillation signal over time, counting a number of occurrences of the feature of interest that occur within the signal over a predetermined duration, and generating the activity data based on the number of occurrences of the feature of interest. 
     Memory  158  stores software to control operation of the controller  151  for nested stimulation therapy as explained herein. The memory  158  also stores neural oscillation signals, therapy parameters, neural oscillation activity level data, sensation scales and the like. For example, the memory  158  may save neural oscillation activity level data for various different therapies as applied over a short or extended period of time. A collection of neural oscillation activity level data is accumulated for different therapies and may be compared to identify high, low and acceptable amounts of sensory activity. 
     A controller device  160  may be implemented to charge/recharge the battery  154  of the IMD  150  (although a separate recharging device could alternatively be employed) and to program the IMD  150  on the pulse specifications while implanted within the patient. Although, in alternative embodiments separate programmer devices may be employed for charging and/or programming the NS system  100 . The controller device  160  may be a processor-based system that possesses wireless communication capabilities. Software may be stored within a non-transitory memory of the controller device  160 , which may be executed by the processor to control the various operations of the controller device  160 . A “wand”  165  may be electrically connected to the controller device  160  through suitable electrical connectors (not shown). The electrical connectors may be electrically connected to a telemetry component  166  (e.g., inductor coil, RF transceiver) at the distal end of wand  165  through respective wires (not shown) allowing bi-directional communication with the IMD  150 . Optionally, in some embodiments, the wand  165  may comprise one or more temperature sensors for use during charging operations. 
     The user may initiate communication with the IMD  150  by placing the wand  165  proximate to the NS system  100 . Preferably, the placement of the wand  165  allows the telemetry system of the wand  165  to be aligned with the far-field and/or near field communication circuitry  155  of the IMD  150 . The controller device  160  preferably provides one or more user interfaces  168  (e.g., touchscreen, keyboard, mouse, buttons, or the like) allowing the user to operate the IMD  150 . The controller device  160  may be controlled by the user (e.g., doctor, clinician) through the user interface  168  allowing the user to interact with the IMD  150 . The user interface  168  may permit the user to move electrical stimulation along and/or across one or more of the lead(s)  110  using different stimulation electrode  121  combinations, for example, as described in U.S. Patent Application Publication No. 2009/0326608, entitled “METHOD OF ELECTRICALLY STIMULATING TISSUE OF A PATIENT BY SHIFTING A LOCUS OF STIMULATION AND SYSTEM EMPLOYING THE SAME,” which is expressly incorporated herein by reference. 
     Also, the controller device  160  may permit operation of the IMD  12 ,  150  according to one or more therapies to treat the patient. Each therapy may include one or more sets of stimulation parameters of the pulse including pulse amplitude, pulse width, pulse frequency or inter-pulse period, firing delay, pulse repetition parameter (e.g., number of times for a given pulse to be repeated for respective stimset during execution of program), biphasic pulses, monophasic pulses, etc. The IMD  150  modifies its internal parameters in response to the control signals from the controller device  160  to vary the stimulation characteristics of the stimulation pulses transmitted through the lead  110  to the tissue of the patient. NS systems, stimsets, and multi-stimset programs are discussed in PCT Publication No. WO 01/93953, entitled “NEUROMODULATION THERAPY SYSTEM,” and U.S. Pat. No. 7,228,179, entitled “METHOD AND APPARATUS FOR PROVIDING COMPLEX TISSUE STIMULATION PATTERNS,” which are expressly incorporated herein by reference. 
       FIGS. 2A-2I  illustrate example stimulation leads  14  that may be used for electrically stimulating the predetermined site to treat one or more neurological disorders or conditions. As described above, each of the one or more stimulation leads  14  incorporated in stimulation systems  10 ,  100  includes one or more stimulation electrodes  18  adapted to be positioned in communication with the predetermined site and used to deliver the stimulation pulses received from IMD  12  (or pulse generating circuitry  157  in  FIG. 1C ). A percutaneous stimulation lead  14  (corresponding to the lead  110  in  FIG. 1C ), such as example stimulation leads  14   a - d , includes one or more circumferential electrodes  18  spaced apart from one another along the length of stimulating portion  20  of stimulation lead  14 . Circumferential electrodes  18  emit electrical stimulation energy generally radially (e.g., generally perpendicular to the axis of stimulation lead  14 ) in all directions. A laminotomy, paddle, or surgical stimulation lead  14 , such as example stimulation leads  14   e - i , includes one or more directional stimulation electrodes  18  spaced apart from one another along one surface of stimulation lead  14 . Directional stimulation electrodes  18  emit electrical stimulation energy in a direction generally perpendicular to the surface of stimulation lead  14  on which they are located. Although various types of stimulation leads  14  are shown as examples, embodiments herein contemplate stimulation system  10  including any suitable type of stimulation lead  14  in any suitable number. In addition, stimulation leads  14  may be used alone or in combination. For example, medial or unilateral stimulation of the predetermined site may be accomplished using a single electrical stimulation lead  14  implanted in communication with the predetermined site in one side of the head, while bilateral electrical stimulation of the predetermined site may be accomplished using two stimulation leads  14  implanted in communication with the predetermined site in opposite sides of the head. 
