Executive control and emotional regulation: the effect of mathematical tasks on cortical activation in anxious patients
Keywords:
executive control, emotional regulation, cortical activation, mathematical taskAbstract
Background: Anxiety is often accompanied by cognitive and emotional deficits, including difficulties in emotional regulation and executive control. Evidence suggests that the activity of the dorsolateral prefrontal cortex (DLPFC) is involved in modulating these processes. Studies indicate that mathematical cognitive tasks can activate this region, promoting emotional regulation. Thus, this study investigates the effect of mental arithmetic on cortical activity in anxious patients, analyzing changes in the alpha band of the EEG and its relationship with anxiety symptoms. Methods: The research included 80 participants (40 anxious patients and 40 healthy controls) recruited from the Institute of Psychiatry at UFRJ. Participants were evaluated before and after performing a mathematical task. Data collection included sociodemographic measures, neuropsychological tests, and psychometric scales (BAI, BDI, and PAS). EEG was recorded from the frontal regions and analyzed to calculate alpha band power (ABP) and frontal alpha asymmetry (FAA). Statistical analysis compared the groups and correlated the electrophysiological changes with psychometric scores. Results: After performing the mathematical task, a reduction in psychometric scale scores was observed in the clinical group. Additionally, there was an increase in ABP in the right hemisphere and a decrease in the left hemisphere, resulting in a reduction in FAA. This change suggests a modulation of cortical activity related to emotional regulation. Correlations indicated that the reduction in FAA was associated with improved anxiety symptoms. Conclusion: The findings suggest that mental arithmetic can modulate cortical activity and contribute to emotional regulation in anxious individuals. Although the observed effects were modest, the results support the hypothesis that cognitive interventions may be explored as complementary strategies for treating anxiety. Future studies should investigate the longterm effects of this approach and consider its integration into cognitive therapies.
References
1. Joormann J, Quinn ME. Cognitive processes and emotion regulation in depression. Depress Anxiety. 2014;31(4):308-15.
2. Domaradzka E, Fajkowska M. Cognitive emotion regulation strategies in anxiety and depression understood as types of personality. Front Psychol. 2018; 9:856.
3. Koenigs M, Huey E, Calamia M, Raymont V, Tranel D, Grafman J. Distinct regions of prefrontal cortex mediate resistance and vulnerability to depression. J Neurosci. 2008;28(47):12341-8.
4. Jenkins L, Stange J, Bessette K, Chang Y, Corwin S, Skerrett K, et al. Differential engagement of cognitive control regions and subgenual cingulate based upon presence or absence of comorbid anxiety with depression. J Affect Disord. 2018.
5. Henriques J, Davidson R. Left frontal hypoactivation in depression. J Abnorm Psychol. 1991;100(4):535-45.
6. Sotres-Bayon F, Cain C, LeDoux J. Brain mechanisms of fear extinction: historical perspectives on the contribution of prefrontal cortex. Biol Psychiatry. 2006; 60:329- 36.
7. Scult, M..; Knodt, A. R.; Swartz, J. R.; Brigid, B. D. and Hariri, A. R. Thinking and Feeling: Individual Differences in Habitual Emotion Regulation and Stress-Related Mood Are Associated With Prefrontal Executive Control. Assoc. Psychological Scien. 2016; Vol. 5, n.1, 150-157.
8. Barlow DH. Anxiety and its disorders: the nature and treatment of anxiety and panic. Guilford Press; 2004.
9. Mendlowicz MV, Stein MB. Quality of life in individuals with anxiety disorders. Am J Psychiatry. 2000;157(5):669-82. https://doi.org/10.1176/appi.ajp.157.5.669.
10. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Arlington, VA: American Psychiatric Publishing; 2013.
11. Beilock SL, Carr TH. When high-powered people fail: working memory and "choking under pressure" in math. Psychol Sci. 2005;16(2):101-5.
