Biology subjects

Carmena, J.

Publications and source records attributed to Carmena, J..

3 recordsLinked to original sources

bioRxiv2022

A neural model of proximity to reward

Throughout learning, refinement of cortical activity in cortex, a process termed "credit assignment", underlies the refinement of behavioral actions leading to reward. While previous research shows striatums role in linking behavior to reward, striatums role in linking the underlying behaviorally-relevant cortical activity to reward remains unclear. Leveraging a neuroprosthetic task while recording from the rat cortex and striatum, we demonstrate that the striatum encodes the dynamics of the proximity of cortical activity to reward. Such encoding was independent from external task feedback and emerged as cortical activity consolidated over learning, with dorsal and ventral striatum playing complementary yet distinct roles. Striatal activity thus constitutes a neural model of cortical progress towards reward, suggesting one mechanism by which the brain implements credit assignment to refine behavior.

neuroscience↗

bioRxiv2021

A non-invasive brain-machine interface via independent control of individual motor units

Brain-machine interfaces (BMIs) have the potential to augment human functions and restore independence in people with disabilities, yet a compromise between non-invasiveness and performance limits their relevance. Here, we demonstrate a BMI controlled by individual motor units non-invasively recorded from the biceps brachii. Through real-time auditory and visual neurofeedback of motor unit activity, 8 participants learned to skillfully and independently control three motor units in order to complete a two-dimensional center-out task, with marked improvements in control over 6 days of training. Concomitantly, dimensionality of the motor unit population increased significantly relative to naturalistic behaviors, largely violating recruitment orders displayed during stereotyped, isometric muscle contractions. Finally, participants demonstrated the potential of a motor unit BMI to power general applications by navigating a virtual keyboard in a spelling task, achieving performances comparable to spelling-tailored non-invasive BMIs that leverage less flexible control strategies to improve performance. These results highlight a largely unexplored level of flexibility of the sensorimotor system and show that this can be exploited to create a versatile, skillfully-controllable non-invasive BMI that has great potential to both provide translational benefit and augment motor functions.

bioengineering↗

bioRxiv2018

An Automated Behavioral Apparatus to Assess Distal Forelimb Function in Non-Human Primates

BackgroundPrimate distal forelimb behaviors are commonly assessed using reach-to-grasp tasks. While these tasks are widely recognized as sensitive assays for forelimb function, they often require experimenter input, lack precise temporal cues for physiological monitoring, and can be expensive.\n\nNew MethodUsing components developed by open-source electronics platforms, we have designed and tested a low-cost system to measure distal forelimb function in non-human primates. Our system is inexpensive; it is made primarily of acrylic and 3D printed plastic parts. Our control software, developed in MATLAB, was also used to control two cameras in order to capture and process video during behavior. The system was equipped with sensors, motors and microcontrollers to control the timing of the task and facilitate synchronization between behavior and neurophysiology with high temporal precision.\n\nResultsWe demonstrate that this system can be used to monitor motor recovery after stroke and investigate neurophysiological correlates of motor control.\n\nComparison with Existing MethodsCompared to a previous version of this task, our setup reduces experimenter input while providing unbiased delivery of behavioral cues and behavioral measurements with the temporal precision necessary for electrophysiological studies.\n\nConclusionsIn summary, our system will allow unbiased monitoring of forelimb function in both healthy and injured animals that is compatible with electrophysiological studies.

neuroscience↗