DOI: 10.5061/dryad.rr4xgxdg6
title: Data from: Interactions between circuit architecture and plasticity in a closed-loop cerebellar system

description: A major challenge in neuroscience is to infer the sites and directions of
 neural plasticity that underlie learned changes in behavior. In
 particular, abundant feedback pathways in the brain impede reasoning about
 cause and effect based on neural recording data alone. We approached this
 problem by studying the interactions between feedback, neural activity,
 and plasticity in the context of vestibulo-ocular reflex learning, a
 closed-loop motor learning paradigm. Our strategy was to fit a series of
 circuit models to a large set of neural and behavioral data. Each model
 differed in the strength of efference copy feedback to Purkinje cells,
 ranging from no feedback to very strong feedback. The primary dataset
 before learning was obtained from male rhesus monkeys (Macaca mulatta)
 trained to perform a visual fixation task, and includes neural activity
 from Purkinje cells in the cerebellar flocculus and horizontal eye
 velocity measurements in response to a wide range of vestibular and visual
 stimuli. Data after learning was obtained from previous publications.
 Whereas each model fit the extracellular recording and behavioral data,
 the patterns of plasticity predicted by the models fundamentally differed,
 with the direction of plasticity at a key site changing from depression to
 potentiation as feedback strength increased. We find that models with weak
 or no efference copy feedback to Purkinje cells are consistent with
 climbing fiber-driven long term depression at parallel fiber-Purkinje cell
 synapses and explain all experimental observations, including paradoxical
 changes in neural activity during a closed-loop visual task that appear to
 contradict the underlying plasticity. These results demonstrate how
 learning-related changes in neural activity can appear to contradict the
 sign of the underlying plasticity when either internal feedback or
 feedback through the environment is present.
description: Neural and behavioral data before learning (“Dataset 1”) were
 obtained from two male rhesus monkeys (<em>Macaca mulatta)
 </em>trained to perform a visual fixation task. A subset of this
 dataset has been published previously (Kimpo et al., 2014; Raymond
 & Lisberger, 1998). Briefly, neural responses were recorded
 extracellularly from Purkinje cells in the floccular complex of the
 cerebellar cortex while the monkeys made horizontal eye movements in
 response to various combinations of visual and vestibular stimuli.
 Vestibular stimuli consisted of passive whole-body rotation in the
 horizontal plane. Visual stimuli consisted of a horizontally moving target
 subtending 0.5° of visual angle, which was accompanied by a larger
 black-and-white pattern subtending 20° to 30° of visual angle for all
 stimulus conditions except for smooth pursuit. Four combinations of visual
 and vestibular stimuli were delivered: head movements in the dark
 (“Vestibular only,” which elicits the VOR), visual target motion with the
 head stationary (“visual only”, which elicits smooth pursuit eye
 movements), visual target and head motion at the same speed but in
 opposite directions (“vestibular + visual”, also referred to as ×2 because
 accurate tracking requires compensatory eye movements that are twice as
 large as normal), and visual target and head motion at the same speed and
 in the same direction (“vestibular – visual”, also referred to as ×0
 because accurate tracking requires <em>no </em>rotation of the
 eyes in their sockets, and also known as “VOR cancellation” since normal
 VOR eye movements are suppressed). These combinations were delivered as
 sine waves in stimulus velocity with frequencies of 0.5 Hz, 2 Hz, 5 Hz,
 and 10 Hz at ±10 ⁰/s, or as steps in stimulus velocity with durations of
 80 ms, 150 ms, 250 ms, and 500 ms at 15 ⁰/s. Smooth pursuit data were only
 available for 0.5 Hz sine waves (delivered at ±31.4 ⁰/s), resulting in a
 total of 25 distinct conditions. Eye position (angle of the eye relative
 to the head) was measured using the scleral search coil method.
