Abstract
Introduction. It is known that the frontoparietal system is involved in both intellectual and creative functions, but no consensus has been achieved on the issue of how these functions and the associated activity of the frontoparietal parts of the brain interplay and reflect each other. The purpose of this study was to identify patterns of neuronal oscillations, which could be predictors of verbal or figurative components of intelligence and/or imaginative creativity.
Methods. The activity of the frontoparietal cortex was analyzed using multichannel electroencephalography (EEG) technique. The study enrolled 37 university students. The EEG baseline power values of 6 frequency bands, from delta to beta2 were analyzed in comparison with the verbal (IQv) and figurative (IQf) components of intelligence assessed using the Amthauer technique and with the imaginative originality when performing the Torrance subtest “Incomplete figures task” (IFT).
Results. When comparing groups with high or low IQv or IFT rates, the following general effects were established: asymmetry in the activity of anterior and posterior-frontal regions in the beta1 frequency band and higher power values of the delta rhythm in frontal regions of the cortex in individuals with higher IQv rate, and in the central-parietal cortex in individuals with higher imaginative originality rates, respectively, along with higher values of the alpha1 rhythm in the central and the alpha2 rhythm in the frontal areas of the cortex. Regression models calculated for IFT and IQv were similar, delta rhythm power values in the frontal leads of the left hemisphere being the main predictor of intellectual and creative abilities.
Discussion. The similarity of the regression models for IFT and IQv with more pronounced differences in frequency and regional representation of the EEG correlates of the imaginative originality should be considered as evidence that intelligence (and the structures associated with it) is a necessary but not sufficient condition for creativity. The detected frequency-spatial relationship between the IFT and IQv may arise from the similar organization of executive control over the imaginative task performance.
References
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Razumnikova, O. M. (2009a). Features of the selection of information in creative thinking. Psychology. Journal of the Higher School of Economics, 6(3), 134–161. doi: http://dx.doi.org/10.17323/1813-8918-2009-3-134-161 (in Russ.).
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Razumnikova, O. M. (2007). The functional significance of α2 frequency range for convergent and divergent verbal thinking. Human Physiology, 33(2), 146–156. doi: http://dx.doi.org/10.1134/S036211970702003X
Shi, L., Sun, J., Xia, Y., Ren, Z., Chen, Q., Wei, D., … Qiu, J. (2018). Large-scale brain network connectivity underlying creativity in resting-state and task fMRI: Cooperation between default network and frontal-parietal network. Biological Psychology, 135, 102–111. doi: http://dx.doi.org/10.1016/j.biopsycho.2018.03.005
Solomon, E. A., Kragel, J. E., Sperling, M. R., Sharan, A., Worrell, G., Kucewicz, M., … Kahana, M. J. (2017). Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition. Nature Communications, 8(1704). doi: http://dx.doi.org/10.1038/s41467-017-01763-2
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Takeshi, O., Aihara, T., Shimokawa, T., & Yamashita, O. (2018). Large-scale brain network associated with creative insight: combined voxel-based morphometry and resting-state functional connectivity analyses. Scientific Reports, 8(6477). doi: http://dx.doi.org/10.1038/s41598-018-24981-0
Aziz-Zadeh, L., Liew, S. L., & Dandekar, F. (2013). Exploring the neural correlates of visual creativity. Social Cognitive and Affective Neuroscience, 8, 475–480. doi: http://dx.doi.org/10.1093/scan/nss021
Beaty, R. E., Benedek, M., Wilkins, R. W., & Jauk, E. (2014). Creativity and the default network: A functional connectivity analysis of the creative brain at rest. Neuropsychologia, 64, 92–98. doi: http://dx.doi.org/10.1016/j.neuropsychologia.2014.09.019
Beaty, R. E., Seli, P., & Schacter, D. L. (2019). Network Neuroscience of Creative Cognition: Mapping Cognitive Mechanisms and Individual Differences in the Creative Brain. Current Opinion in Behavioral Sciences, 27, 22–30. doi: http://dx.doi.org/10.1016/j.cobeha.2018.08.013
Benedek, M., Bergner, S., Könen, T., Fink, A., & Neubauer, A. C. (2011). EEG alpha synchronization is related to top-down processing in convergent and divergent thinking. Neuropsychologia, 49, 3505–3511. doi: http://dx.doi.org/10.1016/j.neuropsychologia.2011.09.004
Benedek, M., Jauk, E., Sommer, M., Arendasy, M., & Neubauer, A. C. (2014). Intelligence, creativity, and cognitive control: The common and differential involvement of executive functions in intelligence and creativity. Intelligence, 46, 73–83. doi: http://dx.doi.org/10.1016/j.intell.2014.05.007
Bhattacharya, J., & Petsche, H. (2005). Drawing on mind's canvas: Differences in cortical integration patterns between artists and non-artists. Human Brain Mapping, 26(1), 1–14. doi: http://dx.doi.org/10.1002/hbm.20104
Boot, N., Baas, M., Mühlfeld, E., de Dreu, C. K. W, & van Gaal, S. (2017). Widespread neural oscillations in the delta band dissociate rule convergence from rule divergence during creative idea generation. Neuropsychologia, 104, 8–17. doi: http://dx.doi.org/10.1016/j.neuropsychologia.2017.07.033
Christensen, A. P., Benedek, M., Silvia, P., & Beaty, R. (2019). Executive and default network connectivity reflects conceptual interference during creative imagery generation. PsyArXiv Preprints. doi: http://dx.doi.org/10.31234/osf.io/n438d
Dikaya, L. A., & Dikii, I. S. (2015). Creative brain: a monograph. Rostov-on-Don: Publishing House of SFU. (in Russ.).
