Daviu N, Bruchas MR, Moghaddam B, et al. Neurobiological links between stress and anxiety. Neurobiol Stress. 2019;11:100191. https://doi.org/10.1016/j.ynstr.2019.100191.

Article  PubMed  PubMed Central  Google Scholar 

Hammen C. Stress and depression. Annu Rev Clin Psychol. 2005;1:293–319. https://doi.org/10.1146/annurev.clinpsy.1.102803.143938.

Article  PubMed  Google Scholar 

Martsenkovskyi D, Shevlin M, Ben-Ezra M, et al. Mental health in Ukraine in 2023. Eur Psychiatry. 2024;67:e27. https://doi.org/10.1192/j.eurpsy.2024.12.

Article  PubMed  PubMed Central  Google Scholar 

Ehrhardt NM, Fietz J, Kopf-Beck J, et al. Separating EEG correlates of stress: cognitive effort, time pressure, and social-evaluative threat. Eur J Neurosci. 2022;55:2464–73. https://doi.org/10.1111/ejn.15211.

Article  CAS  PubMed  Google Scholar 

Vanhollebeke G, De Smet S, De Raedt R, et al. The neural correlates of psychosocial stress: a systematic review and meta-analysis of spectral analysis EEG studies. Neurobiol Stress. 2022;18:100452. https://doi.org/10.1016/j.ynstr.2022.100452.

Article  PubMed  PubMed Central  Google Scholar 

Jaworska N, Blier P, Fusee W, et al. α power, α asymmetry and anterior cingulate cortex activity in depressed males and females. J Psychiatr Res. 2012;46:1483–91. https://doi.org/10.1016/j.jpsychires.2012.08.003.

Article  PubMed  PubMed Central  Google Scholar 

Clancy KJ, Andrzejewski JA, Simon J, et al. Posttraumatic stress disorder is associated with α dysrhythmia across the visual cortex and the default mode network. eNeuro. 2020;7:ENEURO.0053-20.2020. https://doi.org/10.1523/ENEURO.0053-20.2020.

Article  PubMed  PubMed Central  Google Scholar 

Yuan D, Yang X, Wang P, et al. Quantitative EEG and its relationship with attentional control in patients with anxiety disorders. Front Psychiatry. 2024;15:1483433. https://doi.org/10.3389/fpsyt.2024.1483433.

Article  PubMed  PubMed Central  Google Scholar 

Al-Shargie F, Kiguchi M, Badruddin N, et al. Mental stress assessment using simultaneous measurement of EEG and fNIRS. Biomed Opt Express. 2016;7:3882–98. https://doi.org/10.1364/BOE.7.003882.

Article  PubMed  PubMed Central  Google Scholar 

Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods. 2004;134:9–21. https://doi.org/10.1016/j.jneumeth.2003.10.009.

Article  PubMed  Google Scholar 

Pion-Tonachini L, Kreutz-Delgado K, Makeig S. ICLabel: an automated electroencephalographic independent component classifier, dataset, and website. NeuroImage. 2019;198:181–197.https://doi.org/10.1016/j.neuroimage.2019.05.026.

Gramfort A, Luessi M, Larson E, et al. MEG and EEG data analysis with MNE-Python. Front Neurosci. 2013;7:267. https://doi.org/10.3389/fnins.2013.00267.

Article  PubMed  PubMed Central  Google Scholar 

Welch PD. The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans Audio Electroacoust. 1967;15:70–3. https://doi.org/10.1109/TAU.1967.1161901.

Article  Google Scholar 

Gudmundsson S, Runarsson TP, Sigurdsson S, et al. Reliability of quantitative EEG features. Clin Neurophysiol Pract. 2007;118:2162–71. https://doi.org/10.1016/j.clinph.2007.06.018.

Article  PubMed  Google Scholar 

Klimesch W, Sauseng P, Hanslmayr S. EEG alpha oscillations: the inhibition–timing hypothesis. Brain Res Rev. 2007;53:63–88. https://doi.org/10.1016/j.brainresrev.2006.06.003.

