BME PhD Candidate Andria J. Farrens will be defending her dissertation:


The neural and behavioral characteristics of dynamic adaptation of the wrist


  • Location: North STAR Atrium
  • Room #: 113
  • Zoom Link:
  • Password: 113
  • Date: May 16th, 2022
  • Time: 3:00-5:00 pm, EST
  • Committee: Fabrizio Sergi (Chair), Joshua Cashaback, Ryan Zurakowski, Susanne Morton, Shahabeddin Vahdat


Neurorehabilitation is centered on the idea that retraining motor function can be advanced by incorporating concepts of neuromotor control into therapy. Robot-mediated neurorehabilitation (RMN) uses robots as tools to execute rehabilitation protocols to retrain motor control following neural injury. Although many everyday manipulation tasks are performed using the hand and wrist, relatively few studies have focused on the neuromotor control of the wrist, especially during human-robot interaction. This thesis addresses this gap in knowledge, by establishing fundamental behavioral characteristics and neural correlates of neuromotor control of the wrist in healthy, young adults.

In aim one of this study, we performed behavioral experiments to study motor control of the wrist in a variety of dynamic environments during interaction with an exoskeleton device. We combined computational modeling with behavioral measures of wrist kinematics, kinetics and EMG to characterize feed-forward motor control processes utilized during task execution. Results from our experiments validate the use of a two-state model for describing adaptation-based control of the wrist, and determined that deviations from model-predicted behavior were attributable, in part, to muscle co-contraction during these tasks.

In aim 2, we performed a series of task-based fMRI experiments to identify brain regions associated with active motor control of the wrist during dynamic perturbations. After validating measurements taken with our device, we focused on methods for identifying adaptation specific processes during task execution, while controlling for other aspects of task execution such as force production and perception of errors. Results of this work identified regions within the contralateral primary motor cortex, the posterior parietal cortex, and the ipsilateral cerebellum of the trained wrist that were specific to adaptation learning. 

In aim 3, we used resting state fMRI to localize brain regions associated with formation of motor memories following dynamic adaptation via changes in resting state functional connectivity (rsFC).  In this work, we quantified changes in rsFC within task-localized brain regions within the cortico-thalamic-cerebellar (CTC) network and cortical sensorimotor network immediately following dynamic adaptation. RsFC changed in two networks: rsFC increased within the CTC network and decreased interhemispherically within the cortical sensorimotor network. Changes in both networks were associated to day one behavior, while only changes in the CTC network were associated with retention, indicative of memory formation. Behavioral variance decomposition analysis indicated that increases within the CTC network were specific to adaptation, while decreases in the cortical sensorimotor network were associated with alternate error reduction processes.