Neuromotor recovery from stroke: computational models at central, functional, and muscle synergy level

Abstract

Computational models of neuromotor recovery after a stroke might help to unveil the underlying physiological mechanisms and might suggest how to make recovery faster and more effective. At least in principle, these models could serve: (i) To provide testable hypotheses on the nature of recovery; (ii) To predict the recovery of individual patients; (iii) To design patient-specific “optimal” therapy, by setting the treatment variables for maximizing the amount of recovery or for achieving a better generalization of the learned abilities across different tasks. Here we review the state of the art of computational models for neuromotor recovery through exercise, and their implications for treatment. We show that to properly account for the computational mechanisms of neuromotor recovery, multiple levels of description need to be taken into account. The review specifically covers models of recovery at central, functional and muscle synergy level.

Computational neurorehabilitation: modeling plasticity and learning to predict recovery

“…Unsupervised learning is related to the concept of use-dependent learning, which refers to the phenomenon that the motor system can modify its performance through pure repetition of movements, without external feedback as to the success or failure of the movement [ 103 , 111 ]. Several initial models of network dynamics after stroke incorporate unsupervised learning (see review [ 25 ]). Unsupervised learning, together with homeostatic plasticity, likely plays a role in map and neural reorganization post-stroke, and presumably in decreasing movement variability and thereby improving functional performance [ 89 , 112 ].…”

“…There are also models that have focused on altered network dynamics following injury (e.g. [ 21 – 24 ]), and now, the first few models that have incorporated specific aspects of rehabilitation into their dynamics (see below and related reviews [ 25 , 26 ]). What is new about the computational neurorehabilitation approach is that it attempts to mathematically model the mechanisms underlying the rehabilitation process itself in order to understand the recovery of motor behavior, again via both restitution and compensation.…”

Editorial: Modularity in motor control: from muscle synergies to cognitive action representation

“…Uncovering a common underlying neural framework for the modular control of movements and its dysfunction represents an interesting avenue for future work. Casadio et al ( 2013 ) review the state of the art of computational models for neuromotor recovery from stroke through exercise, and their implications for treatment. The review specifically covers models of recovery at central, functional and muscle synergy level.…”

Alterations of Muscle Synergies During Voluntary Arm Reaching Movement in Subacute Stroke Survivors at Different Levels of Impairment

“…The purpose of muscle synergies analysis in people who suffered from motor deficits due to inappropriate muscle coordination is to reveal the underlying physiological mechanisms and offer suggestions on efficient recovery process (Safavynia et al, 2011 ; Casadio et al, 2013 ). Some studies have been conducted to find out how muscle synergies were affected after stroke.…”