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NeuroImage 231 (2021) 117836
Contents lists available at ScienceDirect
NeuroImage
journal homepage: www.elsevier.com/locate/neuroimage
Creativity and the brain: An editorial introduction to the special issue on
the neuroscience of creativity
The creative ability of the human brain, among the newest prod-
ucts of 3.8 billion years of evolution on Earth, may be humanity’s most
identity-defining feature in the age of artificial intelligence. Many of
the most complex things humans do are now done —or soon will be
done —far better by computers. Creativity projects to be the greatest
exception. There has never been more widespread recognition that un-
derstanding and fostering human creativity is a priority for scientific
research. The capacity to generate ideas that are both divergent and
useful is widely recognized as valuable for learning and practice in the
arts and sciences, and as a driver of the modern innovation economy.
This value will only increase in the foreseeable future. Because creativ-
ity has such broad and diverse impacts, the neuroscience of creativity
is being pursued by a diverse set of researchers. As is generally true
in the early stages of a field, research endeavors into creativity neu-
roscience have often been undertaken separately by researchers siloed
within sub-disciplines of psychology, education, industry, and clinical
neuroscience. For the neuroscience of creativity to fulfill its considerable
potential, it is important to develop greater mutual awareness and cohe-
sion among researchers, and communication with educators and other
stakeholders, so that priority directions can be identified and pursued.
Meeting this need is a primary objective of the Society for the Neuro-
science of Creativity (SfNC). This special issue (SI) on the neuroscience
of creativity, guest-edited by a group of us who serve on the SfNC Exec-
utive Committee, is aimed at bringing together both expository and new
empirical work from creativity neuroscience labs across the globe. We
hope that this SI can contribute to (1) mapping the diversity of creativ-
ity neuroscience to increase mutual awareness within the field, while
increasing awareness of creativity neuroscience across the broader cog-
nitive neuroscience community; and (2) highlighting promising research
directions toward stronger coalescence around methods and questions
that have potential to catalyze basic understanding of how creativity
occurs in the brain and how to enhance it. In this editorial, we attempt
to summarize the results and theories reported in this SI, situate them
within a larger cognitive neuroscience framework, and provide a modest
list of research priorities for the field.
Overview of special issue
This SI attempts to provide a snapshot of current research in the
neuroscience of creativity, outlining recent advances in the field. Sev-
eral studies included in this SI address novel questions related to pos-
itive and negative influences on creative performance, including the
impacts of stress ( Nair et al. 2020 ) and disease ( Paulin et al. 2020 ;
Gross et al. 2019 ), as well as influences of mindset ( Wang et al. 2019 ),
cognitive reappraisal ( Wu et al. 2019 ), and pharmacological interven-
tion ( Baas et al. 2020 ). The development of the creative brain is ex-
plored ( Saggar et al. 2019 ) as are particular attributes of brain morphol-
ogy and function found in eminent creative achievers ( Chrysikou, et al.
2020 a; Barrett et al. 2020 ). Innovative studies examined team cre-
ativity using fNIRS hyper-scanning ( Mayseless et al., 2019 ; Lu et al.,
2020 ), and how idea generation takes root in semantic, associative and
mnemonic neurocognition ( Paulin et al. 2020 ; Beaty et al. 2020 ). The
neural correlates of musical creativity were investigated along multi-
ple lines ( Zioga et al. 2020 ; Belden et al. 2020 ; Rosen et al. 2020 ;
Bashwiner et al. 2020 ). Other studies demonstrated the effective ap-
plication of methods that have been thus far underutilized in the field,
including neurogenetics ( Si et al. 2020 ), network science ( Kenett et al.,
2020 a; Saggar et al. 2019 ), oculometric signatures ( Salvi et al. 2020 ),
7-Tesla MRI ( Schuler et al., 2019 ), and machine learning ( Stevens and
Zabelina 2020 ). Several studies also revealed novel morphometric
( Sunavsky and Poppenk 2020 ; Wertz et al.,. 2020 a; Chrysikou, et al.
