Non-causal spike filtering improves decoding of movement intention for intracortical BCIs

Nicolas Y. Masse, Beata Jarosiewicz, John D. Simeral, Daniel Bacher, Sergey D. Stavisky, Sydney S. Cash, Erin M. Oakley, Etsub Berhanu, Emad Eskandar, Gerhard Friehs, Leigh R. Hochberg, John P. Donoghue

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

Background: Multiple types of neural signals are available for controlling assistive devices through brain-computer interfaces (BCIs). Intracortically recorded spiking neural signals are attractive for BCIs because they can in principle provide greater fidelity of encoded information compared to electrocorticographic (ECoG) signals and electroencephalograms (EEGs). Recent reports show that the information content of these spiking neural signals can be reliably extracted simply by causally band-pass filtering the recorded extracellular voltage signals and then applying a spike detection threshold, without relying on "sorting" action potentials. New method: We show that replacing the causal filter with an equivalent non-causal filter increases the information content extracted from the extracellular spiking signal and improves decoding of intended movement direction. This method can be used for real-time BCI applications by using a 4. ms lag between recording and filtering neural signals. Results: Across 18 sessions from two people with tetraplegia enrolled in the BrainGate2 pilot clinical trial, we found that threshold crossing events extracted using this non-causal filtering method were significantly more informative of each participant's intended cursor kinematics compared to threshold crossing events derived from causally filtered signals. This new method decreased the mean angular error between the intended and decoded cursor direction by 9.7° for participant S3, who was implanted 5.4 years prior to this study, and by 3.5° for participant T2, who was implanted 3 months prior to this study. Conclusions: Non-causally filtering neural signals prior to extracting threshold crossing events may be a simple yet effective way to condition intracortically recorded neural activity for direct control of external devices through BCIs.

Original languageEnglish (US)
Pages (from-to)58-67
Number of pages10
JournalJournal of Neuroscience Methods
Volume236
DOIs
StatePublished - Oct 30 2014
Externally publishedYes

Keywords

  • Brain-computer interface
  • Microelectrode array
  • Neural decoding
  • Non-causal filter
  • Spike sorting
  • Threshold crossing

ASJC Scopus subject areas

  • Neuroscience(all)

Fingerprint Dive into the research topics of 'Non-causal spike filtering improves decoding of movement intention for intracortical BCIs'. Together they form a unique fingerprint.

  • Cite this

    Masse, N. Y., Jarosiewicz, B., Simeral, J. D., Bacher, D., Stavisky, S. D., Cash, S. S., Oakley, E. M., Berhanu, E., Eskandar, E., Friehs, G., Hochberg, L. R., & Donoghue, J. P. (2014). Non-causal spike filtering improves decoding of movement intention for intracortical BCIs. Journal of Neuroscience Methods, 236, 58-67. https://doi.org/10.1016/j.jneumeth.2014.08.004