Combinations of stroke neurorehabilitation to facilitate motor recovery: perspectives on Hebbian plasticity and homeostatic metaplasticity

Abstract

Motor recovery after stroke involves developing new neural connections, acquiring new functions, and compensating for impairments. These processes are related to neural plasticity. Various novel stroke rehabilitation techniques based on basic science and clinical studies of neural plasticity have been developed to aid motor recovery. Current research aims to determine whether using combinations of these techniques can synergistically improve motor recovery. When different stroke neurorehabilitation therapies are combined, the timing of each therapeutic program must be considered to enable optimal neural plasticity. Synchronizing stroke rehabilitation with voluntary neural and/or muscle activity can lead to motor recovery by targeting Hebbian plasticity. This reinforces the neural connections between paretic muscles and the residual motor area. Homeostatic metaplasticity, which stabilizes the activity of neurons and neural circuits, can either augment or reduce the synergic effect depending on the timing of combination therapy and types of neurorehabilitation that are used. Moreover, the possibility that the threshold and degree of induced plasticity can be altered after stroke should be noted. This review focuses on the mechanisms underlying combinations of neurorehabilitation approaches and their future clinical applications. We suggest therapeutic approaches for cortical reorganization and maximal functional gain in patients with stroke, based on the processes of Hebbian plasticity and homeostatic metaplasticity. Few of the possible combinations of stroke neurorehabilitation have been tested experimentally; therefore, further studies are required to determine the appropriate combination for motor recovery.

Robotic Assistance for Training Finger Movement Using a Hebbian Model: A Randomized Controlled Trial

“…Evidence supporting the motivational and Hebbian hypotheses is sparse 8,16 . Motivation, measured with end-of-training surveys, is generally higher for robotic compared to conventional training (e.g.…”

Pharmacotherapy to Enhance Cognitive and Motor Recovery Following Stroke

“…However, synaptic plasticity mediated by LTP and LTD may become excessive and needs to be regulated to maintain the physiological stability of the neuronal networks through the so-called homeostatic metaplasticity. The homeostatic metaplasticity is based on the dynamic change of the threshold for induction of LTP and LTD according to the history of activation [8].…”

Brain-machine Interface in Robot-assisted Neurorehabilitation for Patients with Stroke and Upper Extremity Weakness – the Therapeutic Turning Point

“…Appropriate BMIs can give patients the positive feedback [56][57][58]. This operant conditioning associated with the contingent reward via BMI can be linked to the positive feedback [33,37,38,59], which will lead to the increment in motivation of the participants. When the motivation of the patient is high, the chance of reward-based reinforcement learning will also have the chance to be increased [24].…”

“…Immediate feedback during a therapy could enhance more recovery via Hebbian neural plasticity [38] as well as partially due to more engagements in the therapy. As the brain naturally seeks hedonia, it can be beneficial for deeper emersion to the therapy that BMIs give the patient more immediate feedback [55].…”

“…The observation of contingent execution by the robot arm linked to the participant's brain status can give the participant's brain positive feedback [37], which can be associated with favorable outcomes. Selection of adequate brain signal for proper movement and its fine tuning may have favorable influences to the neural plasticity [33,38].…”