TASH: Toolbox for the Automated Segmentation of Heschl’s gyrus

Abstract

Auditory cortex volume and shape differences have been observed in the context of phonetic learning, musicianship and dyslexia. Heschl's gyrus, which includes primary auditory cortex, displays large anatomical variability across individuals and hemispheres. Given this variability, manual labelling is the gold standard for segmenting HG, but is time consuming and error prone. our novel toolbox, called 'toolbox for the Automated Segmentation of HG' or tASH, automatically segments HG in brain structural MRi data, and extracts measures including its volume, surface area and cortical thickness. tASH builds upon freeSurfer, which provides an initial segmentation of auditory regions, and implements further steps to perform finer auditory cortex delineation. We validate TASH by showing significant relationships between HG volumes obtained using manual labelling and using TASH, in three independent datasets acquired on different scanners and field strengths, and by showing good qualitative segmentation. We also present two applications of TASH, demonstrating replication and extension of previously published findings of relationships between HG volumes and (a) phonetic learning, and (b) musicianship. In sum, TASH effectively segments HG in a fully automated and reproducible manner, opening up a wide range of applications in the domains of expertise, disease, genetics and brain plasticity.

A Discriminative Characterization of Heschl’s Gyrus Morphology using Spectral Graph Features

“…We used T1-weighted MRI data of 177 subjects, from professional and amateur musicians and non-musicians. This dataset was previously used to validate the TASH toolbox [11]. Prior visual inspection showed that there were 118 subjects with single gyrus (age mean: 36.69, age standard deviation (sd): 13.22) and 59 subjects with CSDs (age mean: 36.05, age sd: 12.31) in the right hemisphere, and 125 subjects with single gyrus (age mean: 35.97, age sd: 13.49) and 52 subjects with CSDs (age mean: 37.69, age sd: 11.38) in the left hemisphere.…”

“…To represent the structure of HG, we explored two binary undirected graph design schemes: surface-based HG graph and volumetric HG graph. The base of both graph designs is to use the output from the TASH-toolbox [11], which provides labels of HG on the white surface as defined by the FreeSurfer [16]. In designing the surface graph, we treated the TASH-extracted subset of white surface labels as graph vertices, and the graph edges were defined based on the connectivity of the extracted labels on the white surface.…”

“…We used T1-weighted MRI data of 177 subjects, from professional and amateur musicians and non-musicians. This dataset was previously used to validate the TASH toolbox [11]. Prior…”

“…Manual labelling, however, is prone to inter-and intra-rater variation, arising from error and subjective biases. A recently developed toolbox called TASH (Toolbox for the Automated Segmentation of Heschl’s gyrus) allows, however, for the fully automated and reproducible labeling of HG on structural MRI data [11], and for the extraction of measures such as gray matter volume, surface area and cortical thickness of the labeled region. To date, no method has been presented that allows for the automated extraction of shape features of HG; a toolbox aiming at this based on extracting the concavity of the outer contour of HG along different directions is currently in development [12].…”

“…Here, we build on the scheme presented in [15], in order to leverage spectral graph features for enhanced characterization of HG. To this aim, we initially extracted HG of each hemisphere using the TASH toolbox [11]. Each extracted HG was then represented as a graph, both in surface and volumetric form.…”