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Sofonea, A.

Publications and source records attributed to Sofonea, A..

3 recordsLinked to original sources

EEG Microstate Dynamics During Immersive VR Earthquake Exposure: Signatures of Threat Reactivity, Recovery, and Resilience

Adapting to natural disasters requires rapid and flexible regulation of emotional and physiological responses, yet the large-scale brain dynamics supporting this process remain poorly understood. Using an immersive virtual reality (VR) earthquake simulation, we investigated real-time neural adaptation to acute environmental threat and its modulation by resilience. Seventy-six participants were randomly assigned to a VR earthquake condition (VR-ES, n = 38) or a control VR condition (VR-CTRL, n = 38). Resting-state EEG was recorded before and after the VR experience, and continuous mobile EEG was recorded during the simulation. EEG microstate analysis was used to characterize large-scale brain dynamics associated with threat exposure and recovery. Exposure to the simulated disaster induced distinct alterations in microstate dynamics, with opposing changes in microstates C (p<0.001, rb=0.55) and D (p<0.001, rb=0.52) observed specifically in the VR-ES group. Moreover, our results confirm that distinct neural patterns are activated during the recovery resting-state phase following VR-ES. Critically, resilience and childhood adversity moderated the patterns of associations with emotional recovery, such that individuals with higher resilience exhibited more adaptive microstate configurations associated with improved recovery outcomes. These findings suggest that flexible reorganization of large-scale brain states supports adaptation to acute environmental stress and that resilience shapes the neural dynamics underlying recovery. This work highlights the value of ecologically valid VR paradigms combined with mobile neurophysiology for understanding individual differences in responses to environmental threat and their adaptive neural mechanisms.

neuroscience↗

Neural networks implicated in autobiographical memory training

Training of autobiographical memory has been proposed as intervention to improve cognitive functions. The neural substrates for such improvements are poorly understood. Several brain networks have been previously linked to autobiographical recollections, including the default mode network (DMN) and the sensorimotor network. Here we tested the hypothesis that different neural networks support distinct aspects of memory improvement in response to training on a group of 59 subjects. We found that memory training increases DMN connectivity, and this associates with improved recollection of cue-specific memories. On the contrary, training decreased connectivity in the sensorimotor network, a decrease that correlated with improved ability for voluntary recall. Moreover, only decreased sensorimotor connectivity associated with training-induced decrease in the TNF immunological factor, which has been previously linked to improved cognitive performance. We identified functional and biochemical factors that associate with distinct memory processes improved by autobiographical training. Pathways which connect autobiographical memory to both high level cognition and somatic physiology are discussed.

neuroscience↗

Spontaneous thought and microstate activity modulation by social imitation

Social imitation increases well-being and closeness by mechanisms that remain poorly understood. We propose that imitation impacts behavioural states in part by modulating post-imitation mind-wandering. The human mind wanders spontaneously and frequently, revisiting the past and imagining the future of self and of others. External and internal factors can influence wandering spontaneous thoughts, whose content predicts subsequent emotional states. In 43 young subjects, we find that imitating the arm movements of an actor alters the dynamics and the content of subsequent resting-state spontaneous thoughts. Imitation-sensitive features of spontaneous thoughts correlate with both behavioural states and salivary oxytocin levels. EEG microstate analysis reveals that global patterns of correlated neuronal activity predict imitation-induced changes in spontaneous thoughts. Thus, imitation can modulate ongoing activity in specific neural networks to change spontaneous thought patterns as a function of oxytocin levels, and to ultimately orchestrate behavioural states.

neuroscience↗