Elevated emotion network connectivity is associated with fluctuations in depression.
Proc Natl Acad Sci U S A
; 120(45): e2216499120, 2023 Nov 07.
Article
in En
| MEDLINE
| ID: mdl-37903279
ABSTRACT
Elevated emotion network connectivity is thought to leave people vulnerable to become and stay depressed. The mechanism through which this arises is however unclear. Here, we test the idea that the connectivity of emotion networks is associated with more extreme fluctuations in depression over time, rather than necessarily more severe depression. We gathered data from two independent samples of N = 155 paid students and N = 194 citizen scientists who rated their positive and negative emotions on a smartphone app twice a day and completed a weekly depression questionnaire for 8 wk. We constructed thousands of personalized emotion networks for each participant and tested whether connectivity was associated with severity of depression or its variance over 8 wk. Network connectivity was positively associated with baseline depression severity in citizen scientists, but not paid students. In contrast, 8-wk variance of depression was correlated with network connectivity in both samples. When controlling for depression variance, the association between connectivity and baseline depression severity in citizen scientists was no longer significant. We replicated these findings in an independent community sample (N = 519). We conclude that elevated network connectivity is associated with greater variability in depression symptoms. This variability only translates into increased severity in samples where depression is on average low and positively skewed, causing mean and variance to be more strongly correlated. These findings, although correlational, suggest that while emotional network connectivity could predispose individuals to severe depression, it could also be leveraged to bring about therapeutic improvements.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Depression
/
Depressive Disorder
Limits:
Humans
Language:
En
Journal:
Proc Natl Acad Sci U S A
Year:
2023
Document type:
Article
Affiliation country:
Irlanda