Resting-state functional connectome predicts individual differences in depression during Covid-19 pandemic
Bibliographic Data
| ID | 8710217 |
|---|---|
| Authors | Yu Mao (0000-0002-5443-2787, corresponding author), Qunlin Chen (0000-0002-7396-1297), Dong Wei (0000-0003-2544-8015), Dongtao Wei, Wenjing Yang (0000-0001-6378-3397), Yang Wenjing, Jiangzhou Sun (0000-0003-1433-4047), Yaxu Yu (0009-0001-9357-6337), Kaixiang Zhuang (0000-0001-9087-6521), Xiaoqin Wang (0000-0002-3999-0772), He Li (0000-0003-0927-7666), Li He (0000-0002-4720-8269), Tingyong Feng (0000-0001-9278-6474), Lei Xu (0009-0000-3744-0753), Xu Lei (0000-0002-3761-8408), Qinghua He (0000-0001-6396-6273), Hong Chen (0000-0002-9771-6464), Shukai Duan (0000-0002-0040-3796), Jiang Qiu (0000-0003-0269-5910) |
| Year | 2022 |
| Volume | 77 |
| Issue | 6 |
| Pages | 760-769 |
| Publication date | 2022-07-21 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | American Psychologist (JOURNAL) |
| Journal identifiers | ISSN: 0003-066X • E-ISSN: 1935-990X |
| Publisher | American Psychological Association (PUBLISHER • US) |
| DOI | 10.1037/amp0001031 |
| PMID | 35862107 |
| OpenAlex | W4286111236 |
| Language | EN |
| Citations received | 1 |
Stressful life events are significant risk factors for depression, and increases in depressive symptoms have been observed during the COVID-19 pandemic. The aim of this study is to explore the neural makers for individuals' depression during COVID-19, using connectome-based predictive modeling (CPM). Then we tested whether these neural markers could be used to identify groups at high/low risk for depression with a longitudinal dataset. The results suggested that the high-risk group demonstrated a higher level and increment of depression during the pandemic, as compared to the low-risk group. Furthermore, a support vector machine (SVM) algorithm was used to discriminate major depression disorder patients and healthy controls, using neural features defined by CPM. The results confirmed the CPM's ability for capturing the depression-related patterns with individuals' resting-state functional connectivity signature. The exploration for the anatomy of these functional connectivity features emphasized the role of an emotion-regulation circuit and an interoception circuit in the neuropathology of depression. In summary, the present study augments current understanding of potential pathological mechanisms underlying depression during an acute and unpredictable life-threatening event and suggests that resting-state functional connectivity may provide potential effective neural markers for identifying susceptible populations. (PsycInfo Database Record (c) 2022 APA, all rights reserved)
Biology · Cognition · Connectome · Coronavirus disease 2019 (COVID-19 · Depression (economics · Disease · Functional connectivity · MEDLINE · Neural correlates of consciousness · Neuropathology · Pandemic · Psychiatry · PsycINFO · Resting state fMRI · Functional Brain Connectivity Studies · Medicine · Mental Health Research Topics · Neuroscience · Psychology · Clinical Psychology · Internal Medicine
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2025 - 2025 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |