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Neural connectivity underlying reward and emotion-related processing: Evidence from a large-scale network analysis.

Yankouskaya, A., Denholm-Smith, T., Yi, D., Greenshaw, A. J., Cao, B. and Sui, J., 2022. Neural connectivity underlying reward and emotion-related processing: Evidence from a large-scale network analysis. Frontiers in Systems Neuroscience, 16, 833625.

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DOI: 10.3389/fnsys.2022.833625

Abstract

Neuroimaging techniques have advanced our knowledge about neurobiological mechanisms of reward and emotion processing. It remains unclear whether reward and emotion-related processing share the same neural connection topology and how intrinsic brain functional connectivity organization changes to support emotion- and reward-related prioritised effects in decision making. The present study addressed these challenges using a large-scale neural network analysis approach. We applied this approach to two independent functional magnetic resonance imaging datasets, where participants performed a reward value or emotion associative matching task with tight control over experimental conditions. The results revealed that interaction between the Default Mode Network, Frontoparietal, Dorsal Attention and Salience networks engaged distinct topological structures to support the effects of reward, positive and negative emotion processing. Detailed insights into the properties of these connections are important for understanding in detail how the brain responds in the presence of emotion and reward related stimuli. We discuss the linking of reward- and emotion-related processing to emotional regulation, an important aspect of regulation of human behaviour in relation to mental health.

Item Type:Article
ISSN:1662-5137
Additional Information:Funding: This work was supported by grants from the Economic and Social Research Council (ES/K013424/1) and the Leverhulme Trust (RPG-2019-010).
Uncontrolled Keywords:Self-prioritization; reward processing; emotion processing; Default Mode Network; Frontoparietal Network; Salience Network; interaction
Group:Faculty of Science & Technology
ID Code:36842
Deposited By: Symplectic RT2
Deposited On:08 Apr 2022 12:21
Last Modified:19 Apr 2022 10:39

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