12. Richardson, F.C., & Suinn, R.M. The mathematicsanxiety rating scale: Psychometric data. Journal ofCounseling Psychology. 1972; 19, 551–554
13. Hofmann SG, Asnaani A, Vonk IJ, Sawyer AT, Fang A. The efficacy of cognitive behavioral therapy: a review of meta-analyses. Cognit Ther Res. 2012; 36:427-40. https://doi.org/10.1007/s10608-012-9476-1.
14. Goldin PR, Gross JJ. Effects of mindfulness-based stress reduction (MBSR) on emotion regulation in social anxiety disorder. Emotion. 2010;10(1):83. https://doi.org/10.1037/a0018427.
15. Herring MP, O’Connor PJ, Dishman RK. The effect of exercise training on anxiety symptoms among patients: a systematic review. Arch Intern Med. 2010;170(4):321- 31. https://doi.org/10.1001/archinternmed.2009.530.
16. Borkovec TD, Sharpless B. Generalized anxiety disorder: bringing cognitivebehavioral therapy into the valued present. Psychotherapy. 2004;41(3):289-95.
17. Miller EK, Cohen JD. An integrative theory of prefrontal cortex function. Annu Rev Neurosci. 2001;24(1):167-202. https://doi.org/10.1146/annurev.neuro.24.1.167.
18. Ochsner KN, Gross JJ. The cognitive control of emotion. Trends Cogn Sci. 2005;9(5):242-9. https://doi.org/10.1016/j.tics.2005.03.010.
19. Golkar A, Lonsdorf TB, Olsson A, Lindstrom KM, Berrebi J, Fransson P, et al. Distinct contributions of the dorsolateral prefrontal and orbitofrontal cortex during emotion regulation. PLoS One. 2012;7(11):e48107.
20. Barbey AK, Koenigs M, Grafman J. Dorsolateral prefrontal contributions to human working memory. Cortex. 2013;49(5):1195-205. https://doi.org/10.1016/j.cortex.2012.07.003.
21. Root JC, Wong PS, Kinsbourne M. Left hemisphere specialization for response to positive emotional expressions: a divided output methodology. Emotion. 2006;6(3):473-83. https://doi.org/10.1037/1528-3542.6.3.473.
22. Feeser M, Prehn K, Kazzer P, Mungee A, Bajbouj M. Transcranial direct current stimulation enhances cognitive control during emotion regulation. Brain Stimul. 2014;7(1):105-12. https://doi.org/10.1016/j.brs.2013.08.006.
23. Nimmrich V, Grimm C, Draguhn A, Barghorn S, Lehmann A, Schoemaker H, et al. Amyloid β oligomers (Aβ1–42 globulomer) suppress spontaneous synaptic activity by inhibition of P/Q-type calcium currents. J Neurosci. 2008;28(4):788-97. https://doi.org/10.1523/JNEUROSCI.5146-07.2008.
24. Horato N, Quagliato LA, Nardi AE. The relationship between emotional regulation and hemispheric lateralization in depression: a systematic review and a metaanalysis. Transl Psychiatry. 2022;12(1):162.
25. Klimesch W. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res Rev. 1999;29(2-3):169-95. https://doi.org/10.1016/S0165-0173(98)00056-3.
26. Hernández-González S, Perdomo-Perdomo MB, Sánchez-Gamarro R, et al. Electroencefalografía básica para monitores de profundidad anestésica. Rev Mex Anest. 2023;46(2):125-132. doi:10.35366/110199.
27. Goldsmith HH, Davidson RJ. Disambiguating the components of emotion regulation. Child Dev. 2004;75(2):361-5.
28. Coan JA, Allen JJ. Frontal EEG asymmetry as a moderator and mediator of emotion. Biol Psychol. 2004;67(1-2):7-50. https://doi.org/10.1016/j.biopsycho.2004.03.003.
29. Hagemann D, Naumann E, Thayer JF, Bartussek D. Does resting electroencephalograph asymmetry reflect a trait? An application of latent state-trait theory. J Pers Soc Psychol. 2002;82(4):619.
