title: Decoding Local Field Potentials for Neural Interfaces.
abstract: 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.
authors.forename: Andrew
authors.initials: A
authors.lastname: Jackson
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Hall
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001921:Brain / Q000502:physiology; D062207:Brain-Computer Interfaces; D000882:Haplorhini; D006801:Humans; D008253:Macaca mulatta; D012815:Signal Processing, Computer-Assisted