Functional connectivity of resting-state networks in ADHD and salience reward processing: a secondary data analysis study

• Main Author: Bai, Shifan
• Other Authors: Annabel Chen Shen-Hsing
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2023
• Subjects: Social sciences::Psychology
• Online Access: https://hdl.handle.net/10356/168525
• Institution: Nanyang Technological University

This secondary data analysis study is interested in examining: (1) the differences in reward sensitivity between ADHD subjects and controls, (2) ADHD-related alterations in the functional connectivity of resting state neural networks - salience network (SN), default mode network (DMN) and executive control network (ECN), and (3) the relationship of the salience network with regards to reward signalling and sensitivity. Methods: Specifically, this study will conduct a group ICA analysis on resting state fMRI data, followed by univariate analyses using the MANCOVAN toolbox in GIFTICA to study the effect of group on functional connectivity of the resting state networks. Whole brain analysis was then conducted using SPM12 to further locate significant effect of group on activations within resting state networks. Finally, correlational analyses between salience network functional connectivity and the Sensitivity to Reward (SR) indices from the Sensitivity to Punishment and Sensitivity to Reward Questionnaire were applied. Results: No significant difference in reward sensitivity was found between groups. There was partial support for significant effect of group on aberrant functional connectivity within resting-state networks, and no significant correlation was found between salience network connectivity and reward sensitivity.