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Frontoparietal Patterns of Delta and Beta EEG Oscillations as Markers of Creativity Strategies

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Abstract—

Recently, there has been considerable interest in the mechanism of cooperation between the frontoparietal system and the default system, since their “pre-tuning” at rest and the subsequent functional interaction dynamics is associated with individual variety of strategies for task performance upon creativity testing. To study the EEG correlates of these strategies, regional features of resting state ∆- and β-oscillations were analyzed and compared with the results from preliminary creativity and intelligence testing in 37 university students (18 ± 1.1 years; 27 females and 10 males). The response originality indices in the creativity tests were calculated using databases previously designed by the authors for the “Circles,” “Incomplete figures,” and “Unusual use of ordinary objects” subtests and an expert assessment of originality of the sentences composed of words belonging to different semantic categories. The intelligence verbal and figurative components were assessed according to the Amthauer intelligence structure subtests. Using cluster analysis of the listed creativity and intelligence indices, two groups of study participants were identified. One of the groups (GRCIQ) was characterized by a combination of higher values of intelligence and originality of responses in the tasks that required the rejection of stereotypical ideas upon limited search time, and the other group (GRC), characterized by relatively lower intelligence, but high originality of solving the problem upon the creativity testing with a variety of stimuli and without time limits. These two groups differed in regional organization of the ∆- and β2-rhythm power and in the rhythm correlation patterns. In particular, GRCIQ is characterized by generalized high-frequency β-activity and its correlation with low-frequency biopotentials in the frontal cortex, while GRC is characterized by cortical mosaic of the β2-activity with its diffusely distributed correlations with the ∆-rhythm with the exception of the anterior frontal areas. The discovered effects can be considered as a pre-tuning to the “intelligent” search strategy for an original solution in the conditions of resistance to fixation on a stereotyped idea in GRCIQ or to solutions based on spontaneous search for distant associations in GRC.

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REFERENCES

  1. Razumnikova, O.M., The relationship between frequency-spatial parameters of the baseline EEG and levels of intelligence and creativity, Zh. Vyssh. Nervn. Deiat. im I. P. Pavlova, 2009, vol. 59, no. 6, p. 686.

    Google Scholar 

  2. Razumnikova, O.M., Neurophysiological mechanisms for solving experimental creative problems: insight or/and critical analysis?, Psikhol.: Zh. Vyssh. Shk. Ekon., 2021, vol. 18, no 3, p. 623.

  3. Beaty, R.E., Chen, Q., Christensen, A.P., et al., Brain networks of the imaginative mind: dynamic functional connectivity of default and cognitive control networks relates to openness to experience, Hum. Brain Mapp., 2018, vol. 39, no. 2, p. 811.

    Article  PubMed  Google Scholar 

  4. Beaty, R.E., Benedek, M., Silvia, P.J., and Schacter, D.L., Creative cognition and brain network dynamics, Trends Cognit. Sci., 2016, vol. 20, no. 2, p. 87.

    Article  Google Scholar 

  5. Frith, E., Elbich, D.B., Christensen, A.P., et al., Intelligence and creativity share a common cognitive and neural basis, J. Exp. Psychol. Gen., 2020, vol. 150, no. 4, p. 609.

    Article  PubMed  Google Scholar 

  6. Beaty, R.E., Benedek, M., Wilkins, R.W., et al., Creativity and the default network: a functional connectivity analysis of the creative brain at rest, Neuropsychologia, 2014, vol. 64, p. 92.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Beaty, R.E., Seli, P., and Schacter, D.L., Network neuroscience of creative cognition: mapping cognitive mechanisms and individual differences in the creative brain, Curr. Opin. Behav. Sci., 2019, vol. 27, p. 22.

    Article  PubMed  Google Scholar 

  8. Boccia, M., Piccardi, L., Palermo, L., et al., Where do bright ideas occur in our brain? Meta-analytic evidence from neuroimaging studies of domain-specific creativity, Front. Psychol., 2015, vol. 6, p. 1195.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Khalil, R., Godde, B., and Karim, A.A., The link between creativity, cognition, and creative drives and underlying neural mechanisms, Front. Neural Circuits, 2019, vol. 13, p. 18.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Lin, H. and Vartanian, O.A., Neuroeconomic framework for creative cognition, Perspect. Psychol. Sci., 2018, vol. 13, no. 6, p. 655.

