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

Mode-based morphometry: A multiscale approach to mapping human neuroanatomy

Voxel-based morphometry (VBM) and surface-based morphometry (SBM) are two widely used neuroimaging techniques for investigating brain anatomy. These techniques rely on statistical inferences at individual points (voxels or vertices), clusters of points, or a priori regions-of-interest. They are powerful tools for describing brain anatomy, but offer little insights into the generative processes that shape a particular set of findings. Moreover, they are restricted to a single spatial resolution scale, precluding the opportunity to distinguish anatomical variations that are expressed across multiple scales. Drawing on concepts from classical physics, here we develop an approach, called mode-based morphometry (MBM), that can describe any empirical map of anatomical variations in terms of the fundamental, resonant modes-eigenmodes-of brain anatomy, each tied to a specific spatial scale. Hence, MBM naturally yields a multiscale characterization of the empirical map, affording new opportunities for investigating the spatial frequency content of neuroanatomical variability. Using simulated and empirical data, we show that the validity and reliability of MBM are either comparable or superior to classical vertex-based SBM for capturing differences in cortical thickness maps between two experimental groups. Our approach thus offers a robust, accurate, and informative method for characterizing empirical maps of neuroanatomical variability that can be directly linked to a generative physical process.

Curvature analysis of perisylvian epilepsy

PURPOSE

We assess whether alterations in the convolutional anatomy of the deep perisylvian area (DPSA) might indicate focal epileptogenicity.

MATERIALS AND METHODS

The DPSA of each hemisphere was segmented on MRI and a 3D gray-white matter interface (GWMI) geometrical model was constructed. Comparative visual and quantitative assessment of the convolutional anatomy of both the left and right DPSA models was performed. Both the density of thorn-like contours (peak percentage) and coarse interface curvatures was computed using Gaussian curvature and shape index, respectively. The proposed method was applied to a total of 14 subjects; 7 patients with an epileptogenic DPSA and 7 non-epileptic subjects.

RESULTS

A high peak percentage correlated well with the epileptogenic DPSA. It distinguished between patients and non-epileptic subjects (P = 0.029) and identified laterality of the epileptic focus in all but one case. A diminished regional curvature also identified epileptogenicity (P = 0.016) and, moreover, its laterality (P = 0.001).

CONCLUSION

An increased peak percentage from a global view of the GWMI of the DPSA provides some indication of a propensity toward a focal or regional DPSA epileptogenicity. A diminished convolutional anatomy (i.e., smoothing effect) appears also to coincide with the epileptogenic site in the DPSA and to distinguish laterality.

Learning joint surface reconstruction and segmentation, from brain images to cortical surface parcellation

Reconstructing and segmenting cortical surfaces from MRI is essential to a wide range of brain analyses. However, most approaches follow a multi-step slow process, such as a sequential spherical inflation and registration, which requires considerable computation times. To overcome the limitations arising from these multi-steps, we propose SegRecon, an integrated end-to-end deep learning method to jointly reconstruct and segment cortical surfaces directly from an MRI volume in one single step. We train a volume-based neural network to predict, for each voxel, the signed distances to multiple nested surfaces and their corresponding spherical representation in atlas space. This is, for instance, useful for jointly reconstructing and segmenting the white-to-gray-matter interface and the gray-matter-to-CSF (pial) surface. We evaluate the performance of our surface reconstruction and segmentation method with a comprehensive set of experiments on the MindBoggle, ABIDE and OASIS datasets. Our reconstruction error is found to be less than 0.52 mm and 0.97 mm in terms of average Hausdorff distance to the FreeSurfer generated surfaces. Likewise, the parcellation results show over 4% improvements in average Dice with respect to FreeSurfer, in addition to an observed drastic speed-up from hours to seconds of computation on a standard desktop station.

Folding into shape

A new computational tool provides insights into the structure of the cerebellum in mammals.

