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Millipore alpha band power estimates
Alpha Band Power Estimates, supplied by Millipore, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Grand average whole brain resting-state connectivity as a function of frequency (shown in Hz). Three different debiased coupling measures are shown: MIC (maximized imaginary coherence; ), displayed in magenta, Univar, a measure that fixes source orientations such that power is maximized (see main text for details) plotted in green, and our new <t>measure</t> <t>SoSeC</t> (source-to-sensor-coupling) in blue. All connectivity estimates are shown in z values (imaginary coherence (ImCoh) values divided by their standard deviations). In A, values calculated using eLORETA filters are shown, in B beamformer filters are used. Shaded areas denote standard errors of the mean (SEM), darker shadows correspond to data from patients, lighter shadows to data from healthy control participants. Data shown are averaged across 22 patient datasets and 24 control participant datasets, respectively, as well as across 624 voxels. Resting-state connectivity peaks in the <t>alpha</t> frequency range (8-12 Hz).
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Grand average whole brain resting-state connectivity as a function of frequency (shown in Hz). Three different debiased coupling measures are shown: MIC (maximized imaginary coherence; ), displayed in magenta, Univar, a measure that fixes source orientations such that power is maximized (see main text for details) plotted in green, and our new <t>measure</t> <t>SoSeC</t> (source-to-sensor-coupling) in blue. All connectivity estimates are shown in z values (imaginary coherence (ImCoh) values divided by their standard deviations). In A, values calculated using eLORETA filters are shown, in B beamformer filters are used. Shaded areas denote standard errors of the mean (SEM), darker shadows correspond to data from patients, lighter shadows to data from healthy control participants. Data shown are averaged across 22 patient datasets and 24 control participant datasets, respectively, as well as across 624 voxels. Resting-state connectivity peaks in the <t>alpha</t> frequency range (8-12 Hz).
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Grand average whole brain resting-state connectivity as a function of frequency (shown in Hz). Three different debiased coupling measures are shown: MIC (maximized imaginary coherence; ), displayed in magenta, Univar, a measure that fixes source orientations such that power is maximized (see main text for details) plotted in green, and our new <t>measure</t> <t>SoSeC</t> (source-to-sensor-coupling) in blue. All connectivity estimates are shown in z values (imaginary coherence (ImCoh) values divided by their standard deviations). In A, values calculated using eLORETA filters are shown, in B beamformer filters are used. Shaded areas denote standard errors of the mean (SEM), darker shadows correspond to data from patients, lighter shadows to data from healthy control participants. Data shown are averaged across 22 patient datasets and 24 control participant datasets, respectively, as well as across 624 voxels. Resting-state connectivity peaks in the <t>alpha</t> frequency range (8-12 Hz).
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Grand average whole brain resting-state connectivity as a function of frequency (shown in Hz). Three different debiased coupling measures are shown: MIC (maximized imaginary coherence; ), displayed in magenta, Univar, a measure that fixes source orientations such that power is maximized (see main text for details) plotted in green, and our new <t>measure</t> <t>SoSeC</t> (source-to-sensor-coupling) in blue. All connectivity estimates are shown in z values (imaginary coherence (ImCoh) values divided by their standard deviations). In A, values calculated using eLORETA filters are shown, in B beamformer filters are used. Shaded areas denote standard errors of the mean (SEM), darker shadows correspond to data from patients, lighter shadows to data from healthy control participants. Data shown are averaged across 22 patient datasets and 24 control participant datasets, respectively, as well as across 624 voxels. Resting-state connectivity peaks in the <t>alpha</t> frequency range (8-12 Hz).
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Grand average whole brain resting-state connectivity as a function of frequency (shown in Hz). Three different debiased coupling measures are shown: MIC (maximized imaginary coherence; ), displayed in magenta, Univar, a measure that fixes source orientations such that power is maximized (see main text for details) plotted in green, and our new measure SoSeC (source-to-sensor-coupling) in blue. All connectivity estimates are shown in z values (imaginary coherence (ImCoh) values divided by their standard deviations). In A, values calculated using eLORETA filters are shown, in B beamformer filters are used. Shaded areas denote standard errors of the mean (SEM), darker shadows correspond to data from patients, lighter shadows to data from healthy control participants. Data shown are averaged across 22 patient datasets and 24 control participant datasets, respectively, as well as across 624 voxels. Resting-state connectivity peaks in the alpha frequency range (8-12 Hz).

