A multilayer network approach for studying creative ideation from EEG

Rohit Bose, Kumar Ashutosh, Junhua Li, Andrei Dragomir, Nitish Thakor, Anastasios Bezerianos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The neural mechanisms underlying creative ideation are not clearly understood owing to the widespread cognitive processes involved in the brain. Current research states alpha band’s relation to creative ideation, as the most consistent finding. However, creative ideation appear at the signal level within multiple frequency bands and cross-frequency coupling phenomenon. To address this issue, we analyzed both within band and cross-frequency functional connectivity in a single framework using multilayer network. To further investigate the time evolution of creative thinking, we performed the analysis for three phases (early, middle and later). The experimental design used in this study consists of divergent thinking as an indicator of creativity where the subjects were instructed to give alternative uses of an object. As a control task, convergent thinking was used where the subjects were asked to list typical characteristics of an object. We evaluated global and nodal metrics (i.e., clustering coefficient, local efficiency, and nodal degree) for the three phases. Each metric was calculated separately for within band (intra layer) and cross-frequency (inter layer) connectivity. Paired t-test results showed significant difference in the later phase for both inter layer clustering coefficient and inter layer local efficiency. In nodal metrics, significant difference was observed in the later phase for intra layer degree and in all the phases for inter layer degree. The results from this study demonstrate that both the cross-frequency coupling and within-band connectivity can reveal more information regarding the neural processes related to creative ideation.

Original languageEnglish (US)
Title of host publicationBrain Informatics - International Conference, BI 2018, Proceedings
EditorsYang Yang, Vicky Yamamoto, Shouyi Wang, Erick Jones, Jianzhong Su, Tom Mitchell, Leon Iasemidis
PublisherSpringer Verlag
Pages294-303
Number of pages10
ISBN (Print)9783030055868
DOIs
StatePublished - 2018
Externally publishedYes
EventInternational Conference on Brain Informatics, BI 2018 - Arlington, United States
Duration: Dec 7 2018Dec 9 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11309 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Conference on Brain Informatics, BI 2018
CountryUnited States
CityArlington
Period12/7/1812/9/18

Keywords

  • Convergent and divergent thinking
  • Creativity
  • EEG
  • Multilayer network
  • Supra-adjacency matrix

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Bose, R., Ashutosh, K., Li, J., Dragomir, A., Thakor, N., & Bezerianos, A. (2018). A multilayer network approach for studying creative ideation from EEG. In Y. Yang, V. Yamamoto, S. Wang, E. Jones, J. Su, T. Mitchell, & L. Iasemidis (Eds.), Brain Informatics - International Conference, BI 2018, Proceedings (pp. 294-303). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11309 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-030-05587-5_28