Acute alcohol intoxication modulates the temporal dynamics of resting electroencephalography networks

Abstract

This study aimed to provide a currently missing link between general intoxication‐induced changes in overall brain activity and the multiple cognitive control deficits typically observed during acute alcohol intoxication. For that purpose, we analyzed the effects of acute alcohol intoxication (1.1‰) on the four archetypal electroencephalography (EEG) resting networks (i.e., microstates A–D) and their temporal dynamics (e.g., coverage and transitions from one microstate to another), as well as on self‐reported resting‐state cognition in n = 22 healthy young males using a counterbalanced within‐subject design. Our microstate analyses indicated that alcohol increased the coverage of the visual processing‐related microstate B at the expense of the autonomic processing‐related microstate C. Add‐on exploratory analyses revealed that alcohol increased transitions from microstate C to microstate B and decreased bidirectional transitions between microstate C and the attention‐related microstate D. In line with the observed alcohol‐induced decrease of the autonomic processing‐related microstate C, participants reported decreases of their somatic awareness during intoxication, which were positively associated with more transitions from microstate C to microstate B. In sum, the observed effects provide mechanistic insights into how alcohol might hamper cognitive processing by generally prioritizing the bottom‐up processing of visual stimuli over top‐down internal information processing. The fact that this was found during the resting state further proves that alcohol‐induced changes in brain activity are continuously present and do not only emerge during demanding situations or tasks.

Assessment of Classical and Non-Classical Quantitative Electroencephalographic Measures in Patients with Substance Use Disorders

“…Recently, other interesting EEG-based approaches are emerging and need further research to better characterize patients with SUDs, mainly at the individual level. This is the case of connectivity measures, 14 microstates analysis, 34 and machine learning. 35…”

Data-Driven EEG Theta and Alpha Components Are Associated with Subjective Experience during Resting State

“…The Amsterdam Resting-State Questionnaire (ARSQ) [ 16 , 17 ] assesses ten mind-wandering domains that participants might experience during the resting session: Discontinuity of Mind (DoM), referring to the dynamics of ongoing thoughts; Theory of Mind (ToM), referring to other-people-related thoughts; Self, referring to self-related thoughts; Planning, referring to future-directed thoughts; Sleepiness, referring to the level of drowsiness; Comfort, referring to the level of relaxation during the session; Somatic Awareness (SA), referring to the interoceptive awareness of one’s own body; Health Concern (HC), referring to general well-being; Visual Thought (Vis), referring to visual imagery during mind wandering; and Verbal Thought (VT), referring to spontaneous thoughts formulated in words. Several EEG, fMRI, and behavioral studies have reported the relationship between ARSQ domains and physiological or psychological variables in healthy [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ] and clinical cohorts [ 27 , 28 ], confirming the importance of combined measures of subjective experience and biologically defined signals.…”

Trait Aggression is Reflected by a Lower Temporal Stability of EEG Resting Networks

“…Here, we follow a neural trait approach to examine how basic neural processing at rest may help explain the sources of individual levels of aggression. The neural trait approach involves measuring stable characteristics in resting-state brain recordings and investigating whether these characteristics are associated with cognitive, biological, and behavioral processes (e.g., Schiller et al 2014 , 2020a , b , 2021 ; Leota et al 2021 ; Nash et al 2022 ; Kleinert et al 2022 ). This task-independent approach compliments existing, task-dependent analyses of neural and psychological processes (for more on the benefits of task-independence, see Berkman and Falk 2013 ).…”