Hee Jae Jang¹, Alaa Ahmed², Adam Smoulder³, Becket Ebitz⁴

¹New York University, ²University of Colorado Boulder, ³Carnegie Mellon University, ⁴University of Montreal

Movements are often driven by the goal of garnering rewards. It is perhaps unsurprising then that the brain’s pathways for reward processing and motor control are tightly intertwined. In subcortical structures, dopamine (DA) neurons both control movements and encode value and reward-prediction errors (RPEs). Reward signals are also found widely across the brain, including in frontal cortex regions involved in action selection and motor planning/execution (i.e. prefrontal, premotor, and primary motor cortex). This brain-wide entanglement of reward and movement processing is also evident in behavior, where reward invigorates movements and drives decisions. How does the brain integrate reward information into the movements it generates, and how and why does this process fail? In this panel, we will explore these questions in multiple brain areas (striatum, prefrontal and motor cortex) across multiple model organisms (rats, humans, monkeys). First, Hee Jae Jang will discuss how DA release in the striatum balances encoding of movement, reward value, and RPE at distinct timepoints. Using fiber photometry and chemogenetic manipulation in rats, Hee Jae’s data suggest that the heterogeneous DA signals in dorsomedial striatum support value-based decision-making by promoting movement and learning at distinct timepoints for action policies. Second, Alaa Ahmed will detail the relationship between RPEs and movement vigor. Given DA’s association with value representation as well as movements, DA signaling may be the brain’s bridge linking greater rewards with more vigorous movements. Alaa’s work uses human reaching experiments to logically extend this hypothesis by demonstrating that RPEs often encoded by subcortical DA cells influence movement vigor as well. Third, Adam Smoulder will explore how increased rewards can aid-then-interfere with motor planning. While performance typically improves with greater incentives, we sometimes “choke under pressure”, failing when the stakes are highest. Using motor cortex recordings from rhesus macaques performing a reaching task, Adam will present evidence that reward interfering with motor planning is a potential neural mechanism of choking under pressure. Continuing in this theme, Becket Ebitz will consider how the brain generates mistakes: decisions that fail to maximize reward. Becket’s work in the prefrontal cortex of nonhuman primates suggests that mistakes are the result of fundamental nonlinearities in reward processing that may offer advantages for behavior over long timescales, even when they cause failures in the moment. We will conclude with a 20 minute discussion on the influence of reward on motor behavior, decision making, and upstream neural activity, led by Paul Cisek.

Compositionality and high-dimensionality of motor cortex activity

Elom Amematsro¹, Eric Trautmann¹, Najja Marshall², Larry Abbott¹, Mark Churchland¹

¹Columbia University, ²CTRL Labs

Presenting Author: Elom Amematsro

Direct neural perturbations reveal a dynamical mechanism for robust cortical movement generation

Daniel O’Shea¹, Lea Duncker¹, Maneesh Sahani², Krishna Shenoy¹

¹Stanford University, ²Gatsby Computational Neuroscience Unit

Presenting Author: Daniel O’Shea

Self-generated vestibular prosthetic input updates forward internal model of self-motion

Kantapon Pum Wiboonsaksakul¹, Charles Della Santina¹, Kathleen Cullen¹

¹Johns Hopkins University

Presenting Author: Kantapon Pum Wiboonsaksakul

Descending control of turning during walking in Drosophila

Helen Yang¹, Quinn Vanderbeck¹, Laia Serratosa Capdevila¹, Anna Li¹, Jasper Phelps², Brandon Mark³, Zetta AI LLC⁴, John Tuthill³, Wei-Chung Lee⁵, Rachel Wilson¹

¹Harvard Medical School, ²EPFL, ³University of Washington, ⁴Zetta AI LLC, ⁵Boston Children’s Hospital, Harvard Medical School

Presenting Author: Helen Yang

Dynamical mechanisms of flexible pattern generation in spinal neural populations

Lahiru Wimalasena¹, Chethan Pandarinath¹, Nicholas Au Yong²

¹Emory University/ Georgia Tech, ²Emory University

Presenting Author: Lahiru Wimalasena

A novel neural framework to assess movement control at the spinal motor neuron level

Francois Hug¹, Simon Avrillon², Dario Farina²

¹Universite Cote d’Azur, ²Imperial College London

Presenting Author: Francois Hug

Aaron Batista¹,Dagmar Sternad², Steve Chase³, Se-Woong Park⁴, Rachel Swanson⁵, Jon Wolpaw⁶