Spectral-based thickness profiling of the corpus callosum enhances anomaly detection in fetal alcohol spectrum disorders

Introduction

Fetal alcohol spectrum disorders (FASD) range from fetal alcohol syndrome (FAS) to non-syndromic forms (NS-FASD). The neuroanatomical consequences of prenatal alcohol exposure are mainly the reduction in brain size, but also focal abnormalities such as those of the corpus callosum (CC). We previously showed a narrowing of the CC for brain size, using manual measurement and its usefulness to improve diagnostic certainty. Our aim was to automate these measurements of the CC and identify more recurrent abnormalities in FAS subjects, independently of brain size reduction.

Methods

We developed a fast, automated, and normalization-free method based on spectral analysis to generate thicknesses of the CC continuously and at singular points (genu, body, isthmus, and splenium), and its length (LCC). We applied it on midsagittal section of the CC extracted from T1-anatomical brain MRI of 89 subjects with FASD (52 FAS, 37 NS-FASD) and 126 with typically development (6-20 y-o). After adjusting for batch effect, we compared the mean profiles and thicknesses of the singular points across the 3 groups. For each parameter, we established variations with age (growth charts) and brain size in the control group (scaling charts), then identified participants with abnormal measurements (<10th percentile).

Results

We confirmed the slimming of the posterior half of the CC in both FASD groups, and of the genu section in the FAS group, compared to the control group. We found a significant group effect for the LCC, genu, median body, isthmus, and splenium thicknesses (p < 0.05). We described a body hump whose morphology did not differ between groups. According to the growth charts, there was an excess of FASD subjects with abnormal LCC and isthmus, and of FAS subjects with abnormal genu and splenium. According to the scaling charts, this excess remained only for LCC, isthmus and splenium, undersized for brain size.

Conclusion

We characterized size-independent anomalies of the posterior part of the CC in FASD, with an automated method, confirming and extending our previous study. Our new tool brings the use of a neuroanatomical criterion including CC damage closer to clinical practice. Our results suggest that an FAS signature identified in NS-FASD, could improve diagnosis specificity.

Diversity and evolution of cerebellar folding in mammals

The process of brain folding is thought to play an important role in the development and organisation of the cerebrum and the cerebellum. The study of cerebellar folding is challenging due to the small size and abundance of its folia. In consequence, little is known about its anatomical diversity and evolution. We constituted an open collection of histological data from 56 mammalian species and manually segmented the cerebrum and the cerebellum. We developed methods to measure the geometry of cerebellar folia and to estimate the thickness of the molecular layer. We used phylogenetic comparative methods to study the diversity and evolution of cerebellar folding and its relationship with the anatomy of the cerebrum. Our results show that the evolution of cerebellar and cerebral anatomy follows a stabilising selection process. We observed two groups of phenotypes changing concertedly through evolution: a group of 'diverse' phenotypes - varying over several orders of magnitude together with body size, and a group of 'stable' phenotypes varying over less than 1 order of magnitude across species. Our analyses confirmed the strong correlation between cerebral and cerebellar volumes across species, and showed in addition that large cerebella are disproportionately more folded than smaller ones. Compared with the extreme variations in cerebellar surface area, folial anatomy and molecular layer thickness varied only slightly, showing a much smaller increase in the larger cerebella. We discuss how these findings could provide new insights into the diversity and evolution of cerebellar folding, the mechanisms of cerebellar and cerebral folding, and their potential influence on the organisation of the brain across species.

Enhancing fetal alcohol spectrum disorders diagnosis with a classifier based on the intracerebellar gradient of volumetric undersizing

