Increased local and decreased remote functional connectivity at EEG alpha and beta frequency bands in opioid-dependent patients

AbstractRecent studies have shown how MEG can reveal spatial patterns of functional connectivity using frequency-specific oscillatory coupling measures and that these may be modified in disease. However, there is a need to understand both how repeatable these patterns are across participants and how these measures relate to the moment-to-moment variability (or ‘irregularity’) of neural activity seen in healthy brain function. In this study, we used Multi-scale Rank-Vector Entropy (MRVE) to calculate the dynamic timecourses of signal variability over a range of temporal scales. The correlation of MRVE timecourses was then used to detect functional connections in resting state MEG recordings that were robust over 183 participants and varied with temporal scale. We then compared these MRVE connectivity patterns to those derived using more standard amplitude-amplitude coupling measures, using methods designed to quantify the consistency of these patterns across participants.Using oscillatory amplitude envelope correlation (AEC), the most consistent connectivity patterns, across the cohort, were seen in the alpha and beta frequency bands. At fine temporal scales (corresponding to ‘scale frequencies’, fS = 30-150Hz), MRVE correlation detected mostly occipital and parietal connections and these showed high similarity with the networks identified by AEC in the alpha and beta frequency bands. The most consistent connectivity profiles between participants were given by MRVE correlation at fS = 75Hz and AEC in the beta band.It was also found that average mid-to fine scale variability within each region (fS ∼ 10-150Hz) negatively correlated with the region’s overall connectivity strength with other brain areas, as measured by fine scale MRVE correlation (fS ∼ 30-150Hz) and by alpha and beta band AEC. These findings suggest that local activity at frequencies fS ≳ 10Hz becomes more regular when a region exhibits high levels of resting state connectivity.

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Hypnotic induction is followed by state-like changes in the organization of EEG functional connectivity in the theta and beta frequency bands in high-hypnotically susceptible individuals

Frontiers in Human Neuroscience ◽

10.3389/fnhum.2014.00528 ◽

2014 ◽

Vol 8 ◽

Cited By ~ 26

Author(s):

Graham A. Jamieson ◽

Adrian P. Burgess

Keyword(s):

Functional Connectivity ◽

Frequency Bands ◽

Hypnotic Induction ◽

Eeg Functional Connectivity ◽

Beta Frequency

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Reduced Brain Electric Activity and Functional Connectivity in Bipolar Euthymia: An sLORETA Source Localization Study

Clinical EEG and Neuroscience ◽

10.1177/1550059419893472 ◽

2019 ◽

Vol 51 (3) ◽

pp. 155-166

Author(s):

Annamaria Painold ◽

Pascal L. Faber ◽

Eva Z. Reininghaus ◽

Sabrina Mörkl ◽

Anna K. Holl ◽

...

Keyword(s):

Functional Connectivity ◽

Large Scale ◽

Time Course ◽

Temporal Cortex ◽

Electric Activity ◽

Brain Regions ◽

Frequency Bands ◽

Head Surface ◽

Density Values ◽

Surface Eeg

Bipolar disorder (BD) is a chronic illness with a relapsing and remitting time course. Relapses are manic or depressive in nature and intermitted by euthymic states. During euthymic states, patients lack the criteria for a manic or depressive diagnosis, but still suffer from impaired cognitive functioning as indicated by difficulties in executive and language-related processing. The present study investigated whether these deficits are reflected by altered intracortical activity in or functional connectivity between brain regions involved in these processes such as the prefrontal and the temporal cortices. Vigilance-controlled resting state EEG of 13 euthymic BD patients and 13 healthy age- and sex-matched controls was analyzed. Head-surface EEG was recomputed into intracortical current density values in 8 frequency bands using standardized low-resolution electromagnetic tomography. Intracortical current densities were averaged in 19 evenly distributed regions of interest (ROIs). Lagged coherences were computed between each pair of ROIs. Source activity and coherence measures between patients and controls were compared (paired t tests). Reductions in temporal cortex activity and in large-scale functional connectivity in patients compared to controls were observed. Activity reductions affected all 8 EEG frequency bands. Functional connectivity reductions affected the delta, theta, alpha-2, beta-2, and gamma band and involved but were not limited to prefrontal and temporal ROIs. The findings show reduced activation of the temporal cortex and reduced coordination between many brain regions in BD euthymia. These activation and connectivity changes may disturb the continuous frontotemporal information flow required for executive and language-related processing, which is impaired in euthymic BD patients.

