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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.

Author information

1
GIN, UMR 5296, CNRS, CEA, Bordeaux University, Bordeaux, France. Electronic address: marc.joliot@u-bordeaux.fr.
2
GIN, UMR 5296, CNRS, CEA, Bordeaux University, Bordeaux, France.
3
GIP CYCERON, UMS 3408, Caen F-14000, France.

Abstract

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.

KEYWORDS:

Atlas; Brain parcellation; Homotopy; Intrinsic connectivity; Resting state; fMRI

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