¹University of Pittsburgh, ²Northeastern University, ³Carnegie Mellon University, ⁴University of Texas at San Antonio, ⁵New York University, ⁶National Center for Adaptive Neurotechnologies

How do memories endure over time? Consider riding a bike. If you go for decades without riding, you do not lose the skill. Does this mean that the neural substrate encoding this skill remains unchanged? Or, has it changed, due to time and intervening experiences, but in a manner that still preserves skilled performance? This panel presents evidence, drawn from across brain regions, analysis scales, and skill types, that memories are active. The traditional concept of memory as a passive entity that is accessed when needed was suitable for the 1970s conception of a mostly hardwired CNS. By this view, memories were thought to be stored in special sites, specifically in a supposedly small number of modifiable synapses. Since then, new insights have made this concept obsolete. First, it is now clear that the CNS, from cortex to spinal cord, remains ubiquitously plastic through life. Driven largely by activity, neuronal properties change at every level – synapses, dendrites, axons, and hormones; glia change and vasculature changes; in some regions, new neurons can appear. Second, skill substrates are not sequestered to special sites; the plasticity comprising them is widely distributed through the CNS. What are the implications of these insights? How does bike-riding survive for decades in a continually changing CNS? A possible solution is that memories are active – their neural substrates can change, even when their corresponding behaviors are not being performed. The four talks consider, from different perspectives, the premise that memories are active. – Aaron Batista offers a brief overview before the talks, and moderates a panel discussion afterward. – Dagmar Sternad and Se-Woong Park examine the long-term practice and retention of motor skills from a behavioral perspective. They show evidence for stable ‘memories’ in a bimanual polyrhythmic task. What is retained and what is lost over long practice and what can adapt to other task demands? – Steve Chase presents evidence that the representation of a movement in motor cortex is altered by later learning, indicating that memories might be changing their neural substrates to accommodate newly learned skills. – Rachel Swanson considers the active maintenance of memories in the hippocampus and discusses the relation between systems consolidation during sleep and representational drift. Her talk extends the evidence that memories can be active beyond the motor system. – Jon Wolpaw’s message is that such insights invite a new paradigm for considering how skills are preserved. By introducing the concepts of “heksors” and the “negotiated equilibrium” of CNS properties that heksors create, he offers a new paradigm in which heksor plasticity ensures skill stability through life. – The panel concludes with a discussion focused on the themes emerging across the talks.

Terence Sanger¹, Andreas Kardamakis², Leah Krubitzer³, Paul Cisek⁴

¹University of California, Irvine, ²Universitas Miguel Hernandez, ³University of California, Davis, ⁴University of Montreal

Like all biological entities, nervous systems are products of evolution. They were constructed through a long process of gradual modifications, each defined within the developmental constraints of a given ancestral population and sculpted by the demands of survival in a particular niche. Consequently, the resulting circuits and mechanisms are not always readily interpretable in terms of their functional roles in modern animals or in terms of normative theories of how the nervous system should be organized. Nevertheless, a growing body of comparative and developmental data makes it increasingly possible to reconstruct the sequence of modifications that took place in our evolutionary history, providing valuable insights that can constrain theory development and, we believe, help to make better sense of data that might otherwise appear inexplicable. In this panel, we will discuss some of the potential insights that considerations of evolutionary history offer for theories and studies of the neural control of movement. Terry Sanger will begin with a computational perspective, describing how simple control systems set the stage for more complex ones. This will start from basic reflexes to state-dependent control and to multi-step autonomous behaviors based on reward prediction, discussing corresponding innovations in biological circuits. Andreas Kardamakis will take a closer look at some of the specific innovations. In particular, he will describe recent work in his lab comparing the retino-colliculo-spinal circuits involved in visually guided orientation behavior in mice to homologous circuits previously identified in lamprey. Leah Krubitzer will describe how the cerebral cortex was elaborated from early mammals to modern species, including primates. In particular, she will discuss how sensorimotor maps have adapted to species-typical behavioral capacities along different lineages. Paul Cisek will return to computational questions in the context of a summary of the evolutionary history of the lineage that produced primates. He will suggest how the expansion of the behavioral repertoire led to an architecture consisting of parallel and nested behavioral control circuits, including specialized cortical action maps as well as cortico-striatal circuits that arbitrate among them. Finally, Megan Carey will moderate a discussion among members of the panel and the audience, focusing on the implications of evolutionary perspectives for current theories of the neural control of movement and new approaches for studying it.

