Clara Fischer

New human-specific brain landmark: the depth asymmetry of superior temporal sulcus

Significance In the human brain, from early in development through to adulthood, the superior temporal sulcus is deeper in the right than the left cerebral hemisphere in the area ventral of Heschl’s gyrus. Irrespective of gender, handedness, and language lateralization, and present in several pathologies, this asymmetry is widely shared among the human population. Its appearance early in life suggests strong genetic control over this part of the brain. In contrast, the asymmetry is barely visible in chimpanzees. Thus this asymmetry probably is a key locus to look for variations in gene expression among the primate lineage that have favored the evolution of crucial cognitive abilities sustained by this sulcus in our species, namely communication and social cognition. Identifying potentially unique features of the human cerebral cortex is a first step to understanding how evolution has shaped the brain in our species. By analyzing MR images obtained from 177 humans and 73 chimpanzees, we observed a human-specific asymmetry in the superior temporal sulcus at the heart of the communication regions and which we have named the “superior temporal asymmetrical pit” (STAP). This 45-mm-long segment ventral to Heschl’s gyrus is deeper in the right hemisphere than in the left in 95% of typical human subjects, from infanthood till adulthood, and is present, irrespective of handedness, language lateralization, and sex although it is greater in males than in females. The STAP also is seen in several groups of atypical subjects including persons with situs inversus, autistic spectrum disorder, Turner syndrome, and corpus callosum agenesis. It is explained in part by the larger number of sulcal interruptions in the left than in the right hemisphere. Its early presence in the infants of this study as well as in fetuses and premature infants suggests a strong genetic influence. Because this asymmetry is barely visible in chimpanzees, we recommend the STAP region during midgestation as an important phenotype to investigate asymmetrical variations of gene expression among the primate lineage. This genetic target may provide important insights regarding the evolution of the crucial cognitive abilities sustained by this sulcus in our species, namely communication and social cognition.

Larger is twistier: spectral analysis of gyrification (SPANGY) applied to adult brain size polymorphism.

The description of cortical folding pattern (CFP) is challenging because of geometric complexity and inter-subject variability. On a cortical surface mesh, curvature estimation provides a good scalar proxy of CFP. The oscillations of this function can be studied using a Fourier-like analysis to produce a power spectrum representative of the spatial frequency composition of CFP. First, we introduce an original method for the SPectral ANalysis of GYrication (Spangy), which performs a spectral decomposition of the mean curvature of the grey/white interface mesh based on the Laplace-Beltrami operator eigenfunctions. Spangy produces an ordered 7 bands power spectrum of curvature (B0-B6) and provides an anatomically relevant segmentation of CFP based on local spectral composition. A spatial frequency being associated with each eigenfunction, the bandwidth design assumes frequency doubling between consecutive spectral bands. Next, we observed that the last 3 spectral bands (B4, 5 and 6) accounted for 93% of the analyzed spectral power and were associated with fold-related variations of curvature, whereas the lower frequency bands were related to global brain shape. The spectral segmentation of CFP revealed 1st, 2nd and 3rd order elements associated with B4, B5 and B6 respectively. These elements could be related to developmentally-defined primary, secondary and tertiary folds. Finally, we used allometric scaling of frequency bands power and segmentation to analyze the relationship between the spectral composition of CFP and brain size in a large adult dataset. Total folding power followed a positive allometric scaling which did not divide up proportionally between the bands: B4 contribution was constant, B5 increased like total folding power and B6 much faster. Besides, apparition of new elements of pattern with increasing size only concerned the 3rd order. Hence, we demonstrate that large brains are twistier than smaller ones because of an increased number of high spatial frequency folds, ramifications and kinks that accommodate the allometric increase of cortical surface.

Model-Driven Harmonic Parameterization of the Cortical Surface: HIP-HOP

In the context of inter subject brain surface matching, we present a parameterization of the cortical surface constrained by a model of cortical organization. The parameterization is defined via an harmonic mapping of each hemisphere surface to a rectangular planar domain that integrates a representation of the model. As opposed to previous landmark-based registration methods we do not match folds between individuals but instead optimize the fit between cortical sulci and specific iso-coordinate axis in the model. This strategy overcomes some limitation to sulcus-based registration techniques such as topological variability in sulcal landmarks across subjects. Experiments on 62 subjects with manually traced sulci are presented and compared with the result of the Freesurfer software. The evaluation involves a measure of dispersion of sulci with both angular and area distortions. We show that the model-based strategy can lead to a natural, efficient and very fast (less than 5 min per hemisphere) method for defining inter subjects correspondences. We discuss how this approach also reduces the problems inherent to anatomically defined landmarks and open the way to the investigation of cortical organization through the notion of orientation and alignment of structures across the cortex.

Folding of the anterior cingulate cortex partially explains inhibitory control during childhood: A longitudinal study

Highlights • Difficulties in cognitive control are related to several psychiatric conditions.• Inhibitory control (IC) of children predicts academic and professional successes.• ACC sulcal patterns at age 5 were related to IC efficiency at age 5 (Stroop scores).• ACC sulcal patterns at age 5 explained IC efficiency at age 9 (Stroop scores).• ACC sulcal patterns constrain IC efficiency during childhood.