2020 b; Vartanian et al. 2020 ), intrinsic ( Schuler et al. 2019 ;
Marron et al. 2020 ), task-evoked ( Chen et al. 2019 ; Wang et al. 2019 ;
Becker et al., 2020 ; Agnoli et al. 2020 ; Rominger et al. 2020 ;
Benedek et al. 2020 ; Hartung et al. 2020 ; Oh et al. 2020 ; Roberts et al.,
2020 ; Takeuchi et al., et al. 2020 b), and structural connectivity
( Wertz et al. 2020 b; Takeuchi et al., 2020 a) characteristics associ-
ated with individual differences in creative thinking, including con-
nectomic analysis of the novel construct of creativity-specific anxiety
( Ren et al. 2021 ).
Three theoretical/review papers ( Zhang et al., 2020 ; Girn et al. 2020 ;
Matheson and Kenett 2020) and one meta-analytically-based proof of
concept for neurally-informed ontologies ( Kenett et al. 2020 b) helped
capture how cognitive neuroscience researchers conceive of creativity
and how the constructs we use can be mapped onto and constrained
by brain function. The review articles address original questions in-
cluding the role of metacognition and mental states in creativity. The
meta-analysis explores the important issue of how best to operationally
capture cognitive constructs related to creativity with a set of experi-
mental tasks, leveraging the extant pool of neuroimaging data toward a
new method for ontological development that has promise for creativity
research and for all fields of cognitive neuroscience.
Many studies employed neuroimaging to examine task-induced brain
activity and/or brain connectivity (10 studies employed fMRI; 3 stud-
ies used fNIRS), or explore how interindividual differences in creative
abilities relate to white and gray matter regional structure ( n = 7),
https://doi.org/10.1016/j.neuroimage.2021.117836
Available online 5 February 2021
1053-8119/© 2021 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license
( http://creativecommons.org/licenses/by-nc-nd/4.0/ )
NeuroImage 231 (2021) 117836
Fig. 1. Summary statistics as a graph for the 42 articles included in this special issue. The graph represents similarity across the included articles. The similarity
was assessed by comparing keywords provided by the study authors for each article. Different annotations (node coloring schemes) were used to depict different
aspects of each article. The left graph is annotated by the type of neuroimaging modality used, with node coloring as follows: fMRI (dark green), fNIRS (orange),
structural (purple), eye-tracking (pink), pharmacological (light green), genetics (yellow), EEG (brown), and review articles (gray). The middle graph is annotated
by task-type-intrinsic (at rest) vs. evoked task design, with node coloring as follows: resting-state (dark green) and task-based (orange). Lastly, the right graph is
annotated by the continent of the senior author’s lab, with node coloring as follows: Europe (dark green), Asia (orange), North America (purple), Australia (pink),
and South America (light green). In each graph the size of node represents the number of participants used in each study.
or to measure intrinsic functional connectivity during rest ( n = 7).
Reflective of the field of creativity research more broadly, creative
cognition was mainly assessed in the verbal domain (21 studies used
only verbal tasks; 5 studies used figural tasks; 4 used a combination
of assessments in different domains; and 4 used questionnaires to es-
timate creative achievements in real life). Creativity assessment was
most frequently operationalized via divergent thinking tasks ( n = 21),
among which the Alternative Uses Task was predominant (used in 15
studies). Attempts to better capture the diversity of creative cognition
are noteworthy in 4 studies ( Baas et al. 2020 ; Benedek et al. 2020 ;
Chrysikou et al. 2020 a; Sunavsky and Poppenk 2020 ) that used a combi-
nation of measures from distinct frameworks (divergent and convergent
thinking, creative achievement, openness to experience). In addition, 5
studies ( Barrett et al. 2020 ; Bashwiner et al. 2020 ; Belden et al. 2020 ;
Rosen et al. 2020 ; Zioga et al. 2020 ) represent the substantial and
methodologically diverse presence of musical creativity within the field.