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Connectivity of EEG synchronization networks increases for Parkinson’s disease patients with freezing of gait

Communications Biology ◽

10.1038/s42003-021-02544-w ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Eitan E. Asher ◽

Meir Plotnik ◽

Moritz Günther ◽

Shay Moshel ◽

Orr Levy ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Freezing Of Gait ◽

Motor Task ◽

Frequency Bands ◽

Hand Tapping ◽

Patient Groups ◽

Beta Frequency ◽

Relationship Of ◽

Insight Into

AbstractFreezing of gait (FoG), a paroxysmal gait disturbance commonly experienced by patients with Parkinson’s disease (PD), is characterized by sudden episodes of inability to generate effective forward stepping. Recent studies have shown an increase in beta frequency of local-field potentials in the basal-ganglia during FoG, however, comprehensive research on the synchronization between different brain locations and frequency bands in PD patients is scarce. Here, by developing tools based on network science and non-linear dynamics, we analyze synchronization networks of electroencephalography (EEG) brain waves of three PD patient groups with different FoG severity. We find higher EEG amplitude synchronization (stronger network links) between different brain locations as PD and FoG severity increase. These results are consistent across frequency bands (theta, alpha, beta, gamma) and independent of the specific motor task (walking, still standing, hand tapping) suggesting that an increase in severity of PD and FoG is associated with stronger EEG networks over a broad range of brain frequencies. This observation of a direct relationship of PD/FoG severity with overall EEG synchronization together with our proposed EEG synchronization network approach may be used for evaluating FoG propensity and help to gain further insight into PD and the pathophysiology leading to FoG.

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Characterizing Thalamocortical Disturbances in Cervical Spondylotic Myelopathy: Revealed by Functional Connectivity under Two Slow Frequency Bands

PLoS ONE ◽

10.1371/journal.pone.0125913 ◽

2015 ◽

Vol 10 (6) ◽

pp. e0125913 ◽

Cited By ~ 5

Author(s):

Fuqing Zhou ◽

Lin Wu ◽

Xiaojia Liu ◽

Honghan Gong ◽

Keith Dip-Kei Luk ◽

...

Keyword(s):

Functional Connectivity ◽

Cervical Spondylotic Myelopathy ◽

Frequency Bands ◽

Slow Frequency

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Heritability of Magnetoencephalography Phenotypes Among Patients With Genetic Generalized Epilepsy and Their Siblings

Neurology ◽

10.1212/wnl.0000000000012144 ◽

2021 ◽

pp. 10.1212/WNL.0000000000012144

Author(s):

Christina Stier ◽

Adham Elshahabi ◽

Yiwen Li Hegner ◽

Raviteja Kotikalapudi ◽

Justus Marquetand ◽

...

Keyword(s):