Journal: bioRxiv

Article Title: Source to sensor coupling (SoSeC) as an effective tool to localize interacting sources from EEG and MEG data

doi: 10.1101/2024.12.18.629132

Figure Lengend Snippet: Grand average whole brain resting-state connectivity as a function of frequency (shown in Hz). Three different debiased coupling measures are shown: MIC (maximized imaginary coherence; ), displayed in magenta, Univar, a measure that fixes source orientations such that power is maximized (see main text for details) plotted in green, and our new measure SoSeC (source-to-sensor-coupling) in blue. All connectivity estimates are shown in z values (imaginary coherence (ImCoh) values divided by their standard deviations). In A, values calculated using eLORETA filters are shown, in B beamformer filters are used. Shaded areas denote standard errors of the mean (SEM), darker shadows correspond to data from patients, lighter shadows to data from healthy control participants. Data shown are averaged across 22 patient datasets and 24 control participant datasets, respectively, as well as across 624 voxels. Resting-state connectivity peaks in the alpha frequency range (8-12 Hz).

Article Snippet: To characterize the spatial distribution of the connectivity results, we exemplarily show restingstate coupling in the alpha band (8-12 Hz) for SoSeC, Univar, and MIC separately ( ).

Techniques: Control

Source connectivity in the alpha frequency range (8-12 Hz). Three different debiased coupling measures are shown: MIC (maximized imaginary coherence; ), displayed in A, Univar, a measure that fixes source orientations such that power is maximized (see main text for details) plotted in B, and our new measure SoSeC (source-to-sensor-coupling) in C. All connectivity estimates are shown in z values (imaginary coherence (ImCoh) values divided by their standard deviations). Only patient data are shown (average across 22 datasets), projected to the cortical surface. Warmer (yellow) colors indicate higher values. In D and E, repeated-measures correlations of different source connectivity estimates in the alpha frequency range (8-12 Hz) are presented. In D, the relation of SoSeC and MIC values (maximized imaginary coherence; ; y-axis) is plotted. In E, data for SoSeC (x-axis) and Univar (y-axis) estimates are displayed. For both plots, z values are shown. Dot clouds of different colors show data of single patient datasets (n=22) for 624 voxels, complemented by their regression lines. The dashed line illustrates the correlation at the group level. Both correlations are statistically significant ( p < 0.001), indicating similar spatial distributions for the different connectivity measures investigated.

Journal: bioRxiv

Article Title: Source to sensor coupling (SoSeC) as an effective tool to localize interacting sources from EEG and MEG data

doi: 10.1101/2024.12.18.629132

Figure Lengend Snippet: Source connectivity in the alpha frequency range (8-12 Hz). Three different debiased coupling measures are shown: MIC (maximized imaginary coherence; ), displayed in A, Univar, a measure that fixes source orientations such that power is maximized (see main text for details) plotted in B, and our new measure SoSeC (source-to-sensor-coupling) in C. All connectivity estimates are shown in z values (imaginary coherence (ImCoh) values divided by their standard deviations). Only patient data are shown (average across 22 datasets), projected to the cortical surface. Warmer (yellow) colors indicate higher values. In D and E, repeated-measures correlations of different source connectivity estimates in the alpha frequency range (8-12 Hz) are presented. In D, the relation of SoSeC and MIC values (maximized imaginary coherence; ; y-axis) is plotted. In E, data for SoSeC (x-axis) and Univar (y-axis) estimates are displayed. For both plots, z values are shown. Dot clouds of different colors show data of single patient datasets (n=22) for 624 voxels, complemented by their regression lines. The dashed line illustrates the correlation at the group level. Both correlations are statistically significant ( p < 0.001), indicating similar spatial distributions for the different connectivity measures investigated.

Article Snippet: To characterize the spatial distribution of the connectivity results, we exemplarily show restingstate coupling in the alpha band (8-12 Hz) for SoSeC, Univar, and MIC separately ( ).

Techniques: