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Table 2 Neuroplasticity: state-of-the-art and future directions

From: NSF DARE—transforming modeling in neurorehabilitation: a patient-in-the-loop framework

State-of-the-art

a. Hebbian learning models: spike-time dependence, long-term potentiation,

homeostatic plasticity, and long-term depression

b. Models at distinct spatial scales: microscale, mesoscale, phenotypic / behaviour.

c. Brain-machine interface algorithms that relate neuronal activity to behaviour.

Future directions

a. Experiments and models that link the multiple spatial and temporal scales of

neuroplasticity that can be used to developed informed and optimized treatment.

b. Improving brain machine interface (BMI) design and developing brain machine

interface algorithms that enhance neuroplasticity.

c. More fundamental studies that examine understand the influence of movement

on structural and functional neuroplasticity.