Alpha Band Resting-State EEG Connectivity Is Associated With Non-verbal Intelligence.
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ABSTRACT:
SUBMITTER: Zakharov I
PROVIDER: S-EPMC7010914 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The present study investigates the relationship between individual differences in verbal and non-verbal cognitive abilities and resting-state EEG network characteristics. We used a network neuroscience approach to analyze both large-scale topological characteristics of the whole brain as well as local brain network characteristics. The characteristic path length, modularity, and cluster coefficient for different EEG frequency bands (alpha, high and low; beta1 and beta2, and theta) were calculated to estimate large-scale topological integration and segregation properties of the brain networks. Betweenness centrality, nodal clustering coefficient, and local connectivity strength were calculated as local network characteristics. We showed that global network integration measures in the alpha band were positively correlated with non-verbal intelligence, especially with the more difficult part of the test (Raven's total scores and E series), and the ability to operate with verbal information (the "Conclusions" verbal subtest). At the same time, individual differences in non-verbal intelligence (Raven's total score and C series), and vocabulary subtest of the verbal intelligence tests, were negatively correlated with the network segregation measures. Our results show that resting-state EEG functional connectivity can reveal the functional architecture associated with an individual difference in cognitive performance.
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Project description:ObjectiveNeuroimaging studies in Alzheimer's disease (AD) yield conflicting results due to selective investigation. We conducted a comprehensive magnetoencephalography study of connectivity changes in AD and healthy ageing in the resting-state.MethodsWe performed a whole-brain, source-space assessment of oscillatory neural signalling in multiple frequencies comparing AD patients, elderly and young controls. We compared eyes-open and closed group oscillatory envelope activity in networks obtained through temporal independent component analysis, and calculated whole-brain node-based amplitude and phase connectivity.ResultsIn bilateral parietotemporal areas, oscillatory envelope amplitude increased with healthy ageing, whereas both local amplitude and node-to-global connectivity decreased with AD. AD-related decreases were spatially specific and restricted to the alpha and beta bands. A significant proportion of the variance in areas of peak group difference was explained by cognitive integrity, in addition to group. None of the groups differed in phase connectivity. Results were highly similar for eyes-open and closed resting-state.ConclusionsThese results support the disconnection syndrome hypothesis and suggest that AD shows distinct and unique patterns of disrupted neural functioning, rather than accelerated healthy ageing.SignificanceWhole-brain assessments show that disrupted regional oscillatory envelope amplitude and connectivity in the alpha and beta bands play a key role in AD.
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Project description:Cognitive reserve (CR) is the adaptability of cognitive processes that helps to explain differences in the susceptibility of cognitive or daily functions to resist the onslaught of brain-related injury or the normal aging process. The underlying brain mechanisms of CR studied through electroencephalogram (EEG) are scarcely reported. To our knowledge, few studies have considered a combination of exclusively dynamic proxy measures of CR. We evaluated the association of CR with cognition and resting-state EEG in older adults using three of the most frequently used dynamic proxy measures of CR: verbal intelligence, leisure activities, and physical activities. Multiple linear regression analyses with the CR proxies as independent variables and cognitive performance and the absolute power (AP) on six resting-state EEG components (beta, alpha1, alpha2, gamma, theta, and delta) as outcomes were performed. Eighty-eight healthy older adults aged 60-77 (58 female) were selected from previous study data. Verbal intelligence was a significant positive predictor of perceptual organization, working memory, processing speed, executive functions, and central delta power. Leisure activities were a significant positive predictor of posterior alpha2 power. The dynamic proxy variables of CR are differently associated with cognitive performance and resting-state EEG. Implementing leisure activities and tasks to increase vocabulary may promote better cognitive performance through compensation or neural efficiency mechanisms.
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Project description:In the past decade, the fast and transient coupling and uncoupling of functionally related brain regions into networks has received much attention in cognitive neuroscience. Empirical tools to study network coupling include functional magnetic resonance imaging (fMRI)-based functional and/or effective connectivity, and electroencephalography (EEG)/magnetoencephalography-based measures of neuronal synchronization. Here we use simultaneously recorded EEG and fMRI to assess whether fMRI-based connectivity and frequency-specific EEG power are related. Using data collected during resting state, we studied whether posterior EEG alpha power fluctuations are correlated with connectivity within the visual network and between the visual cortex and the rest of the brain. The results show that when alpha power increases, BOLD connectivity between the primary visual cortex and occipital brain regions decreases and that the negative relation of the visual cortex with the anterior/medial thalamus decreases and the ventral-medial prefrontal cortex is reduced in strength. These effects were specific for the alpha band, and not observed in other frequency bands. The decreased connectivity within the visual system may indicate an enhanced functional inhibition during a higher alpha activity. This higher inhibition level also attenuates long-range intrinsic functional antagonism between the visual cortex and the other thalamic and cortical regions. Together, these results illustrate that power fluctuations in posterior alpha oscillations result in local and long-range neural connectivity changes.