In fetal alcohol spectrum disorders (FASD), brain growth deficiency is a hallmark of subjects both with fetal alcohol syndrome (FAS) and with non-syndromic FASD (NS-FASD, i.e., those without specific diagnostic features). However, although the cerebellum was suggested to be more severely undersized than the rest of the brain, it has not yet been given a specific place in the FASD diagnostic criteria where neuroanatomical features still count for little if anything in diagnostic specificity. We applied a combination of cerebellar segmentation tools on a 1.5 T 3DT1 brain MRI dataset from a monocentric population of 89 FASD (52 FAS, 37 NS-FASD) and 126 typically developing controls (6-20 years old), providing 8 volumes: cerebellum, vermis and 3 lobes (anterior, posterior, inferior), plus total brain volume. After adjustment of confounders, the allometric scaling relationship between these cerebellar volumes (V_i ) and the total brain or cerebellum volume (V_t ) was fitted (V_i  = bV_t ^a ), and the effect of group (FAS, control) on allometric scaling was evaluated. We then estimated for each cerebellar volume in the FAS population the deviation from the typical scaling (_v DTS) learned in the controls. Lastly, we trained and tested two classifiers to discriminate FAS from controls, one based on the total cerebellum _v DTS only, the other based on all the cerebellar _v DTS, comparing their performance both in the FAS and the NS-FASD group. Allometric scaling was significantly different between FAS and control group for all the cerebellar volumes (p < .001). We confirmed the excess of total cerebellum volume deficit (_v DTS = -10.6%) and revealed an antero-inferior-posterior gradient of volumetric undersizing in the hemispheres (-12.4%, 1.1%, 2.0%, repectively) and the vermis (-16.7%, -9.2%, -8.6%, repectively). The classifier based on the intracerebellar gradient of _v DTS performed more efficiently than the one based on total cerebellum _v DTS only (AUC = 92% vs. 82%, p = .001). Setting a high probability threshold for >95% specificity of the classifiers, the gradient-based classifier identified 35% of the NS-FASD to have a FAS cerebellar phenotype, compared to 11% with the cerebellum-only classifier (p_FISHER  = 0.027). In a large series of FASD, this study details the volumetric undersizing within the cerebellum at the lobar and vermian level using allometric scaling, revealing an anterior-inferior-posterior gradient of vulnerability to prenatal alcohol exposure. It also strongly suggests that this intracerebellar gradient of volumetric undersizing may be a reliable neuroanatomical signature of FAS that could be used to improve the specificity of the diagnosis of NS-FASD.

Defining putative tertiary sulci in lateral prefrontal cortex in chimpanzees using human predictions

Similarities and differences in brain structure and function across species are of major interest in systems neuroscience, comparative biology, and brain mapping. Recently, increased emphasis has been placed on tertiary sulci, which are shallow indentations of the cerebral cortex that appear last in gestation, continue to develop after birth, and are largely either human or hominoid specific. While tertiary sulcal morphology in lateral prefrontal cortex (LPFC) has been linked to functional representations and cognition in humans, it is presently unknown if small and shallow LPFC sulci also exist in non-human hominoids. To fill this gap in knowledge, we leveraged two freely available multimodal datasets to address the following main question: Can small and shallow LPFC sulci be defined in chimpanzee cortical surfaces from human predictions of LPFC tertiary sulci? We found that 1-3 components of the posterior middle frontal sulcus (pmfs) in the posterior middle frontal gyrus are identifiable in nearly all chimpanzee hemispheres. In stark contrast to the consistency of the pmfs components, we could only identify components of the paraintermediate frontal sulcus (pimfs) in two chimpanzee hemispheres. Putative LPFC tertiary sulci were relatively smaller and shallower in chimpanzees compared to humans. In both species, two of the pmfs components were deeper in the right compared to the left hemisphere. As these results have direct implications for future studies interested in the functional and cognitive role of LPFC tertiary sulci, we share probabilistic predictions of the three pmfs components to guide the definitions of these sulci in future studies.

