Engineering Commons^™

Cortical Statistical Correlation Tomography Of Eeg Resting State Networks, Chuang Li, Han Yuan, Guofa Shou, Yoon-Hee Cha, Sridhar Sunderam, Walter Besio, Lei Ding

Biomedical Engineering Faculty Publications

Resting state networks (RSNs) have been found in human brains during awake resting states. RSNs are composed of spatially distributed regions in which spontaneous activity fluctuations are temporally and dynamically correlated. A new computational framework for reconstructing RSNs with human EEG data has been developed in the present study. The proposed framework utilizes independent component analysis (ICA) on short-time Fourier transformed inverse source maps imaged from EEG data and statistical correlation analysis to generate cortical tomography of electrophysiological RSNs. The proposed framework was evaluated on three sets of resting-state EEG data obtained in the comparison of two conditions: (1) healthy …

Segway: A Simple Framework For Unsupervised Sleep Segmentation In Experimental Eeg Recordings, Farid Yaghouby, Sridhar Sunderam

Biomedical Engineering Faculty Publications

Sleep analysis in animal models typically involves recording an electroencephalogram (EEG) and electromyogram (EMG) and scoring vigilance state in brief epochs of data as Wake, REM (rapid eye movement sleep) or NREM (non-REM) either manually or using a computer algorithm. Computerized methods usually estimate features from each epoch like the spectral power associated with distinctive cortical rhythms and dissect the feature space into regions associated with different states by applying thresholds, or by using supervised/unsupervised statistical classifiers; but there are some factors to consider when using them:

• Most classifiers require scored sample data, elaborate heuristics or computational steps not easily …