Megan Carey¹, Andrew Pruszynski², Abigail Person³, Javier Medina⁴

¹Champalimaud Center for the Unknown, ²Western University, ³University of Colorado, ⁴Baylor College of Medicine

The concept of internal models has been extremely influential for the study of motor control. This panel will bring together research from a variety of behaviors and brain systems, including control of reaching movements, locomotion, and associative learning, to discuss recent progress in our understanding of how internal models are implemented by the brain. First, Andrew Pruszynski and Abigail Person will discuss internal models for the control of reaching movements in humans, monkeys, and mice. They will present recent results that suggest how internal models are represented in cerebral cortex and cerebellum and how they contribute to voluntary, reflexive, and adaptive control. Next, Megan Carey will present recent evidence that individual cerebellar Purkinje cells simultaneously encode movements of multiple limbs and body parts and discuss how this information could be used within an internal model framework to achieve precise coordination of whole-body movement during locomotion. Finally, Javier Medina will describe associative learning experiments in mice that reveal how recurrent cerebellar circuits can form distinct modules to implement inverse and forward models, allowing the cerebellum to rapidly generate accurate motor commands.

Dynamic synchronization between hippocampal spatial representations and the stepping rhythm

Abhilasha Joshi¹, Eric Denovellis¹, Abhijith Mankili¹, Yagiz Meneksedag², Thomas Davidson¹, Anna Gillespie¹, Jennifer Guidera¹, Demetris Roumis¹, Loren Frank¹

¹University of California, San Francisco, ²Hacettepe University

Presenting Author: Abhilasha Joshi

Neural basis of skilled behaviors

Adam Hantman¹

¹University of North Carolina – Chapel Hill

Presenting Author: Adam Hantman

Slower cortical responses during balance recovery associated with nonparetic postural compensation and stiffer biomechanical reactions in people post stroke

Jacqueline Palmer¹, Aiden Payne², Jasmine Mirdamadi³, Lena Ting³, Michael Borich³

¹University of Kansas Medical Center, ²Florida State University, ³Emory University

Presenting Author: Jacqueline Palmer

Characterization of locomotor adaptation and generalization dynamics from high-dimensional neuromuscular data

Dulce Mariscal¹, Krista Fjeld¹, Gelsy Torres-Oviedo¹

¹University of Pittsburgh

Presenting Author: Dulce Mariscal

Uncertainty differentially shapes premotor and primary motor activity during movement planning

Bence Bagi¹, Brian Dekleva², Lee Miller³, Juan Gallego¹

¹Imperial College London, ²University of Pittsburgh, ³Northwestern University

Presenting Author: Bence Bagi

Cerebellar granule cells and climbing fibers jointly acquire signals to learn reward timing

Mark Wagner¹, Martha Garcia Garcia¹, Lina Takemaru¹, Akash Kapoor¹, Oluwatobi Akinwale¹, Tony Hyun Kim², Casey Paton³, Mark Schnitzer², Liqun Luo², Ashok Litwin-Kumar⁴

¹National Institutes of Health, ²Stanford University, ³Cornell University, ⁴Columbia University

Presenting Author: Mark Wagner

Join us to learn more about the society, the financial position, incoming board members and more!

Jean-Jacques Orban de xivry¹, Di Cao², Jovin Jacobs³, Alanna Watt⁴

¹KU Leuven, ²Johns Hopkins University, ³Champalimaud Centre for the Unknown, ⁴McGill University