Development of cortical folds in the human brain: An attempt to review biological hypotheses, early neuroimaging investigations and functional correlates

The folding of the human brain mostly takes place in utero, making it challenging to study. After a few pioneer studies looking into it in post-mortem foetal specimen, modern approaches based on neuroimaging have allowed the community to investigate the folding process in vivo, its normal progression, its early disturbances, and its relationship to later functional outcomes. In this review article, we aimed to first give an overview of the current hypotheses on the mechanisms governing cortical folding. After describing the methodological difficulties raised by its study in fetuses, neonates and infants with magnetic resonance imaging (MRI), we reported our current understanding of sulcal pattern emergence in the developing brain. We then highlighted the functional relevance of early sulcal development, through recent insights about hemispheric asymmetries and early factors influencing this dynamic such as prematurity. Finally, we outlined how longitudinal studies have started to relate early folding markers and the child's sensorimotor and cognitive outcome. Through this review, we hope to raise awareness on the potential of studying early sulcal patterns both from a fundamental and clinical perspective, as a window into early neurodevelopment and plasticity in relation to growth in utero and postnatal environment of the child.

Longitudinal Allometry of Sulcal Morphology in Health and Schizophrenia

Scaling between subcomponents of folding and total brain volume (TBV) in healthy individuals (HIs) is allometric. It is unclear whether this is true in schizophrenia (SZ) or first-episode psychosis (FEP). This study confirmed normative allometric scaling norms in HIs using discovery and replication samples. Cross-sectional and longitudinal diagnostic differences in folding subcomponents were then assessed using an allometric framework. Structural imaging from a longitudinal (Sample 1: HI and SZ, nHI Baseline = 298, nSZ Baseline = 169, nHI Follow-up = 293, nSZ Follow-up = 168, totaling 1087 images, all individuals ≥ 2 images, age 16-69 years) and a cross-sectional sample (Sample 2: nHI = 61 and nFEP = 89, age 10-30 years), all human males and females, is leveraged to calculate global folding and its nested subcomponents: sulcation index (SI, total sulcal/cortical hull area) and determinants of sulcal area: sulcal length and sulcal depth. Scaling of SI, sulcal area, and sulcal length with TBV in SZ and FEP was allometric and did not differ from HIs. Longitudinal age trajectories demonstrated steeper loss of SI and sulcal area through adulthood in SZ. Longitudinal allometric analysis revealed that both annual change in SI and sulcal area was significantly stronger related to change in TBV in SZ compared with HIs. Our results detail the first evidence of the disproportionate contribution of changes in SI and sulcal area to TBV changes in SZ. Longitudinal allometric analysis of sulcal morphology provides deeper insight into lifespan trajectories of cortical folding in SZ.SIGNIFICANCE STATEMENT Psychotic disorders are associated with deficits in cortical folding and brain size, but we lack knowledge of how these two morphometric features are related. We leverage cross-sectional and longitudinal samples in which we decompose folding into a set of nested subcomponents: sulcal and hull area, and sulcal depth and length. We reveal that, in both schizophrenia and first-episode psychosis, (1) scaling of subcomponents with brain size is different from expected scaling laws and (2) caution is warranted when interpreting results from traditional methods for brain size correction. Longitudinal allometric scaling points to loss of sulcal area as a principal contributor to loss of brain size in schizophrenia. These findings advance the understanding of cortical folding atypicalities in psychotic disorders.

Diffusion-informed spatial smoothing of fMRI data in white matter using spectral graph filters

Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas in large disregarded for probing white matter (WM). This unbalanced treatment has been in part due to controversies in relation to the nature of the blood oxygenation level-dependent (BOLD) contrast in WM and its detectability. However, an accumulating body of studies has provided solid evidence of the functional significance of the BOLD signal in WM and has revealed that it exhibits anisotropic spatio-temporal correlations and structure-specific fluctuations concomitant with those of the cortical BOLD signal. In this work, we present an anisotropic spatial filtering scheme for smoothing fMRI data in WM that accounts for known spatial constraints on the BOLD signal in WM. In particular, the spatial correlation structure of the BOLD signal in WM is highly anisotropic and closely linked to local axonal structure in terms of shape and orientation, suggesting that isotropic Gaussian filters conventionally used for smoothing fMRI data are inadequate for denoising the BOLD signal in WM. The fundamental element in the proposed method is a graph-based description of WM that encodes the underlying anisotropy observed across WM, derived from diffusion-weighted MRI data. Based on this representation, and leveraging graph signal processing principles, we design subject-specific spatial filters that adapt to a subject's unique WM structure at each position in the WM that they are applied at. We use the proposed filters to spatially smooth fMRI data in WM, as an alternative to the conventional practice of using isotropic Gaussian filters. We test the proposed filtering approach on two sets of simulated phantoms, showcasing its greater sensitivity and specificity for the detection of slender anisotropic activations, compared to that achieved with isotropic Gaussian filters. We also present WM activation mapping results on the Human Connectome Project's 100-unrelated subject dataset, across seven functional tasks, showing that the proposed method enables the detection of streamline-like activations within axonal bundles.

