Emotion dynamics as hierarchical Bayesian inference in time. (27th August 2022)
- Record Type:
- Journal Article
- Title:
- Emotion dynamics as hierarchical Bayesian inference in time. (27th August 2022)
- Main Title:
- Emotion dynamics as hierarchical Bayesian inference in time
- Authors:
- Majumdar, Gargi
Yazin, Fahd
Banerjee, Arpan
Roy, Dipanjan - Abstract:
- Abstract: What fundamental property of our environment would be most valuable and optimal in characterizing the emotional dynamics we experience in daily life? Empirical work has shown that an accurate estimation of uncertainty is necessary for our optimal perception, learning, and decision-making. However, the role of this uncertainty in governing our affective dynamics remains unexplored. Using Bayesian encoding, decoding and computational modeling, on a large-scale neuroimaging and behavioral data on a passive movie-watching task, we showed that emotions naturally arise due to ongoing uncertainty estimations about future outcomes in a hierarchical neural architecture. Several prefrontal subregions hierarchically encoded a lower-dimensional signal that highly correlated with the evolving uncertainty. Crucially, the lateral orbitofrontal cortex (lOFC) tracked the temporal fluctuations of this uncertainty and was predictive of the participants' predisposition to anxiety. Furthermore, we observed a distinct functional double-dissociation within OFC with increased connectivity between medial OFC and DMN, while with that of lOFC and FPN in response to the evolving affect. Finally, we uncovered a temporally predictive code updating an individual's beliefs spontaneously with fluctuating outcome uncertainty in the lOFC. A biologically relevant and computationally crucial parameter in the theories of brain function, we propose uncertainty to be central to the definition of complexAbstract: What fundamental property of our environment would be most valuable and optimal in characterizing the emotional dynamics we experience in daily life? Empirical work has shown that an accurate estimation of uncertainty is necessary for our optimal perception, learning, and decision-making. However, the role of this uncertainty in governing our affective dynamics remains unexplored. Using Bayesian encoding, decoding and computational modeling, on a large-scale neuroimaging and behavioral data on a passive movie-watching task, we showed that emotions naturally arise due to ongoing uncertainty estimations about future outcomes in a hierarchical neural architecture. Several prefrontal subregions hierarchically encoded a lower-dimensional signal that highly correlated with the evolving uncertainty. Crucially, the lateral orbitofrontal cortex (lOFC) tracked the temporal fluctuations of this uncertainty and was predictive of the participants' predisposition to anxiety. Furthermore, we observed a distinct functional double-dissociation within OFC with increased connectivity between medial OFC and DMN, while with that of lOFC and FPN in response to the evolving affect. Finally, we uncovered a temporally predictive code updating an individual's beliefs spontaneously with fluctuating outcome uncertainty in the lOFC. A biologically relevant and computationally crucial parameter in the theories of brain function, we propose uncertainty to be central to the definition of complex emotions. … (more)
- Is Part Of:
- Cerebral cortex. Volume 33:Number 7(2023)
- Journal:
- Cerebral cortex
- Issue:
- Volume 33:Number 7(2023)
- Issue Display:
- Volume 33, Issue 7 (2023)
- Year:
- 2023
- Volume:
- 33
- Issue:
- 7
- Issue Sort Value:
- 2023-0033-0007-0000
- Page Start:
- 3750
- Page End:
- 3772
- Publication Date:
- 2022-08-27
- Subjects:
- emotion dynamics -- Bayesian inference -- orbitofrontal cortex -- uncertainty -- emotional states
Cerebral cortex -- Periodicals
Brain -- Periodicals
612.825 - Journal URLs:
- http://cercor.oupjournals.org ↗
http://cercor.oxfordjournals.org ↗
http://www.ncbi.nlm.nih.gov/pmc/?term=%22Cereb ↗
http://ukcatalogue.oup.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1093/cercor/bhac305 ↗
- Languages:
- English
- ISSNs:
- 1047-3211
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3120.027550
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 26812.xml