RMP Rumination fMRI Dataset (TSP-3 Dataset)

Submitted by YAN Chao-Gan on

RMP Rumination fMRI Dataset (TSP-3 Dataset)


This dataset was used to investigate the brain mechanism underlying rumination state (Chen et al., 2020, NeuroImage). This is also a Traveling Subject Project – 3 Sites dataset (TSP-3), including resting-state fMRI data.

The data was shared through the R-fMRI Maps Project (RMP) and Psychological Science Data Bank (http://doi.org/10.57760/sciencedb.o00115.00002).

(Phenotypic data available here)

Or use FTP software: Host: lab.rfmri.org Username: ftpdownload Password: FTPDownload Path: /sharing/RfMRIMaps/PaperDataSharing/Chen_2020_RuminationfMRIData/RuminationfMRIData.tar.gz


Investigators and Affiliations

Xiao Chen, Ph. D. 1, 2, 3, 4, Chao-Gan Yan, Ph. D. 1, 2, 3, 4

1.     CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China;

2.     International Big-Data Center for Depression Research, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China;

3.     Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China;

4.     Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.



We would like to thank the National Center for Protein Sciences at Peking University in Beijing, China, for assistance with data acquisition at PKU and Dr. Men Weiwei for his technical support during data collection.



National Key R&D Program of China (2017YFC1309902);

National Natural Science Foundation of China (81671774 and 81630031);

13th Five-year Informatization Plan of Chinese Academy of Sciences (XXH13505);

Key Research Program of the Chinese Academy of Sciences (ZDBS-SSW-JSC006);

Beijing Nova Program of Science and Technology (Z191100001119104);

Scientific Foundation of Institute of Psychology, Chinese Academy of Sciences (Y9CX422005);

China Postdoctoral Science Foundation (2019M660847).


Publication Related to This Dataset

The following publication include the data shared in this data collection:

Chen, X., Chen, N.X., Shen, Y.Q., Li, H.X., Li, L., Lu, B., Zhu, Z.C., Fan, Z., Yan, C.G. (2020). The subsystem mechanism of default mode network underlying rumination: a reproducible neuroimaging study. NeuroImage, In Press.


Sample Size

Total: 41 (22 females; mean age = 22.7 ± 4.1 years).

Exclusion criteria: Any MRI contraindications, current psychiatric or neurological disorders, clinical diagnosis of neurologic trauma, use of psychotropic medication and any history of substance or alcohol abuse.


Scan procedures and Parameters

MRI scanning

Several days prior to scanning, participants were interviewed and briefed on the purpose of the study and the mental states to be induced in the scanner. Subjects also generated key words of 4 individual negative autobiographical events as the stimuli for the sad memory phase. We measured participants’ rumination tendency with the Ruminative Response Scale (RRS) (Nolen-Hoeksema and Morrow, 1991), which can be further divided into a more unconstructive subtype, brooding and a more adaptive subtype, reflection (Treynor, 2003).


All participants completed identical fMRI tasks on 3 different MRI scanners (order was counter-balanced across participants). Time elapsed between 2 sequential visits were 22.0 ± 14.6 days. The fMRI session included 4 runs: resting state, sad memory, rumination state and distraction state. An 8-minute resting state came first as a baseline. Participants were prompted to look at a fixation cross on the screen, not to think anything in particular and stay awake. Then participants would recall negative autobiographical events prompted by individualized keywords from the prior interview. Participants were asked to recall as vividly as they could and imagine they were re-experiencing those negative events. In the rumination state, questions such as “Think: Analyze your personality to understand why you feel so depressed in the events you just remembered” were presented to help participants think about themselves, while in the distraction state, prompts like “Think: The layout of a typical classroom” were presented to help participants focus on an objective and concrete scene. All mental states (sad memory, rumination and distraction) except for the resting state contained four randomly sequentially presented stimuli (keywords or prompts). Each stimulus lasted for 2 minutes, and then was switched to the next without any inter-stimuli intervals (ISI), forming an 8-minute continuous mental state. The resting state and negative autobiographical events recall were sequenced first and second while the order of rumination and distraction states was counter-balanced across participants. Before the resting state and after each mental state, we assessed participants’ subjective affect with a scale (item score ranged from 1 = very unhappy to 9 = very happy). Thinking contents and the phenomenology during each mental state were assessed with a series of items which were derived from a factor analysis (Gorgolewski et al., 2014) regarding self-generated thoughts (item scores ranged from 1 = not at all to 9 = almost all).


Image Acquisition

Images were acquired on 3 Tesla GE MR750 scanners at the Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences (henceforth IPCAS) and Peking University (henceforth PKUGE) with 8-channel head-coils. Another 3 Tesla SIEMENS PRISMA scanner (henceforth PKUSIEMENS) with an 8-channel head-coil in Peking University was also used. Before functional image acquisitions, all participants underwent a 3D T1-weighted scan first (IPCAS/PKUGE: 192 sagittal slices, TR = 6.7 ms, TE = 2.90 ms, slice thickness/gap = 1/0mm, in-plane resolution = 256 × 256, inversion time (IT) = 450ms, FOV = 256 × 256 mm, flip angle = 7º, average = 1; PKUSIEMENS: 192 sagittal slices, TR = 2530 ms, TE = 2.98 ms, slice thickness/gap = 1/0 mm, in-plane resolution = 256 × 224, inversion time (TI) = 1100 ms, FOV = 256 × 224 mm, flip angle = 7º, average=1). After T1 image acquisition, functional images were obtained for the resting state and all three mental states (sad memory, rumination and distraction) (IPCAS/PKUGE: 33 axial slices, TR = 2000 ms, TE = 30 ms, FA = 90º, thickness/gap = 3.5/0.6 mm, FOV = 220 × 220 mm, matrix = 64 × 64; PKUSIEMENS: 62 axial slices, TR = 2000 ms, TE = 30 ms, FA = 90º, thickness = 2 mm, multiband factor = 2, FOV = 224 × 224 mm).


Code availability

Analysis codes and other behavioral data are openly shared at https://github.com/Chaogan-Yan/PaperScripts/tree/master/Chen_2020_NeuroImage.



Gorgolewski, K.J., Lurie, D., Urchs, S., Kipping, J.A., Craddock, R.C., Milham, M.P., Margulies, D.S., Smallwood, J., 2014. A correspondence between individual differences in the brain's intrinsic functional architecture and the content and form of self-generated thoughts. PLoS One 9, e97176-e97176.

Nolen-Hoeksema, S., Morrow, J., 1991. A Prospective Study of Depression and Posttraumatic Stress Symptoms After a Natural Disaster: The 1989 Loma Prieta Earthquake.

Treynor, W., 2003. Rumination Reconsidered: A Psychometric Analysis.

(Note: Part of the content of this post was adapted from the original NeuroImage paper)