Ventricle shape analysis using modified WKS for atrophy detection

Brain ventricle is one of the biomarkers for detecting neurological disorders. Studying the shape of the ventricles will aid in the diagnosis process of atrophy and other CSF-related neurological disorders, as ventricles are filled with CSF. This paper introduces a spectral analysis algorithm based on wave kernel signature. This shape signature was used for studying the shape of segmented ventricles from the brain images. Based on the shape signature, the study groups were classified as normal subjects and atrophy subjects. The proposed algorithm is simple, effective, automated, and less time consuming. The proposed method performed better than the other methods heat kernel signature, scale invariant heat kernel signature, wave kernel signature, and spectral graph wavelet signature, which were used for validation purpose, by producing 94-95% classification accuracy by classifying normal and atrophy subjects correctly for CT, MR, and OASIS datasets.

Sex Differences in Lifespan Trajectories and Variability of Human Sulcal and Gyral Morphology

Sex differences in the development and aging of human sulcal morphology have been understudied. We charted sex differences in trajectories and inter-individual variability of global sulcal depth, width, and length, pial surface area, exposed (hull) gyral surface area, unexposed sulcal surface area, cortical thickness, gyral span, and cortex volume across the lifespan in a longitudinal sample (700 scans, 194 participants 2 scans, 104 three scans, age range: 16-70 years) of neurotypical males and females. After adjusting for brain volume, females had thicker cortex and steeper thickness decline until age 40 years; trajectories converged thereafter. Across sexes, sulcal shortening was faster before age 40, while sulcal shallowing and widening were faster thereafter. Although hull area remained stable, sulcal surface area declined and was more strongly associated with sulcal shortening than with sulcal shallowing and widening. Males showed greater variability for cortex volume and lower variability for sulcal width. Our findings highlight the association between loss of sulcal area, notably through sulcal shortening, with cortex volume loss. Studying sex differences in lifespan trajectories may improve knowledge of individual differences in brain development and the pathophysiology of neuropsychiatric conditions.

Gradients of connectivity as graph Fourier bases of brain activity

The application of graph theory to model the complex structure and function of the brain has shed new light on its organization, prompting the emergence of network neuroscience. Despite the tremendous progress that has been achieved in this field, still relatively few methods exploit the topology of brain networks to analyze brain activity. Recent attempts in this direction have leveraged on the one hand graph spectral analysis (to decompose brain connectivity into eigenmodes or gradients) and the other graph signal processing (to decompose brain activity "coupled to" an underlying network in graph Fourier modes). These studies have used a variety of imaging techniques (e.g., fMRI, electroencephalography, diffusion-weighted and myelin-sensitive imaging) and connectivity estimators to model brain networks. Results are promising in terms of interpretability and functional relevance, but methodologies and terminology are variable. The goals of this paper are twofold. First, we summarize recent contributions related to connectivity gradients and graph signal processing, and attempt a clarification of the terminology and methods used in the field, while pointing out current methodological limitations. Second, we discuss the perspective that the functional relevance of connectivity gradients could be fruitfully exploited by considering them as graph Fourier bases of brain activity.

