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Updated: Mar 27, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
A Multimodal Dataset to Investigate Task-Evoked Negative BOLD Response and Neurodegeneration
Bardiya Ghaderi Yazdi1, Sindy Ozoria1, Seyed Hani Hojjati2
1Department of Radiology, Weill Cornell Medicine Brain Health Imaging Institute, Quantitative Neuroimaging Laboratory, New York, NY, USA.
Abstract:
The Quantitative Neuroimaging Laboratory Dataset provides magnetic resonance imaging (MRI) modalities and two resting-state and twelve task-based functional MRI (fMRI) tapping into four cognitive domains (episodic memory, fluid reasoning, processing speed, and crystallized memory). It also includes three positron emission tomography (PET) scans ([18 F]Fluorodeoxyglucose (FDG), Florbetaben, and MK-6240), plus neuropsychological assessments, and vital signs. Currently, 356 participants consented (97 young: 20 ~ 40 years; and 259 elderly: 60 ~ 80 years), while 259 completed at least one scan. We uploaded 4688 MRI/fMRI and 719 PET scans (232 Florbetaben, 251 FDG, and 236 MK-6240). 189 participants completed all scan modalities. All imaging underwent an in-house, pre-processing pipeline developed for each modality. This dataset aims to characterize the spatial and temporal properties of the brain's hemodynamic response in the opposite direction (i.e., brain deactivation), its task dependency, and its interaction with the brain's large-scale functional connectivity networks. Ultimately, this will enable the translation of neuroimaging findings into personalized medicine approaches that better characterize and predict individual pathologies in neuropsychiatric diseases.

