Latent factors and dynamics in motor cortex and their application to brain-machine interfaces

• DOI: 10.7287/peerj.preprints.27217v1
• Publication Date: 2018-09-15T23:04:59Z
• Authors: Chethan Pandarinath; K. Cora Ames; Abigail A Russo; Ali Farshchian; Lee E Miller; Eva L Dyer; Jonathan C Kao
• Keywords: Leverage (statistics); Neural engineering; Systems neuroscience; Computational neuroscience

In the fifty years since Evarts first recorded single neurons in motor cortex of behaving monkeys, great effort has been devoted to understanding their relation movement. Yet these exist within a vast network, nature which largely inaccessible. With advances recording technologies, algorithms, and computational power, ability study network-level phenomena is increasing exponentially. Recent experimental results suggest that dynamical properties networks are critical movement planning execution. Here we discuss this systems perspective, how it reshaping our cortices. Following an overview key studies cortex, techniques uncover “latent factors” underlying observed neural population activity. Finally, efforts leverage factors improve performance brain-machine interfaces, promising make findings broadly relevant neuroengineering as well neuroscience.