Article  PubMed  Google Scholar 

Jensen O, Mazaheri A. Shaping functional architecture by oscillatory alpha activity: gating by inhibition. Front Hum Neurosci. 2010;4:186. https://doi.org/10.3389/fnhum.2010.00186.

Article  PubMed  PubMed Central  Google Scholar 

Michelmann S, Griffiths B, Hanslmayr S. The role of alpha and beta oscillations in the human EEG during perception and memory processes. In: Gable PA, Miller MW, Bernat EM, editors. The Oxford Handbook of EEG Frequency. Oxford: Oxford University Press; 2022.

Google Scholar 

Palacios-García I, Silva J, Villena-González M, et al. Increase in beta power reflects attentional top-down modulation after psychosocial stress induction. Front Hum Neurosci. 2021;15:630813. https://doi.org/10.3389/fnhum.2021.630813.

Article  PubMed  PubMed Central  Google Scholar 

Forner-Phillips NA, Mills C, Ross RS. Tendency to ruminate and anxiety are associated with altered alpha and beta oscillatory power dynamics during memory for contextual details. Cogn Affect Behav Neurosci. 2020;20:698–716. https://doi.org/10.3758/s13415-020-00797-2.

Tran Y, Craig A, Craig R, et al. The influence of mental fatigue on brain activity: evidence from a systematic review with meta-analyses. Psychophysiology. 2020;57:e13554. https://doi.org/10.1111/psyp.13554.

Article  PubMed  Google Scholar 

Spitzer B, Haegens S. Beyond the status quo: a role for beta oscillations in endogenous content (re)activation. eNeuro. 2017;4:ENEURO.0170-17.2017. https://doi.org/10.1523/ENEURO.0170-17.2017.

Article  PubMed  PubMed Central  Google Scholar 

Engel AK, Fries P. Beta-band oscillations—signalling the status quo? Curr Res Neurobiol. 2010;20:156–65. https://doi.org/10.1016/j.conb.2010.02.015.

Article  CAS  PubMed  Google Scholar 

Choi Y, Kim M, Chun C. Measurement of occupants’ stress based on electroencephalograms (EEG) in twelve combined environments. Build Environ. 2015;88:65–72. https://doi.org/10.1016/j.buildenv.2014.10.003.

Article  Google Scholar 

van Son D, De Blasio FM, Fogarty JS, et al. Frontal EEG theta/beta ratio during mind wandering episodes. Biol Psychol. 2019;140:19–27. https://doi.org/10.1016/j.biopsycho.2018.11.003.

Article  PubMed  Google Scholar 

Hanslmayr S, Staudigl T, Fellner MC. Oscillatory power decreases and long-term memory: the information via desynchronization hypothesis. Front Hum Neurosci. 2012;6:74. https://doi.org/10.3389/fnhum.2012.00074.

Article  PubMed  PubMed Central  Google Scholar 

Mitchell JF, Sundberg KA, Reynolds JH, et al. Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4. Neuron. 2009;63:879–88. https://doi.org/10.1016/j.neuron.2009.09.013.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Borghini G, Vecchiato G, Toppi J, et al. Assessment of mental fatigue during car driving by using high resolution EEG activity and neurophysiologic indices. Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:6442–5. https://doi.org/10.1109/EMBC.2012.6347469.

Article  CAS  PubMed  Google Scholar 

Xie J, Xu G, Wang J, et al. Effects of mental load and fatigue on steady-state evoked potential based brain-computer interface tasks: a comparison of periodic flickering and motion-reversal based visual attention. PLoS One. 2016;11:e0163426. https://doi.org/10.1371/journal.pone.0163426.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Käthner I, Wriessnegger SC, Müller-Putz GR, et al. Effects of mental workload and fatigue on the P300, alpha and theta band power during operation of an ERP (P300) brain-computer interface. Biol Psychol. 2014;102:118–29. https://doi.org/10.1016/j.biopsycho.2014.07.014.

Vanhollebeke G, Kappen M, De Raedt R, et al. Effects of acute psychosocial stress on source level EEG power and functional connectivity measures. Sci Rep. 2023;13:8807. https://doi.org/10.1038/s41598-023-35808-y.

Article  CAS  PubMed  PubMed Central  Google Scholar