Biology subjects

Shadmehr, R.

Publications and source records attributed to Shadmehr, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Climbing fibers encode the gradient of a loss function for the cerebellum

Neurons in the brain are often many synapses away from motoneurons, yet if a movement results in error, each distant neuron needs a teacher that considers its specific contribution to production of that movement. This credit assignment problem is solved in machine learning via gradient descent of a loss function, where the loss defines the subjective cost incurred by error. Does the brain use gradient descent to teach individual neurons? We trained marmosets to make saccades to visual targets and then varied the loss by assigning reward value to each target. The climbing fibers, which are the teachers of Purkinje cells (P-cells) in the cerebellum, used a multiplicative encoding to scale the spatial properties of the error vector with its reward properties, incorporating reward prediction errors. Using spike-triggered suppression of P-cells, we quantified the potent vector that mapped each P-cells output to eye movements and discovered that the climbing fibers were not merely transmitting errors. Rather, they were providing a signal that was, on average, proportional to the dot product of the reward dependent error vector upon the P-cells potent vector. Thus, the climbing fibers solved the credit assignment problem by providing the gradient of a loss function with respect to the output of their individual P-cells.

neuroscience↗

bioRxiv2025

Coordination of spike timing among the neurons of the cerebellum

We tend to think of neurons as either excitatory or inhibitory, but certain neurons chemically inhibit their downstream targets while electrically exciting each other. For example, in the cerebellum, molecular layer interneurons type 1 (MLI1s) inhibit Purkinje cells (P-cells) via release of GABA but promote spiking in each other via gap junctions. P-cells inhibit nucleus neurons while exciting each other via ephaptic coupling. What is gained by excitatory interactions among inhibitory neurons? We recorded from the marmoset cerebellum during saccadic eye movements and found that spike timing in electrically coupled P-cell pairs, as well as MLI1 pairs, exhibited a mathematical regularity: as firing rates increased, the rate of spikes that were within 1ms of each other grew disproportionately while 2-4ms intervals were suppressed. We isolated triplets in which two MLI1s converged onto a single P-cell and found that if the MLI1s spiked within 1ms of each other, they produced superposition of their individual effects on their target; a deep inhibition followed by a post-inhibitory rebound. This enhanced the temporal precision in the downstream P-cells next spike. However, when the MLI1s spiked 2-4ms apart, the two spikes interfered with each other, producing partial cancellation. Thus, electrical coupling of inhibitory neurons promoted production of spike intervals that induced constructive superposition. This reduced the variance of spike timing in the downstream neuron.

neuroscience↗

bioRxiv2024

A vector calculus for neural computation in the cerebellum

Null space theory predicts that a neuron will often generate spikes not to produce behavior, but to prevent another neurons impact on behavior. Here, we present a direct test of this theory in the brain. In the marmoset cerebellum, spike-triggered averaging identified a vector for each Purkinje cell (P-cell) along which its spikes displaced the eyes. Two spikes in two different P-cells produced superposition of their vectors. In the resulting population activity, the spikes were canceled if their contributions were perpendicular to the intended movement. Mossy fibers provided a copy of the motor commands and the sensory goal of the movement. Molecular layer interneurons transformed these inputs so that the P-cell population predicted when the movement had reached the goal and should be stopped.