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Project description:BackgroundSchizophrenia has long been suggested to represent a disorder with prominent neural dysconnectivity. Gamma-band oscillations are highly relevant in this context, due both to their proposed involvement in neuronal synchronization and to their association with neurotransmitter systems relevant for schizophrenia. Several task-related studies have confirmed reduced power and synchronization of gamma-band oscillations in schizophrenia, but it has been suggested that these findings might not apply to the resting state. The present study aimed to investigate resting-state gamma-band connectivity in patients with schizophrenia.MethodsSixty-four channel resting-state electroencephalography (eyes closed) was recorded in 22 patients with first-episode schizophrenia and 22 healthy controls matched for age and gender. Orthogonalized power envelope correlation was used as a measure of connectivity across 80 cortical regions at 40 Hz. Mean connectivity at each region was compared across groups using the nonparametric randomization approach. Additionally, the network-based statistic was applied to identify affected networks in patients.ResultsPatients displayed increased mean functional gamma-band connectivity compared to controls in the left rolandic operculum. Network-based analyses indicated increased connectivity in patients within a strongly lateralized network consisting mainly of left inferior frontal/orbitofrontal, lateral and medial temporal, and inferior parietal areas. Within this network, gamma-band connectivity was higher in patients with low positive and disorganization symptom levels.ConclusionsThe present study provides a link between resting-state gamma-band connectivity and the core symptoms of schizophrenia. The observed findings are different than those reported by task-related studies, suggesting that resting-state studies might reveal new aspects in the pathophysiology of schizophrenia.
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Project description:Functional and effective connectivity are known to change systematically over time. These changes might be explained by several factors, including intrinsic fluctuations in activity-dependent neuronal coupling and contextual factors, like experimental condition and time. Furthermore, contextual effects may be subject-specific or conserved over subjects. To characterize fluctuations in effective connectivity, we used dynamic causal modelling (DCM) of cross spectral responses over 1- min of electroencephalogram (EEG) recordings during rest, divided into 1-sec windows. We focused on two intrinsic networks: the default mode and the saliency network. DCM was applied to estimate connectivity in each time-window for both networks. Fluctuations in DCM connectivity parameters were assessed using hierarchical parametric empirical Bayes (PEB). Within-subject, between-window effects were modelled with a second-level linear model with temporal basis functions as regressors. This procedure was conducted for every subject separately. Bayesian model reduction was then used to assess which (combination of) temporal basis functions best explain dynamic connectivity over windows. A third (between-subject) level model was used to infer which dynamic connectivity parameters are conserved over subjects. Our results indicate that connectivity fluctuations in the default mode network and to a lesser extent the saliency network comprised both subject-specific components and a common component. For both networks, connections to higher order regions appear to monotonically increase during the 1- min period. These results not only establish the predictive validity of dynamic connectivity estimates - in virtue of detecting systematic changes over subjects - they also suggest a network-specific dissociation in the relative contribution of fluctuations in connectivity that depend upon experimental context. We envisage these procedures could be useful for characterizing brain state transitions that may be explained by their cognitive or neuropathological underpinnings.
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Project description:Simultaneous resting state functional magnetic resonance imaging (rsfMRI)-resting state electroencephalography (rsEEG) studies in healthy adults showed robust positive associations of signal power in the alpha band with BOLD signal in the thalamus, and more heterogeneous associations in cortical default mode network (DMN) regions. Negative associations were found in occipital regions. In Alzheimer's disease (AD), rsfMRI studies revealed a disruption of the DMN, while rsEEG studies consistently reported a reduced power within the alpha band. The present study is the first to employ simultaneous rsfMRI-rsEEG in an AD sample, investigating the association of alpha band power and BOLD signal, compared to healthy controls (HC). We hypothesized to find reduced positive associations in DMN regions and reduced negative associations in occipital regions in the AD group. Simultaneous resting state fMRI-EEG was recorded in 14 patients with mild AD and 14 HC, matched for age and gender. Power within the EEG alpha band (8-12 Hz, 8-10 Hz, and 10-12 Hz) was computed from occipital electrodes and served as regressor in voxel-wise linear regression analyses, to assess the association with the BOLD signal. Compared to HC, the AD group showed significantly decreased positive associations between BOLD signal and occipital alpha band power in clusters in the superior, middle and inferior frontal cortex, inferior temporal lobe and thalamus (p < 0.01, uncorr., cluster size ≥ 50 voxels). This group effect was more pronounced in the upper alpha sub-band, compared to the lower alpha sub-band. Notably, we observed a high inter-individual heterogeneity. Negative associations were only reduced in the lower alpha range in the hippocampus, putamen and cerebellum. The present study gives first insights into the relationship of resting-state EEG and fMRI characteristics in an AD sample. The results suggest that positive associations between alpha band power and BOLD signal in numerous regions, including DMN regions, are diminished in AD.
