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From learning to creativity: Identifying the behavioural and neural correlates of learning to predict human judgements of musical creativity

Zioga, Ioanna; Harrison, Peter M. C.; Pearce, Marcus T.; Bhattacharya, Joydeep and Luft, C B D. 2019. From learning to creativity: Identifying the behavioural and neural correlates of learning to predict human judgements of musical creativity. Cognitive Neurodynamics, ISSN 1871-4080 [Article] (In Press)

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Abstract or Description

Human creativity is strongly linked to acquired knowledge. However, to date learning a new musical style and subsequent creativity have largely been studied in isolation. We introduced a novel experimental paradigm combining behavioural, electrophysiological, and computational methods, to examine the neural correlates of unfamiliar music learning, and to investigate how neural and computational measures can predict human creativity. We investigated music learning by training non-musicians (N = 40) on an artificial music grammar. Participants’ knowledge of the grammar was tested before and after three training sessions by assessing explicit recognition of the notes of the grammar, while additionally recording EEG. After each training session, participants created their own musical compositions, which were later evaluated by human experts. A computational model of auditory expectation was used to quantify the statistical properties of both the grammar and the compositions. Results showed that participants successfully learned the grammar. This was also reflected in the N100, P200, and P3a components, which were higher in response to incorrect than correct notes. Delta band power in response to grammatical notes during first exposure to the grammar positively correlated with learning, suggesting a potential encoding neural mechanism. On the other hand, better learning was associated with lower alpha and higher beta band power after training, potentially reflecting neural mechanisms of retrieval. Importantly, learning was a significant predictor of creativity, as judged by experts. There was also an inverted U-shaped relationship between percentage of correct intervals and creativity, as compositions with an intermediate proportion of correct intervals were associated with the highest creativity. Finally, the P200 in response to incorrect notes was predictive of creativity, suggesting a link between the neural correlates of learning, and creativity. Overall, our findings shed light on the neural mechanisms of learning an unfamiliar music grammar, as well as offering contributions to the associations between learning measures and human evaluation of creativity.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.1016/j.neuroimage.2019.116311

Keywords:

Creativity, Artificial music grammar, EEG, Statistical learning, Training, IDyOM

Departments, Centres and Research Units:

Psychology

Dates:

DateEvent
22 October 2019Accepted
25 October 2019Published Online

Item ID:

27299

Date Deposited:

25 Oct 2019 12:11

Last Modified:

27 Nov 2019 09:02

Peer Reviewed:

Yes, this version has been peer-reviewed.

URI:

http://research.gold.ac.uk/id/eprint/27299

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