     The IMD  12 ,  150  allow each electrode of each lead to be defined as a positive, a negative, or a neutral polarity. For each electrode combination (e.g., the defined polarity of at least two electrodes having at least one cathode and at least one anode), an electrical signal can have at least a definable amplitude (e.g., current level or voltage), pulse width, and frequency, where these variables may be independently adjusted to finely select the sensory transmitting brain tissue required to inhibit transmission of neuronal signals. Generally, amplitudes, pulse widths, and frequencies are determinable by the capabilities of the neurostimulation systems, which are known by those of skill in the art. 
     In embodiments herein, the therapy parameter of signal frequency is varied to achieve a burst type rhythm, or burst mode stimulation. Generally, the burst stimulus frequency may be in the range of about 0.01 Hz to about 100 Hz, more particular, in the range of about 1 Hz to about 12 Hz, and more particularly, in the range of about 1 Hz to about 4 Hz, 4 Hz to about 7 Hz or about 8 Hz to about 12 Hz for each burst. Each burst stimulus comprises at least two spikes, for example, each burst stimulus can comprise about 2 to about 100 spikes, more particularly, about 2 to about 10 spikes. The respective spikes within a given burst may exhibit a pulse repetition rate or frequency in the range of about 50 Hz to about 1000 Hz, more particularly, in the range of about 200 Hz to about 500 Hz. The frequency of spike repetition within one or more burst can vary. The inter-spike interval can be also vary, for example, the inter-spike interval, can be about 0.1 milliseconds to about 100 milliseconds or any range there between. 
     The burst stimulus is followed by an inter-burst interval, during which substantially no stimulus is applied. The inter-burst interval has duration in the range of about 1 milliseconds to about 5 seconds, more preferably, 10 milliseconds to about 300 milliseconds. It is envisioned that the burst stimulus has a duration in the range of about 1 milliseconds to about 5 seconds, more particular, in the range of about 250 msec to 1000 msec (1-4 Hz burst firing), 145 msec to about 250 msec (4-7 Hz), 145 msec to about 80 msec (8-12 Hz) or 1 to 5 seconds in plateau potential firing. The burst stimulus and the inter-burst interval can have a regular pattern or an irregular pattern (e.g., random or irregular harmonics). More specifically, the burst stimulus can have a physiological pattern or a pathological pattern. Additional details regarding burst stimulation may be found in U.S. Pat. No. 8,897,870, which is incorporated herein by reference. 
     It is envisaged that the patient may require intermittent assessment with regard to patterns of stimulation. Different electrodes on the lead can be selected by suitable computer programming, such as that described in U.S. Pat. No. 5,938,690, which is incorporated by reference here in full. Utilizing such a program allows an optimal stimulation pattern to be obtained at minimal voltages. This ensures a longer battery life for the implanted systems. 
       FIGS. 2A-2I  respectively depict stimulation portions for inclusion at the distal end of lead. Stimulation portion depicts a conventional stimulation portion of a “percutaneous” lead with multiple ring electrodes. Stimulation portion depicts a stimulation portion including several segmented electrodes. Example fabrication processes are disclosed in U.S. patent application Ser. No. 12/895,096, entitled, “METHOD OF FABRICATING STIMULATION LEAD FOR APPLYING ELECTRICAL STIMULATION TO TISSUE OF A PATIENT,” which is incorporated herein by reference. Stimulation portion includes multiple planar electrodes on a paddle structure. 
     In certain embodiments, for example, patients may have an electrical stimulation lead or electrode implanted directly into the brain for deep brain stimulation or adjacent to the dura for cortical stimulation. The anatomical targets or predetermined site may be stimulated directly or affected through stimulation in another region of the brain. 
     Once electrical stimulation lead  14 ,  110  has been positioned adjacent to the dura or in the brain, lead  14 ,  110  is uncoupled from any stereotactic or other implant equipment present, and the equipment is removed. Where stereotactic equipment is used, the cannula may be removed before, during, or after removal of the stereotactic equipment. Connecting portion  16  of electrical stimulation lead  14 ,  110  is laid substantially flat along the skull. Where appropriate, any burr hole cover seated in the burr hole may be used to secure electrical stimulation lead  14 ,  110  in position and possibly to help prevent leakage from the burr hole and entry of contaminants into the burr hole. 