30. Sörnmo L, Laguna P. Bioelectrical signal processing in cardiac and neurological applications. 1st ed. Academic Press; 2005.
31. Nunez PL, Srinivasan R. Electric fields of the brain: the neurophysics of EEG. Oxford University Press; 2006.
32. Thibodeau R, Jorgensen RS, Kim S. Depression, anxiety, and resting frontal EEG asymmetry: a meta-analytic review. J Abnorm Psychol. 2006;115(4):715. https://doi.org/10.1037/0021-843X.115.4.715.
33. Knyazev GG. Motivation, emotion, and their inhibitory control mirrored in brain oscillations. Neurosci Biobehav Rev. 2007;31(3):377-95. https://doi.org/10.1016/j.neubiorev.2006.10.004.
34. Sheehan DV, Lecrubier Y, Sheehan KH, Janavs J, Weiller E, Keskiner A, et al. The validity of the Mini International Neuropsychiatric Interview (MINI) according to the SCID-P and its reliability. Eur Psychiatry. 1997;12(5):232-41. https://doi.org/10.1016/S0924-9338(97)83144-0.
35. Rey A. L'examen clinique en psychologie. Presses Universitaires de France; 1958.
36. Salgado JV, Malloy-Diniz LF, Abrantes SSC, Moreira L, Schlottfeldt CG, Guimarães W, et al. Applicability of the Rey Auditory-Verbal Learning Test to an adult sample in Brazil. Braz J Psychiatry. 2011; 33:234-7. https://doi.org/10.1590/S1516-44462011000300004. 76
37. de Figueiredo VL, Nascimento ED. Desempenhos nas duas tarefas do subteste dígitos do WISC-III e do WAIS-III. Psicologia: Teoria e Pesquisa. 2007; 23:313-8. doi:10.1590/S1678-25282007000300007.
38. Gorenstein C, Pang WY, Argimon IDL, Werlang BSG. Manual do Inventário de depressão de Beck-BDI-II. São Paulo: Casa do Psicólogo; 2011.
39. Quintão S, Delgado AR, Prieto G. Validity study of the Beck Anxiety Inventory (Portuguese version) by the Rasch rating scale model. Psicologia: Reflexão e Crítica. 2013; 26:305-10. doi:10.1590/S0102-79722013000200007.
40. Bandelow B. Assessing the efficacy of treatments for panic disorder and agoraphobia. II. The Panic and Agoraphobia Scale. Int Clin Psychopharmacol. 1995;10(2):73-82. doi:10.1097/00004850-199506000-00002.
41. D’Agostino RB, Stephens MA. Goodness-of-fit techniques. New York: SpringerVerlag; 1990.
42. Lilliefors HW. On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown. J Am Stat Assoc. 1967;62(318):399-402.
43. Field A. Discovering statistics using IBM SPSS statistics. 4th ed. London: SAGE; 2013.
44. Cohen P. Review lecture: protein phosphorylation and hormone action. Proc R Soc Lond B Biol Sci. 1988;234(1275):115-44.
45. Wilcoxon F. Some uses of statistics in plant pathology. Biometrics Bull. 1945;1(4):41-5.
46. Bakeman R. Recommended effect size statistics for repeated measures designs. Behav Res Methods. 2005;37(3):379-84.
47. Spearman FH. The strategy of great railroads. New York: C. Scribner’s Sons; 1904.
48. Pearson K. VII. Mathematical contributions to the theory of evolution. —III. Regression, heredity, and panmixia. Philos Trans R Soc Lond A. 1896; 187:253- 318.
49. Tabachnick BG, Fidell LS, Ullman JB. Using multivariate statistics. 6th ed. Boston: Pearson; 2013.
50. Lakens D. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and anovas. Front Psychol. 2013; 4:863
Downloads
Published
How to Cite
License
Copyright (c) 2026 Natia Gabriela Griffo Horato
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
