A deformation-based approach for characterizing brain asymmetries at different spatial scales of resolution

Duplicated Heschl's gyrus associations with phonological decoding

The reason(s) for why a complete duplication of the left hemisphere Heschl's gyrus (HG) has been observed in people with reading disability are unclear. This study was designed to replicate and advance understanding of the HG and phonological decoding association, as well as test competing hypotheses that this HG duplication association is specifically localized to the HG or could be due to co-occurring atypical development of other brain regions that support reading and language development. Participants were selected on the basis of having a duplicated left hemisphere HG (N = 96) or a single HG (N = 96) and matched according to age, sex, and research site in this multi-site study. Duplicated and single HG morphology specific templates were created to determine the extent to which HG sizes were related to phonological decoding within each HG morphology group. The duplicated HG group had significantly lower phonological decoding (F = 4.48, p = 0.04) but not verbal IQ (F = 1.39, p = 0.41) compared to the single HG group. In addition, larger HG were significantly associated with lower phonological decoding in the duplicated HG group, with effects driven by the size of the lateral HG after controlling for age, sex, research site, and handedness (ps < 0.05). Brain regions that exhibited structural covariance with HG did not clearly explain the HG and phonological decoding associations. Together, the results suggest that presence of a duplicated HG indicates some risk for lower phonological decoding ability compared to verbal IQ, but the reason(s) for this association remain unclear.

Auditory Cortex Asymmetry Associations with Individual Differences in Language and Cognition

A longstanding cerebral lateralization hypothesis predicts that disrupted development of typical leftward structural asymmetry of auditory cortex explains why children have problems learning to read. Small sample sizes and small effects, potential sex-specific effects, and associations that are limited to specific dimensions of language are thought to have contributed inconsistent results. The large ABCD study dataset (baseline visit: N = 11,859) was used to test the hypothesis of significant associations between surface area asymmetry of auditory cortex and receptive vocabulary performance across boys and girls, as well as an oral word reading effect that was specific to boys. The results provide modest support (Cohen's d effect sizes ≤ 0.10) for the cerebral lateralization hypothesis.

Deep Learning Classification of Reading Disability with Regional Brain Volume Features

Developmental reading disability is a prevalent and often enduring problem with varied mechanisms that contributes to its phenotypic heterogeneity. This mechanistic and phenotypic variation, as well as relatively modest sample sizes, may have limited the development of accurate neuroimaging-based classifiers for reading disability, including because of the large feature space of neuroimaging datasets. An unsupervised learning model was used to reduce deformation-based data to a lower-dimensional manifold and then supervised learning models were used to classify these latent representations in a dataset of 96 reading disability cases and 96 controls (mean age: 9.86 ± 1.56). A combined unsupervised autoencoder and supervised convolutional neural network approach provided an effective classification of cases and controls (accuracy: 77%; precision: 0.75; recall: 0.78). Brain regions that contributed to this classification accuracy were identified by adding noise to the voxel-level image data, which showed that reading disability classification accuracy was most influenced by the superior temporal sulcus, dorsal cingulate, and lateral occipital cortex. Regions that were most important for the accurate classification of controls included the supramarginal gyrus, orbitofrontal, and medial occipital cortex. The contribution of these regions reflected individual differences in reading-related abilities, such as non-word decoding or verbal comprehension. Together, the results demonstrate an optimal deep learning solution for classification using neuroimaging data. In contrast with standard mass-univariate test results, results from the deep learning model also provided evidence for regions that may be specifically affected in reading disability cases.

Structural Covariance of the Duplicated Heschl's Gyrus: A Sulcal/Gyral Template Morphology Approach

Heschl's gyrus (HG) can occur as a single gyrus or with a completely duplicated posterior HG that has been related to a variety of abilities and disorders. Voxel-based studies typically involve the normalization of these qualitatively different HG types, thus making it difficult to evaluate the contribution of sulcal/gyral variability to voxel-based effects and perhaps obscuring some effects. To examine the structural covariance of single and duplicated HG, templates were created for the left single and duplicated HG. Structural covariance analysis with a Jacobian measure of volumetric displacement demonstrated consistent spatial covariance with homologous structure in the right hemisphere across qualitatively different HG morphology. These results suggest that HG duplication is aptly named with respect to cortical structure variation and demonstrate a multi-template approach for studying qualitatively unique brain function and structure linked to perceptual and cognitive functions.