     Once electrical stimulation lead  14 ,  110  has been inserted and secured, connecting portion of lead  14 ,  110  extends from the lead insertion site to the implant site at which IMD  12 ,  150  is implanted. The implant site is typically a subcutaneous pocket formed to receive and house IMD  12 ,  150 . The implant site is usually positioned a distance away from the insertion site, such as near the chest, below the clavicle or alternatively near the buttocks or another place in the torso area. Once all appropriate components of stimulation system  10 ,  100  are implanted, these components may be subject to mechanical forces and movement in response to movement of the person&#39;s body. A doctor, the patient, or another user of IMD  12 ,  150  may directly or in directly input signal parameters for controlling the nature of the electrical stimulation provided. 
     Although example steps are illustrated and described, embodiments herein contemplate two or more steps taking place substantially simultaneously or in a different order. In addition, embodiments herein contemplate using methods with additional steps, fewer steps, or different steps, so long as the steps remain appropriate for implanting an example stimulation system  10 ,  100  into a person for electrical stimulation of the person&#39;s brain. 
     As described above, each of the one or more leads  14  incorporated in stimulation system  10  includes one or more electrodes  18  adapted to be positioned near the target brain tissue and used to deliver electrical stimulation energy to the target brain tissue in response to electrical signals received from IMD  12 . A percutaneous lead  14  may include one or more circumferential electrodes  18  spaced apart from one another along the length of lead  14 . Circumferential electrodes  18  emit electrical stimulation energy generally radially in all directions and may be inserted percutaneously or through a needle. The electrodes  18  of a percutaneous lead  14  may be arranged in configurations other than circumferentially, for example as in a “coated” lead  14 . A laminotomy or paddle style lead  14 , such as example leads  14   e - i , includes one or more directional electrodes  18  spaced apart from one another along one surface of lead  14 . Directional electrodes  18  emit electrical stimulation energy in a direction generally perpendicular to the surface of lead  14  on which they are located. Although various types of leads  14  are shown as examples, embodiments herein contemplate stimulation system  10  including any suitable type of lead  14  in any suitable number, including three-dimensional leads and matrix leads as described below. In addition, the leads may be used alone or in combination. 
     Although example steps are illustrated and described, embodiments herein contemplate two or more steps taking place substantially simultaneously or in a different order. In addition, embodiments herein contemplate using methods with additional steps, fewer steps, or different steps, so long as the steps remain appropriate for implanting stimulation system  10  into a person for electrical stimulation of the predetermined site. 
     One or more of the operations described above in connection with the methods may be performed using one or more processors. The different devices in the systems described herein may represent one or more processors, and two or more of these devices may include at least one of the same processors. In one embodiment, the operations described herein may represent actions performed when one or more processors (e.g., of the devices described herein) execute program instructions stored in memory (for example, software stored on a tangible and non-transitory computer readable storage medium, such as a computer hard drive, ROM, RAM, or the like). 
     The processor(s) may execute a set of instructions that are stored in one or more storage elements, in order to process data. The storage elements may also store data or other information as desired or needed. The storage element may be in the form of an information source or a physical memory element within the controllers and the controller device. The set of instructions may include various commands that instruct the controllers and the controller device to perform specific operations such as the methods and processes of the various embodiments of the subject matter described herein. The set of instructions may be in the form of a software program. The software may be in various forms such as system software or application software. Further, the software may be in the form of a collection of separate programs or modules, a program module within a larger program or a portion of a program module. The software also may include modular programming in the form of object-oriented programming. The processing of input data by the processing machine may be in response to user commands, or in response to results of previous processing, or in response to a request made by another processing machine. 
     The controller may include any processor-based or microprocessor-based system including systems using microcontrollers, reduced instruction set computers (RISC), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), logic circuits, and any other circuit or processor capable of executing the functions described herein. When processor-based, the controller executes program instructions stored in memory to perform the corresponding operations. Additionally or alternatively, the controllers and the controller device may represent circuits that may be implemented as hardware. The above examples are exemplary only, and are thus not intended to limit in any way the definition and/or meaning of the term “controller.” 
     It is to be understood that the subject matter described herein is not limited in its application to the details of construction and the arrangement of components set forth in the description herein or illustrated in the drawings hereof. The subject matter described herein is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of “including,” “comprising,” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. 
     It is to be understood that the above description is intended to be illustrative, and not restrictive. For example, the above-described embodiments (and/or aspects thereof) may be used in combination with each other. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from its scope. While the dimensions, types of materials and coatings described herein are intended to define the parameters of the invention, they are by no means limiting and are exemplary embodiments. Many other embodiments will be apparent to those of skill in the art upon reviewing the above description. The scope of the invention should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. In the appended claims, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Moreover, in the following claims, the terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to impose numerical requirements on their objects. Further, the limitations of the following claims are not written in means—plus-function format and are not intended to be interpreted based on 45 U.S.C. § 112(f), unless and until such claim limitations expressly use the phrase “means for” followed by a statement of function void of further structure.