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Hum Brain Mapp. 2016 Apr;37(4):1573-92. doi: 10.1002/hbm.23121. Epub 2016 Jan 27.

MarsAtlas: A cortical parcellation atlas for functional mapping.

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Institut de Neurosciences de la Timone, UMR 7289, Aix Marseille Université, CNRS, Marseille, France.
Laboratoire des Sciences de l'Information et des Systèmes, UMR 7296, Aix Marseille Université, CNRS, Marseille, France.


An open question in neuroimaging is how to develop anatomical brain atlases for the analysis of functional data. Here, we present a cortical parcellation model based on macroanatomical information and test its validity on visuomotor-related cortical functional networks. The parcellation model is based on a recently developed cortical parameterization method (Auzias et al., [2013]: IEEE Trans Med Imaging 32:873-887), called HIP-HOP. This method exploits a set of primary and secondary sulci to create an orthogonal coordinate system on the cortical surface. A natural parcellation scheme arises from the axes of the HIP-HOP model running along the fundus of selected sulci. The resulting parcellation scheme, called MarsAtlas, complies with dorsoventral/rostrocaudal direction fields and allows inter-subject matching. To test it for functional mapping, we analyzed a MEG dataset collected from human participants performing an arbitrary visuomotor mapping task. Single-trial high-gamma activity, HGA (60-120 Hz), was estimated using spectral analysis and beamforming techniques at cortical areas arising from a Talairach atlas (i.e., Brodmann areas) and MarsAtlas. Using both atlases, we confirmed that visuomotor associations involve an increase in HGA over the sensorimotor and fronto-parietal network, in addition to medial prefrontal areas. However, MarsAtlas provided: (1) crucial functional information along both the dorsolateral and rostrocaudal direction; (2) an increase in statistical significance. To conclude, our results suggest that the MarsAtlas is a valid anatomical atlas for functional mapping, and represents a potential anatomical framework for integration of functional data arising from multiple techniques such as MEG, intracranial EEG and fMRI.


MEG; cortical parameterization; cortical parcellation; dorsoventral and rostrocaudal axes; functional segregation; gammaband neural activity; human brain atlas; visuomotor behaviors

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