A Group Level Analysis of Self-evaluations Associated with Cognitive Load

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Abstract

Self-evaluation, or self-rating, is the process by which people evaluate themselves with the purpose of improving several aspects of their personalities or skills and it is closely related to the cognitive function of metacognition. The purpose of the study was to investigate the degree of implication of various brain areas to meta-cognition as it relates to subjective ratings of cognitive effort when performing mathematical problems of different complexity. To achieve this, participants were recruited to solve mathematical problems (addition, subtraction, multiplication, and division) in three levels of difficulty, while inside an fMRI scanner. After solving a given task, they were asked to evaluate the amount of effort they spent to solve it. Brain signal was collected during their answers, which was then analyzed with the aid of computer software. Results of the analysis show that increases in task difficulty activate the frontal lobe, cingulate and insular cortex areas. The parietal lobule, the precuneus and the cingulate gyrus were found to be active as well as during all four mathematical operations.

About the authors

Alexios Kouzalis

HSE University

Author for correspondence.
Email: alexiskouzalis@gmail.com
ORCID iD: 0000-0002-0986-7896
SPIN-code: 8038-5980
Scopus Author ID: 57223436261

doctoral student of the Doctoral School of Psychology

20 Myasnitskaya St, Moscow, 101000, Russian Federation

References

  1. Adelman, G. (2009). Encyclopedia of neuroscience (M. D. Binder, N. Hirokawa & U. Windhorst, Eds.). Berlin: Springer; Heidelberg. https://doi.org/10.1007/978-3-540-29678-2
  2. Arsalidou, M., & Taylor, M.J. (2011). Is 2 + 2 = 4? Meta-analyses of brain areas needed for numbers and calculations. NeuroImage, 54(3), 2382-2393. https://doi.org/10.1016/j.neuroimage.2010.10.009
  3. Arsalidou, M., Pawliw-Levac, M., Sadeghi, M., & Pascual-Leone, J. (2018). Brain areas associated with numbers and calculations in children: Meta-analyses of fMRI studies. Developmental Cognitive Neuroscience, 30, 239-250. https://doi.org/10.1016/j.dcn.2017.08.002
  4. Baird, B., Cieslak, M., Smallwood, J., Grafton, S.T., & Schooler, J.W. (2015). Regional white matter variation associated with domain-specific metacognitive accuracy. Journal of Cognitive Neuroscience, 27(3), 440-452. https://doi.org/10.1162/jocn_a_00741
  5. Baird, B., Smallwood, J., Gorgolewski, K.J., & Margulies, D.S. (2013). Medial and lateral networks in anterior prefrontal cortex support metacognitive ability for memory and perception. The Journal of Neuroscience, 33(42), 16657-16665. https://doi.org/10.1523/JNEUROSCI.0786-13.2013
  6. Berlucchi, G. (2009). Chapter 13: The contributions of neurophysiology to clinical neurology: An exercise in contemporary history. In S. Finger, F. Boller & K. Tyler (Eds.), History of Neurology (vol. 95, pp. 169-188). Elsevier Science. https://doi.org/10.1016/S0072-9752(08)02113-1
  7. Chua, E.F., Schacter, D.L., Rand-Giovannetti, E., & Sperling, R.A. (2006). Understanding metamemory: Neural correlates of the cognitive process and subjective level of confidence in recognition memory. NeuroImage, 29(4), 1150-1160. https://doi.org/10.1016/j.neuroimage.2005.09.058
  8. D’Argembeau, A., Ruby, P., Collette, F., Degueldre, C., Balteau, E., Luxen, A., Maquet, P., & Salmon, E. (2007). Distinct regions of the medial prefrontal cortex are associated with self-referential processing and perspective taking. Journal of Cognitive Neuroscience, 19(6), 935-944. https://doi.org/10.1162/jocn.2007.19.6.935
  9. Fechir, M., Gamer, M., Blasius, I., Bauermann, T., Breimhorst, M., Schlindwein, P., Schlereth, T., & Birklein, F. (2010). Functional imaging of sympathetic activation during mental stress. NeuroImage, 50(2), 847-854. https://doi.org/10.1016/j.neuroimage.2009.12.004
  10. Fleming, S. M., & Dolan, R. J. (2012). The neural basis of metacognitive ability. Philosophical Transactions of the Royal Society B: Biological Sciences, 367(1594), 1338-1349. https://doi.org/10.1098/rstb.2011.0417
  11. Fleming, S. M., & Lau, H. C. (2014). How to measure metacognition. Frontiers in Human Neuroscience, 8, 443. https://doi.org/10.3389/fnhum.2014.00443
  12. Hankinson, R.J. (1991). Galen’s anatomy of the soul. Phronesis, 36(2), 197-233. https://doi.org/10.1163/156852891321052787
  13. Lokhorst, G.-J. (2005). Descartes and the pineal gland. Retrieved April 20, 2023, from https://plato.stanford.edu/archives/win2021/entries/pineal-gland
  14. Morales, J., Lau, H., & Fleming, S.M. (2018). Domain-general and domain-specific patterns of activity supporting metacognition in human prefrontal cortex. The Journal of Neuroscience, 38(14), 3534-3546. https://doi.org/10.1523/JNEUROSCI.2360-17.2018
  15. Rolls, E.T. (2006). Brain mechanisms of emotion and decision-making. International Congress Series, 1291, 3-13. https://doi.org/10.1016/j.ics.2005.12.079
  16. Sandrone, S., Bacigaluppi, M., Galloni, M.R., & Martino, G. (2012). Angelo Mosso (1846-1910). Journal of Neurology, 259(11), 2513-2514. https://doi.org/10.1007/s00415-012-6632-1
  17. Sedikides, C. (1993). Assessment, enhancement, and verification determinants of the self-evaluation process. Journal of Personality and Social Psychology, 65(2), 317-338. https://doi.org/10.1037/0022-3514.65.2.317
  18. Spalletta, G., Piras, F., Piras, F., Caltagirone, C., & Orfei, M. D. (2014). The structural neuroanatomy of metacognitive insight in schizophrenia and its psychopathological and neuropsychological correlates. Human Brain Mapping, 35(9), 4729-4740. https://doi.org/10.1002/hbm.22507
  19. Sridharan, D., Levitin, D.J., & Menon, V. (2008). A critical role for the right frontoinsular cortex in switching between central-executive and default-mode networks. Proceedings of the National Academy of Sciences, 105(34), 12569-12574. https://doi.org/10.1073/pnas.0800005105
  20. Sweller, J. (1988). Cognitive load during problem solving: effects on learning. Cognitive Science, 12(2), 257-285. https://doi.org/10.1207/s15516709cog1202_4
  21. Van der Meer, L., de Vos, A.E., Stiekema, A.P.M., Pijnenborg, G.H.M., van Tol, M.-J., Nolen, W.A., David, A.S., & Aleman, A. (2013). Insight in schizophrenia: Involvement of self-reflection networks? Schizophrenia Bulletin, 39(6), 1288-1295. https://doi.org/10.1093/schbul/sbs122

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