Open AccessDecoding Local Field Potentials for Neural Interfaces
Author(s) -
Andrew Jackson,
Thomas M. Hall
Publication year - 2016
Publication title -
ieee transactions on neural systems and rehabilitation engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.093
H-Index - 140
eISSN - 1558-0210
pISSN - 1534-4320
DOI - 10.1109/tnsre.2016.2612001
Subject(s) - bioengineering , computing and processing , robotics and control systems , signal processing and analysis , communication, networking and broadcast technologies
The stability and frequency content of local field potentials (LFPs) offer key advantages for long-term, low-power neural interfaces. However, interpreting LFPs may require new signal processing techniques which should be informed by a scientific understanding of how these recordings arise from the coordinated activity of underlying neuronal populations. We review current approaches to decoding LFPs for brain–machine interface (BMI) applications, and suggest several directions for future research. To facilitate an improved understanding of the relationship between LFPs and spike activity, we share a dataset of multielectrode recordings from monkey motor cortex, and describe two unsupervised analysis methods we have explored for extracting a low-dimensional feature space that is amenable to biomimetic decoding and biofeedback training.