neuroscience↗

bioRxiv2024

Control of tongue movements by the Purkinje cells of the cerebellum

We use our tongue much like our hands: to interact with objects and transport them. For example, we use our hands to sense properties of objects and transport them in the nearby space, and we use our tongue to sense properties of food morsels and transport them through the oral cavity. But what does the cerebellum contribute to control of tongue movements? Here, we trained head-fixed marmosets to make skillful tongue movements to harvest food from small tubes that were placed at sharp angles to their mouth. We identified the lingual regions of the cerebellar vermis and then measured the contribution of each Purkinje cell (P-cell) to control of the tongue by relying on the brief but complete suppression that they experienced following an input from the inferior olive. When a P-cell was suppressed during protraction, the tongues trajectory became hypermetric, and when the suppression took place during retraction, the tongues return to the mouth was slowed. Both effects were amplified when two P-cells were simultaneously suppressed. Therefore, suppression of P-cells in the lingual vermis disrupted the forces that would normally decelerate the tongue as it approached the target. Notably, the population simple spike activity peaked near deceleration onset when the movement required precision (aiming for a tube), but not when the movement was for the purpose of grooming. Thus, the P-cells appeared to signal when to stop protrusion as the tongue approached its target.

neuroscience↗

bioRxiv2024

Rejuvenating silicon probes for acute electrophysiology

Electrophysiological recording with a new probe often yields better signal quality than with a used probe. Why does the signal quality degrade after only a few experiments? Here, we considered silicon probes in which the contacts are densely packed, and each is coated with a conductive polymer that increases its surface area. We tested 12 Cambridge Neurotech silicon probes during 61 recording sessions from the brain of 3 marmosets. Out of the box, each probe arrived with an electrodeposited polymer coating on 64 gold contacts, and an impedance of around 50k Ohms. With repeated use, the impedance increased and there was a corresponding decrease in the number of well-isolated neurons. Imaging of the probes suggested that the reduction in signal quality was due to a gradual loss of the polymer coating. To rejuvenate the probes, we first stripped the contacts, completely removing their polymer coating, and then recoated them in a solution of 10 mM EDOT monomer with 32 uM PSS using a current density of about 3mA/cm2 for 30 seconds. This recoating process not only returned probe impedance to around 50k Ohms, it also yielded significantly improved signal quality during neurophysiological recordings. Thus, insertion into the brain promoted loss of the polymer that coated the contacts of the silicon probes. This led to degradation of signal quality, but recoating rejuvenated the probes.

neuroscience↗

bioRxiv2023

A software tool for at-home measurement of sensorimotor adaptation

Sensorimotor adaptation is traditionally studied in well-controlled laboratory settings with specialized equipment. However, recent public health concerns such as the COVID-19 pandemic, as well as a desire to recruit a more diverse study population, have led the motor control community to consider at-home study designs. At-home motor control experiments are still rare because of the requirement to write software that can be easily used by anyone on any platform. To this end, we developed software that runs locally on a personal computer. The software provides audiovisual instructions and measures the ability of the subject to control the cursor in the context of visuomotor perturbations. We tested the software on a group of at-home participants and asked whether the adaptation principles inferred from in-lab measurements were reproducible in the at-home setting. For example, we manipulated the perturbations to test whether there were changes in adaptation rates (savings and interference), whether adaptation was associated with multiple timescales of memory (spontaneous recovery), and whether we could selectively suppress subconscious learning (delayed feedback, perturbation variability) or explicit strategies (limited reaction time). We found remarkable similarity between in-lab and at-home behaviors across these experimental conditions. Thus, we developed a software tool that can be used by research teams with little or no programming experience to study mechanisms of adaptation in an at-home setting. SignificanceSensorimotor learning is traditionally studied in the laboratory, but recent public health emergencies have caused the community to consider at-home data collection. To accelerate this effort, we implemented a software tool that remotely tracks motor learning. Compared with previous remote data collection strategies, our software (1) generates experiments of arbitrary length that (2) run locally on a participants laptop which (3) can be modified without any programming expertise in the research laboratory. Here we show a close correspondence between behaviors captured by our tool and those observed in laboratory environments including savings, interference, spontaneous recovery, and variations in implicit and explicit learning due to changes in perturbation variance, reaction time constraints, and feedback delay. Our software and its corresponding manuals are available here: https://osf.io/e8b63/.

