Neural Characterization of the Improvisational Creative Process

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dc.contributor.advisorContreras-Vidal, Jose L.
dc.contributor.committeeMemberPrasad, Saurabh
dc.contributor.committeeMemberMayerich, David
dc.contributor.committeeMemberRivera Garza, Cristina
dc.contributor.committeeMemberKalantari, Saleh
dc.creatorCruz Garza, Jesus Gabriel
dc.creator.orcid0000-0002-8440-6416
dc.date.accessioned2020-01-03T06:00:09Z
dc.date.createdDecember 2019
dc.date.issued2019-12
dc.date.submittedDecember 2019
dc.date.updated2020-01-03T06:00:10Z
dc.description.abstractMobile Brain-Body Imaging (MoBI) enables the study of the human creative process in freely-behaving participants in natural settings. Past studies on human creativity rely on neuroimaging technology that requires participants to remain in a confined, motionless space. This limits the study design to static, queued actions that oversimplify creative actions. Other studies rely on psychometric tests that compare scores to brain activity at rest, which cannot claim a specific bearing on the creative process. The main goal of this dissertation is develop novel experimental and analytical approaches to assay the human creative process in natural settings. To accomplish this goal, developed two experiments: 1) We examined the creative process in professional visual artists working collaboratively, in an adaptation of the Exquisite Corpse surrealist game; 2) we examined neural data of college students as they created compositions before and after a 16-week creative writing workshop. These experiments aim to identify and characterize neural features associated with the highly dynamic creative process. We used frequency-domain, time-domain, and functional connectivity features from scalp Electroencephalography (EEG). Both classical machine learning and deep learning approaches were deployed to identify the most relevant features. Two major findings were obtained. First, the functional connectivity analysis identified patterns between right parietal with left central-frontal scalp areas during creative execution, which were enhanced with experience. Second, the machine learning methods successfully classified neural EEG data in both studies. In the Visual Arts experiment, the classification accuracy reached 53.5 ± 2.4% for 5-classes: two rest conditions, planning, mark making, and writing. In Creative Writing, the classification accuracy reached 79.3 ± 3.1% for 4-classes: two rest conditions, transcription, and creative writing. Overall, these findings suggest that creative execution tasks can be characterized by a state of long-range cortico-cortical communication between multisensory integration in parietal brain regions and high-order execution and planning areas in frontal regions of the brain. This dissertation provides evidence for common information flow patterns in professional visual artists and student writers matching increased flexibility for creative evocation. In conclusion, this approach provided a better understanding of the human creative process through neural feature characterizations in real world settings.
dc.description.departmentElectrical and Computer Engineering, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.citationPortions of this document appear in: Cruz-Garza, Jesus G., Girija Chatufale, Dario Robleto, and Jose L. Contreras-Vidal. "Your Brain on Art: A New Paradigm to Study Artistic Creativity Based on the ‘Exquisite Corpse’Using Mobile Brain-Body Imaging." In Brain Art, pp. 283-308. Springer, Cham, 2019.
dc.identifier.urihttps://hdl.handle.net/10657/5654
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectCreativity
dc.subjectEEG
dc.subjectMoBI
dc.subjectCreative process
dc.subjectNeurosciences
dc.subjectNeural interfaces
dc.subjectBrain computer interface (BCI)
dc.subjectBCI
dc.subjectNeuroengineering
dc.subjectCreative writing
dc.subjectVisual arts
dc.titleNeural Characterization of the Improvisational Creative Process
dc.type.dcmiText
dc.type.genreThesis
local.embargo.lift2021-12-01
local.embargo.terms2021-12-01
thesis.degree.collegeCullen College of Engineering
thesis.degree.departmentElectrical and Computer Engineering, Department of
thesis.degree.disciplineElectrical Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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