MIST: A multi-resolution parcellation of functional brain networks

Sebastian Urchs,Yassine Benhajali,Jolène St-Aubin,Pierre Bellec,Jonathan Armoza,Pierre Orban

doi:10.12688/mniopenres.12767.1

Abstract

Functional brain connectomics investigates functional connectivity between distinct brain parcels. There is an increasing interest to investigate connectivity across several levels of spatial resolution, from networks down to localized areas. Here we present the Multiresolution Intrinsic Segmentation Template (MIST), a multi-resolution parcellation of the cortical, subcortical and cerebellar gray matter. We provide annotated functional parcellations at nine resolutions from 7 to 444 functional parcels. The MIST parcellations compare well with prior work in terms of homogeneity and generalizability. We found that parcels at higher resolutions largely fell within the boundaries of larger parcels at lower resolutions. This allowed us to provide an overlap based pseudo-hierarchical decomposition tree that relates parcels across resolutions in a meaningful way. We provide an interactive web interface to explore the MIST parcellations and also made it accessible in the neuroimaging library nilearn. We believe that the MIST parcellation will facilitate future investigations of the multiresolution basis of brain function.

Highlights

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]
Brain parcellations based on resting-state functional magnetic resonance imaging have been shown to better summarize the whole-brain connectivity than parcellations based on histological or anatomical features[7]

Summary

Introduction

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]. A wide range of functional brain parcellations have been proposed in the literature, ranging in resolution from large functional systems (e.g. 3) to individual functional nodes (e.g. 4) Each of these resolutions represent a different level of organization along a continuum of brain organization[10]. We manually labeled the parcels at every resolution, maintaining consistent labelling conventions across resolutions and using labels that reflect the current usage in the fMRI literature

Methods

Labels and descriptive properties

Brodmann K

Findings

25. Bellec P: Mining the Hierarchy of Resting-State Brain Networks