neuroscience↗

bioRxiv2023

Effort cost of reaching prompts vigor reduction in older adults

As people age, they move slower. Is age-related reduction in vigor a reflection of a reduced valuation of reward by the brain, or a consequence of increased effort costs by the muscles? Here, we quantified cost of movements objectively via the metabolic energy that young and old participants consumed during reaching and found that in order reach at a given speed, older adults expended more energy than the young. We next quantified how reward modulated movements in the same populations and found that like the young, older adults responded to increased reward by initiating their movements earlier. Yet, their movements were less sensitive to increased reward, resulting in little or no modulation of reach speed. Lastly, we quantified the effect of increased effort on how reward modulated movements in young adults. Like the effects of aging, when faced with increased effort the young adults responded to reward primarily by reacting faster, with little change in movement speed. Therefore, reaching required greater energetic expenditure in the elderly, suggesting that the slower movements and reactions exhibited in aging are partly driven by an adaptive response to an elevation in the energetic landscape of effort. That is, moving slower appears to be a rational economic consequence of aging. Significance statementHealthy aging coincides with a reduction in speed, or vigor, of walking, reaching, and eye movements. Here we focused on disentangling two opposing sources of aging-related movement slowing: reduced reward sensitivity due to loss of dopaminergic tone, or increased energy expenditure movements related to mitochondrial or muscular inefficiencies. Through a series of three experiments and construction of a computational model, here we demonstrate that transient changes in reaction time and movement speed together offer a quantifiable metric to differentiate between reward- and effort-based alterations in movement vigor. Further, we suggest that objective increases in the metabolic cost of moving, not reductions in reward valuation, are driving much of the movement slowing occurring alongside healthy aging.

neuroscience↗

bioRxiv2023

Complex spikes perturb movements, revealing the sensorimotor map of Purkinje cells

The cerebellar cortex performs computations that are critical for control of our actions, and then transmits that information via simple spikes of Purkinje cells (P-cells) to downstream structures. However, because P-cells are many synapses away from muscles, we do not know how their output affects behavior. Furthermore, we do not know the level of abstraction, i.e., the coordinate system of the P-cells output. Here, we recorded spiking activities of hundreds of P-cells in the oculomotor vermis of marmosets during saccadic eye movements and found that following the presentation of a visual stimulus, the olivary input to a P-cell encoded a probabilistic signal that coarsely described both the direction and the amplitude of that stimulus. When this input was present, the resulting complex spike briefly suppressed the P-cells simple spikes, disrupting the P-cells output during that saccade. Remarkably, this brief suppression altered the saccades trajectory by pulling the eyes toward the part of the visual space that was preferentially encoded by the olivary input to that P-cell. Thus, analysis of behavior in the milliseconds following a complex spike unmasked how the P-cells output influenced behavior: the preferred location in the coordinates of the visual system as conveyed probabilistically from the inferior olive to a P-cell defined the action in the coordinates of the motor system for which that P-cells simple spikes directed behavior. SignificanceWe are lacking general principles that can describe how changes in a P-cells simple spikes might alter behavior. Here, we show that a brief suppression of a P-cells simple spikes in the oculomotor vermis consistently pulls the eyes in a direction that corresponds to the preferred location of the sensory space as conveyed probabilistically to that P-cell from the inferior olive. Thus, the inferior olive defines the coordinate system regarding the information that a P-cell is providing to the rest of the brain.

neuroscience↗

bioRxiv2023

Effort cost of harvest affects decisions and movement vigor of marmosets during foraging