Relation between clinical risk factors, early cortical changes, and neurodevelopmental outcome in preterm infants

Cortical folding mainly takes place in the third trimester of pregnancy and may therefore be influenced by preterm birth. The aim of this study was to evaluate the development of specific cortical structures between early age (around 30weeks postmenstrual age) and term-equivalent age (TEA, around 40weeks postmenstrual age) in 71 extremely preterm infants, and to associate this to clinical characteristics and neurodevelopmental outcome at two years of age. First, analysis showed that the central sulcus (CS), lateral fissure (LF) and insula (INS) were present at early MRI in all infants, whereas the other sulci (post-central sulcus [PCS], superior temporal sulcus [STS], superior [SFS] and inferior [IFS] frontal sulcus) were only seen in part of the infants. Relative growth from early to TEA examination was largest in the SFS. A rightward asymmetry of the surface area was seen in development between both examinations except for the LF, which showed a leftward asymmetry at both time points. Second, lower birth weight z-score, multiple pregnancy and prolonged mechanical ventilation showed negative effects on cortical folding of the CS, LF, INS, STS and PCS, mainly on the first examination, suggesting that sulci developing the earliest were the most affected by clinical factors. Finally, in this cohort, a clear association between cortical folding and neurodevelopmental outcome at two years corrected age was found, particularly for receptive language.

Predictive support recovery with TV-Elastic Net penalty and logistic regression: an application to structural MRI

The use of machine-learning in neuroimaging offers new perspectives in early diagnosis and prognosis of brain diseases. Although such multivariate methods can capture complex relationships in the data, traditional approaches provide irregular (ℓ2 penalty) or scattered (ℓ1 penalty) predictive pattern with a very limited relevance. A penalty like Total Variation (TV) that exploits the natural 3D structure of the images can increase the spatial coherence of the weight map. However, TV penalization leads to non-smooth optimization problems that are hard to minimize. We propose an optimization framework that minimizes any combination of ℓ1, ℓ2, and TV penalties while preserving the exact ℓ1 penalty. This algorithm uses Nesterovs smoothing technique to approximate the TV penalty with a smooth function such that the loss and the penalties are minimized with an exact accelerated proximal gradient algorithm. We propose an original continuation algorithm that uses successively smaller values of the smoothing parameter to reach a prescribed precision while achieving the best possible convergence rate. This algorithm can be used with other losses or penalties. The algorithm is applied on a classification problem on the ADNI dataset. We observe that the TV penalty does not necessarily improve the prediction but provides a major breakthrough in terms of support recovery of the predictive brain regions.

Fast surface-based measurements using first eigenfunction of the Laplace-Beltrami Operator: Interest for sulcal description

In this paper we propose a fast method to compute the longitudinal extension of surfaces using the extrema of the first eigenfunction of Laplace-Beltrami Operator and the hot spots conjecture. We also propose an original definition of the surface width based on the distance to the longest geodesic. We show that the implementation of our new definition of length is consistent with the one computed from brute force and that the time complexity is considerably improved. We have tested the numerical efficiency of our approach on simple simulations and applied it to cortical surface patches from a real MRI dataset. Besides our approach enriches global descriptors of sulci shapes with a third dimension : length, depth and now width.

Model-driven harmonic parameterization of the cortical surface

In the context of inter subject brain surface matching, we present a parameterization of the cortical surface constrained by a model of cortical organization. The parameterization is defined via an harmonic mapping of each hemisphere surface to a rectangular planar domain that integrates a representation of the model. As opposed to previous landmark-based registration methods we do not match folds between individuals but instead optimize the fit between cortical sulci and specific iso-coordinate axis in the model. This strategy overcomes some limitation to sulcus-based registration techniques such as topological variability in sulcal landmarks across subjects. Experiments on 62 subjects with manually traced sulci are presented and compared with the result of the Freesurfer software. The evaluation involves a measure of dispersion of sulci with both angular and area distortions. We show that the model-based strategy can lead to a natural, efficient and very fast (less than 5 min per hemisphere) method for defining inter subjects correspondences. We discuss how this approach also reduces the problems inherent to anatomically defined landmarks and open the way to the investigation of cortical organization through the notion of orientation and alignment of structures across the cortex.

Influences of Brain Size, Sex, and Sex Chromosome Complement on the Architecture of Human Cortical Folding.

Abstract Gyrification is a fundamental property of the human cortex that is increasingly studied by basic and clinical neuroscience. However, it remains unclear if and how the global architecture of cortical folding varies with 3 interwoven sources of anatomical variation: brain size, sex, and sex chromosome dosage (SCD). Here, for 375 individuals spanning 7 karyotype groups (XX, XY, XXX, XYY, XXY, XXYY, XXXXY), we use structural neuroimaging to measure a global sulcation index (SI, total sulcal/cortical hull area) and both determinants of sulcal area: total sulcal length and mean sulcal depth. We detail large and patterned effects of sex and SCD across all folding metrics, but show that these effects are in fact largely consistent with the normative scaling of cortical folding in health: larger human brains have disproportionately high SI due to a relative expansion of sulcal area versus hull area, which arises because disproportionate sulcal lengthening overcomes a lack of proportionate sulcal deepening. Accounting for these normative allometries reveals 1) brain size‐independent sulcal lengthening in males versus females, and 2) insensitivity of overall folding architecture to SCD. Our methodology and findings provide a novel context for future studies of human cortical folding in health and disease.

Sulcus Identification and Labeling

The complexity and the variability of the cortical folding pattern are overwhelming for human experts. Computational anatomy helps the field to harness the folding variability considered as a proxy for architectural variability. First, bottom-up processing pipelines convert the implicit encoding of the cortical folding pattern embedded in the geometry of the cortical surface into a synthetic graphic representation. Then, learning-based pattern recognition methods assemble the building blocks of the folding making up this representation in order to reconstruct the sulci of the standard nomenclature. Some attempts at improving current folding models using the same bottom-up strategy could have some impact in the near future.