神经科学
物理医学与康复
冲程(发动机)
神经可塑性
透视图(图形)
神经生理学
心理学
神经康复
医学
计算机科学
康复
人工智能
机械工程
工程类
作者
Karunesh Ganguly,Preeya Khanna,Robert J. Morecraft,David Lin
出处
期刊:Neuron
[Elsevier]
日期:2022-08-01
卷期号:110 (15): 2363-2385
被引量:3
标识
DOI:10.1016/j.neuron.2022.06.024
摘要
Stroke is a leading cause of disability. While neurotechnology has shown promise for improving upper limb recovery after stroke, efficacy in clinical trials has been variable. Our central thesis is that to improve clinical translation, we need to develop a common neurophysiological framework for understanding how neurotechnology alters network activity. Our perspective discusses principles for how motor networks, both healthy and those recovering from stroke, subserve reach-to-grasp movements. We focus on neural processing at the resolution of single movements, the timescale at which neurotechnologies are applied, and discuss how this activity might drive long-term plasticity. We propose that future studies should focus on cross-area communication and bridging our understanding of timescales ranging from single trials within a session to across multiple sessions. We hope that this perspective establishes a combined path forward for preclinical and clinical research with the goal of more robust clinical translation of neurotechnology.
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