Abstract
The functional architecture of the brain is organized across multiple levels of spatial resolutions, from distributed networks to the localized areas they are made of. A brain parcellation that defines functional nodes at multiple resolutions is required to investigate the functional connectome across these scales. Here we present the Multiresolution Intrinsic Segmentation Template (MIST), a multi-resolution group level parcellation of the cortical, subcortical and cerebellar gray matter. The individual MIST parcellations match other published group parcellations in internal homogeneity and reproducibility and perform very well in real-world application benchmarks. In addition, the MIST parcellations are fully annotated and provide a hierarchical decomposition of functional brain networks across nine resolutions (7 to 444 functional parcels). We hope that the MIST parcellation will accelerate research in brain connectivity across resolutions. Because visualizing multiresolution parcellations is challenging, we provide an interactive web interface to explore the MIST. The MIST is also available through the popular nilearn toolbox.
Highlights
Understanding the building blocks of the human brain is a longstanding goal of neuroscience
We have extended our discussion of these comparisons and emphasize that while the Multiresolution Intrinsic Segmentation Template (MIST) parcellation matches existing parcellations in metrics of reproducibility and generalizability, it adds unique functionality not otherwise available
Brain parcellations based on restingstate functional magnetic resonance imaging have been shown to better summarize the whole-brain connectivity than parcellations based on histological or anatomical features[7] and are a reasonable choice for investigations of functional connectivity
Summary
Understanding the building blocks of the human brain is a longstanding goal of neuroscience. An early and important example is the parcellation of the brain into distinct areas of homogeneous cytoarchitecture by Korbinian Brodmann at the beginning of last century[1]. This line of work has since been extended to include brain parcellations based on a range of brain modalities, such as sulcal landmarks[2], functional connectivity[3], task activation[4], gene expression patterns[5], and combinations of different imaging modalities[6]. Connectivity is instead often estimated at the level of larger brain regions or networks that are delineated by a brain parcellation, providing an informed way of spatial dimensionality reduction. Brain parcellations based on restingstate functional magnetic resonance imaging (rsfMRI) have been shown to better summarize the whole-brain connectivity than parcellations based on histological or anatomical features[7] and are a reasonable choice for investigations of functional connectivity
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