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Annual Review of Psychology

Volume 73, 2022

Exploring Cognition with Brain–Machine Interfaces

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.

Keyword(s): brain–machine interface, cognition, learning, posterior parietal cortex, semantics, somatosensation
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/content/journals/10.1146/annurev-psych-030221-030214
2022-01-04
2024-04-20
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/content/journals/10.1146/annurev-psych-030221-030214
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Exploring Cognition with Brain–Machine Interfaces
Annual Review of Psychology 73, 131 (2022); https://doi.org/10.1146/annurev-psych-030221-030214
/content/journals/10.1146/annurev-psych-030221-030214
/content/journals/10.1146/annurev-psych-030221-030214
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