Independent components of human brain morphology

Quantification of brain morphology has become an important cornerstone in understanding brain structure. Measures of cortical morphology such as thickness and surface area are frequently used to compare groups of subjects or characterise longitudinal changes. However, such measures are often treated as independent from each other. A recently described scaling law, derived from a statistical physics model of cortical folding, demonstrates that there is a tight covariance between three commonly used cortical morphology measures: cortical thickness, total surface area, and exposed surface area. We show that assuming the independence of cortical morphology measures can hide features and potentially lead to misinterpretations. Using the scaling law, we account for the covariance between cortical morphology measures and derive novel independent measures of cortical morphology. By applying these new measures, we show that new information can be gained; in our example we show that distinct morphological alterations underlie healthy ageing compared to temporal lobe epilepsy, even on the coarse level of a whole hemisphere. We thus provide a conceptual framework for characterising cortical morphology in a statistically valid and interpretable manner, based on theoretical reasoning about the shape of the cortex.

A gyrification analysis approach based on Laplace Beltrami eigenfunction level sets

An accurate measure of the complexity of patterns of cortical folding or gyrification is necessary for understanding normal brain development and neurodevelopmental disorders. Conventional gyrification indices (GIs) are calculated based on surface curvature (curvature-based GI) or an outer hull surface of the cortex (outer surface-based GI). The latter is dependent on the definition of the outer hull surface and a corresponding function between surfaces. In the present study, we propose the Laplace Beltrami-based gyrification index (LB-GI). This is a new curvature-based local GI computed using the first three Laplace Beltrami eigenfunction level sets. As with outer surface-based GI methods, this method is based on the hypothesis that gyrification stems from a flat surface during development. However, instead of quantifying gyrification with reference to corresponding points on an outer hull surface, LB-GI quantifies the gyrification at each point on the cortical surface with reference to their surrounding gyral points, overcoming several shortcomings of existing methods. The LB-GI was applied to investigate the cortical maturation profile of the human brain from preschool to early adulthood using the PING database. The results revealed more detail in patterns of cortical folding than conventional curvature-based methods, especially on frontal and posterior tips of the brain, such as the frontal pole, lateral occipital, lateral cuneus, and lingual. Negative associations of cortical folding with age were observed at cortical regions, including bilateral lingual, lateral occipital, precentral gyrus, postcentral gyrus, and superior frontal gyrus. The results also indicated positive significant associations between age and the LB-GI of bilateral insula, the medial orbitofrontal, frontal pole and rostral anterior cingulate regions. It is anticipated that the LB-GI will be advantageous in providing further insights in the understanding of brain development and degeneration in large clinical neuroimaging studies.

Heritability of Structural Patterning in the Human Cerebral Cortex

Genetic influences that govern the spatial patterning of the human cortex and its structural variability are still incompletely known. We analyzed structural MR images in twins, siblings, and pairs of unrelated subjects. A comprehensive set of methods was employed to quantify properties of cortical features at different spatial scales. Measures were used to assess the influence of genetic similarity on structural patterning. Results indicated that: (1) Genetic effects significantly influence all structural features assessed here at all spatial resolutions, albeit at different strengths. (2) While strong genetic effects were found at the whole-brain and hemisphere level, effects were weaker at the regional and vertex level, depending on the measure under study. (3) Besides cortical thickness, sulcal (geodesic) depth was found to be under strong genetic control. The local pattern indicated that two axes along (a) the anterior-posterior direction (insula to parieto-occipital sulcus), and (b) superior-inferior direction (central sulcus to callosal sulcus) presumably determine the segregation of four quadrants in each hemisphere early in development. (4) While strong structural asymmetries were found at the regional level, genetic influences on laterality were relatively minor.

On early brain folding patterns using biomechanical growth modeling

Abnormal cortical folding patterns may be related to neurodevelopmental disorders such as lissencephaly and polymicrogyria. In this context, computational modeling is a powerful tool to provide a better understanding of the early brain folding process. Recent studies based on biomechanical modeling have shown that mechanical forces play a crucial role in the formation of cortical convolutions. However, the correlation between simulation results and biological facts, and the effect of physical parameters in these models remain unclear. In this paper, we propose a new brain longitudinal length growth model to improve brain model growth. In addition, we investigate the effect of the initial cortical thickness on folding patterns, quantifying the folds by the surface-based three-dimensional gyrification index and a spectral analysis of gyrification. The results tend to show that the use of such biomechanical models could highlight the links between neurodevelopmental diseases and physical parameters.