 Eye velocity and neural activity from Dataset 1 were further
 processed as follows. Eye velocity was calculated by differentiating eye
 position. Saccades were removed from eye velocity traces using an
 automatic threshold algorithm with a threshold of 30 ⁰/s. To allow
 comparison across datasets and with previous studies, we analyzed
 horizontal gaze velocity Purkinje cells (HGVPs), which are the largest
 subpopulation of floccular Purkinje cells and are widely considered to be
 important for horizontal gaze control (Katoh et al., 2015; Lisberger,
 Pavelko, Bronte-Stewart, et al., 1994). Purkinje cells were considered
 HGVPs if (1) during smooth pursuit, firing rate was modulated by at least
 ±10 sp/s and the phase difference between peak firing rate and peak
 ipsiversive eye velocity was less than 45°; (2) during VOR cancellation,
 firing rate was modulated by at least ±10 sp/s and the phase difference
 between peak firing rate and peak ipsiversive head velocity was less than
 45°; and (3) firing rate modulation was greater during horizontal than
 during vertical smooth pursuit. Purkinje cell firing rates were calculated
 by convolving raw simple spikes times with a 10 ms standard deviation
 Gaussian filter. Baseline firing rates were removed by subtracting a
 moving average calculated over an 11 s window. Eye velocity and Purkinje
 cell firing rates were then averaged across stimulus cycles for each cell.
 Neurons were only recorded on one side of the brain, so to account for the
 corresponding population in the opposite hemisphere, Purkinje cell
 responses to ipsiversive stimulation were averaged together with the
 inverted response to contraversive stimulation. Finally, data were
 averaged across all cells to create mean Purkinje cell firing rate and
 mean eye velocity traces for each stimulus condition.
description: # Data from: Interactions between circuit architecture and plasticity in a
 closed-loop cerebellar system
 [https://doi.org/10.5061/dryad.rr4xgxdg6](https://doi.org/10.5061/dryad.rr4xgxdg6) ## Description of the data and file structure Files are stored in matlab (.mat) format ### File naming Each file contains trial-averaged data for one signal type and one condition. The **signal types** are: * "**head**": horizontal head velocity, a.k.a. vestibular stimulus [Stimulus] * "**target**": horizontal visual stimulus velocity [Stimulus] * "**eye**": horizontal eye velocity [Response] * "**PC**": Purkinje cell firing rate [Response] The stimuli are delivered as either sine waves of steps in stimulus velocity. The **conditions** are: * "**dark**": head movements in the dark, which elicits the VOR ("vestibular only") * "**pursuit**": visual target motion with the head stationary, which elicits smooth pursuit eye movements ("visual only") * "**x2**": visual target and head motion at the same speed but in opposite directions (“vestibular + visual”, also referred to as x2 because accurate tracking requires compensatory eye movements that are twice as large as normal), * "**x0**": visual target and head motion at the same speed and in the same direction ( “vestibular – visual”, also referred to as x0 because accurate tracking requires *no* rotation of the eyes in their sockets, and also known as “VOR cancellation” since normal VOR eye movements are suppressed The **variants** are: * "**05Hz**", "**2Hz**", "**5Hz**", "**10Hz**": sine waves in stimulus velocity at ±10 ⁰/s with frequencies of 0.5 Hz, 2 Hz, 5 Hz, and 10 Hz, respectively * "**80ms**", "**150ms**", "**250ms**", "**500ms**": steps in stimulus velocity at ±15 ⁰/s with durations of 80 ms, 150 ms, 250 ms, and 500 ms, respectively The files are named according to: **VARIANT_CONDITON_SIGNALTYPE.mat**. For example, 2Hz_dark_eye.mat indicates the eye velocity measured during 2 Hz sinusoidal vestibular stimulation in the dark. ### File content Each file contains three variables: * **allcellsipsi** (nt x 1): data averaged over trials and cells, in response to ipsiversive stimulation, e.g. head turns towards the side of the recording. If both vestibular and visual stimuli are present, "ipsi" refers to the direction of the vestibular stimulus. Units are sp/s (Purkinje cell data) or deg/s (all other signal types). Number of cells for each condition are available in the associated publication, Figure 3. * **allcellscontra** (nt x 1): averaged data in response to contraversive stimulation, e.g. head turns away from the side of the recording * **time** (nt x 1): the time stamps for the data listed above, in seconds ## Sharing/Access information This dataset, as well as other information necessary to reproduce the results in the associated publication, are available on GitHub. We recommend that the dataset is accessed through the following link: * [https://github.com/goldman-lab/VOR-model-Payne](https://github.com/goldman-lab/VOR-model-Payne) ## Code/Software * [https://github.com/goldman-lab/VOR-model-Payne](https://github.com/goldman-lab/VOR-model-Payne)