HIGHLIGHTS

Qualitatively unique sulcal/gyral features can affect voxel-based analyses.Heschl's gyrus is highly variable across people.Morphology-specific templates were created to study Heschl's gyrus structural covariance.Single and duplicated Heschl's gyrus exhibited a similar pattern of covariance.

Persistence Cycles for Visual Exploration of Persistent Homology

Persistent homology is a fundamental tool in topological data analysis used for the most diverse applications. Information captured by persistent homology is commonly visualized using scatter plots representations. Despite being widely adopted, such a visualization technique limits user understanding and is prone to misinterpretation. This article proposes a new approach for the efficient computation of persistence cycles, a geometric representation of the features captured by persistent homology. We illustrate the importance of rendering persistence cycles when analyzing scalar fields, and we discuss the advantages that our approach provides compared to other techniques in topology-based visualization. We provide an efficient implementation of our approach based on discrete Morse theory, as a new module for the Topology Toolkit. We show that our implementation has comparable performance with respect to state-of-the-art toolboxes while providing a better framework for visually analyzing persistent homology information.

Cortical asymmetries at different spatial hierarchies relate to phonological processing ability

The ability to map speech sounds to corresponding letters is critical for establishing proficient reading. People vary in this phonological processing ability, which has been hypothesized to result from variation in hemispheric asymmetries within brain regions that support language. A cerebral lateralization hypothesis predicts that more asymmetric brain structures facilitate the development of foundational reading skills like phonological processing. That is, structural asymmetries are predicted to linearly increase with ability. In contrast, a canalization hypothesis predicts that asymmetries constrain behavioral performance within a normal range. That is, structural asymmetries are predicted to quadratically relate to phonological processing, with average phonological processing occurring in people with the most asymmetric structures. These predictions were examined in relatively large samples of children (N = 424) and adults (N = 300), using a topological asymmetry analysis of T1-weighted brain images and a decoding measure of phonological processing. There was limited evidence of structural asymmetry and phonological decoding associations in classic language-related brain regions. However, and in modest support of the cerebral lateralization hypothesis, small to medium effect sizes were observed where phonological decoding accuracy increased with the magnitude of the largest structural asymmetry across left hemisphere cortical regions, but not right hemisphere cortical regions, for both the adult and pediatric samples. In support of the canalization hypothesis, small to medium effect sizes were observed where phonological decoding in the normal range was associated with increased asymmetries in specific cortical regions for both the adult and pediatric samples, which included performance monitoring and motor planning brain regions that contribute to oral and written language functions. Thus, the relevance of each hypothesis to phonological decoding may depend on the scale of brain organization.

The Topology of Pediatric Structural Asymmetries in Language-Related Cortex

Structural asymmetries in language-related brain regions have long been hypothesized to underlie hemispheric language laterality and variability in language functions. These structural asymmetries have been examined using voxel-level, gross volumetric, and surface area measures of gray matter and white matter. Here we used deformation-based and persistent homology approaches to characterize the three-dimensional topology of brain structure asymmetries within language-related areas that were defined in functional neuroimaging experiments. Persistence diagrams representing the range of values for each spatially unique structural asymmetry were collected within language-related regions of interest across 212 children (mean age (years) = 10.56, range 6.39–16.92; 39% female). These topological data exhibited both leftward and rightward asymmetries within the same language-related regions. Permutation testing demonstrated that age and sex effects were most consistent and pronounced in the superior temporal sulcus, where older children and males had more rightward asymmetries. While, consistent with previous findings, these associations exhibited small effect sizes that were observable because of the relatively large sample. In addition, the density of rightward asymmetry structures in nearly all language-related regions was consistently higher than the density of leftward asymmetric structures. These findings guide the prediction that the topological pattern of structural asymmetries in language-related regions underlies the organization of language.