To better understand the scope of research covered by this special
issue in terms of neuroimaging modality, demographics, and experimen-
tal design, we embedded all 42 articles in a low-dimensional space and
examined the similarity between them ( Fig. 1 ). To embed each article,
we applied Google’s Universal Sentence Encoder ( Cer et al. 2018 ) to
keywords submitted with each article. The similarity across articles was
then assessed using Euclidean distance. The resulting similarity matrix
was visualized in a 2-D force layout as a graph, where nodes represent ar-
ticles and edges represent similarity. We annotated the generated graph
using different meta-information: modality used, experimental design,
and geographical location of the lab. Fig. 1 left graph illustrates the clear
prevalence of fMRI among modalities for exploring brain bases for cre-
ativity, followed by structural morphometric, and diffusion-based stud-
ies. Largest node-sizes represent consortium-level studies with > 1000
participants enrolled. As shown in Fig. 1 middle graph, evoked or task-
based studies were most strongly represented within this special issue,
compared with examinations of intrinsic or spontaneous correlates of
creative thinking. Lastly, Fig. 1 right graph represents geographic lo-
cation of the labs contributing to the SI (based on senior author affili-
ations). Labs in North America are most frequently represented in the
SI, followed by labs in Asia. Overall, these analyses indicate the breadth
and diversity of the selection of articles included in this SI, which re-
flect our current understanding of the cognitive and neural mechanisms
of creative thought.
Outlook and future directions for the neuroscience of creativity
Ten years ago, having a special issue on the neuroscience of cre-
ativity in a mainstream neuroimaging journal, with 42 outstanding
contributions selected from a much larger set of high-quality submis-
sions, would not have appeared likely. Even just a decade ago, under-
standing the neural bases of creative thinking was at the outskirts of
cognitive neuroscience research. Much has changed since then. A key
drivers of the movement of creativity neuroscience toward a more cen-
tral position within cognitive neuroscience has been the commitment of
creativity researchers to situate and examine creative thinking within
better-established aspects of cognition, such as semantic and autobio-
graphical memory, attention, mentalization, and cognitive control, e.g.,
( Beaty et al. 2016 ; Chrysikou 2018 ; 2019 ; Kenett et al. 2018 ; Volle 2018 ;
Zabelina and Andrews-Hanna 2016 ; Xie et al. 2021 ; Abraham 2014 ). Un-
derstanding creativity necessitates understanding how these processes
take place in the context of creative thinking tasks. On the other hand,
creativity is more than the sum of its ‘cognitive parts’: A comprehen-
sive understanding of how new ideas can come about from already ex-
isting knowledge requires a synthesis of extant findings toward a work-
ing theoretical framework of creativity neuroscience. Although pieces of
this framework are evident across the excellent research featured in this
SI, future work toward theoretical unification will be essential. Addi-
tionally, questions of the where , and —critically —when and how creativ-
ity happens within and between key neural networks, and in conjunc-
tion with activity throughout the brain still remain. Are these processes
consistent across creative domains? Does the current evidence on task-
evoked creativity neuroscience, much of which is featured in this SI, gen-
eralize to long-term (e.g., multi-year) creative endeavors? Critically, can
creativity be enhanced by enhancing activity in the identified brain sys-
tems using non-invasive brain stimulation (e.g., Chrysikou et al. 2013 ;
Green et al. 2017 ; Lucchiari et al., 2018 ; Radel et al. 2015 ) or domain-
general training ( Saggar et al. 2017 )?
The rise of creativity neuroscience research holds strong potential to
advance our understanding of more traditional cognitive neuroscience
domains. By examining how memory, attention, cognitive control, and
social cognition processes, among others, contribute and interact within
creative cognition, we can test the validity of well-established knowl-
edge in these subfields. Parallels between creativity research and re-
search examining cognitive and behavioral flexibility are also beginning
2
NeuroImage 231 (2021) 117836
to emerge ( Uddin, 2021 ). Creativity neuroscience thus presents a unique
testbed for theories across all cognitive neuroscience research. Never-
theless, because fundamental research and methodologies within these
domains are advancing rapidly, increased interdisciplinary collabora-
tions among creativity neuroscientists and experts from other cognitive
neuroscience domains will be required to advance knowledge.
