Skip to Main content Skip to Navigation
Journal articles

Macroanatomy and 3D probabilistic atlas of the human insula

Abstract : The human insula is implicated in numerous functions. More and more neuroimaging studies focus on this region, however no atlas offers a complete subdivision of the insula in a reference space. The aims of this study were to define a protocol to subdivide insula, to create probability maps in the MNI152 stereotaxic space, and to provide normative reference volume measurements for these subdivisions. Six regions were manually delineated bilaterally on 3D T1 MR images of 30 healthy subjects: the three short gyri, the anterior inferior cortex, and the two long gyri. The volume of the insular grey matter was 7.7 ± 0.9cm3 in native space and 9.9 ± 0.6cm3 in MNI152 space. These volumes expressed as a percentage of the ipsilateral grey matter volume were minimally larger in women (2.7±0.2%) than in men (2.6±0.2%). After spatial normalization, a stereotactic probabilistic atlas of each subregion was produced, as well as a maximum-probability atlas taking into account surrounding structures. Automatically labelling insular subregions via a multi-atlas propagation and label fusion strategy (MAPER) in a leave-one-out experiment showed high spatial overlaps of such automatically defined insular subregions with the manually derived ones (mean Jaccard index 0.65, corresponding to a mean Dice index of 0.79), with an average mean volume error of 2.6%. Probabilistic and maximum probability atlases and the original delineations are available on the web under free academic licences.
Document type :
Journal articles
Complete list of metadata
Contributor : Isabelle Faillenot Connect in order to contact the contributor
Submitted on : Tuesday, February 1, 2022 - 2:19:34 PM
Last modification on : Saturday, September 24, 2022 - 3:04:06 PM


Publication funded by an institution



Isabelle Faillenot, Rolf Heckemann, Maud Frot, Alexander Hammers. Macroanatomy and 3D probabilistic atlas of the human insula. NeuroImage, Elsevier, 2017, 150, pp.88-98. ⟨10.1016/j.neuroimage.2017.01.073⟩. ⟨inserm-03551069⟩



Record views


Files downloads