Data from: Human cerebral blood flow activity with diurnal variation differentially correlated with the suprachiasmatic nucleus
Data files
Abstract
This study examined diurnal variations in human cerebral activity by measuring baseline cerebral blood flow at rest using magnetic resonance imaging, four times a day, every six hours. Cerebral regions in the limbic and sensorimotor areas showed higher activity at noon. In contrast, the hippocampus exhibited peak activity at midnight and lower activity at noon. Functional connectivity analysis revealed stronger SCN-hippocampus connectivity than that between the SCN and other cerebral regions.
This study investigated diurnal variations in human cerebral activity by measuring baseline cerebral blood flow at rest using magnetic resonance imaging, four times a day, every six hours.
NIfTI (.nii) and CIFTI (dscalar.nii) files showing the results of statistical analyses for the CBF and functional connectivity data are provided. CSV files showing the data of brain activity and the functional connectivity, which were used to make the line and bar graphs, are provided.
The data of diurnal variations of cerebral CBF activity
Cerebral regions in the limbic and sensorimotor areas showed higher activity at noon. In contrast, the hippocampus exhibited peak activity at midnight and lower activity at noon.
The file of the statistical data of brain activity at the whole-brain level: Fig1C.nii, Fig2.csv
The file of the statistical data of brain activity in the hippocampus: Fig4A.nii, Fig4B.csv
The file of the statistical data of brain activity in the primary visual area: Fig5A.nii, Fig5B.csv
The data of functional connectivity
Functional connectivity analysis revealed stronger SCN-hippocampus connectivity than that between the SCN and other cerebral regions.
The file of the functional connectivity of the SCN: Fig3A.dscalar.nii, Fig3B.csv
The data of supplementary analyses
The file of the sub-voxel deviation (mm) in the spatial normalization: FigS1.csv
The file of the percentage of voxels exhibiting diurnal variations in CBF across three regional groups: FigS5.csv
Softwares
The NIfTI files can be opened using SPM, MRIcron, and FSL.
The CIFTI files can be opened using Connectome Workbench.
NaN indicate the lacking data due to technical issues.
Human subjects data
All data are the results of statistical analyses (e.g., average). No personally identifiable information is included.
Whole-brain perfusion images were acquired using the pCASL technique with multiband imaging. The acquisition of two M0 images was included in the pCASL sequence. The perfusion images were corrected for motion and distortion. The cerebral blood flow (CBF) images in the standard MNI (Montreal Neurological Institute) space were calculated using BASIL (Bayesian Inference for Arterial Spin Labeling) toolbox. Spatial smoothing (full-width at half maximum of Gaussian kernel (FWHM) = 8.0 mm) was applied to the CBF images. For analyzing the SCN, minimal spatial smoothing (FWHM = 2.0 mm) was used to accurately localize signals within this structure. We performed a one-way repeated-measures analysis of variance (ANOVA) for the CBF activity.
Preprocessed functional images were downloaded from the HCP 7T database (db.humanconnectome.org). The global signal was regressed out from the whole brain, and spatial smoothing (FWHM = 6.0 mm) was applied across the vertices in the cerebrum. The time series of fMRI signals of the SCN were extracted from volumetric images, and Pearson correlation coefficients with the time series of cerebral fMRI signals were calculated in a vertex-wise manner. The correlation coefficients were transformed into Fisher-z values.