Erickson, B., Truelove-Hill, M., Oh, Y., Anderson, J., Zhang, F. Z., & Kounios, J. (2018). Resting-state brain oscillations predict trait-like cognitive styles. Neuropsychologia, 120, 1–8. doi: http://dx.doi.org/10.1016/j.neuropsychologia.2018.09.014
Fink, A., & Benedek, M. (2014). EEG alpha power and creative ideation. Neuroscience and Biobehavioral Reviews, 44, 111–123. doi: http://dx.doi.org/10.1016/j.neubiorev.2012.12.002
Foster, P. S., Williamson, J. B., & Harrison, D. W. (2005). The ruff figural fluency test: heightened right frontal lobe delta activity as a function of performance. Archives of Clinical Neuropsychology, 20, 427–434. doi: http://dx.doi.org/10.1016/j.acn.2004.09.010
Gulbinaite, R., van Rijn, H., & Cohen, M. X. (2014). Fronto-parietal network oscillations reveal relationship between working memory capacity and cognitive control. Frontiers in Human Neuroscience, 8(761). doi: http://dx.doi.org/10.3389/fnhum.2014.00761
Hahm, J., Kim, K. K., Park, S. H., & Lee, H. M. (2017). Brain areas subserving Torrance tests of creative thinking: an functional magnetic resonance imaging study. Dementia and Neurocognitive Disorders, 16(2), 48–53 doi: http://dx.doi.org/10.12779/dnd.2017.16.2.48
Hearne, L. J., Mattingley, J. B., & Cocchi, L. (2016). Functional brain networks related to individual differences in human intelligence at rest. Scientific Reports, 6(32328). doi: http://dx.doi.org/10.1038/srep32328
Heinonen, J., Numminen, J., Hlushchuk, Y., Antell, H., Taatila, V., & Suomala, J. (2016). Default Mode and Executive Networks Areas: Association with the Serial Order in Divergent Thinking. PLoS ONE, 11(9), e0162234. doi: http://dx.doi.org/10.1371/journal.pone.0162234
Herrmann, C. S., Strüber, D., Helfrich, R. F., & Engel, A. K. (2016). EEG oscillations: From correlation to causality. International Journal of Psychophysiology, 103, 12–21. doi: http://dx.doi.org/10.1016/j.ijpsycho.2015.02.003
Hirshorn, E. A., & Thompson-Schill, S. L. (2006). Role of the left inferior frontal gyrus in covert word retrieval: neural correlates of switching during verbal fluency. Neuropsychologia, 44(12), 2547–2557. doi: http://dx.doi.org/10.1016/j.neuropsychologia.2006.03.035
Jauk, E., Benedek, M., Dunst, B., & Neubauer, A. C. (2013). The relationship between intelligence and creativity: New support for the threshold hypothesis by means of empirical breakpoint detection. Intelligence, 41, 212–221. doi: http://dx.doi.org/10.1016/j.intell.2013.03.003
Jung, R. E., & Haier, R. J. (2007). The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence. Behavioral and Brain Sciences, 30(2), 135–154. doi: http://dx.doi.org/10.1017/S0140525X07001185
Jung, R. E., Mead, B. S., Carrasco, J., & Flores, R. A. (2013). The structure of creative cognition in the human brain. Frontiers in Human Neuroscience, 7, 330. doi: http://dx.doi.org/10.3389/fnhum.2013.00330
Karwowski, M., Dul, J., Gralewski, J., Jauk, E., Jankowska, D. M., Gajda, A., … Benedek, M. (2016). Is creativity without intelligence possible? A Necessary Condition Analysis. Intelligence, 57, 105–117. doi: http://dx.doi.org/10.1016/j.intell.2016.04.006
Kenett, Y. N., Medaglia, J. D., Beaty, R. E., Chen, Q., Betzel, R. F., Thompson-Schill, S. L., & Qiu, J. (2018). Driving the brain towards creativity and intelligence: A network control theory analysis. Neuropsychologia, 118(PtA), 79–90. doi: http://dx.doi.org/10.1016/j.neuropsychologia.2018.01.001
Knyazev, G. G. (2007). Motivation, emotion, and their inhibitory control mirrored in brain oscillations. Neuroscience and Biobehavioral Reviews, 31(3), 377–395. doi: http://dx.doi.org/10.1016/j.neubiorev.2006.10.004
Knyazev, G. G. (2012). EEG delta oscillations as a correlate of basic homeostatic and motivational processes. Neuroscience & Biobehavioral Reviews, 36(1), 677–695. doi: http://dx.doi.org/10.1016/j.neubiorev.2011.10.002
Kounios, J., Fleck, J. I., Green, D. L., Payne, L., Stevenson, J. L., Bowden, E. M., & Jung-Beeman, M. (2008). The origins of insight in resting-state brain activity. Neuropsychologia, 46, 281–291. doi: http://dx.doi.org/10.1016/j.neuropsychologia.2007.07.013
