Structural and functional brain scans from the cross-sectional Southwest University adult lifespan dataset

Abstract

Recently, the field of developmental neuroscience has aimed to uncover the developmental trajectory of the human brain and to understand the changes that occur as a function of ageing. Here, we present a dataset of functional magnetic resonance imaging (fMRI) data covering the adult lifespan that includes structural MRI and resting-state functional MRI. Four hundred ninety-four healthy adults (age range: 19-80 years; Males=187) were recruited and completed two multi-modal MRI scan sessions at the Brain Imaging Center of Southwest University, Chongqing, China. The goals of the dataset are to give researchers the opportunity to map the developmental trajectories of structural and functional changes in the human brain and to replicate previous findings.

Figure 1. The distribution of participants based on age and gender.

Participants were separated into 11 groups based on their age and gender respectively. The x-axis indicates the age group, and the y-axis indicates the number of participants. The blue bar indicates male participants, and the red bar indicates female participants; in addition, the exact numbers of them are shown on the corresponding bar. Note that, for a relatively balanced distribution, the age span was set as 4 years in the first two groups, and 6 years in the remaining groups.

Figure 2. The distributions of several representative QA measures of the structural MRI data across all participants.

SNR is the abbreviation for the signal-to-noise ratio. This ratio indicates the mean intensity within the grey matter divided by the standard deviation of the values outside the brain. Higher values are better. FBER is the abbreviation for the foreground to background energy ratio. This ratio indicates the variance among the voxels inside the brain divided by the variance among the voxels outside the brain. Higher values are better. Qi1 means the percent of artefact voxels, which implies the proportion of voxels outside the brain with artefacts to the total number of voxels outside the brain. Lower values are better.

Figure 3. The distributions of several representative QA measures of the resting-state fMRI data across the participants.

SNR is the abbreviation for the signal-to-noise ratio. This ratio indicates the mean intensity within the grey matter divided by the standard deviation of the values outside the brain. Higher values are better. FBER is the abbreviation for the foreground to background energy ratio. This ratio indicates the variance among the voxels inside the brain divided by the variance among the voxels outside the brain. Higher values are better. Mean FD refers to the mean fractional displacement-Jenkinson. It is a measure of subject head motion that compares the motion between the current and previous volumes. Mean FD is calculated by summing the absolute value of the displacement changes in the x, y and z directions and rotational changes about those three axes. The rotational changes are given as distance values based on the changes across the surface of a sphere with a radius of 80 mm. Lower values are better.

Figure 4. The effects of the mean FD on age and SNR.

The x-axes indicate age and SNR values, respectively. The y-axis indicates the mean FD values.

Figure 5. Brain regions with GMV reductions during normal ageing.

L-R means from the left hemisphere of the brain to the right hemisphere.

Figure 6. Within-system connectivity decline with age.

(a) Demonstrates the negative correlation between age and mean connectivity. (b) Displays the different brain networks involved in this analysis. The mean connectivity in (a) was calculated by averaging the intrinsic functional connectivity within each of the networks. (c) Displays the functional connectivity matrices of three representative age groups. The networks were arranged in the same order as b. It can be seen that the within-system connectivity apparently declined with age.