    Article  PubMed  Google Scholar 

  11. Ogawa, T., Aihara, T., Shimokawa, T., and Yamashita, O., Large-scale brain network associated with creative insight: combined voxel-based morphometry and resting-state functional connectivity analyses, Sci. Rep., 2018, vol. 8, no. 1, p. 6477.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Colom, R., Karama, S., Jung, R.E., and Haier, R.J., Human intelligence and brain networks, Dialogues Clin. Neurosci., 2010, vol. 12, no. 4, p. 489.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Dubois, J., Galdi, P., Paul, L.K., and Adolphs, R., A distributed brain network predicts general intelligence from resting-state human neuroimaging data, Philos. Trans. R. Soc. Lond., B, 2018, vol. 373, no. 1756, p. 20170284.

  14. Langer, N., Pedroni, A., Gianotti, L.R., et al., Functional brain network efficiency predicts intelligence, Hum. Brain Mapp., 2012, vol. 33, no. 6, p. 1393.

    Article  PubMed  Google Scholar 

  15. Tadayon, E., Pascual-Leone, A., and Santarnecchi, E., Differential contribution of cortical thickness, surface area, and gyrification to fluid and crystallized intelligence, Cereb. Cortex, 2020, vol. 30, no. 1, p. 215.

    Article  PubMed  Google Scholar 

  16. Kenett, Y.N., Medaglia, J.D., Beaty, R.E., et al., Driving the brain towards creativity and intelligence: a network control theory analysis, Neuropsychologia, 2018, vol. 118, part A, p. 79.

  17. Zhu, F., Zhang, Q., and Qiu, J., Relating inter-individual differences in verbal creative thinking to cerebral structures: an optimal voxel-based morphometry study, PLoS One, 2013, vol. 8, no. 11, e79272.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Heinonen, J., Numminen, J., Hlushchuk, Y., et al., Default mode and executive networks areas: association with the serial order in divergent thinking, PLoS One, 2016, vol. 11, no. 9, e0162234.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Feng, Q., He, L., Yang, W., et al., Verbal creativity is correlated with the dynamic reconfiguration of brain networks in the resting state, Front. Psychol., 2019, vol. 10, p. 894.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Hahm, J., Kim, K.K., and Park, S.H., Cortical correlates of creative thinking assessed by the figural Torrance test of creative thinking, Neuroreport, 2019, vol. 30, no. 18, p. 1289.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Mihov, K.M., Denzler, M., and Förster, J., Hemispheric specialization and creative thinking: a meta-analytic review of lateralization of creativity, Brain Co-gnit., 2010, vol. 72, no. 3, p. 442.

    Article  Google Scholar 

  22. Aziz-Zadeh, L., Liew, S.L., and Dandekar, F., Exploring the neural correlates of visual creativity, Soc. Cognit. Affect. Neurosci., 2013, vol. 8, no. 4, p. 475.

    Article  Google Scholar 

  23. Li, W., Yang, J., Zhang, Q., et al., The association between resting functional connectivity and visual creativity, Sci. Rep., 2016, vol. 6, p. 25395.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Stevens, C.E.J. and Zabelina, D.L., Creativity comes in waves: an EEG-focused exploration of the creative brain, Curr. Opin. Behav. Sci., 2019, vol. 27, p. 154.

    Article  Google Scholar 

  25. Takeuchi, H., Taki, Y., Hashizume, H., et al., The association between resting functional connectivity and creativity, Cereb. Cortex, 2012, vol. 22, no. 12, p. 2921.

    Article  PubMed  Google Scholar 

  26. Benedek, M., Bergner, S., Könen, T., et al., EEG alpha synchronization is related to top-down processing in convergent and divergent thinking, Neuropsychologia, 2011, vol. 49, no. 12, p. 3505.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Benedek, M., Jauk, E., Sommer, M., et al., Intelligence, creativity, and cognitive control: the common and differential involvement of executive functions in intelligence and creativity, Intelligence, 2014, vol. 46, p. 73.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Lustenberger, C., Boyle, M.R., Foulser, A.A., et al., Functional role of frontal alpha oscillations in creativity, Cortex, 2015, vol. 67, p. 74.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Erickson, B., Truelove-Hill, M., Oh, Y., Anderson, J., Zhang, F. Z., and Kounios, J., Resting-state brain oscillations predict trait-like cognitive styles, Neuropsychologia, 2018, vol. 120, p. 1.

    Article  PubMed  Google Scholar 

  30. Kounios, J., Fleck, J.I., Green, D.L., et al., The origins of insight in resting-state brain activity, Neuropsychologia, 2008, vol. 46, no. 1, p. 281.