Lee, K. H., Choi, Y. Y., Gray, J. R., Cho, S. H., Chae, J. H., Lee, S., & Kim, K. (2006). Neural correlates of superior intelligence: Stronger recruitment of posterior parietal cortex. NeuroImage, 29, 578–586. doi: http://dx.doi.org/10.1016/j.neuroimage.2005.07.036
Li, W., Yang, J., Zhang, Q., Li, G., & Qiuc, J. (2016). The Association between Resting Functional Connectivity and Visual Creativity. Scientific Reports, 6(25395). doi: http://dx.doi.org/10.1038/srep25395
Lustenberger, C., Boyle, M. R., Foulser, A. A., Mellin, J. M., & Fröhlich, F. (2015). Functional role of frontal alpha oscillations in creativity. Cortex, 67, 74–82. doi: http://dx.doi.org/10.1016/j.cortex.2015.03.012
Nagornova, Zh. V. (2007). Dynamics of EEG power when performing tasks on non-verbal (figurative) creativity. Human Physiology, 33(3), 26–34. (in Russ.).
Nusbaum, E. C., & Silvia, P. J. (2011). Are intelligence and creativity really so different? Fluid intelligence, executive processes, and strategy use in divergent thinking. Intelligence, 39, 36–45.
Pamplona, G. S. P., Neto, G. S. S., Rosset, S. R. E., Rogers, B. P., & Salmon, C. E. G. (2015). Analyzing the association between functional connectivity of the brain and intellectual performance. Frontiers in Human Neuroscience, 9, 1–11. doi: http://dx.doi.org/10.3389/fnhum.2015.00061
Pidgeon, L. M., Grealy, M., Duffy, A. H., Hay, L., McTeague, C., Vuletic, T., … Gilbert, S. J. (2016). Functional neuroimaging of visual creativity: a systematic review and meta-analysis. Brain and Behavior, 6, e00540. doi: http://dx.doi.org/10.1002/brb3.540
Preckel, F., Holling, H., & Wiese, M. (2006). Relationship of intelligence and creativity in gifted and non-gifted students: An investigation of threshold theory. Personality and Individual Differences, 40, 159–170. doi: http://dx.doi.org/10.1016/j.paid.2005.06.022
Pulvermuller, F., Birbaumer, N., Lutzenverger, W., & Mohr, B. (1997). High-frequency brain activity: Its possible role in attention, perception and language processing. Progress in Neurobiology, 52, 427–445.
Razumnikova, O. M. (2002). Methods for determining creativity. Novosibirsk: NSTU Publishing House. (in Russ.).
Razumnikova, O. M. (2009a). Features of the selection of information in creative thinking. Psychology. Journal of the Higher School of Economics, 6(3), 134–161. doi: http://dx.doi.org/10.17323/1813-8918-2009-3-134-161 (in Russ.).
Razumnikova, O. M. (2009b). The relationship of the frequency-spatial parameters of the background EEG with the level of intelligence and creativity. Journal of Higher Nervous Activity, 59(6), 686–695. (in Russ.).
Razumnikova, O. M. (2007). The functional significance of α2 frequency range for convergent and divergent verbal thinking. Human Physiology, 33(2), 146–156. doi: http://dx.doi.org/10.1134/S036211970702003X
Shi, L., Sun, J., Xia, Y., Ren, Z., Chen, Q., Wei, D., … Qiu, J. (2018). Large-scale brain network connectivity underlying creativity in resting-state and task fMRI: Cooperation between default network and frontal-parietal network. Biological Psychology, 135, 102–111. doi: http://dx.doi.org/10.1016/j.biopsycho.2018.03.005
Solomon, E. A., Kragel, J. E., Sperling, M. R., Sharan, A., Worrell, G., Kucewicz, M., … Kahana, M. J. (2017). Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition. Nature Communications, 8(1704). doi: http://dx.doi.org/10.1038/s41467-017-01763-2
Stevens, C. E. J., & Zabelina, D. L. (2019). Creativity comes in waves: An EEG-focused exploration of the creative brain. Current Opinion in Behavioral Sciences, 27, 154–162. doi: http://dx.doi.org/10.31234/osf.io/ke6wq
Takeshi, O., Aihara, T., Shimokawa, T., & Yamashita, O. (2018). Large-scale brain network associated with creative insight: combined voxel-based morphometry and resting-state functional connectivity analyses. Scientific Reports, 8(6477). doi: http://dx.doi.org/10.1038/s41598-018-24981-0