Literature DB >> 29339474

Robust prediction of individual creative ability from brain functional connectivity.

Roger E Beaty1, Yoed N Kenett2, Alexander P Christensen3, Monica D Rosenberg4, Mathias Benedek5, Qunlin Chen6, Andreas Fink5, Jiang Qiu6, Thomas R Kwapil7, Michael J Kane3, Paul J Silvia3.   

Abstract

People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems-intrinsic functional networks that tend to work in opposition-suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

Entities:  

Keywords:  connectome; creativity; divergent thinking; fMRI

Mesh:

Year:  2018        PMID: 29339474      PMCID: PMC5798342          DOI: 10.1073/pnas.1713532115

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  31 in total

1.  Creative constraints: Brain activity and network dynamics underlying semantic interference during idea production.

Authors:  Roger E Beaty; Alexander P Christensen; Mathias Benedek; Paul J Silvia; Daniel L Schacter
Journal:  Neuroimage       Date:  2017-01-08       Impact factor: 6.556

Review 2.  A matched filter hypothesis for cognitive control.

Authors:  Evangelia G Chrysikou; Matthew J Weber; Sharon L Thompson-Schill
Journal:  Neuropsychologia       Date:  2013-11-05       Impact factor: 3.139

3.  Using connectome-based predictive modeling to predict individual behavior from brain connectivity.

Authors:  Xilin Shen; Emily S Finn; Dustin Scheinost; Monica D Rosenberg; Marvin M Chun; Xenophon Papademetris; R Todd Constable
Journal:  Nat Protoc       Date:  2017-02-09       Impact factor: 13.491

Review 4.  The role of default network deactivation in cognition and disease.

Authors:  Alan Anticevic; Michael W Cole; John D Murray; Philip R Corlett; Xiao-Jing Wang; John H Krystal
Journal:  Trends Cogn Sci       Date:  2012-11-08       Impact factor: 20.229

Review 5.  Dynamic network interactions supporting internally-oriented cognition.

Authors:  Darya L Zabelina; Jessica R Andrews-Hanna
Journal:  Curr Opin Neurobiol       Date:  2016-07-13       Impact factor: 6.627

Review 6.  Characterizing Attention with Predictive Network Models.

Authors:  M D Rosenberg; E S Finn; D Scheinost; R T Constable; M M Chun
Journal:  Trends Cogn Sci       Date:  2017-02-23       Impact factor: 20.229

7.  Training of verbal creativity modulates brain activity in regions associated with language- and memory-related demands.

Authors:  Andreas Fink; Mathias Benedek; Karl Koschutnig; Eva Pirker; Elisabeth Berger; Sabrina Meister; Aljoscha C Neubauer; Ilona Papousek; Elisabeth M Weiss
Journal:  Hum Brain Mapp       Date:  2015-07-14       Impact factor: 5.038

8.  The promises and perils of the neuroscience of creativity.

Authors:  Anna Abraham
Journal:  Front Hum Neurosci       Date:  2013-06-05       Impact factor: 3.169

9.  A neuromarker of sustained attention from whole-brain functional connectivity.

Authors:  Monica D Rosenberg; Emily S Finn; Dustin Scheinost; Xenophon Papademetris; Xilin Shen; R Todd Constable; Marvin M Chun
Journal:  Nat Neurosci       Date:  2015-11-23       Impact factor: 24.884

10.  Functional brain networks related to individual differences in human intelligence at rest.

Authors:  Luke J Hearne; Jason B Mattingley; Luca Cocchi
Journal:  Sci Rep       Date:  2016-08-26       Impact factor: 4.379

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  114 in total

1.  A comprehensive approach to study the resting-state brain network related to creative potential.

Authors:  Claire Deshayes; Véronique Paban; Marie-Hélène Ferrer; Béatrice Alescio-Lautier; Caroline Chambon
Journal:  Brain Struct Funct       Date:  2021-05-07       Impact factor: 3.270

2.  Intrinsic Connectivity Patterns of Task-Defined Brain Networks Allow Individual Prediction of Cognitive Symptom Dimension of Schizophrenia and Are Linked to Molecular Architecture.

Authors:  Ji Chen; Veronika I Müller; Juergen Dukart; Felix Hoffstaedter; Justin T Baker; Avram J Holmes; Deniz Vatansever; Thomas Nickl-Jockschat; Xiaojin Liu; Birgit Derntl; Lydia Kogler; Renaud Jardri; Oliver Gruber; André Aleman; Iris E Sommer; Simon B Eickhoff; Kaustubh R Patil
Journal:  Biol Psychiatry       Date:  2020-10-03       Impact factor: 13.382

3.  Toward Robust Anxiety Biomarkers: A Machine Learning Approach in a Large-Scale Sample.

Authors:  Emily A Boeke; Avram J Holmes; Elizabeth A Phelps
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2019-06-21

4.  Individualized prediction of trait narcissism from whole-brain resting-state functional connectivity.

Authors:  Chunliang Feng; Jie Yuan; Haiyang Geng; Ruolei Gu; Hui Zhou; Xia Wu; Yuejia Luo
Journal:  Hum Brain Mapp       Date:  2018-05-10       Impact factor: 5.038

5.  Multivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors.

Authors:  Kwangsun Yoo; Monica D Rosenberg; Stephanie Noble; Dustin Scheinost; R Todd Constable; Marvin M Chun
Journal:  Neuroimage       Date:  2019-04-27       Impact factor: 6.556

6.  Connectome-based model predicts individual differences in propensity to trust.

Authors:  Xiaping Lu; Ting Li; Zhichao Xia; Ruida Zhu; Li Wang; Yue-Jia Luo; Chunliang Feng; Frank Krueger
Journal:  Hum Brain Mapp       Date:  2019-01-11       Impact factor: 5.038

7.  Similarity in functional brain connectivity at rest predicts interpersonal closeness in the social network of an entire village.

Authors:  Ryan Hyon; Yoosik Youm; Junsol Kim; Jeanyung Chey; Seyul Kwak; Carolyn Parkinson
Journal:  Proc Natl Acad Sci U S A       Date:  2020-12-14       Impact factor: 11.205

8.  An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation.

Authors:  Adam Safron
Journal:  Front Artif Intell       Date:  2020-06-09

9.  Individual differences in aesthetic engagement are reflected in resting-state fMRI connectivity: Implications for stress resilience.

Authors:  Paula G Williams; Kimberley T Johnson; Brian J Curtis; Jace B King; Jeffrey S Anderson
Journal:  Neuroimage       Date:  2018-06-17       Impact factor: 6.556

10.  Editorial: Functional Connectivity: Dissecting the Relationship Between the Brain and "Pain Centralization" in Rheumatoid Arthritis.

Authors:  Yvonne C Lee; Vitaly Napadow; Marco L Loggia
Journal:  Arthritis Rheumatol       Date:  2018-05-15       Impact factor: 10.995

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