Impact Factor

Original Research ARTICLE

Front. Hum. Neurosci., 23 December 2009 | http://dx.doi.org/10.3389/neuro.09.061.2009

High-frequency broadband modulations of electroencephalographic spectra

Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA
High-frequency cortical potentials in electroencephalographic (EEG) scalp recordings have low amplitudes and may be confounded with scalp muscle activities. EEG data from an eyes-closed emotion imagination task were linearly decomposed using independent component analysis (ICA) into maximally independent component (IC) processes. Joint decomposition of IC log spectrograms into source- and frequency-independent modulator (IM) processes revealed three distinct classes of IMs that separately modulated broadband high-frequency (∼15–200 Hz) power of brain, scalp muscle, and likely ocular motor IC processes. Multi-dimensional scaling revealed significant but spatially complex relationships between mean broadband brain IM effects and the valence of the imagined emotions. Thus, contrary to prevalent assumption, unitary modes of spectral modulation of frequencies encompassing the beta, gamma, and high gamma frequency ranges can be isolated from scalp-recorded EEG data and may be differentially associated with brain sources and cognitive activities.
EEG, ICA, gamma, neuromodulator, emotion, ECoG, ocular motor tremor, EMG
Onton J and Makeig S (2009). High-frequency broadband modulations of electroencephalographic spectra. Front. Hum. Neurosci. 3,:61. doi: 10.3389/neuro.09.061.2009
16 March 2009;
 Paper pending published:
18 June 2009;
18 November 2009;
 Published online:
23 December 2009.

Edited by:

Srikantan S. Nagarajan, University of California, USA

Reviewed by:

Johanna Zumer, University of Nottingham, UK
Srikantan S. Nagarajan, University of California, USA
© 2009 Onton and Makeig. This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.
Julie Onton, Swartz Center for Computational Neuroscience, Institute for Neural Computation # 0961, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0961, USA. e-mail: julie@sccn.ucsd.edu