Human ECoG analysis during speech perception using matching pursuit: a comparison between stochastic and dyadic dictionaries

Supratim Ray; Christophe C Jouny; Nathan E Crone; Dana Boatman; Nitish V Thakor; Piotr J Franaszczuk

doi:10.1109/TBME.2003.819852

Human ECoG analysis during speech perception using matching pursuit: a comparison between stochastic and dyadic dictionaries

IEEE Trans Biomed Eng. 2003 Dec;50(12):1371-3. doi: 10.1109/TBME.2003.819852.

Authors

Supratim Ray¹, Christophe C Jouny, Nathan E Crone, Dana Boatman, Nitish V Thakor, Piotr J Franaszczuk

Affiliation

¹ Biomedical Engineering, Johns Hopkins University, 3400 N. Charles Street, 338 Krieger Hall, Room 253, Baltimore, MD 21218, USA. sray@bme.jhu.edu

PMID: 14656066
DOI: 10.1109/TBME.2003.819852

Abstract

We use the matching pursuit (MP) algorithm to detect induced gamma activity in human EEG during speech perception. We show that the MP algorithm is particularly useful for detecting small power changes at high gamma frequencies (> 70 Hz). We also compare the performance of the MP using a stochastic versus a dyadic dictionary and show that despite the frequency bias the time-frequency power plot (averaged over 100 trials) generated by the dyadic MP is almost identical (> 98.5%) to the one generated by the stochastic MP. However, the dyadic MP is computationally much faster than the stochastic MP.

Publication types

Comparative Study
Evaluation Study
Research Support, U.S. Gov't, P.H.S.
Validation Study

MeSH terms

Algorithms*
Auditory Cortex / physiology*
Electroencephalography / methods*
Evoked Potentials, Auditory / physiology*
Humans
Signal Processing, Computer-Assisted*
Speech Perception / physiology*

Abstract

Publication types

MeSH terms

Grants and funding