Frontal midline theta oscillations during mental arithmetic: effects of stress

Gärtner, Matti; Grimm, Simone; Bajbouj, Malek

doi:10.3389/fnbeh.2015.00096

Cited by 65 publications

(52 citation statements)

References 47 publications

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“…The EEG results showed significant decrease in alpha rhythm power (p<0.01) and increase in beta rhythm power (p<0.02) on the PFC under stress condition. The decrease in alpha rhythm power in this study is consistent with previous emotional and anxiety studies [28, [73][74][75]. Additionally, previous EEG studies, reported an increase in alpha and decrease in beta rhythm in the frontal cortex under fatigue (fatigue task with 90-150 minutes time) which is not the case in this study [76,77].…”

Section: Discussionsupporting

confidence: 81%

Mental stress assessment using simultaneous measurement of EEG and fNIRS

Al-Shargie

Kiguchi

Badruddin

et al. 2016

Biomed. Opt. Express

204

159

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Previous studies reported mental stress as one of the major contributing factors leading to various diseases such as heart attack, depression and stroke. An accurate stress assessment method may thus be of importance to clinical intervention and disease prevention. We propose a joint independent component analysis (jICA) based approach to fuse simultaneous measurement of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) on the prefrontal cortex (PFC) as a means of stress assessment. For the purpose of this study, stress was induced by using an established mental arithmetic task under time pressure with negative feedback. The induction of mental stress was confirmed by salivary alpha amylase test. Experiment results showed that the proposed fusion of EEG and fNIRS measurements improves the classification accuracy of mental stress by +3.4% compared to EEG alone and +11% compared to fNIRS alone. Similar improvements were also observed in sensitivity and specificity of proposed approach over unimodal EEG/fNIRS. Our study suggests that combination of EEG (frontal alpha rhythm) and fNIRS (concentration change of oxygenated hemoglobin) could be a potential means to assess mental stress objectively. References and links1. J. Decker, "The Stress Syndrome," Am. J. Nurs. 65(3), 97-99 (1965). 2. L. R. Murphy, "Stress management in work settings: a critical review of the health effects," Am. J. Health Promot. 11(2), 112-135 (1996). 3. B. Czéh, T. Michaelis, T. Watanabe, J. Frahm, G. de Biurrun, M. van Kampen, A. Bartolomucci, and E. Fuchs, "Stress-induced changes in cerebral metabolites, hippocampal volume, and cell proliferation are prevented by antidepressant treatment with tianeptine," Proc. Natl. Acad. Sci. U.S.A. 98(22), 12796-12801 (2001). 4. C. M. Vander Weele, C. Saenz, J. Yao, S. S. Correia, and K. A. Goosens, "Restoration of hippocampal growth hormone reverses stress-induced hippocampal impairment," Front. Behav. Neurosci. 7, 66 (2013). 5. A. Vyas, R. Mitra, B. S. Shankaranarayana Rao, and S. Chattarji, "Chronic stress induces contrasting patterns of dendritic remodeling in hippocampal and amygdaloid neurons," J. Neurosci. 22(15), 6810-6818 (2002). 6. B. S. McEwen, "Central effects of stress hormones in health and disease: Understanding the protective and damaging effects of stress and stress mediators," Eur. J. Pharmacol. 583(2-3), 174-185 (2008). 7. P. C. Strike and A. Steptoe, "Systematic review of mental stress-induced myocardial ischaemia," Eur. Heart J.24(8), 690-703 (2003). 8. A. Tsutsumi, K. Kayaba, and S. Ishikawa, "Impact of occupational stress on stroke across occupational classes and genders," Soc. Sci. Med. 72(10), 1652-1658 (2011). 9. R. A. Ajjan and P. J. Grant, "Cardiovascular disease prevention in patients with type 2 diabetes: The role of oral anti-diabetic agents," Diab. Vasc. Dis. Res. 3(3), 147-158 (2006). 10. C. Hammen, "Stress and depression," Annu. Rev. Clin. Psychol. 1(1), 293-319 (2005 532-545 (1972). 22. T. G. Vrijkotte, L. J. van Doornen, and E. ...

