Listening to the music of the brain: Live analysis of ECoG recordings using digital audio workstation software

Griffin Milsap, Matthew Fifer, Nathan Crone, Nitish Thakor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

A process is presented for analyzing electrocor-ticographic (ECoG) recordings and prototyping brain computer interfaces in which complex signal processing chains are able to be rapidly developed and iterated in digital audio workstation (DAW) software. DAW software includes many built-in 'drag and drop' blocks that perform common, low-level signal processing algorithms such as filtering and envelope extraction. In addition to being optimized for real-time performance, DAW software also produces audio output, allowing for listening to raw and processed signals. Hearing these sonifications can impart new insights that may not be apparent in purely visual representations. A simple functional mapping analysis is performed in a DAW called Pure Data and compared to the results from a more traditional spatiotemporal analysis in MATLAB. Channels exhibiting qualitative activation in the resulting functional maps were further analyzed in another DAW called Renoise, wherein several high frequency (i.e., >400 Hz) features were observed. This study demonstrates an example use of DAW software, which we suggest is an easy-to-use and intuitive environment for real-time exploratory analyses and sophisticated sonification of ECoG recordings.

Original languageEnglish (US)
Title of host publication2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
Pages682-685
Number of pages4
DOIs
StatePublished - 2013
Event2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013 - San Diego, CA, United States
Duration: Nov 6 2013Nov 8 2013

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Other

Other2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013
Country/TerritoryUnited States
CitySan Diego, CA
Period11/6/1311/8/13

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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