A review of issues related to data acquisition and analysis in EEG/MEG studies
A Puce, MS Hämäläinen - Brain sciences, 2017 - mdpi.com
Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive
electrophysiological methods, which record electric potentials and magnetic fields due to …
electrophysiological methods, which record electric potentials and magnetic fields due to …
Unsupervised feature extraction by time-contrastive learning and nonlinear ica
A Hyvarinen, H Morioka - Advances in neural information …, 2016 - proceedings.neurips.cc
Nonlinear independent component analysis (ICA) provides an appealing framework for
unsupervised feature learning, but the models proposed so far are not identifiable. Here, we …
unsupervised feature learning, but the models proposed so far are not identifiable. Here, we …
Aging of human alpha rhythm
Alpha rhythm (AR) changes are the most pronounced electroencephalogram phenomenon
in the aging brain. We analyzed them based on the inherent AR structure obtained by …
in the aging brain. We analyzed them based on the inherent AR structure obtained by …
Combination of group singular value decomposition and eLORETA identifies human EEG networks and responses to transcranial photobiomodulation
Transcranial Photobiomodulation (tPBM) has demonstrated its ability to alter
electrophysiological activity in the human brain. However, it is unclear how tPBM modulates …
electrophysiological activity in the human brain. However, it is unclear how tPBM modulates …
Automatic determination of EMG-contaminated components and validation of independent component analysis using EEG during pharmacologic paralysis
SP Fitzgibbon, D DeLosAngeles, TW Lewis… - Clinical …, 2016 - Elsevier
Objective Validate independent component analysis (ICA) for removal of EMG
contamination from EEG, and demonstrate a heuristic, based on the gradient of EEG spectra …
contamination from EEG, and demonstrate a heuristic, based on the gradient of EEG spectra …
[图书][B] Nanobrain: the making of an artificial brain from a time crystal
A Bandyopadhyay - 2020 - taylorfrancis.com
Making an artificial brain is not a part of artificial intelligence. It will be a revolutionary
journey of mankind exploring a science where one cannot write an equation, a material will …
journey of mankind exploring a science where one cannot write an equation, a material will …
Phasic modulation of human somatosensory perception by transcranially applied oscillating currents
Background Why are weak sensory stimuli sometimes perceived and other times not?
Experimental paradigms using near-threshold stimuli suggest that spontaneous brain …
Experimental paradigms using near-threshold stimuli suggest that spontaneous brain …
Spatiospectral decomposition of multi-subject EEG: evaluating blind source separation algorithms on real and realistic simulated data
Electroencephalographic (EEG) oscillations predominantly appear with periods between 1 s
(1 Hz) and 20 ms (50 Hz), and are subdivided into distinct frequency bands which appear to …
(1 Hz) and 20 ms (50 Hz), and are subdivided into distinct frequency bands which appear to …
Exploring frequency-dependent brain networks from ongoing EEG using spatial ICA during music listening
Recently, exploring brain activity based on functional networks during naturalistic stimuli
especially music and video represents an attractive challenge because of the low signal-to …
especially music and video represents an attractive challenge because of the low signal-to …
Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks
L Rutter, SR Nadar, T Holroyd, FW Carver… - Frontiers in …, 2013 - frontiersin.org
Complex networks have been observed to comprise small-world properties, believed to
represent an optimal organization of local specialization and global integration of …
represent an optimal organization of local specialization and global integration of …