Speaker
Description
In current neuroimaging analyses the hippocampus is typically modelled as a subcortical volume, but it is actually made up of a folded archicortical mantle, or ‘ribbon’. Representing the hippocampus as such can be leveraged to enable qualitatively new analyses, such as registration, despite inter-individual differences in gyrification and folding structure, through topological alignment. Additionally, representation as a ribbon allows the hippocampus to be factorized into surface area and thickness, which can be further subdivided for laminar analyses. These methods are thus critical in advancing MRI research from the macroscopic scale to the subfield, cortical column, and laminar scales.
This demo will apply HippUnfold, an App that we have developed for the purposes outlined above, to both standard in-vivo MRI and microscale ex-vivo imaging (MRI, BigBrain histology, or 3D polarized light imaging). We illustrate how the same principles and code applied at different spatial scales can still make up a good basis for morphological, functional, or laminar structural analyses. This demo will cover common usages, individual subject outputs, and ways to visualize results and build second-level analyses. Support for any attendees wishing to apply these tools to their own datasets will be provided offline following the demo, or at any time via github.
