Resting‐state connectivity and network parameter analysis in alcohol‐dependent males. A simultaneous EEG‐MEG study

Abstract

There is supporting evidence of alcohol negative effects on the brain: neuroimaging and psychophysiological studies finding anatomical and functional connectivity (FC) changes associated with the dependence process. Thus, the aim of this work was to evaluate brain FC and network characteristics of alcohol‐dependent individuals in resting state. For this study, we included males diagnosed with alcohol dependence (N = 25) and a group of healthy individuals (N = 23). Simultaneous EEG‐MEG (electroencephalographic and magnetoencephalographic) activity was recorded in 5 min of eyes‐closed resting state. EEG‐MEG activity was preprocessed and FC was computed through the leakage‐corrected version of phase locking value (ciPLV). Additionally, local (degree, efficiency, clustering) and global (efficiency, characteristic path length) network parameters were computed. Connectivity analysis showed an increase in phase‐lagged synchronization, mainly between frontal and frontotemporal regions, in high beta band, and a decrease in interhemispheric gamma, for alcohol‐dependent individuals. Network analysis revealed intergroup differences at the local level for high beta, indicating higher degree, clustering, and efficiency, mostly at frontal nodes, together with a decrease in these measures at more posterior sites for patients’ group. The hyper‐synchronization in beta, next to the hypo‐synchronization in gamma, could indicate an alteration in communication between hemispheres, but also a possible functional compensation mechanism in neural circuits. This could be also supported by network characteristic data, where local alterations in communication are observed.

Neural correlates of visuoperceptive changes in severe alcohol use disorder: A critical review of neuroimaging and electrophysiological findings

“…Top-down processing is particularly important when the mapping between sensory inputs, thoughts, and actions is weakened (Miller & Cohen, 2001), as it is most probably happening in SAUD. This lower gamma power, also observed at rest (Sion et al, 2020), combined with the potential decrease in communication between distant areas indexed by lower responses in the delta and theta range, might suggest impaired frontal-visual connectivity in SAUD. Such a proposal is consistent with results from resting-state EEG documenting lower spectral power in the alpha frequency range (7.5-12 Hz) in bilateral occipital areas of individuals with SAUD, although specifically in men (Ehlers & Phillips, 2007).…”

“…Slow frequencies are thought to mirror synchronized neuronal activity throughout distant cerebral regions, while fast frequencies correspond to the synchronization of groups of neurons in more restricted brain areas, a pattern of activity generally associated with sensory processing (Von Stein & Sarnthein, 2000). Whereas the most common finding in SAUD is a decrease in delta (1-3 Hz) and theta (3.5-7.5 Hz) EROs, thought to reflect the high-level processes underlying the P3 ERP component (e.g., Andrew & Fein, 2010;Pandey et al, 2012;Porjesz & Begleiter, 2003;Rangaswamy & Porjesz, 2014), changes in the gamma band (28.5-50 Hz) have also been highlighted (Padmanabhapillai et al, 2006;Sion et al, 2020). Interestingly, gamma oscillations have been linked to vision and integrative functions such as "feature binding" (e.g., shape and color) as well as top-down interactions with frontal regions during sensory processing (Başar et al, 1999;Porjesz & Begleiter, 2003).…”

“…Alteration of integrative functions (e.g., "feature binding"); Padmanabhapillai et al (2006), Padma Sriraam (2016, 2017), Sion et al (2020) Impaired top-down interactions with frontal regions during sensory processing…”

Source-level EEG and graph theory reveal widespread functional network alterations in focal epilepsy

“…Each frequency band was analysed separately. Analyses were conducted on a range of predefined density values (López-Sanz et al 2017; Sion et al 2020). Graph metrics were calculated on both the whole-network (global) and the node (local) levels.…”

Anomalies in global network connectivity associated with early recovery from alcohol dependence: A network transcranial magnetic stimulation and electroencephalography study

“…Electroencephalography (EEG), an economic and convenient neuroimaging tool with high temporal resolution, is capable of characterising brain network connectivity within a millisecond timescale. 31 , 32 , 33 To date, only a limited number of EEG studies have explored the presence of altered network topology associated with short‐term 34 and long‐term 35 , 36 alcohol consumption, and these studies have presented mixed findings. Therefore, preliminary studies, while providing broad support for the use of EEG to identify network anomalies, examined network connectivity from multiple levels (resting‐state and task‐activated) and utilised a diverse range of techniques (EEG and combined EEG‐MEG) and connectivity analyses (phase‐synchronisation index, coherence and cross‐correlation) as well as varied statistical analyses techniques (group‐wise comparisons and data mining models) which may account for discrepant results.…”