AICHA: An atlas of intrinsic connectivity of homotopic areas

Marc Joliot, Gaël Jobard, Mikaël Naveau, Nicolas Delcroix, Laurent Petit, Laure Zago, Fabrice Crivello, Emmanuel Mellet, Bernard Mazoyer, Nathalie Tzourio-Mazoyer
Journal of Neuroscience Methods. 2015-10-01; 254: 46-59
DOI: 10.1016/j.jneumeth.2015.07.013

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1. J Neurosci Methods. 2015 Oct 30;254:46-59. doi: 10.1016/j.jneumeth.2015.07.013.
Epub 2015 Jul 23.

AICHA: An atlas of intrinsic connectivity of homotopic areas.

Joliot M(1), Jobard G(2), Naveau M(2), Delcroix N(3), Petit L(2), Zago L(2),
Crivello F(2), Mellet E(2), Mazoyer B(2), Tzourio-Mazoyer N(2).

Author information:
(1)GIN, UMR 5296, CNRS, CEA, Bordeaux University, Bordeaux, France. Electronic
address: .
(2)GIN, UMR 5296, CNRS, CEA, Bordeaux University, Bordeaux, France.
(3)GIP CYCERON, UMS 3408, Caen F-14000, France.

BACKGROUND: Atlases of brain anatomical ROIs are widely used for functional MRI
data analysis. Recently, it was proposed that an atlas of ROIs derived from a
functional brain parcellation could be advantageous, in particular for
understanding how different regions share information. However, functional
atlases so far proposed do not account for a crucial aspect of cerebral
organization, namely homotopy, i.e. that each region in one hemisphere has a
homologue in the other hemisphere.
NEW METHOD: We present AICHA (for Atlas of Intrinsic Connectivity of Homotopic
Areas), a functional brain ROIs atlas based on resting-state fMRI data acquired
in 281 individuals. AICHA ROIs cover the whole cerebrum, each having
1-homogeneity of its constituting voxels intrinsic activity, and 2-a unique
homotopic contralateral counterpart with which it has maximal intrinsic
connectivity. AICHA was built in 4 steps: (1) estimation of resting-state
networks (RSNs) using individual resting-state fMRI independent components, (2)
k-means clustering of voxel-wise group level profiles of connectivity, (3)
homotopic regional grouping based on maximal inter-hemispheric functional
correlation, and (4) ROI labeling.
RESULTS: AICHA includes 192 homotopic region pairs (122 gyral, 50 sulcal, and 20
gray nuclei). As an application, we report inter-hemispheric (homotopic and
heterotopic) and intra-hemispheric connectivity patterns at different sparsities.
COMPARISON WITH EXISTING METHOD: ROI functional homogeneity was higher for AICHA
than for anatomical ROI atlases, but slightly lower than for another functional
ROI atlas not accounting for homotopy.
CONCLUSION: AICHA is ideally suited for intrinsic/effective connectivity
analyses, as well as for investigating brain hemispheric specialization.

Copyright © 2015 Elsevier B.V. All rights reserved.

DOI: 10.1016/j.jneumeth.2015.07.013
PMID: 26213217 [Indexed for MEDLINE]

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