A recent focus in functional MRI research on individual difference is on precision functional connectivity research and on the precise measurement of individual network characteristics [1]. Such research might enable the development of robust biomarkers for individualized treatment planning and prediction and potential discovery of connectivity-based subtypes of brain disorders [2]. Recent studies in healthy individuals have shown that considerable interindividual differences exist in functional network connectivity and network topography, which are reliable and display trait-like characteristics and relate to individual differences in cognitive abilities and personality [1,3], see here.
However, for the identification of such reliable individual network characteristics and individual networks, dense sampling of data for each individual is required. Accordingly, a larger amount of resting-state fMRI data has to be collected for each individual, adequate levels of reliability for functional connectivity between cortical regions and for the identification of individual network variants were only reached with at least 40 minutes of high-quality data. These large amounts of data, which contain hundreds and thousands of time-points for each voxel of the recorded functional MRI brain images (each composed of at least 60 000 voxels and more depending on resolution) take several hours per subject for data preprocessing and preparing data for statistical analysis on standard high-end computers.
Using the MACH-2 supercomputer enables us to process multiple subjects in parallel allowing us to perform data processing for hundreds of subjects in the same time required for processing one subject on a standard high-end computer. Subsequent connectivity analysis and multimodal statistical analysis on the relation between functional and structural neuroanatomy will likewise be several magnitudes faster when performed on the MACH-2. The massive memory and parallel computing capabilities of the MACH-2 will also enable us to explore new multivariate and advanced data modelling approaches to uncover individual differences in functional and structural neuroanatomy.
References
[1] Kong R, Li J, Orban C, Sabuncu MR, Liu H, Schaefer A, et al. Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion. Cereb Cortex. 2019;29: 2533–2551. Online version.
[2] Gratton C, Kraus BT, Greene DJ, Gordon EM, Laumann TO, Nelson SM, et al. Defining Individual-Specific Functional Neuroanatomy for Precision Psychiatry. Biol Psychiatry. 2020;88: 28–39. Online version.
[3]. Laumann TO, Gordon EM, Adeyemo B, Snyder AZ, Joo SJ, Chen M-Y, et al. Functional System and Areal Organization of a Highly Sampled Individual Human Brain. Neuron. 2015;87: 657–670. Online version.