Hip-Hop Cortical Parameterization
Hip-Hop Cortical ParameterizationThis pipeline performs the Hip-Hop cortical surface parameterization. The purpose of such process is to build a coordinate system on the surface of each hemisphere, that provides a cortical surface inter-subject matching. A cortical surface parcellation is also performed at the end of the pipeline.
For references and a detailed description of the process, a couple of research papers are given below.
The Hip-Hop method is described in:
Auzias G, Lefèvre J, Le Troter A, Fischer C, Perrot M, Régis J, Coulon O (2013). Model-driven Harmonic Parameterization of the Cortical Surface : HIP-HOP, IEEE Trans. on Medical Imaging, 32(5):873-887.
The MarsAtlas cortical parcellation method is described in:
Auzias G, Coulon O, Brovelli A (2016). MarsAtlas : A cortical parcellation atlas for functional mapping, Human Brain Mapping 37(4):1573-1592.
The 'Hip-Hop cortical surface parameterization' process has to be ran AFTER the 'morphologist 2015' pipeline.
In order to produce a parameterization and a parcellation of the cortical surface of each hemisphere you need to segment the white/grey interface and represent it as a triangulated surface (Morphologist 2015), and you need to extrat the sulci graph and label it. Therefore in the 'Morphologist 2015' pipeline you need to make sure that 'Sulci Recognition' is ticked on for each hemisphere (it is of by default). Our recommendation is to use the 'Sulci Recognition with SPAM' option, it is both faster and overall more reliable.
The only input you need to provide to the pipeline if the left or right labelled sulci graph and the attribute that identifies sulci. This attribute is set to 'label' by default, which is alright if the sulci recognition has been performed automatically as mentioned above. If you have labelled your sulci by hand you probably need to set it on 'name'.
The pipeline produces a number of useful files that are briefly listed below:
- a flat rectangular mesh ('rectangular_mesh') corresponding to the HIP projection of the neo-cortex.
- a flat rectangular mesh ('cstr_rectangular_mesh') corresponding to the HOP projection of the neo-cortex registered with the model.
- longitude and latitude textures that go with the white_mesh of the subject. These two textures indicates the sperical coordinates at each point. This is the information that is primarily used for parcellation and inter-subject matching
- two parcellation textures, 'texture_model_parcels' and 'texture_coarse_parcels'.
- 'texture_model_parcels' is the parcellation strictly defined by the model used for the HOP step.
- 'texture_marsAtlas_parcels' is the recommended parcellation sheme. It has been optimized for functional data analysis and embed embed hypotheses about the anatomical and functional cortical organization.
It is possible to generate a volume-based parcellation of the cortex from the surface-based one using the process 2D Parcellation to 3D Parcellation available in the low-level category of the toolbox.
To know more about the Hip-Hop parameterization process and how to use it check out this page.
To know more about the MarsAtlas parcellation model check out this page.
Lgraph: Labelled Cortical folds graph ( input )This is the labelled sulci graph for the left hemisphere.
Rgraph: Labelled Cortical folds graph ( input )This is the labelled sulci graph for the left hemisphere.
sulcus_identification: Choice ( input )In the graphs, sulci can be identified by labels (usually if the labelling has been done automatically) or by names (usually if the labelling has been done or modified manually).
Toolbox : Cortical Surface
User level : 0
Identifier :
HipHopCorticalParameterizationFile name :
brainvisa/toolboxes/cortical_surface/processes/anatomy/HipHopCorticalParameterization.pySupported file formats :
Lgraph :Graph and data, Graph and dataRgraph :Graph and data, Graph and data