Statistical modeling and analysis of laser-evoked potentials of electrocorticogram recordings from awake humans.
This article is devoted to statistical modeling and analysis of electrocorticogram (ECoG) signals induced by painful cutaneous laser stimuli, which were recorded from implanted electrodes in awake humans. Specifically, with statistical tools of factor analysis and independent component analysis, the pain-induced laser-evoked potentials (LEPs) were extracted and investigated under different controlled conditions. With the help of wavelet analysis, quantitative and qualitative analyses were conducted regarding the LEPs' attributes of power, amplitude, and latency, in both averaging and single-trial experiments. Statistical hypothesis tests were also applied in various experimental setups. Experimental results reported herein also confirm previous findings in the neurophysiology literature. In addition, single-trial analysis has also revealed many new observations that might be interesting to the neuroscientists or clinical neurophysiologists. These promising results show convincing validation that advanced signal processing and statistical analysis may open new avenues for future studies of such ECoG or other relevant biomedical recordings.
Chen
Zhe
Z
Laboratory for Advanced Brain Signal Processing, RIKEN Brain Science Institute, Wako-shi 351-0198, Saitama, Japan. zhechen@neurostat.mgh.harvard.edu
Ohara
Shinji
S
Cao
Jianting
J
Vialatte
François
F
Lenz
Fred A
FA
Cichocki
Andrzej
A