    Article  PubMed  Google Scholar 

  31. Briley, P.M., Liddle, E.B., Groom, M.J., et al., Development of human electrophysiological brain networks, J. Neurophysiol., 2018, vol. 120, no. 6, p. 3122.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Razumnikova, O.M. and Krivonogova, K.D., Electroencephalographic correlates of the activity of the frontoparietal system as predictors of verbal intelligence and non-verbal creativity, Ross. Psikhol. Zh., 2019, vol. 16, no. 2/1, p. 45. https://doi.org/10.21702/rpj.2019.2.1.4

  33. Solomon, E.A., Kragel, J.E., Sperling, M.R., et al., Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition, Nat. Commun., 2017, vol. 8, no. 1, p. 1704.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Hacker, C.D., Snyder, A.Z., Pahwa, M., et al., Frequency-specific electrophysiologic correlates of resting state fMRI networks, NeuroImage, 2017, vol. 149, p. 446.

    Article  PubMed  Google Scholar 

  35. Razumnikova, O.M., Sposoby opredeleniya kreativnosti (Methods for Determining Creativity), Novosibirsk: Novosibirsk. Gos. Tekh. Univ., 2002.

  36. Harms, M., Reiter-Palmon, R., and Derrick, D.C., The role of information search in creative problem solving, Psychol. Aesthetics Creat. Arts, 2020, vol. 14, no. 3, p. 367.

    Article  Google Scholar 

  37. Harmony, T., The functional significance of delta oscillations in cognitive processing, Front. Integr. Neuros-ci., 2013, vol. 7, p. 83.

    Google Scholar 

  38. Knyazev, G.G., EEG delta oscillations as a correlate of basic homeostatic and motivational processes, Neu-rosci. Biobehav. Rev., 2012, vol. 36, no. 1, p. 677.

  39. Rogala, J., Kublik, E., Krauz, R., and Wróbel, A., Resting-state EEG activity predicts fronto-parietal network reconfiguration and improved attentional performance, Sci. Rep., 2020, vol. 10, no. 1, p. 5064.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Stoll, F.M., Wilson, C.R.E., Faraut, M.C.M., et al., The effects of cognitive control and time on frontal beta oscillations, Cereb. Cortex, 2016, vol. 26, no. 4, p. 1715.

    Article  PubMed  Google Scholar 

  41. Shaw, G.A. and DeMers, S.T., The relationship of imagery to originality, flexibility and fluency in creative thinking, J. Ment. Imagery, 1986, vol. 10, no. 1, p. 65.

    CAS  Google Scholar 

  42. Zabelina, D.L. and Robinson, M., Creativity as flexible cognitive control, Psychol. Aesthetics Creat. Arts, 2010, vol. 4, no. 3, p. 136.

    Article  Google Scholar 

  43. Nijstad, B.A., De Dreu, C.K.W., Rietzschel, E.F., and Baas, M., The dual pathway to creativity model: creative ideation as a function of flexibility and persistence, Eur. Rev. Soc. Psychol., 2010, vol. 21, p. 34.

    Article  Google Scholar 

  44. Benedek, M., Franz, F., Heene, M., and Neubauer, A.C., Differential effects of cognitive inhibition and intelligence on creativity, Pers. Individ. Dif., 2012, vol. 53, no. 4, p. 480.

    Article  PubMed  Google Scholar 

  45. Chen, Q.L., Xu, T., Yang, W.J., et al., Individual differences in verbal creative thinking are reflected in the precuneus, Neuropsychologia, 2015, vol. 75, p. 441.

    Article  PubMed  Google Scholar 

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ACKNOWLEDGMENTS

The author thanks A.A. Yashanina, E.A. Khoroshavtseva, and K.D. Krivonogova, who took part in the recording and primary EEG processing, as well as in the psychometric testing of creativity.

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  1. Novosibirsk State Technical University, Novosibirsk, Russia

    O. M. Razumnikova

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Conflict of interest. The authors declare the absence of obvious and potential conflicts of interest related to the publication of this article.

Statement of compliance with standards of research involving humans as subjects. All studies were carried out in accordance with the principles of biomedical ethics formulated in the Declaration of Helsinki of 1984 and its subsequent updates, and approved by local ethics committee of the Faculty of Humanities, Novosibirsk State Technical University (Novosibirsk). Each participant in the study provided a signed voluntary written informed consent after explaining the potential risks and benefits, as well as the nature of the upcoming study.

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Translated by N. Maleeva

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Razumnikova, O.M. Frontoparietal Patterns of Delta and Beta EEG Oscillations as Markers of Creativity Strategies. Hum Physiol 49, 308–315 (2023). https://doi.org/10.1134/S0362119723700330

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