The cerebellum plays multiple roles in skilled motor function, including maintaining calibrated movement, error correction, prediction of target motion, and internal model simulation. These functions are not specific to a particular movement or limb. Given its importance, cerebellar injury or degeneration can have devastating consequences. Cerebellar dysfunction leads to a range of motor symptoms including impaired inter-joint coordination, inaccurate movements, balance problems, and inability to perform repeated movements. Yet, we are missing a link between the structural changes in the cerebellum that are caused by age and disease (mostly in animal models) and the changes in function (mostly in human studies). The goal of this panel is to bridge this gap by providing an overview of the links between age- or disease-related changes in the cerebellum and their impact on motor function. This overview will be based on animal models and human data on both healthy aging and cerebellar degeneration. It will span different tasks (reaching, locomotion, etc.) and different techniques (electrophysiology, pharmacological manipulation, mathematical modeling). Jean-Jacques Orban de Xivry will present new results on the effect of aging on cerebellar motor tasks. He will suggest the existence of a motor reserve, similar to the idea of a cognitive reserve. Di Cao will present data she collected during COVID using a “ship-to-home” VR system. Her data reveal the structure of computational deficits in feedforward and feedback control pathways for individuals with cerebellar ataxia. Using a control-theoretic experimental approach, we found that damage to the cerebellum does cause two computational deficits: cerebellar damage increases time delay on both pathways and reduces the ability to extract useful information from time-lead (preview) information. Alanna Watt will discuss recent work from her lab demonstrating that similar cellular changes occur in Purkinje cells in the mouse cerebellum in both aging and ataxia. Jovin Jacobs will present recent work on how loss of Purkinje cell/granule cells in adult mice affects locomotion and locomotor learning. He will show that; 1) the behavioral effects largely overlap with that seen in Purkinje cell degeneration mice, 2) that the effects scale as a function of cell death magnitude and 3) that the data suggests locomotion is more resilient to loss of Purkinje cells than granule cells. Together, this panel will aim at highlighting how much change in cerebellar structure leads to actual changes in motor function and what are the key components for understanding the link between cerebellar structure and function. It will also provide the opportunity to discuss how understanding how age- and disease-related changes in cerebellum can teach us about cerebellar function.

The activity of populations of single neurons underlying behavior is well captured by relatively few population-wide patterns. Intriguingly, the study of these activity patterns—the “latent dynamics”—has shed light into questions about cognition, motor control, and learning that had remained elusive when focusing on the activity of individual neurons.

In this talk, I will give an overview of our work to understand the neural basis of motor control and learning from this perspective. This research is based on the hypothesis that the latent dynamics arise from “neural manifolds” that reflect fundamental biophysical constraints on circuit function. Under this assumption, first I will show that animals generate the same latent dynamics as they perform the same covert or overt behavior on different days, which we can uncover even when we record from different neurons. Second, I will show how adopting this framework reveals large similarities in neural manifolds underlying a variety of reaching and wrist manipulation tasks, even if the properties of single neurons change dramatically across them. Third, I will provide evidence that adopting this framework helps identify region-specific contributions to motor adaptation. Finally, I will present recent results showing that even if each animal has a brain that is unique, individuals from the same species that are engaged in the same behavior share preserved latent dynamics.

Thus, the study of neural manifolds and their associated latent dynamics provides insights into how individual animals both consistently and flexibly perform a variety of behaviors, and may enable principled studies across groups of individuals, and even comparative studies across different species.

Ismael Seáñez⁴, Elvira Pirondini¹, Monica Perez², John Krakauer³

¹University of Pittsburgh, ²Shirley Ryan Ability Lab, ³Johns Hopkins University and The Santa Fe Institute, ⁴Washington University

Decades of basic research in animals and humans provided evidence that changes in the CNS can lead to behavioral improvements after damage to the motor system after either stroke or spinal cord injury. However, despite this knowledge, we still lack a therapeutic approach that achieves much beyond what can be expected from spontaneous biological recovery. As a result, most rehabilitation approaches emphasize compensatory strategies rather than true restoration. In exciting parallel advancements in neuro-technologies for animal and human research offered new tools to investigate and manipulate the neural activity of specific populations of neurons across the entire nervous system. In consequence, against this somewhat pessimistic backdrop, we will suggest that recent results from new studies in humans and non-human primates using these tools and combining intense behavioral training and electrical stimulation provide reason for optimism. Dr. Elvira Pirondini will open the panel with discussing the neural changes that occur both at single cell and a neural population level in non-human primate after a sub-cortical stroke and showing how the investigation of these changes led to the development of a novel deep brain stimulation approach to treat post-stroke motor deficits. Dr. Ismael Seáñez, will then shift toward human applications of electrical spinal cord stimulation. Specifically, he will discuss the neural mechanisms behind improvements in muscle recruitment selectivity by non-invasive technologies, and why understanding these is crucial for translation into effective rehabilitation strategies. Dr. Monica Perez will then show that electrical and magnetic stimulation can be used to tap into ancestral mechanisms of synaptic plasticity to boost functional recovery in people with spinal cord injury highlighting the relevance of working on protocol optimization. Finally, Dr. John Krakauer will close the panel, by summarizing the evidence accumulated so far and discussing the very concept of recovery, compensation and plasticity after injury. The open discussion will revolve around an important question: are we ready now to design technologies that can really improve the life of people with motor deficits?

