In my lab, we are intrigued by the question of why we move the way we do. Understanding the mechanisms that underlie motor behavior and motor recovery after brain injury are of high interest in the lab.
— Asst. Prof. Firas Mawase

An overview of our exciting new research endeavors

 
  • Understanding the core behavioral components underlying dexterity

  • Characterizing finger individuation, temporal synchronization and force control of single and multi-finger movements

  • Exploring the (dis)similarity between flexor and extensor-based dexterous movements

  • Implementing univariate and multivariate fMRI representations of dexterity in different regions of the sensorimotor system

  • Elucidating the mechanism underlying neural control of dexterity in non-human primates

Neural control of
dexterity


Deciphering the mechanisms that determine extent of recovery following Stroke

  • Developing MRI-based techniques to examine the neural basis of recovery post stroke

  • Unravelling the underlying process of spontaneous biological recovery

  • Neurorehabilitation - developing a closed-loop neuromodulation system

  • Using big data computational algorithms to characterize and predict the extent of recovery


Formation of motor memories: adaptation, skill and habit

  • Developing behavioral (reaching/walking) imaging and recording (fMRI, DTI, EEG) experiments for understanding motor behavior (adaptation, skills and habit)

  • Developing non-invasive brain stimulation protocols for understanding the neurophysiological mechanisms that underlie motor learning 

  • Understanding the role of cognitive processes (e.g. motivation) in motor behavior


Neuroplasticity following motor practice

  • Leveraging use-dependent plasticity as a simplified model for understanding neuroplasticity

  • Determining the role of use-dependent plasticity in voluntary behavior

  • Uncovering the neural basis of training-based neuroplasticity   


  • Developing EMG and EEG-based prosthetic hand for amputees

  • Developing a complete bidirectional neural interface for a prosthesis: from motor neurons back to the somatosensory neurons

Algorithms for neuroprostetic control