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Project description:BackgroundTheoretical conceptions of autism spectrum disorder (ASD) and experimental studies of cerebral blood flow suggest abnormalities in connections among distributed neural systems in ASD.MethodsFunctional connectivity was assessed with electroencephalographic coherence between pairs of electrodes in a high-density electrode array in narrow frequency bands among 18 adults with ASD and 18 control adults in an eyes closed resting state.ResultsIn the theta (3-6 Hz) frequency range, locally elevated coherence was evident for the ASD group, especially within left hemisphere frontal and temporal regions. In the lower alpha range (8-10 Hz), globally reduced coherence was evident for the ASD group within frontal regions and between frontal and all other scalp regions. The ASD group exhibited significantly greater relative power between 3 and 6 Hz and 13-17 Hz and significantly less relative power between 9 and 10 Hz.ConclusionsRobust patterns of over- and under-connectivity are apparent at distinct spatial and temporal scales in ASD subjects in the eyes closed resting state.
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Project description:Schizophrenia (SZ) is associated with functional decoupling between cortical regions, but we do not know whether and where this occurs in low-frequency electromagnetic oscillations. The goal of this study was to use magnetoencephalography (MEG) to identify brain regions that exhibit abnormal resting-state connectivity in the alpha frequency range in patients with schizophrenia and investigate associations between functional connectivity and clinical symptoms in stable outpatient participants.Thirty patients with SZ and 15 healthy comparison participants were scanned in resting-state MEG (eyes closed). Functional connectivity MEG source data were reconstructed globally in the alpha range, quantified by the mean imaginary coherence between a voxel and the rest of the brain.In patients, decreased connectivity was observed in left prefrontal cortex (PFC) and right superior temporal cortex, whereas increased connectivity was observed in left extrastriate cortex and the right inferior PFC. Functional connectivity of left inferior parietal cortex was negatively related to positive symptoms. Low left PFC connectivity was associated with negative symptoms. Functional connectivity of midline PFC was negatively correlated with depressed symptoms. Functional connectivity of right PFC was associated with other (cognitive) symptoms.This study demonstrates direct functional disconnection in SZ between specific cortical fields within low-frequency resting-state oscillations. Impaired alpha coupling in frontal, parietal, and temporal regions is associated with clinical symptoms in these stable outpatients. Our findings indicate that this level of functional disconnection between cortical regions is an important treatment target in SZ.
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Project description:BackgroundFunctional magnetic resonance imaging (fMRI) resting-state studies show generalized social anxiety disorder (gSAD) is associated with disturbances in networks involved in emotion regulation, emotion processing, and perceptual functions, suggesting a network framework is integral to elucidating the pathophysiology of gSAD. However, fMRI does not measure the fast dynamic interconnections of functional networks. Therefore, we examined whole-brain functional connectomics with electroencephalogram (EEG) during resting-state.MethodsResting-state EEG data was recorded for 32 patients with gSAD and 32 demographically-matched healthy controls (HC). Sensor-level connectivity analysis was applied on EEG data by using Weighted Phase Lag Index (WPLI) and graph analysis based on WPLI was used to determine clustering coefficient and characteristic path length to estimate local integration and global segregation of networks.ResultsWPLI results showed increased oscillatory midline coherence in the theta frequency band indicating higher connectivity in the gSAD relative to HC group during rest. Additionally, WPLI values positively correlated with state anxiety levels within the gSAD group but not the HC group. Our graph theory based connectomics analysis demonstrated increased clustering coefficient and decreased characteristic path length in theta-based whole brain functional organization in subjects with gSAD compared to HC.ConclusionsTheta-dependent interconnectivity was associated with state anxiety in gSAD and an increase in information processing efficiency in gSAD (compared to controls). Results may represent enhanced baseline self-focused attention, which is consistent with cognitive models of gSAD and fMRI studies implicating emotion dysregulation and disturbances in task negative networks (e.g., default mode network) in gSAD.
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