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Attention is hypothesized to increase the brain's functional connectivity measured as EEG coherence between brain areas. Is this true for different types of attention compared to no-task resting?
In 25 healthy, meditation-naïve, right-handed, male students 58-channel EEG was recorded during three conditions of 5 minutes each with closed eyes in randomized order: (1) resting [3 runs], (2) mental arithmetic [2 runs], and (3) breath counting, a meditation initiation technique [2 runs]. For the 8 EEG frequency bands, the artifacted EEG was recomputed into sLORETA intracerebral current densities. To avoid localization ambiguities, we computed EEG coherence between sLORETA areas. To avoid effects of volume conduction, we computed intracerebral `lagged coherence' connectivity between sLORETA current densities in 19 areas. Averaged resting runs were compared to those breath counting and arithmetic runs of which participants post-hoc reported that their concentration was best.
Paired t-tests between conditions yielded differences of coherence at p< 0.1 (corrected for multiple testing) for 5 EEG frequency bands (delta, theta, alpha1, alpha2, beta3) [number of connections in brackets]: coherence was lower in breath counting than arithmetic (delta, beta3 [1,1]). Coherence was lower in resting than arithmetic (alpha2 ), but higher in resting than breath counting (theta, alpha1, alpha2, beta3 [2,1,1,1]).
Attention to breath counting showed lowest, to arithmetic highest demands on intracerebral functional connectivity. Breath counting and mental arithmetic induce mental states whose inter-area connectivity differs in opposite directions from resting. The results do not support a global hypothesis of increased coherence during attention.
The measure of complex dimensionality assesses the number of independent processes that generate an observed time series.
To investigate whether meditation exercises are associated with fewer or more independently active brain processes, and whether different meditation traditions show different results.
Does brain electric complex dimensionality differ between the state of meditation and of task free resting in different meditation traditions?
Multichannel EEG recordings (19 to 25 channels) from experienced meditators of five meditation traditions (13 Tibetan Buddhists, 15 Qigong, 14 Shaja Yoga, 14 Ananda Marga Yoga, and 15 Zen) were analyzed (bandpass 1.5–30 Hz) using ‘Omega Complexity’ that obtains a single value for a set of simultaneously recorded EEG time series from a given person (J. Wackermann, Acta Neurobiol Exp (Wars) 1996;56:197–208). Omega Complexity during meditation was compared to the mean of Omega Complexity during pre- and post-meditation resting.
During meditation relative to resting (paired t tests), Omega Complexity was higher in all five traditions, significant for Tibetan Buddhists (p = 0.01), Ananda Marga Yoga (p = 0.007) and Zen (p = 0.0003).
The subjectively experienced agreeable feelings during meditation apparently occur, across meditation traditions, during a brain functional state that is characterized by an increase of independent brain processes compared to task free resting.
Different meditation practices reportedly affect brain electric activity.
To assess common characteristics in brain electric activity during the state of meditation across different meditation traditions.
Do meditation traditions share commonalities in EEG spectral power changes from task-free resting to meditation?
Data from 71 experienced meditators of five meditation traditions were analyzed (13 Tibetan Buddhists, 15 Qigong, 14 Shaja Yoga, 14 Ananda Marga Yoga, and 15 Zen). Power spectral results of multichannel EEG recordings (average reference) during meditation were compared with those during pre- and post-meditation task-free resting. Spectra were averaged across channels (19–58), and subject-wise normalized. Integrated power was computed for the eight independent frequency bands (delta through gamma).
During meditation compared to the average of pre- and post-meditation resting, across the five traditions, there was a significant decrease of power in the alpha-2 band (10.5–12 Hz), and significant increases of power in the beta-3 (21.5–30 Hz) and gamma (35–44 Hz) bands; theta (6.5–8 Hz) band power showed an increase at p = 0.14.
The results indicate that EEG spectral power differences between task-free resting state EEG versus meditation state EEG show communalities that are shared by all five meditation traditions in spite of important differences in meditation techniques.
Arithmetic reportedly involves left parietal areas.
To test this in independent groups of healthy persons.
Which brain regions are activated / inhibited during mental arithmetic compared to task-free resting?
We examined four independent groups of healthy adults (N = 15, 14, 14, 23, respectively) during simple arithmetic (continuous subtraction of 7) and task-free resting before and after arithmetic, all with closed eyes. Multichannel head surface EEG (19–58 channels) was continually recorded, then recomputed (using sLORETA functional tomography) into current density for 6239 cortical voxels, for each of the eight EEG frequency bands (delta through gamma, 1.5–44 Hz). Pre- and post-arithmetic resting was averaged. Using paired t-tests, frequency band-wise normalized and log-transformed current density was compared between arithmetic and resting for each group. The resulting p-values were combined across groups using Fisher’s combination procedure. For each frequency band, sLORETA voxels differing between conditions at Fisher’s (across groups) p < 0.05 were computed into centers of gravity separately for increased and decreased activation.
Activity that was stronger during arithmetic compared to resting had gravity centers in midline anterior regions for slow frequency bands (delta, theta, alpha-1) and in right posterior regions for fast frequency bands (alpha-2 through gamma). Activity that was weaker during arithmetic compared to resting was centered around left parietal areas for all eight frequency bands.
The results suggest that arithmetic compared to resting involves frontal inhibition coupled with increased right parietal activation, and left parietal reduced facilitatory and reduced inhibitory activity.
Functional network disruption in degenerative dementia has been reported. EEG coherence is used to assess functional connectivity between brain areas. Previous studies of Huntington's disease (HD) reported about electroencephalography (EEG) spectral power and source location, but coherence has not yet been examined.
Objectives and Aims
To examine EEG intracortical functional connectivity in HD using low-resolution brain electromagnetic tomography (LORETA).
In 55 HD patients and 55 controls, 3-minute 19-channel vigilance-controlled EEG was recorded, and recomputed to current densities of 6239 cortical sLORETA voxels. These were recomputed into source model time series for 19 regions of interest (ROIs). Coherence overestimation due to volume conduction was avoided by computing functional connectivity as ‘lagged’ coherence. This was done for each ROI pair (19*18/2=171) in each of 8 EEG frequency bands (delta through gamma). Statistics tested coherences (a) HD patients versus controls, and (b) HD patients in early versus late disease stages.
(a) HD patients showed only reduced connectivities compared to controls (p < 0.05 corrected for multiple comparison), involving EEG theta, alpha-1-2 and beta1-2-3 frequency bands. The largest number of reduced connectivities occurred in alpha-1 (79 cases) and beta-2 (96 cases). (b) HD stage-1 versus stage-3-4 revealed only one significant difference.
HD compared to controls showed massive reduction of functional connectivity. This occurred early and remained stable during disease progression. As in other dementing disorders, for example Alzheimer disease, the largest reduction concerned alpha and beta EEG frequencies. The results suggest a neocortical disconnection syndrome of a primarily subcortical disease.
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