Decreased Resting State Inter- and Intra-Network Functional Connectivity Is Associated with Perceived Stress in a Sample of University Students: An eLORETA Study

Abstract

<b><i>Introduction:</i></b> Although the study of the Triple Network (TN) model has gained attention in the exploration of stress-related processes, the neurophysiological mechanisms of TN in relation to perceived stress have been relatively understudied in nonclinical samples so far. The main objective of the present study was to investigate, in a sample of university students, the association of perceived stress with resting state electroencephalography (EEG) functional connectivity in the TN. <b><i>Methods:</i></b> Ninety university students (40 males and 50 females; mean age 22.30 ± 2.43 years; mean educational level 16.60 ± 1.62 years) were enrolled. EEG data were analyzed through the exact low-resolution electromagnetic tomography (eLORETA). <b><i>Results:</i></b> Higher levels of perceived stress were associated with decreased delta EEG connectivity within the central executive network (CEN) and between the CEN and the salience network (SN). Higher levels of perceived stress were also associated with decreased theta EEG connectivity between the CEN and the SN. The associations between perceived stress and EEG connectivity data were significant even when relevant confounding factors (i.e., sex, age, educational level, and psychopathological symptoms) were controlled for. <b><i>Discussion:</i></b> Taken together, our results suggest that higher levels of perceived stress are associated with a dysfunctional synchronization within the CEN and between the SN and the CEN. This functional pattern might in part reflect the negative impact of high levels of perceived stress on cognitive functioning.

Exposure to nature is associated with decreased functional connectivity within the distress network: A resting state EEG study

“…Particularly, the electroencephalography (EEG) is widely used for the investigation of brain activity related to the exposure of natural settings ( Grassini et al, 2022 ), providing an important source of information on changes in neurophysiological dynamics associated with stress-related processes ( Alonso et al, 2015 ; Giannakakis et al, 2019 ; Saeed et al, 2020 ; Massullo et al, 2022 ). More specifically, compared to the traditional visual EEG scoring, through quantitative EEG (qEEG; i.e., numerical computations of parameters from the EEG data) it is possible to estimate different parameters, such as EEG power spectra (i.e., the power distribution of EEG series in the frequency domain), that offer a significant source of information in terms of brain activity ( Thatcher, 2010 ; Lehembre et al, 2012 ).…”