The Temporal Dynamics of Spontaneous Emotional Brain States and Their Implications for Mental Health.
Saved in:
| Title: | The Temporal Dynamics of Spontaneous Emotional Brain States and Their Implications for Mental Health. |
|---|---|
| Authors: | Kragel, Philip A. (AUTHOR), Hariri, Ahmad R. (AUTHOR), LaBar, Kevin S. (AUTHOR) |
| Source: | Journal of Cognitive Neuroscience. May2022, Vol. 34 Issue 5, p715-728. 14p. 1 Chart, 3 Graphs. |
| Subjects: | Emotional state, Mental health policy, Contentment, Markov processes, Network hubs, Sadness, Fear |
| Abstract: | Temporal processes play an important role in elaborating and regulating emotional responding during routine mind wandering. However, it is unknown whether the human brain reliably transitions among multiple emotional states at rest and how psychopathology alters these affect dynamics. Here, we combined pattern classification and stochastic process modeling to investigate the chronometry of spontaneous brain activity indicative of six emotions (anger, contentment, fear, happiness, sadness, and surprise) and a neutral state. We modeled the dynamic emergence of these brain states during resting-state fMRI and validated the results across two population cohorts—the Duke Neurogenetics Study and the Nathan Kline Institute Rockland Sample. Our findings indicate that intrinsic emotional brain dynamics are effectively characterized as a discrete-time Markov process, with affective states organized around a neutral hub. The centrality of this network hub is disrupted in individuals with psychopathology, whose brain state transitions exhibit greater inertia and less frequent resetting from emotional to neutral states. These results yield novel insights into how the brain signals spontaneous emotions and how alterations in their temporal dynamics contribute to compromised mental health. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Cognitive Neuroscience is the property of MIT Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