Get out and experience Victoria!  Further information regarding excursion options can be found on the Excursions page.

Fabio Rizzoglio¹, Xuan Ma¹, Carlos Vargas-Irwin², Joanna Chang³

¹Northwestern University, ²Brown University, ³Imperial College London

The interconnected networks of neurons generate coordinated activity that plans and executes our highly varied motor behaviors. Within this varied movement repertoire are many stereotypic behaviors that tend to be preserved across individuals, despite the idiosyncratic neural circuitry of any given individual’s brain. An obvious question is whether there may be a shared neural representation of these preserved behaviors, or that each individual has found a unique solution to a shared problem. Experimental work has shown that the space of observed neural activity patterns is constrained to a low-dimensional manifold. Perhaps the signals within this latent space might contain a stable representation across individuals. However, as the manifold is embedded in a space with ever-changing neurons over time, comparisons of population activity across individuals seem impossible. Recently, though, it has been shown that a consistent image of motor intent over time can be recovered, at least for highly stereotypical tasks, if one performs a change of basis and “aligns” the manifolds from a given day to that of another day. This has enabled fixed decoders to make accurate predictions over periods as long as two years. Might similar alignment methods allow us to address the question of how motor intent for shared behaviors is represented across individuals? Our work addresses this question across several species and types of motor behaviors. We have discovered that latent spaces are preserved not only across time, but also across individuals of several species and different brain areas, extending even across human and non-human primates performing (or attempting to perform) the same behavior. A similar phenomenon is also observed in the same individual but for the case of different behaviors, with a significant portion of neural covariance pattern preserved across quite varied movements. Carlos Vargas-Irwin will introduce the cross-individual analysis and show that neural population patterns in primary motor cortex (M1) and ventral premotor cortex are preserved across monkeys performing reach and grasp. Joanna Chang will expand on these concepts by showing preserved latent dynamics across the dorsolateral striatum of mice grasping and pulling a joystick, as well as across M1 of monkeys performing a reach task under both overt and covert conditions. Fabio Rizzoglio will discuss how the consistency of task representation extends across species, showing that the latent dynamics in the neural manifold of a monkey can be aligned to those of a human with a paralyzed arm attempting to do the same task and that such aligned latent dynamics allowed to make EMG predictions without computing a new decoder. Xuan Ma will expand the topic of the panel to the cases of different motor tasks, showing that neural manifolds in monkey M1 are partially preserved across multiple unconstrained grasping movements, even though the limb states and contexts vary greatly.

How does the cortical hand representation change following amputation? A pre- and post-amputation fMRI study

Hunter Schone¹, Mathew Kollamkulam², Craig Gerrand³, Norbert Kang⁴, Alexander Woollard⁴, Imad Sedki³, Roni Maimon Mor², Chris Baker¹, Tamar Makin⁵

¹National Institutes of Health, ²University College London, ³The Royal National Orthopaedic Hospital NHS Trust, ⁴Royal Free Hospital NHS Trust, ⁵University of Cambridge

Presenting Author: Hunter Schone

The role of sensory variability in closed-loop sensorimotor control

Kassia Love¹, Marissa Rosenberg², Raquel Galvan-Garza³, Torin Clark⁴, Faisal Karmali¹

¹Mass Eye and Ear, ²Space X, ³Lockheed Martin, ⁴University of Colorado – Boulder

Presenting Author: Kassia Love

Is implicit reward-based motor learning possible?

