TCMC Session
Organized by John Krakauer, MD & Maurice Smith, MD, PhD

Featured Speakers:
Jose Carmena, PhD
Jörn Diedrichsen, PhD
 

Large-Scale Neural Circuit Dynamics During Neuroprosthetic Skill Learning

We are interested in how sensorimotor skills are learned and consolidated in the brain. We approach this problem using a neuroprosthetic skill learning paradigm. This is a very powerful framework for studying the neural correlates of learning behavior as it offers researchers the unique opportunity to directly control the causal relationship between neuronal activity and behavioral output. In particular, we focus on the question of how neuroplasticity relates to the acquisition and consolidation of neuroprosthetic skills, i.e. accurate, readily-recalled control of disembodied actuators irrespective of natural physical movement. The importance of this question is paramount as it impacts both brain function and dysfunction. In this talk I will present recent work from our laboratory using electrophysiology and imaging techniques in awake behaving primates and rodents, showing that 1) neuroplasticity facilitates consolidation of neuroprosthetic motor skill in a way that resembles that of natural motor learning; 2) corticostriatal plasticity is necessary for neuroprosthetic skill learning, and 3) operant learning occurs through the selection of specific neural patterns via feedback and reinforcement. A greater understanding of the neural substrates of neuroprosthetic skill learning can provide insight into the mechanisms of natural sensorimotor learning as well as help guide the development of neurobiologically-informed neuroprosthetic systems designed to aid people suffering from devastating neurological conditions.

Jörn Diedrichsen, PhD

The cortical hierarchy of motor representations:
Decoding the building blocks of motor skill

Skilled hand movements are generated through coordinated activity across a network of primary and secondary motor areas.  What is the role of each of these regions within the cortical control hierarchy? How can we characterise neural representations within each region? In our work, we use multivoxel pattern analysis of fMRI data to describe movement representations across various levels of the motor hierarchy in the human brain. I will present data that argues that the patterns of natural hand use shape the representations of single finger movements in primary motor regions. Building on these elementary representations, our experiments provide new insights into how the motor system represents longer sequences of finger movements, with premotor areas exhibiting representations of transitions between finger presses, as well as of hierarchically organised movement chunks. The ability to elucidate complex representations of motor skills in the human brain promises not only to accelerate our understanding of the neural mechanisms of skill learning, but is also important for translational research into motor disorders.