Spatio-temporal clustering of firing rates for neural state estimation

Austin J. Brockmeier, Il Park, Babak Mahmoudi, Justin C. Sanchez, José C. Príncipe

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

2 Scopus citations

Abstract

Characterizing the dynamics of neural data by a discrete state variable is desirable in experimental analysis and brain-machine interfaces. Previous successes have used dynamical modeling including Hidden Markov Models, but the methods do not always produce meaningful results without being carefully trained or initialized. We propose unsupervised clustering in the spatio-temporal space of neural data using time embedding and a corresponding distance measure. By defining performance measures, the method parameters are investigated for a set of neural and simulated data with promising results. Our investigations demonstrate a different view of how to extract information to maximize the utility of state estimation.

Original languageEnglish (US)
Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Pages6023-6026
Number of pages4
DOIs
StatePublished - Dec 1 2010
Event2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
Duration: Aug 31 2010Sep 4 2010

Publication series

Name2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Other

Other2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
CountryArgentina
CityBuenos Aires
Period8/31/109/4/10

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Health Informatics

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  • Cite this

    Brockmeier, A. J., Park, I., Mahmoudi, B., Sanchez, J. C., & Príncipe, J. C. (2010). Spatio-temporal clustering of firing rates for neural state estimation. In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 (pp. 6023-6026). [5627600] (2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10). https://doi.org/10.1109/IEMBS.2010.5627600