Time-frequency analysis of vibrotactile driving responses by matching pursuit

A new method of time-frequency analysis, based on the Matching Pursuit (MP) algorithm, was used to extract and quantify EEG `driving' or frequency-following responses produced in human primary somatosensory cortex (SI) by 33 Hz vibrotactile stimulation of the right index fingertip in a single s...

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Bibliographic Details
Published in:Journal of neuroscience methods 1998-06, Vol.81 (1), p.121-129
Main Authors: Zygierewicz, J., Kelly, E.F., Blinowska, K.J., Durka, P.J., Folger, S.E.
Format: Article
Language:English
Subjects:
Algorithms
Analysis of Variance
Biological and medical sciences
EEG
Electroencephalography - methods
Frequency-following response
Fundamental and applied biological sciences. Psychology
General aspects. Models. Methods
Humans
Matching Pursuit
Models, Neurological
Models, Theoretical
Physical Stimulation
Sensory evoked potentials
Signal Processing, Computer-Assisted
Time Factors
Time-frequency analysis
Touch - physiology
Vertebrates: nervous system and sense organs
Vibration
Vibrotactile stimuli
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Summary:A new method of time-frequency analysis, based on the Matching Pursuit (MP) algorithm, was used to extract and quantify EEG `driving' or frequency-following responses produced in human primary somatosensory cortex (SI) by 33 Hz vibrotactile stimulation of the right index fingertip in a single subject. EEG signals were recorded from a 5×5 array of electrodes centered over the left hand area, time-locked to repeated presentations of four vibratory stimulus amplitudes. The MP algorithm was used to decompose the edited and and filtered EEG signals into waveforms selected from a large and redundant dictionary. Statistical discrimination of the vibratory stimulus amplitudes was then readily achieved in terms of trial-by-trial measures of response amplitude constructed in automated fashion from the calculated MP parameters. The results were orderly and physiologically coherent, and potentially open the way to correlation of psychophysical magnitude estimates with measures of neurophysiological response on a trial-by-trial basis. The approach developed here appears well suited to detection and characterisation of time dependent or transient target signals embedded in a noisy background.
ISSN:0165-0270
1872-678X
DOI:10.1016/S0165-0270(98)00016-8