Manually-parcellated gyral data accounting for all known anatomical variability

Abstract

Morphometric brain changes occur throughout the lifetime and are often investigated to understand healthy ageing and disease, to identify novel biomarkers, and to classify patient groups. Yet, to accurately characterise such changes, an accurate parcellation of the brain must be achieved. Here, we present a manually-parcellated dataset of the superior frontal, the supramarginal, and the cingulate gyri of 10 healthy middle-aged subjects along with a fully detailed protocol based on two anatomical atlases. Gyral parcels were hand-drawn then reviewed by specialists blinded from the protocol to ensure consistency. Importantly, we follow a procedure that allows accounting for anatomical variability beyond what is usually achieved by standard analysis packages and avoids mutually referring to neighbouring gyri when defining gyral edges. We also provide grey matter thickness, grey matter volume, and white matter surface area information for each parcel. This dataset and corresponding measurements are useful in assessing the accuracy of equivalent parcels and metrics generated by image analysis tools and their impact on morphometric studies.

Individual structural features constrain the mouse functional connectome

“…We propose that the emergence of individual features in the functional data is, at least partially, driven by the individual's structural connectivity with stable features encoded in the connectome ( Figure 1E). In addition to connectome specificity, other structural data features may drive functional inter-subject variability including foremost regional variance such as synaptic receptor type and density (39), but also methodological variations such as parcellation differences (3). Notwithstanding, we cannot exclude that the variations in hemodynamic response functions (HRF) across animals and brain location affect SC-FC relations, as it has been shown to contribute to individual variability in human FC estimation (40).…”

“…Structural connectivity (SC) refers to set of physical links between brain areas (Connectome, (1)) and constitutes an individual fingerprint in humans (2,3). Since the connectome provides the physical substrate for information flow in the brain, it should impose strong constraints on whole brain dynamics.…”

A controlled comparison of thickness, volume and surface areas from multiple cortical parcellation packages

“…A coronal high resolution 3D T1-weighted (FSGE, 1*1.3*1 mm voxel size, TE 4.01 ms TR 9.8 ms flip angle 8°), an axial T2-weighted (SE, 1*1*2 mm voxel size, TE 104.9 ms TR 1320 ms flip angle 8°), and a T2 FLAIR volume were acquired for each subject, and reviewed by a consultant radiologist ensuring their good health. Additional details can be found in [21].…”

“…The results from these tools were compared to those of our morphometrics tool, Masks2Metrics [29, 30], which we ran on the same data with corresponding consistent ground truth. Briefly, the T1 and T2 images were combined to enhance grey-white matter borders and parcels drawn manually using a detailed protocol which accounted for all known anatomical variability (see [21] for details and validation). Using this ground truth allowed to conduct a controlled comparison by measuringdeviations from it for each package.…”

“…We concluded with an emphasis on the need for such details due to the direct influences that the derived parcels would have on any consequent analysis. Here we present a controlled comparison between FreeSurfer, BrainSuite and BrainGyrusMapping to quantify how differences in algorithms and protocols led to differences in parcel metrics, in comparison to ground truth data [21].…”