The power of smiling: The adult brain networks underlying learned infant emotionality
Publication year
2020Number of pages
11 p.
Source
Cerebral Cortex, 30, 4, (2020), pp. 2019-2029ISSN
Publication type
Article / Letter to editor
Display more detailsDisplay less details
Organization
SW OZ BSI OGG
Journal title
Cerebral Cortex
Volume
vol. 30
Issue
iss. 4
Languages used
English (eng)
Page start
p. 2019
Page end
p. 2029
Subject
Developmental PsychopathologyAbstract
The perception of infant emotionality, one aspect of temperament, starts to form in infancy, yet the underlying mechanisms of how infant emotionality affects adult neural dynamics remain unclear. We used a social reward task with probabilistic visual and auditory feedback (infant laughter or crying) to train 47 nulliparous women to perceive the emotional style of six different infants. Using functional neuroimaging, we subsequently measured brain activity while participants were tested on the learned emotionality of the six infants. We characterized the elicited patterns of dynamic functional brain connectivity using Leading Eigenvector Dynamics Analysis and found significant activity in a brain network linking the orbitofrontal cortex with the amygdala and hippocampus, where the probability of occurrence significantly correlated with the valence of the learned infant emotional disposition. In other words, seeing infants with neutral face expressions after having interacted and learned their various degrees of positive and negative emotional dispositions proportionally increased the activity in a brain network previously shown to be involved in pleasure, emotion, and memory. These findings provide novel neuroimaging insights into how the perception of happy versus sad infant emotionality shapes adult brain networks.
This item appears in the following Collection(s)
- Academic publications [242560]
- Electronic publications [129511]
- Faculty of Social Sciences [29963]
- Open Access publications [104127]
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.