Abstract

In everyday life, the stream of affect results from the interaction between past experiences, expectations and the unfolding of events. How the brain represents the relationship between time and affect has been hardly explored, as it requires modeling the complexity of everyday life in the laboratory setting. Movies condense into hours a multitude of emotional responses, synchronized across subjects and characterized by temporal dynamics alike real-world experiences. Here, we use time-varying intersubject brain synchronization and real-time behavioral reports to test whether connectivity dynamics track changes in affect during movie watching. The results show that polarity and intensity of experiences relate to the connectivity of the default mode and control networks and converge in the right temporoparietal cortex. We validate these results in two experiments including four independent samples, two movies and alternative analysis workflows. Finally, we reveal chronotopic connectivity maps within the temporoparietal and prefrontal cortex, where adjacent areas preferentially encode affect at specific timescales.

Details

Title
Default and control network connectivity dynamics track the stream of affect at multiple timescales
Author
Lettieri, Giada 1 ; Handjaras, Giacomo 1 ; Setti, Francesca 2 ; Elisa Morgana Cappello 1 ; Bruno, Valentina 3 ; Diano, Matteo 4 ; Leo, Andrea 5 ; Ricciardi, Emiliano 2 ; Pietrini, Pietro 2 ; Cecchetti, Luca 1 

 Social and Affective Neuroscience Group, IMT School for Advanced Studies Lucca , Lucca 55100, Italy 
 Molecular Mind Laboratory, IMT School for Advanced Studies Lucca , Lucca 55100, Italy 
 MANIBUS Lab, Department of Psychology, University of Turin , Turin 10124, Italy 
 Department of Psychology, University of Turin , Turin 10124, Italy 
 Department of Translational Research and Advanced Technologies in Medicine and Surgery, University of Pisa , Pisa 56126, Italy 
Pages
461-469
Publication year
2022
Publication date
May 2022
Publisher
Oxford University Press
ISSN
17495016
e-ISSN
17495024
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3171547597
Copyright
© The Author(s) 2021. Published by Oxford University Press. This work is published under https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.