Nina van Mastrigt¹, Jonathan Tsay², Tianhe Wang², Guy Avraham², Sabrina Abram², Katinka van der Kooij¹, Jeroen B.J. Smeets¹, Rich Ivry²

¹Vrije Universiteit Amsterdam, ²UC Berkeley

Presenting Author: Nina M. van Mastrigt

Autonomic correlate of human motor learning and contextual inference

Atsushi Yokoi¹

¹National Institute of Information and Communications Technology

Presenting Author: Atsushi Yokoi

Neural mechanisms of eye-head coordination during active gaze redirection in mice

Brandie Verdone¹, Hui Ho Chang¹, Dale Roberts¹, Kathleen Cullen¹

¹Johns Hopkins University

Presenting Author: Brandie Morris Verdone

Neural correlates of online movement preparation

Mahdiyar Shahbazi¹, Giacomo Ariani², Andrew Pruszynski¹, Jörn Diedrichsen¹

¹University of Western Ontario, ²Nature Human Behaviour

Presenting Author: Mahdiyar Shahbazi

Kahori Kita¹, Lucas Dal’Bello², Amy Orsborn³, Andrea d’Avella⁴

¹Johns Hopkins University, ²University of Tsukuba, ³University of Washington, ⁴IRCCS Fondazione Santa Lucia / University of Messina

How can people learn new skills? De novo learning is a topic of increasing interest in the motor control field. In the real world, we often face situations where we have to learn unfamiliar and arbitrary relationships between our actions and their consequences from scratch, for instance, driving a car or controlling a drone. New control policy is acquired typically through multiple hours of practice. One long-standing paradigm used in motor learning research is adaptation which challenges participants to learn rather minor perturbations to their existing controllers of motion. Despites its importance, de novo learning has received less attention than adaptation and mechanisms of de novo learning are still unclear. In this panel, four speakers, using a range of physiological, behavioral, and computational methods, will present different perspectives to provide new insights into de novo learning. Amy Osborn will present work exploring de novo learning in brain-computer interfaces (BCIs). BCIs define novel sensorimotor mappings from neural activity to behavior that engage learning with marked parallels to natural motor skill learning. She will present analysis of experimental data and neural network models that explore how the “decoder” that maps neural activity to movement influences learning computations in the brain. Andrea d’Avella will address de novo learning in the context of muscle synergies. In a synergy-based controller, de novo learning may require learning of new synergies. Virtual tendon-transfer surgeries, i.e. remapping of muscle forces simulated in virtual reality using myoelectric control, allow to investigate learning of new control policies with or without learning of new synergies. He will present recent results on adaptation to virtual surgeries across multiple days. Kahori Kita will present her work about de novo learning from a behavioral perspective. In everyday life, we need to learn novel motor skills through “de novo” learning and frequently switch between those skills. For instance, picking up and using different tools or getting on or off a bike. It’s unclear whether analogous switch costs exist in the context of switching between entirely different motor skills. She will introduce her latest results of learning two de novo policies and switching between them. Lucas Rebelo Dal’Bello will present a computational model that elucidates the role of motor exploration on error-based de novo learning. In his computational model, motor exploration is used to learn an internal model responsible for correcting movement errors, which is then used to guide the error-based learning of a new control policy for the task. He will then show how his model can replicate the results from multiple behavioral studies. Lastly, Dagmar Sternad will energize a 20-minutes discussion on key aspects of de novo learning, possible universal principles across domains.

The role(s) of the cerebellum are still uncertain. A prominent theory is that the cerebellum holds a predictive internal model of the sensory-motor system. This is a crucial component in the process of state estimation, combining information from descending motor commands and ascending sensory afferent signals to predict the outcome of actions, helping determine the current state of the motor system. Without state estimation, feedback delays in sensory pathways would degrade performance. State estimate is also likely to underpin coordinated actions, again overcoming feedback delays to allow synchronicity of different effectors. This role would explain the contribution the cerebellum makes to control action, as well as its obvious importance for and dependence on learning and adaptation.  Inaccuracy in state estimates would lead to hypometria and dyscoordination like that observed in cerebellar ataxia. The fundamental role of prediction in state estimation also suggests a wider role for the cerebellum in non-motor domains.

In this lecture I describe studies from my laboratory that support this theory, using laboratory-based motor tasks to explore movement control and coordination. Our motor studies have included testing the effects of artificially extending visual feedback delays, adaptation tasks, and recording, inactivating, and imaging cerebellar activity. We have also used transcranial magnetic and electrical stimulation to disrupt its operations, in movement and in cognitive tasks. I will end with some recent experiments testing novel “event related” methods of TDCS to enhance motor adaptation.

Following the Distinguished Career Award presentation and talk, join us for a drink to celebrate NCM 2023!