CoSpine open access simultaneous cortico-spinal fMRI database of thermal pain and motor tasks.
Authors
Affiliations (8)
Affiliations (8)
- State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, China.
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- State Key Laboratory of Cognitive Science and Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China. [email protected].
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China. [email protected].
Abstract
Simultaneous cortico-spinal functional magnetic resonance imaging (fMRI) enables non-invasive investigation of integrated central nervous system function, but acquisition challenges have restricted the availability of public datasets and slowed the development of advanced analytic methods. Here, we introduce the CoSpine database, the first open-access, BIDS-compliant cortico-spinal task-based fMRI resource (N = 61), acquired using a novel single-field-of-view (FOV) imaging protocol covering the whole brain (including cortical, subcortical, brainstem, and cerebellar regions) and cervical spinal cord. The dataset contains raw images, field maps, physiological recordings, and BIDS event files from thermal pain and voluntary motor tasks. An optimized acquisition and preprocessing framework is provided, validated by quality-control metrics such as temporal signal-to-noise ratio and alignment precision. Spanning a broad age range and standardized paradigms, CoSpine serves as a reference for neuroimaging methods development (e.g., hyperalignment) and for artificial intelligence (AI) model benchmarking. Potential applications include sensorimotor phenotyping, studies of age-related neurodegeneration, and exploratory work in neurorehabilitation, while also supporting early-stage development of brain-computer interface (BCI) systems involving spinal activity and personalized neuromodulation strategies.