Exploring Cognition with Brain-Machine Interfaces.

IF 6.5 1区 物理与天体物理 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY ACS Photonics Pub Date : 2022-01-04 DOI:10.1146/annurev-psych-030221-030214
Richard A Andersen, Tyson Aflalo, Luke Bashford, David Bjånes, Spencer Kellis
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Abstract

Traditional brain-machine interfaces decode cortical motor commands to control external devices. These commands are the product of higher-level cognitive processes, occurring across a network of brain areas, that integrate sensory information, plan upcoming motor actions, and monitor ongoing movements. We review cognitive signals recently discovered in the human posterior parietal cortex during neuroprosthetic clinical trials. These signals are consistent with small regions of cortex having a diverse role in cognitive aspects of movement control and body monitoring, including sensorimotor integration, planning, trajectory representation, somatosensation, action semantics, learning, and decision making. These variables are encoded within the same population of cells using structured representations that bind related sensory and motor variables, an architecture termed partially mixed selectivity. Diverse cognitive signals provide complementary information to traditional motor commands to enable more natural and intuitive control of external devices.

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利用脑机接口探索认知。
传统的脑机接口能解码大脑皮层的运动指令,从而控制外部设备。这些指令是更高层次认知过程的产物,发生在大脑区域网络中,用于整合感官信息、计划即将到来的运动动作以及监控正在进行的运动。我们回顾了最近在神经假体临床试验中发现的人类后顶叶皮层的认知信号。这些信号表明,大脑皮层的小区域在运动控制和身体监测的认知方面扮演着多种角色,包括感觉运动整合、计划、轨迹表征、躯体感觉、动作语义、学习和决策。这些变量在同一细胞群中通过结构化表征进行编码,将相关的感觉和运动变量结合在一起,这种结构被称为部分混合选择性。多样化的认知信号为传统的运动指令提供了补充信息,使外部设备的控制更加自然和直观。
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来源期刊
ACS Photonics
ACS Photonics NANOSCIENCE & NANOTECHNOLOGY-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
11.90
自引率
5.70%
发文量
438
审稿时长
2.3 months
期刊介绍: Published as soon as accepted and summarized in monthly issues, ACS Photonics will publish Research Articles, Letters, Perspectives, and Reviews, to encompass the full scope of published research in this field.
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