Evidence map›Paper›PMID 34673987›Full record

ArticleSocial cognitive and affective neuroscience2022

Default and control network connectivity dynamics track the stream of affect at multiple timescales.

Giada Lettieri, Giacomo Handjaras, Francesca Setti, Elisa Morgana Cappello, Valentina Bruno, Matteo Diano, Andrea Leo, Emiliano Ricciardi, Pietro Pietrini, Luca Cecchetti

Abstract read
In one paragraph

Article in Social cognitive and affective neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Generalizable neural models of emotional engagement and disengagement.Social cognitive and affective neuroscience · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Giada LettieriSocial and Affective Neuroscience Group, IMT School for Advanced Studies Lucca, Lucca 55100, Italy.ORCID 0000-0001-8027-9053
Giacomo HandjarasSocial and Affective Neuroscience Group, IMT School for Advanced Studies Lucca, Lucca 55100, Italy.ORCID 0000-0001-5677-8434
Francesca SettiMolecular Mind Laboratory, IMT School for Advanced Studies Lucca, Lucca 55100, Italy.ORCID 0000-0001-9274-4493
Elisa Morgana CappelloSocial and Affective Neuroscience Group, IMT School for Advanced Studies Lucca, Lucca 55100, Italy.ORCID 0000-0002-4147-956X
Valentina BrunoMANIBUS Lab, Department of Psychology, University of Turin, Turin 10124, Italy.ORCID 0000-0003-2878-695X
Matteo DianoDepartment of Psychology, University of Turin, Turin 10124, Italy.ORCID 0000-0001-7024-5183
Andrea LeoDepartment of Translational Research and Advanced Technologies in Medicine and Surgery, University of Pisa, Pisa 56126, Italy.ORCID 0000-0002-1948-6608
Emiliano RicciardiMolecular Mind Laboratory, IMT School for Advanced Studies Lucca, Lucca 55100, Italy.ORCID 0000-0002-7178-9534
Pietro PietriniMolecular Mind Laboratory, IMT School for Advanced Studies Lucca, Lucca 55100, Italy.ORCID 0000-0002-6768-5556
Luca CecchettiSocial and Affective Neuroscience Group, IMT School for Advanced Studies Lucca, Lucca 55100, Italy.ORCID 0000-0001-5184-6477

Funding

European Research Council 772953
6 · The paper itself

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.

Indexed as

BrainMagnetic Resonance ImagingBrain MappingCerebral CortexHumansMotion PicturesNerve Netaffectcontrol networkdefault mode networkfMRInaturalistic stimulation

Identifiers

PMID34673987
PMCPMC9071410

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.