Abstract
Artistic training is a complex learning that requires the meticulous orchestration of sophisticated polysensory, motor, cognitive, and emotional elements of mental capacity to harvest an aesthetic creation. In this study, we investigated the architecture of the resting-state functional connectivity networks from professional painters, dancers and pianists. Using a graph-based network analysis, we focused on the art-related changes of modular organization and functional hubs in the resting-state functional connectivity network. We report that the brain architecture of artists consists of a hierarchical modular organization where art-unique and artistic form-specific brain states collectively mirror the mind states of virtuosos. We show that even in the resting state, this type of extraordinary and long-lasting training can macroscopically imprint a neural network system of spontaneous activity in which the related brain regions become functionally and topologically modularized in both domain-general and domain-specific manners. The attuned modularity reflects a resilient plasticity nurtured by long-term experience.
Highlights
Michelangelo declared five centuries ago that ‘‘a man paints with his brains and not with his hands.’’ Artistic training is a form of complex learning that requires the learner to use experience to consolidate versatile perceptual, polysensory, skillful motor, complex cognitive and profound emotional elements [1,2,3]
In addition to unique capacities specific to their virtuosity, all artists require heightened skills in computing kinematic information for producing movements with high accuracy and precision. Such a skill is mandated by the cerebellum, as part of the timing system for processing temporally organized events, engineering action-related information automatically [4]. all artists require a heightened sensitivity for dynamic interplay between the self and the environment, esthetic appraisal, and a high level of sentience regarding the intention and feeling of others [1,3] We hypothesized, in the context of learning-related brain neuroplasticity, that such diverse artisticmind traits can be differentially echoed by their corresponding brain organizations, respectively, of which parallel information processing among the sets of related regions can be efficiently organized even in the resting state of the brain
The resting-state functional connectivity during low-frequency oscillations, as studied by functional magnetic resonance imaging, may reflect the brain state of self-referential internal representation [5], exteroceptive and interoceptive deployment of attention [6], and readiness of the brain to engineer an instant mind operation [7]. rsFC can be rapidly sculpted by intensive short-term learning in a behaviorally specific manner coupled with contingent regional coactivations [8,9]
Summary
Michelangelo declared five centuries ago that ‘‘a man paints with his brains and not with his hands.’’ Artistic training is a form of complex learning that requires the learner to use experience to consolidate versatile perceptual, polysensory, skillful motor, complex cognitive and profound emotional elements [1,2,3]. In addition to unique capacities specific to their virtuosity, all artists require heightened skills in computing kinematic information for producing movements with high accuracy and precision Such a skill is mandated by the cerebellum, as part of the timing system for processing temporally organized events, engineering action-related information (velocity, intensity, and timing) automatically [4]. All artists require a heightened sensitivity for dynamic interplay between the self and the environment, esthetic appraisal, and a high level of sentience regarding the intention and feeling of others (i.e., the experience of embodiment and empathy) [1,3] We hypothesized, in the context of learning-related brain neuroplasticity, that such diverse artisticmind traits can be differentially echoed by their corresponding brain organizations, respectively, of which parallel information processing among the sets of related regions can be efficiently organized even in the resting state of the brain. The functional dynamics of these consolidated neural ensembles, including modular processing, in brain networks can be better studied using topological approaches [10,11]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