Our decisions are guided by how we perceive the value of an option, but this evaluation also affects how we move to acquire that option. Why should economic variables such as reward and effort alter the vigor of our movements? In theory, both the option that we choose and the vigor with which we move contribute to a measure of fitness in which the objective is to maximize rewards minus efforts, divided by time. To explore this idea, we engaged marmosets in a foraging task in which on each trial they decided whether to work by making saccades to visual targets, thus accumulating food, or to harvest by licking what they had earned. We varied the effort cost of harvest by moving the food tube with respect to the mouth. Theory predicted that the subjects should respond to the increased effort costs by choosing to work longer, stockpiling food before commencing harvest, but reduce their movement vigor to conserve energy. Indeed, in response to an increased effort cost of harvest, marmosets extended their work duration, but slowed their movements. These changes in decisions and movements coincided with changes in pupil size. As the effort cost of harvest declined, work duration decreased, the pupils dilated, and the vigor of licks and saccades increased. Thus, when acquisition of reward became effortful, the pupils constricted, the decisions exhibited delayed gratification, and the movements displayed reduced vigor. Significance statementOur results suggest that as the brainstem neuromodulatory circuits that control pupil size respond to effort costs, they alter computations in the brain regions that control decisions, encouraging work and delaying gratification, and the brain regions that control movements, reducing vigor and suppressing energy expenditure. This coordinated response suggests that decisions and actions are part of a single control policy that aims to maximize a variable relevant to fitness: the capture rate.

neuroscience↗

bioRxiv2022

Independence and interaction between the control of moving and holding still in post-stroke arm paresis

Moving and holding-still (holding) have been posited to be under separate control regimes for both eye and arm movements. The paretic arm after stroke exhibits different abnormalities during rest vs. movement, providing an opportunity to ask whether control of these behaviors is independently affected in stroke. Here, we quantified resting postural abnormalities in stroke patients by measuring their biases in force production as they held their hand still in various locations in a planar workspace, and then assessed the influence of these resting force biases on reaching in the same workspace. We found that patients had marked resting force biases at each location, even when the arm was supported. However, these biases did not transfer to arm-supported planar reaching movements: not during initial acceleration, not in response to mid-trajectory perturbations, and not during deceleration to a stop. Rather, the abnormal resting forces only appeared to switch on after a movement had fully stopped. These findings suggest that moving and holding are functionally separable modes of control. At the same time, we found that the resting biases mirrored characteristics of abnormal synergies during movement: they markedly decreased when arm support was provided; they were higher in more distant positions that require breaking out of flexion; and they scaled with the Fugl-Meyer score for the upper extremity (a measure of intrusion of abnormal synergies during active movement). These three shared features suggest a common mechanism for resting biases and abnormal synergies, which appears to be a contradiction given the functional separation of moving and holding observed in the same patients. To resolve this paradox, we propose a conceptual model that predicts a breakdown in the functional separation between reaching and holding when patients move in the absence of weight support. This conceptual model posits that synergies are the behavioral manifestation of a spillover of posture into movement. Mapping these functional systems onto anatomical and physiological details of lesioned substrate after stroke may provide implementation-level insight into how normal arm motor control is assembled.

neuroscience↗

bioRxiv2022

Perturbation variance suppresses error sensitivity in the implicit learning system

When variability is added to a sensorimotor perturbation, total adaptation is impaired. In Albert et al.1 we explored this phenomenon, and observed that it is the brains implicit, i.e., subconscious learning system that is most affected by perturbation variance. We observed that perturbation variability impaired implicit learning by downregulating its sensitivity to error. Recently, Wang et al.2 present an alternate viewpoint: implicit error sensitivity does not change with experience, only the errors observed by the implicit system change. Here we evaluated this alternate view by empirically measuring error sensitivity as a function of error size. We found that perturbation variability strongly downregulates implicit error sensitivity when controlling for error size, consistent with our original results, counter to the inflexible model argued by Wang et al. With that said, a pre-existing relationship between error sensitivity and error magnitude noted by Wang et al. can contribute at least in part to implicit behavior. State-space models that start with this pre-existing error sensitivity curve and then update it with training according to a memory of errors most accurately tracked measured behavior.

neuroscience↗

bioRxiv2022

Signaling the agency of an erroneous outcome via synchronization of spikes in the cerebellum

