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Surface-Based Display of Volume-Averaged Cerebellar Imaging Data

Diedrichsen, J; Zotow, E; (2015) Surface-Based Display of Volume-Averaged Cerebellar Imaging Data. PLoS One , 10 (7) , Article e0133402. 10.1371/journal.pone.0133402. Green open access

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Abstract

The paper presents a flat representation of the human cerebellum, useful for visualizing functional imaging data after volume-based normalization and averaging across subjects. Instead of reconstructing individual cerebellar surfaces, the method uses a white- and grey-matter surface defined on volume-averaged anatomical data. Functional data can be projected along the lines of corresponding vertices on the two surfaces. The flat representation is optimized to yield a roughly proportional relationship between the surface area of the 2D-representation and the volume of the underlying cerebellar grey matter. The map allows users to visualize the activation state of the complete cerebellar grey matter in one concise view, equally revealing both the anterior-posterior (lobular) and medial-lateral organization. As examples, published data on resting-state networks and task-related activity are presented on the flatmap. The software and maps are freely available and compatible with most major neuroimaging packages.

Type: Article
Title: Surface-Based Display of Volume-Averaged Cerebellar Imaging Data
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pone.0133402
Publisher version: http://dx.doi.org/10.1371/journal.pone.0133402
Language: English
Additional information: © 2015 Diedrichsen, Zotow. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
URI: https://discovery.ucl.ac.uk/id/eprint/1472458
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