Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
505-02-003 ISMRM Abstract

Mapping intrinsic neural timescale alterations in major depressive disorder

Primary: Neuro - Psychiatric Disorders
Secondary: Neuro - Gray Matter
505-02-003 · Insights into Psychiatric Disorders and the Human Connectome · Wednesday, 13 May, 8:20 AM–10:10 AM · Ballroom West
Keywords: Brain function Neurotransmitter mapping Major depressive disorder
Accepted
Yao Ge 1, Lijuan Chen1, Bo Liu1, Xiaojuan Lv1, Yan Bai1, Wei Wei1, 亚平 吴1, Li Kaixin2, MENGZHU WANG2, Meiyun Wang3
1Department of Radiology, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
2MR Research Collaboration, Siemens Healthineers Ltd., Beijing, China
3Henan Provincial People's Hospital, Zhengzhou, China
Presenting Author: Yao Ge

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. S Gallo, A El-Gazzar, P Zhutovsky, et al. Functional connectivity signatures of major depressive disorder: machine learning analysis of two multicenter neuroimaging studies. Mol Psychiatry 2023;28(7):3013-22. doi:10.1038/s41380-023-01977-5. [doi]
2. T Watanabe, G Rees, N Masuda. Atypical intrinsic neural timescale in autism. eLife 2019;8 doi:10.7554/eLife.42256. [doi]
3. J D Murray, A Bernacchia, D J Freedman, et al. A hierarchy of intrinsic timescales across primate cortex. Nature neuroscience 2014;17(12):1661-3. doi:10.1038/nn.3862. [doi]
4. S C Tanaka, A Yamashita, N Yahata, et al. A multi-site, multi-disorder resting-state magnetic resonance image database. Scientific data 2021;8(1):227. doi:10.1038/s41597-021-01004-8. [doi]
5. O Esteban, C J Markiewicz, R W Blair, et al. fMRIPrep: a robust preprocessing pipeline for functional MRI. Nature methods 2019;16(1):111-16. doi:10.1038/s41592-018-0235-4. [doi]
6. M F Glasser, T S Coalson, E C Robinson, et al. A multi-modal parcellation of human cerebral cortex. Nature 2016;536(7615):171-78. doi:10.1038/nature18933. [doi]
7. B Fischl, D H Salat, E Busa, et al. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 2002;33(3):341-55. doi:10.1016/s0896-6273(02)00569-x. [doi]
8. B T Yeo, F M Krienen, J Sepulcre, et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of neurophysiology 2011;106(3):1125-65. doi:10.1152/jn.00338.2011. [doi]
9. J Dukart, S Holiga, M Rullmann, et al. JuSpace: A tool for spatial correlation analyses of magnetic resonance imaging data with nuclear imaging derived neurotransmitter maps. Human brain mapping 2021;42(3):555-66. doi:10.1002/hbm.25244. [doi]
10. T Yarkoni, R A Poldrack, T E Nichols, et al. Large-scale automated synthesis of human functional neuroimaging data. Nature methods 2011;8(8):665-70. doi:10.1038/nmeth.1635. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/505-02-003