Neurons in the inferior olive are thought to anatomically organize the Purkinje cells (P-cells) of the cerebellum into computational modules. To better understand what is computed by these modules, we designed a saccade task in marmosets that dissociated sensory and motor events and then recorded the complex and simple spikes of hundreds of P-cells. We found that when a visual target was presented at a random location, the olive reported the direction of that sensory event to one group of P-cells, but not to a second group. However, just before movement onset it reported the direction of the planned movement to both groups, even if that movement was not toward the target. At the end of the movement if there was an error but the subject chose to withhold the corrective movement, only the first group received information about the sensory prediction error. We organized the P-cells based on the information content of their olivary input and found that in the group that received sensory information, the simple spikes were suppressed during fixation, then produced a burst before saccade onset in a direction consistent with assisting the movement. In the second group the simple spikes were not suppressed during fixation but burst near saccade deceleration in a direction consistent with stopping the movement. Thus, the olive differentiated the P-cells based on whether they would receive sensory or motor information, and this defined their contributions to control of movements as well as holding still. Significance statementWe found that in the oculomotor region of the vermis, the olive informed a subset of P-cells about sensory events that were prediction errors, but all P-cells about the forthcoming movement. Using the information content of the olivary input we labeled the P-cells and produced a population code, revealing two groups with simple spikes that were antagonistic to each other, one contributing to movement initiation, the other signaling movement end.

neuroscience↗

bioRxiv2022

The vigor paradox: saccade velocity during deliberation encodes utility of effortful actions

During deliberation, as the brain considers its options, the neural activity representing the goodness of each option rises toward a threshold, and the choice is often dictated by the option for which the rise is fastest. Here we report a surprising correlate of these activities: saccade vigor. We engaged human subjects in a decision-making task in which they considered effortful options, each requiring walking various durations and inclines. As they deliberated, they made saccades between the symbolic representations of those options. These saccades had no bearing on the effort that they would later expend, yet as they deliberated, saccade velocities increased. The rate of rise in vigor was faster for saccades toward the option that they later indicated as their choice, and encoded the difference in the subjective value of the two effortful options. Once deliberation ended, following a brief delay the subjects indicated their choice by making another saccade. Remarkably, vigor for this saccade dropped to baseline and no longer encoded subjective value. These results are consistent with an urgency model of decision-making in which a global signal in the brain drives both the neural circuits that make decisions, and the neural circuits that make movements. Paradoxically, this common drive is shared between the oculomotor circuits and the decision-making circuits, even when the decision involves effortful expenditure during a future event. SignificanceThere is a link between the decisions we make and the movements that follow. Not only do we prefer options of greater value, but we also move faster to acquire them. When deliberating between options, neural activity rises to a threshold and the option that wins this race is the one chosen. We report a potential correlate of this in the motor control circuits; during deliberation, saccade vigor to both options rise, but faster for the option ultimately chosen. Thus, our movements appear to mirror the neural activity conducting the decision-making process. Paradoxically, this is true even when the movements have no direct bearing on the decision at hand.

neuroscience↗

bioRxiv2021

Synchronous spiking of cerebellar Purkinje cells during control of movements

The information that the brain transmits from one region to another is often viewed through the lens of firing rates. However, if the output neurons could vary the timing of their spikes with respect to each other, then through synchronization they could highlight information that may be critical for control of behavior. In the cerebellum, the computations that are performed by the cerebellar cortex are conveyed to the nuclei via inhibition. Yet, synchronous activity entrains nucleus neurons, making them fire. Does the cerebellar cortex rely on spike synchrony within populations of Purkinje cells (P-cells) to convey information to the nucleus? We recorded from multiple P-cells while marmosets performed saccadic eye movements and organized them into populations that shared a complex spike response to error. Before movement onset, P-cells transmitted information via a rate code: the simple spike firing rates predicted the direction and velocity of the impending saccade. However, during the saccade, the spikes became temporally aligned within the population, signaling when to stop the movement. Thus, the cerebellar cortex relies on spike synchronization within a population of P-cells, not individual firing rates, to convey to the nucleus when to stop a movement.