As evident in the multiple and complementary methods employed
in the studies featured in this SI, creativity neuroscience has pro-
gressed from simple ‘activation-based’ fMRI studies to complex net-
work analytical paradigms. Much knowledge has been gained from
these methods, and cognitive neuroscience methods continue to ad-
vance with respect to resolution and multidimensionality. Methodologi-
cal advances notwithstanding an emerging research gap concerns the
relationship between how we study creativity in the lab and how
creativity happens in the real world. Although several studies fea-
tured in this SI examined aspects of ‘real world’ creativity such as
team problem solving (e.g., Mayseless et al., 2020), musical creativ-
ity (e.g., ( Zioga et al. 2020 ; Belden et al. 2020 ; Rosen et al. 2020 ;
Bashwiner et al. 2020 ), and real-life high creative achievers (e.g.,
Chrysikou et al., 2020 a; Chrysikou et al., 2020 b), much additional work
using ecologically valid, real-world tasks will be required to ensure
broad generalizability of creativity neuroscience findings.
For both lab-based and real-world creativity measures, a key future
direction for creativity neuroscience is the development of a clearer and
more uniform ontology of creativity constructs and measurement. In
order for studies to inform each other, researchers must agree on a vo-
cabulary so that the same terms refer to the same constructs and, most
importantly, use consistent measurement instruments/tasks to opera-
tionalize these constructs. In this SI, ( Kenett et al., 2020 b) demonstrate
proof-of-concept for a novel approach to deriving a neurally-informed
ontology of creativity measurement that leverages meta-analytic neu-
roimaging data in combination with representational similarity analy-
sis. Approaches such as this one that leverage the ever-growing body of
creativity neuroimaging data to empirically optimize the fit of tasks to
constructs are promising for the future of creativity measurement.
Across these promising directions for future research, creativity neu-
roscience has substantial opportunity to benefit from, and contribute to,
the momentum toward open science that has developed in the broader
fields of neuroimaging and cognitive neuroscience ( Poldrack and Gor-
golewski 2014 ). To reduce publication bias, preregistering a study plan
with details about data acquisition, exclusion criteria, and data analysis
before any data have been acquired should be encouraged when prac-
ticable ( Gorgolewski and Poldrack 2016 ; Open Science Collaboration
2016 ). Further, data sharing irrespective of the sample size of the study
should also be encouraged. It has been convincingly argued that greater
availability of data from small-sample studies could help with failing
faster, developing innovative methods, improving statistical power for
future studies ( Mumford, 2012 ), as well as validating older results on
newer datasets ( Saggar and Uddin 2019 ).
There is no lack of enthusiasm for creativity neuroscience, but the
growth of the field depends greatly on how effectively that energy can
be harnessed. In these early days, individual studies are not always
clearly contextualized in relation to existing studies, and there are in-
stances of crosstalk and redundancy that cloud interpretation and slow
progress. Scientific societies play a crucial role in the development of
a field by providing platforms for sharing new ideas, establishing stan-
dards for methodological rigor, and fostering cohesion and collaboration
to achieve a force multiplier-effect. SfNC was formed with the academic
charter to support interdisciplinary research on the neural and cognitive
bases of creativity and related processes, and to provide an inclusive fo-
rum for communicating this research so that it has maximal impacts for
education, health, innovation, and artistic performance. SfNC and other
organizations focused on the rigorous empirical study of creativity, and
projects such as this SI that present the field both to itself and to the
broader neuroscientific community, are essential for combining the en-
ergy sources surrounding creativity neuroscience to advance the field in
productive directions.
Acknowledgements
We are grateful to the authors for submitting their original research
to this special issue. We are also indebted to the ‘unsung heroes’ –re-
viewers, who have devoted substantial amounts of their time and exper-
tise to improving submitted articles with their constructive feedback. We
also thank the staff at the NeuroImage editorial office for their unending
support and guidance throughout the development of the special issue.
Manish Saggar
Department of Psychiatry & Behavioral Sciences, Stanford University,
Stanford, CA, USA
Emmanuelle Volle
Institut du Cerveau et de la Moelle Épinière (ICM), Sorbonne Université,
Paris, France
Lucina Q. Uddin
∗
Department of Psychology, University of Miami, Coral Gables, FL, USA
Evangelia G. Chrysikou
Department of Psychology, Drexel University, Philadelphia, PA, USA
Adam E. Green
Department of Psychology, Georgetown University, Washington, DC, USA
∗
Corresponding author.
E-mail address: l.uddin@miami.edu (L.Q. Uddin)
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