Brain–computer interfaces for dissecting cognitive processes underlying sensorimotor control. (April 2016)

• Record Type: Journal Article
• Authors: Golub, Matthew D; Chase, Steven M; Batista, Aaron P; Yu, Byron M
• Is Part Of: Current opinion in neurobiology. Volume 37(2016)
• Page Start: 53
• Page End: 58
• Publication Date: 2016-04
• Subjects: Neurobiology -- Periodicals; 573.8
• DOI: 10.1016/j.conb.2015.12.005
• Languages: English
• ISSNs: 0959-4388

Abstract

Abstract : Highlights: Brain–computer interfaces (BCIs) facilitate studies of sensorimotor control. BCI can provide insights into prediction, learning, and multisensory integration. Components of a BCI are simple, well-defined, and easily manipulable. Similar cognitive processes underlie arm reaching and BCI control. Abstract: Sensorimotor control engages cognitive processes such as prediction, learning, and multisensory integration. Understanding the neural mechanisms underlying these cognitive processes with arm reaching is challenging because we currently record only a fraction of the relevant neurons, the arm has nonlinear dynamics, and multiple modalities of sensory feedback contribute to control. A brain–computer interface (BCI) is a well-defined sensorimotor loop with key simplifying advantages that address each of these challenges, while engaging similar cognitive processes. As a result, BCI is becoming recognized as a powerful tool for basic scientific studies of sensorimotor control. Here, we describe the benefits of BCI for basic scientific inquiries and review recent BCI studies that have uncovered new insights into the neural mechanisms underlying sensorimotor control.