neuroscience↗

bioRxiv2021

Effects of reward history on decision-making and movement vigor

During foraging, animals explore a site and harvest reward, and then abandon that site and travel to the next opportunity. One aspect of this behavior involves decision-making, while the other involves movement control. We recently proposed that control of decision-making and movements may be linked via a desire to maximize a single normative utility: the sum of all rewards acquired, minus all efforts expended, divided by time. If this is the case, then the history of rewards, and not just its immediate availability, should dictate how long one decides to stay and harvest reward, and how fast one travels to the next opportunity. We tested this theory in a series of experiments in which humans used their hand to harvest tokens at a reward patch, and then used their arm to reach toward a subsequent opportunity. Experiencing a history of poor rewards not only led people to forage longer, but they also reached slower toward the next reward site. Thus, reward history had a consistent effect on both the decision-making process regarding when to abandon a reward site, and the motor control process regarding how fast to move to the next opportunity.

neuroscience↗

bioRxiv2021

P-sort: an open-source software for cerebellar neurophysiology

Analysis of electrophysiological data from Purkinje cells (P-cells) of the cerebellum presents challenges for spike detection. Complex spikes have waveforms that vary significantly from one event to the next, raising the problem of misidentification. Even when complex spikes are detected correctly, the simple spikes may belong to a different P-cell, raising the danger of misattribution. Here, we analyzed data from over 300 P-cells in marmosets, macaques, and mice, using an open-source, semi-automated software called P-sort that addresses the spike identification and attribution problems. Like other sorting software, P-sort relies on nonlinear dimensionality reduction to cluster spikes. However, it also uses the statistical relationship between simple and complex spikes to merge seemingly disparate clusters, or split a single cluster. In comparison with expert manual curation, occasionally P-sort identified significantly more complex spikes, as well as prevented misattribution of clusters. Three existing automatic sorters performed less well, particularly for identification of complex spikes. To improve development of analysis tools for the cerebellum, we provide labeled data for 313 recording sessions, as well as statistical characteristics of waveforms and firing patterns.

neuroscience↗

bioRxiv2021

The cost of correcting for error during sensorimotor adaptation

Learning from error is often a slow process. To accelerate learning, previous motor adaptation studies have focused on explicit factors such as reward or punishment, but the results have been inconsistent. Here, we considered the idea that a movement error carries an implicit cost for the organism because the act of correcting for error consumes time and energy. If this implicit cost could be modulated, it may robustly alter how the brain learns from error. To vary the cost of error, we considered a simple saccade adaptation task but combined it with motion discrimination: movement errors resulted in corrective saccades, but those corrections took time away from acquiring information in the discrimination task. We then modulated error cost using coherence of the discrimination task and found that when error cost was large, pupil diameter increased, and the brain learned more from error. However, when error cost was small, the pupil constricted, and the brain learned less from the same error. Thus, during sensorimotor adaptation, the act of correcting for error carried an implicit cost for the brain. Modulating this cost affects how the brain learns from error.

neuroscience↗

bioRxiv2020

Competition between parallel sensorimotor learning systems

Sensorimotor adaptation benefits from learning in two parallel systems: one that has access to explicit knowledge, and another that relies on implicit, unconscious correction. However, it is unclear how these systems interact: does enhancing one systems contributions, for example through instruction, impair the other, or do they learn independently? Here we illustrate that certain contexts can lead to competition between implicit and explicit learning. In some cases, each system is responsive to a task-related visual error. This shared error appears to create competition between these systems, such that when the explicit system increases its response, errors are siphoned away from the implicit system, thus reducing its learning. This model suggests that explicit strategy can mask changes in implicit error sensitivity related to savings and interference. Other contexts suggest that the implicit system can respond to multiple error sources. When these error sources conflict, a second type of competition occurs. Thus, the data show that during sensorimotor adaptation, behavior is shaped by competition between parallel learning systems.

neuroscience↗