Functional Connectivity ◽

Age Of Onset ◽

Subcortical Structures ◽

Beta Band ◽

Cross Sectional ◽

Frequency Bands ◽

Gamma Frequency ◽

Epileptiform Discharges ◽

Healthy Siblings ◽

Generalized Epilepsy

ObjectiveTo assess whether neuronal signals in patients with genetic generalized epilepsy (GGE) are heritable, we examined magnetoencephalography (MEG) resting-state recordings in patients and their healthy siblings.MethodsIn a prospective, cross-sectional design, we investigated source-reconstructed power and functional connectivity in patients, siblings and controls. We analyzed 5 minutes of cleaned and awake data without epileptiform discharges in six frequency bands (1-40 Hz). We further calculated intraclass correlations (ICC) to estimate heritability for the imaging patterns within families.ResultsCompared with controls (n = 45), patients with GGE (n = 25) showed widespread increased functional connectivity (theta to gamma frequency bands) and power (delta to gamma frequency bands) across the spectrum. Siblings (n = 18) fell between the levels of patients and controls. Heritability of the imaging metrics was observed in regions, where patients strongly differed from controls, mainly in beta frequencies, but also for delta and theta power. Network connectivity in GGE was heritable in frontal, central and inferior parietal brain areas and power in central, temporo-parietal, and subcortical structures. Presence of generalized spike-wave activity during recordings and medication were associated with the network patterns, whereas other clinical factors such as age of onset, disease duration or seizure control were not.ConclusionMetrics of brain oscillations are well suited to characterize GGE and likely relate to genetic factors rather than the active disease or treatment. High power and connectivity levels co-segregated in patients with GGE and healthy siblings, predominantly in the beta band, representing an endophenotype of GGE.

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Spectral graph theory of brain oscillations -- revisited and improved

10.1101/2021.09.28.462078 ◽

2021 ◽

Author(s):

Parul Verma ◽

Srikantan Nagarajan ◽

Ashish Raj

Keyword(s):

Graph Theory ◽

Spatial Patterns ◽

Spectral Graph Theory ◽

Frequency Spectra ◽

Varying Parameters ◽

Frequency Bands ◽

Spectral Graph ◽

Macro Scale ◽

Beta Frequency ◽

The Brain

Mathematical modeling of the relationship between the functional activity and the structural wiring of the brain has largely been undertaken using non-linear and biophysically detailed mathematical models with regionally varying parameters. While this approach provides us a rich repertoire of multistable dynamics that can be displayed by the brain, it is computationally demanding. Moreover, although neuronal dynamics at the microscopic level are nonlinear and chaotic, it is unclear if such detailed nonlinear models are required to capture the emergent meso- (regional population ensemble) and macro-scale (whole brain) behavior, which is largely deterministic and reproducible across individuals. Indeed, recent modeling effort based on spectral graph theory has shown that an analytical model without regionally varying parameters can capture the empirical magnetoencephalography frequency spectra and the spatial patterns of the alpha and beta frequency bands accurately. In this work, we demonstrate an improved hierarchical, linearized, and analytic spectral graph theory-based model that can capture the frequency spectra obtained from magnetoencephalography recordings of resting healthy subjects. We reformulated the spectral graph theory model in line with classical neural mass models, therefore providing more biologically interpretable parameters, especially at the local scale. We demonstrated that this model performs better than the original model when comparing the spectral correlation of modeled frequency spectra and that obtained from the magnetoencephalography recordings. This model also performs equally well in predicting the spatial patterns of the empirical alpha and beta frequency bands.

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Aberrant striatal oscillations after dopamine loss in parkinsonian non-human primates

10.1101/650770 ◽

2019 ◽

Cited By ~ 1

Author(s):

Arun Singh ◽

Stella M. Papa

Keyword(s):

Basal Ganglia ◽

Oscillatory Activity ◽

Field Potentials ◽

Striatal Neurons ◽

Dopamine Depletion ◽

Frequency Bands ◽

Oscillatory Pattern ◽

Motor Abnormalities ◽

Beta Frequency

AbstractDopamine depletion in Parkinson’s disease (PD) is associated with abnormal oscillatory activity in the cortico-basal ganglia network. However, the oscillatory pattern of striatal neurons in PD remains poorly defined. Here, we analyzed the local field potentials in one untreated and five MPTP-treated non-human primates (NHP) to model advanced PD. Augmented oscillatory activity in the alpha (8-13 Hz) and low-beta (13-20 Hz) frequency bands was found in the striatum in parallel to the motor cortex and globus pallidus of the NHP-PD model. The coherence analysis showed increased connectivity in the cortico-striatal and striato-pallidal pathways at alpha and low-beta frequency bands, confirming the presence of abnormal 8-20 Hz activity in the cortico-basal ganglia network. The acute L-Dopa injection that induced a clear motor response normalized the amplified 8-20 Hz oscillations. These findings indicate that pathological striatal oscillations at alpha and low-beta bands are concordant with the basal ganglia network changes after dopamine depletion, and thereby support a key role of the striatum in the generation of parkinsonian motor abnormalities.

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