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

Griffin Milsap, Matthew Fifer, Nathan E Crone, Nitish V Thakor

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

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 publicationInternational IEEE/EMBS Conference on Neural Engineering, NER
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

Other

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

Fingerprint

Brain
Signal processing
Brain computer interface
Audition
MATLAB
Drag
Chemical activation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

Cite this

Milsap, G., Fifer, M., Crone, N. E., & Thakor, N. V. (2013). Listening to the music of the brain: Live analysis of ECoG recordings using digital audio workstation software. In International IEEE/EMBS Conference on Neural Engineering, NER (pp. 682-685). [6696026] https://doi.org/10.1109/NER.2013.6696026

Listening to the music of the brain : Live analysis of ECoG recordings using digital audio workstation software. / Milsap, Griffin; Fifer, Matthew; Crone, Nathan E; Thakor, Nitish V.

International IEEE/EMBS Conference on Neural Engineering, NER. 2013. p. 682-685 6696026.

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

Milsap, G, Fifer, M, Crone, NE & Thakor, NV 2013, Listening to the music of the brain: Live analysis of ECoG recordings using digital audio workstation software. in International IEEE/EMBS Conference on Neural Engineering, NER., 6696026, pp. 682-685, 2013 6th International IEEE EMBS Conference on Neural Engineering, NER 2013, San Diego, CA, United States, 11/6/13. https://doi.org/10.1109/NER.2013.6696026
Milsap, Griffin ; Fifer, Matthew ; Crone, Nathan E ; Thakor, Nitish V. / Listening to the music of the brain : Live analysis of ECoG recordings using digital audio workstation software. International IEEE/EMBS Conference on Neural Engineering, NER. 2013. pp. 682-685
@inproceedings{aad6cd5e38a74f33849800834b1ab847,
title = "Listening to the music of the brain: Live analysis of ECoG recordings using digital audio workstation software",
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.",
author = "Griffin Milsap and Matthew Fifer and Crone, {Nathan E} and Thakor, {Nitish V}",
year = "2013",
doi = "10.1109/NER.2013.6696026",
language = "English (US)",
isbn = "9781467319690",
pages = "682--685",
booktitle = "International IEEE/EMBS Conference on Neural Engineering, NER",

}

TY - GEN

T1 - Listening to the music of the brain

T2 - Live analysis of ECoG recordings using digital audio workstation software

AU - Milsap, Griffin

AU - Fifer, Matthew

AU - Crone, Nathan E

AU - Thakor, Nitish V

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84897734578&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84897734578&partnerID=8YFLogxK

U2 - 10.1109/NER.2013.6696026

DO - 10.1109/NER.2013.6696026

M3 - Conference contribution

AN - SCOPUS:84897734578

SN - 9781467319690

SP - 682

EP - 685

BT - International IEEE/EMBS Conference on Neural Engineering, NER

ER -