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Section: Discussionsupporting

confidence: 81%

Mental stress assessment using simultaneous measurement of EEG and fNIRS

Al-Shargie

Kiguchi

Badruddin

et al. 2016

Biomed. Opt. Express

204

159

View full text Add to dashboard Cite

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“…In contrast, increased cognitive effort to maintain consistent RT across the two types of Go responses was likely driven by frontal theta activity, which correlated with RT (inversely) and motor cortical activity. A relation between theta and RT is in agreement with a study showing that frontal theta power was decreased and onset delayed during stress, which correlated with longer RTs (Gartner et al 2015). This suggests that speeded responses may depend on theta signaling, while being a finite resource.…”

Section: Frontal Theta Is Related To Behavioral Output Via Motor Cortsupporting

confidence: 90%

“…The current study identified a strong relation between mTEPR and oscillatory theta power and further demonstrated that these tracked parametric increases in cognitive control. Previous research has linked frontal theta with a variety of cognitive control processes, such as mental arithmetic (Gartner et al 2015), response preparation (Womelsdorf et al 2010), response switching (Cheyne et al 2012) and response inhibition (Isabella et al 2015). One study demonstrated the sensitivity of frontal theta to increasing load in a working memory task (Jensen et al 2002).…”

Section: Inhibitory Control In the Absence Of Awareness: Role For Fromentioning

confidence: 99%

Unconscious learning and automatic inhibition are accompanied by frontal theta and sensorimotor interactions

Isabella

Cheyne

2019

Preprint

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Cognitive control of behavior is often accompanied by theta--band activity in the frontal cortex, and is crucial for overriding habits and producing desired actions. However, the functional role of theta activity in controlled behavior remains to be determined. Here, we used a behavioral task (Isabella et al., 2019) that covertly manipulated the ability to inhibit (and switch) motor responses using a repeating pattern of stimuli that reduced reaction times (RT) to probable over unexpected stimuli, without participants' awareness of the pattern. We combined this task with concurrent measures of brain activity and pupil diameter (as a measure of cognitive activity) of 16 healthy adults during response preparation and inhibition during changes in stimulus probability. Observed RT provided evidence of pattern learning and pupillometry revealed parametric changes in cognitive activity with stimulus probability. Critically, reliable pupillary effects (Hedge's g = 1.38) in the absence of RT differences (g = 0.10) indicated that cognitive activity increased without overt changes in behavior (RT). Such increased cognitive activity was accompanied by parametric increases in frontal theta and sensorimotor gamma. In addition, correlation between pre--stimulus beta and pre--response gamma in the motor cortex and post--stimulus frontal theta activity suggest bidirectional interactions between motor and frontal areas. These interactions likely underlie recruitment of preparatory and inhibitory neural activity during rapid motor control. Furthermore, pupillary and frontal theta effects during learned switches demonstrate that increases in inhibitory control of behavior can occur automatically, without conscious awareness.

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“…Our results showed differences in the cortical activation pattern between participants who won and those who lost in the same tasks. Increases in theta power, when difficulty increased, have been previously reported [14,15,29]. In the same way, when comparing two performance groups,…”

Section: Discussionsupporting

confidence: 62%

Chess Players Increase the Theta Power Spectrum When the Difficulty of the Opponent Increases: An EEG Study

Fuentes-García

Villafaina

Collado-Mateo

et al. 2019

IJERPH

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The present study aimed to analyze differences in the electroencephalogram (EEG) power spectrum (theta, alpha, and beta) between participants who won (winning group) and those who lost (losing group) in three different chess games: against their same Elo (100% chess games), 25% over their Elo (125% chess games), and 25% under their Elo (75% chess games). EEG was assessed at baseline and during the chess games. Method: 14 male chess players (age: 35.36 ± 13.77 and Elo: 1921 ± 170) played three games of 3 min, plus two additional seconds per move, while EEG was assessed. There were three difficulty levels (75%, 100%, and 125%), with two games (one with white pieces and another with black pieces) per level. The winning group showed higher theta power in the frontal, central, and posterior brain regions when difficulty increased (p-value < 0.05). Besides this, alpha power showed higher values (p-value < 0.05) in 125% games than in 75% chess games in C3, T3, T4, T5, and T6. The losing group showed a significant decrease (p-value < 0.05) in the beta and alpha power spectrum in frontal, central, parietotemporal, and occipital areas, when the opponent’s difficulty increased. Moreover, between groups, analyses showed higher theta power in the losing group than in the winning group, in C3, T5, T6, P4, and Pz (p-value < 0.05). Therefore, the winning group was able to adapt to each difficulty level, increasing theta power in the frontal, central, and posterior brain areas, as the efficiency hypothesis postulated. These changes were not observed in the losing group. Moreover, increases in alpha power during the most difficult games, in comparison with the easier, could have been caused by creative ideation and divergent thinking, as participants looked for alternative solutions against a higher-skilled opponent.

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Frontal midline theta oscillations during mental arithmetic: effects of stress

Cited by 65 publications

References 47 publications

Mental stress assessment using simultaneous measurement of EEG and fNIRS

Mental stress assessment using simultaneous measurement of EEG and fNIRS

Unconscious learning and automatic inhibition are accompanied by frontal theta and sensorimotor interactions

Chess Players Increase the Theta Power Spectrum When the Difficulty of the Opponent Increases: An EEG Study

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