Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex

By Salim Arslan, Sofia Ira Ktena, Antonios Makropoulos, Emma Claire Robinson, Daniel Rueckert, Sarah Parisot. NeuroImage, 2017

350 citations recorded by the source corpus.

ABSTRACT The macro‐connectome elucidates the pathways through which brain regions are structurally connected or functionally coupled to perform a specific cognitive task. It embodies the notion of representing and understanding all connections within the brain as a network, while the subdivision of the brain into interacting functional units is inherent in its architecture. As a result, the definition of network nodes is one of the most critical steps in connectivity network analysis. Although brain atlases obtained from cytoarchitecture or anatomy have long been used for this task, connectivity‐driven methods have arisen only recently, aiming to delineate more homogeneous and functionally coherent regions. This study provides a systematic comparison between anatomical, connectivity‐driven and random parcellation methods proposed in the thriving field of brain parcellation. Using resting‐state functional MRI data from the Human Connectome Project and a plethora of quantitative evaluation techniques investigated in the literature, we evaluate 10 subject‐level and 24 groupwise parcellation methods at different resolutions. We assess the accuracy of parcellations from four different aspects: (1) reproducibility across different acquisitions and groups, (2) fidelity to the underlying connectivity data, (3) agreement with fMRI task activation, myelin maps, and cytoarchitectural areas, and (4) network analysis. This extensive evaluation of different parcellations generated at the subject and group level highlights the strengths and shortcomings of the various methods and aims to provide a guideline for the choice of parcellation technique and resolution according to the task at hand. The results obtained in this study suggest that there is no optimal method able to address all the challenges faced in this endeavour simultaneously. HIGHLIGHTSA systematic comparison of state‐of‐the‐art parcellation methods is provided.10 subject‐ and 24 group‐level methods are evaluated using publicly available data.Experiments consist of quantitative assessments of parcellations at varying scales.Several criteria are simultaneously considered to evaluate parcellations.Results suggest that there is no optimal method able to address all the challenges.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/b9ca538e6f147c080a7c82ea656fe961c7649ae3

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In Cognitive Neuroscience

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Comparing spatial null models for brain maps (2021, background): “…( Eickhoﬀ et al., 2018 ), as recent work has highlighted the role of brain region deﬁnition in analyses including test-retest reliability ( Arslan et al., 2018 ), structure-function coupling ( Messé, 2020; Vázquez-Rodríguez et al., 2019 ), individual ﬁngerprint-ing ( Finn et al., 2015 ),…”
Metric learning with spectral graph convolutions on brain connectivity networks (2018, background): “These brain connectivity networks result from the subdivision of the brain into regions using anatomical landmarks, cytoarchitecture or function (Arslan et al., 2017).”