Decoding Movement From Electrocorticographic Activity: A Review

Ksenia Volkova; Mikhail A Lebedev; Alexander Kaplan; Alexei Ossadtchi

doi:10.3389/fninf.2019.00074

Decoding Movement From Electrocorticographic Activity: A Review

Front Neuroinform. 2019 Dec 3:13:74. doi: 10.3389/fninf.2019.00074. eCollection 2019.

Authors

Ksenia Volkova¹, Mikhail A Lebedev¹, Alexander Kaplan^{1

2

3}, Alexei Ossadtchi¹

Affiliations

¹ Center for Bioelectric Interfaces, Higher School of Economics, National Research University, Moscow, Russia.
² Center for Biotechnology Development, National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.
³ Laboratory for Neurophysiology and Neuro-Computer Interfaces, Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia.

Abstract

Electrocorticography (ECoG) holds promise to provide efficient neuroprosthetic solutions for people suffering from neurological disabilities. This recording technique combines adequate temporal and spatial resolution with the lower risks of medical complications compared to the other invasive methods. ECoG is routinely used in clinical practice for preoperative cortical mapping in epileptic patients. During the last two decades, research utilizing ECoG has considerably grown, including the paradigms where behaviorally relevant information is extracted from ECoG activity with decoding algorithms of different complexity. Several research groups have advanced toward the development of assistive devices driven by brain-computer interfaces (BCIs) that decode motor commands from multichannel ECoG recordings. Here we review the evolution of this field and its recent tendencies, and discuss the potential areas for future development.

Keywords: BCI; ECoG; brain-computer interface; electrocorticography; movement decoding.

Publication types

Review