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High-frequency Broadband Modulations of Electroencephalographic Spectra.

Onton J, Makeig S - Front Hum Neurosci (2009)

Bottom Line: High-frequency cortical potentials in electroencephalographic (EEG) scalp recordings have low amplitudes and may be confounded with scalp muscle activities.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.

View Article: PubMed Central - PubMed

Affiliation: Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA.

ABSTRACT
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 ( approximately 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.

No MeSH data available.


Value-sorted time course correlations of all within-subject IM pairs for each pair of IM clusters. Traces represent sorted correlation coefficients between time weights from pair-wise comparisons of 11 IM clusters, each point representing a within-subject correlation of two IM time courses over 14 emotion imagination periods (excepting ‘compassion,’ see main text). IM clusters affected spectral changes in Delta, low Theta1, high Theta2, below-peak Alpha1, at-peak Alpha2, above-peak Alpha3, low to high Beta1-4 bands, and Broadband high-frequency activity, respectively. See Table 1 legend for frequency-band limits. Most time course correlations were quite weak, but were typically positive between all lower-frequency IM clusters. Correlations for broadband versus broadband IM pairs (arrow) were more often positive than for any other IM cluster pairs. Correlations of broadband IM time courses with lower-frequency IMs (ellipse) tended to be negatively correlated, though nearly all IM time course correlations were weak (/r/ < 0.4).
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Figure 6: Value-sorted time course correlations of all within-subject IM pairs for each pair of IM clusters. Traces represent sorted correlation coefficients between time weights from pair-wise comparisons of 11 IM clusters, each point representing a within-subject correlation of two IM time courses over 14 emotion imagination periods (excepting ‘compassion,’ see main text). IM clusters affected spectral changes in Delta, low Theta1, high Theta2, below-peak Alpha1, at-peak Alpha2, above-peak Alpha3, low to high Beta1-4 bands, and Broadband high-frequency activity, respectively. See Table 1 legend for frequency-band limits. Most time course correlations were quite weak, but were typically positive between all lower-frequency IM clusters. Correlations for broadband versus broadband IM pairs (arrow) were more often positive than for any other IM cluster pairs. Correlations of broadband IM time courses with lower-frequency IMs (ellipse) tended to be negatively correlated, though nearly all IM time course correlations were weak (/r/ < 0.4).

Mentions: Since the independence maximized by the IMs in our analysis was between their frequency templates, not their time-window weights, the IM time courses were free to be correlated with one another in nearly any manner (though separate IMs could not be perfectly correlated or anti-correlated). Therefore, we computed within-subject temporal correlations between IM weights assigned to 11 brain IM clusters. Table 1 gives the within- and between-cluster correlation means and half inter-quartile ranges. In general, the number of significant correlations in any IM cluster pairing was low, where significance limits were determined by performing correlations using IM time course weights from different rather than the same subjects (p < 0.01). On average, 20% ± 13% (mean ± SD) of IM pair correlations within any cluster pair were significant by this measure. The time courses of broadband IMs were relatively more positively correlated with those of other broadband IMs (r = 0.15 ± 0.17, mean ± half inter-quartile range) than were the time courses of lower-frequency IMs with each other (p < 0.0001 by t-test). Also, the time courses of broadband IMs were weakly negatively correlated with those of lower-frequency IMs (r = −0.09 ± 0.07, p < 0.0001 by t-test; Figure 6).


High-frequency Broadband Modulations of Electroencephalographic Spectra.

Onton J, Makeig S - Front Hum Neurosci (2009)

Value-sorted time course correlations of all within-subject IM pairs for each pair of IM clusters. Traces represent sorted correlation coefficients between time weights from pair-wise comparisons of 11 IM clusters, each point representing a within-subject correlation of two IM time courses over 14 emotion imagination periods (excepting ‘compassion,’ see main text). IM clusters affected spectral changes in Delta, low Theta1, high Theta2, below-peak Alpha1, at-peak Alpha2, above-peak Alpha3, low to high Beta1-4 bands, and Broadband high-frequency activity, respectively. See Table 1 legend for frequency-band limits. Most time course correlations were quite weak, but were typically positive between all lower-frequency IM clusters. Correlations for broadband versus broadband IM pairs (arrow) were more often positive than for any other IM cluster pairs. Correlations of broadband IM time courses with lower-frequency IMs (ellipse) tended to be negatively correlated, though nearly all IM time course correlations were weak (/r/ < 0.4).
© Copyright Policy - open-access
Related In: Results  -  Collection

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Show All Figures
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Figure 6: Value-sorted time course correlations of all within-subject IM pairs for each pair of IM clusters. Traces represent sorted correlation coefficients between time weights from pair-wise comparisons of 11 IM clusters, each point representing a within-subject correlation of two IM time courses over 14 emotion imagination periods (excepting ‘compassion,’ see main text). IM clusters affected spectral changes in Delta, low Theta1, high Theta2, below-peak Alpha1, at-peak Alpha2, above-peak Alpha3, low to high Beta1-4 bands, and Broadband high-frequency activity, respectively. See Table 1 legend for frequency-band limits. Most time course correlations were quite weak, but were typically positive between all lower-frequency IM clusters. Correlations for broadband versus broadband IM pairs (arrow) were more often positive than for any other IM cluster pairs. Correlations of broadband IM time courses with lower-frequency IMs (ellipse) tended to be negatively correlated, though nearly all IM time course correlations were weak (/r/ < 0.4).
Mentions: Since the independence maximized by the IMs in our analysis was between their frequency templates, not their time-window weights, the IM time courses were free to be correlated with one another in nearly any manner (though separate IMs could not be perfectly correlated or anti-correlated). Therefore, we computed within-subject temporal correlations between IM weights assigned to 11 brain IM clusters. Table 1 gives the within- and between-cluster correlation means and half inter-quartile ranges. In general, the number of significant correlations in any IM cluster pairing was low, where significance limits were determined by performing correlations using IM time course weights from different rather than the same subjects (p < 0.01). On average, 20% ± 13% (mean ± SD) of IM pair correlations within any cluster pair were significant by this measure. The time courses of broadband IMs were relatively more positively correlated with those of other broadband IMs (r = 0.15 ± 0.17, mean ± half inter-quartile range) than were the time courses of lower-frequency IMs with each other (p < 0.0001 by t-test). Also, the time courses of broadband IMs were weakly negatively correlated with those of lower-frequency IMs (r = −0.09 ± 0.07, p < 0.0001 by t-test; Figure 6).

Bottom Line: High-frequency cortical potentials in electroencephalographic (EEG) scalp recordings have low amplitudes and may be confounded with scalp muscle activities.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.

View Article: PubMed Central - PubMed

Affiliation: Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA.

ABSTRACT
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 ( approximately 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.

No MeSH data available.