"Plis de passage" Deserve a Role in Models of the Cortical Folding Process

Cortical folding is a hallmark of brain topography whose variability across individuals remains a puzzle. In this paper, we call for an effort to improve our understanding of the pli de passage phenomenon, namely annectant gyri buried in the depth of the main sulci. We suggest that plis de passage could become an interesting benchmark for models of the cortical folding process. As an illustration, we speculate on the link between modern biological models of cortical folding and the development of the Pli de Passage Frontal Moyen (PPFM) in the middle of the central sulcus. For this purpose, we have detected nine interrupted central sulci in the Human Connectome Project dataset, which are used to explore the organization of the hand sensorimotor areas in this rare configuration of the PPFM.

Alteration of the Cortex Shape as a Proxy of White Matter Swelling in Severe Cerebral Small Vessel Disease

CADASIL is a monogenic small vessel disease characterized by the accumulation of brain tissue lesions of microvascular origin leading to strokes and cognitive deficits. Both cortical and parenchymal alterations have been described using various MRI markers. However, relationships between cortical and subcortical alterations remain largely unexplored. While brain atrophy is a preponderant feature in cerebral small vessel disease, recent results in CADASIL suggest slightly larger brain volumes and increased white matter water content at early stages of the disease by comparison to controls. We hypothesized in this study that increased water content in gyral white matter balances expected brain atrophy. Direct white matter volume computation is challenging in these patients given widespread subcortical alterations. Instead, our approach was that a gyral white matter swelling would translate into a modification of the shape of cortical gyri. Our goal was then to assess the relationship between subcortical lesions and possible alteration of the cortex shape. More specifically, aims of this work were to assess 1) morphometric differences of the cortex shape between CADASIL patients and controls 2) the relationship between the cortex shape and the volume of white matter hyperintensities (WMH), a reflect of white matter alterations. Twenty-one patients at the early stage of the disease and 28 age- and sex-matched controls were included. Cortical surfaces were reconstructed from 3D-T1-weighted images. Folding power assessed from spectral analysis of gyrification and cortical morphometry using curvedness and shape index were computed as proxies of the cortex shape. Influence of segmentation errors were evaluated through the simulation of WMH in controls. As a result, patients had larger folding power and curvedness compared to controls. They also presented lower shape indices both related to sulci and gyri. In patients, the volume of WMH was associated with decreased gyral shape index. These results suggest that the cortex shape of CADASIL patients is different compared to controls and that the enlargement of gyri is related to the extent of white matter alterations. The study of the cortex shape might be another way to evaluate subcortical swelling or atrophy in various neurological disorders.

Determinants of structural segregation and patterning in the human cortex

This study aimed at uncovering mechanisms that govern the spatio-temporal patterning of the human cortex and its structural variability, and drawing links between fetal brain development and variability in adult brains. A data-driven analytic approach based on structural MR images revealed the following findings: (1) The cortical surface can be subdivided into 13 independent regions ("communities") based on macroscopic features. (2) Thirty centers of low inter-subject variability were found in major sulci on the cortical surface. Their variability showed a strong positive correlation with the known time points at which they appear in fetal development. Centers forming early induce a higher inter-subject regularity in a larger local vicinity, while those forming later result in smaller regions of higher variability. (3) The layout of sulcal and gyral patterns within a community is governed typically by two centers. Depending on the relative variability of each center, communities can be classified into structural sub-types. (4) Sub-types across ipsi-lateral communities are independent, but associated with the sub-type of the same community on the contra-lateral side. Results shown here integrate well with current knowledge about macroscopic, microscopic, and genetic determinants of brain development.

Three-Dimensional Probabilistic Maps of Mesial Temporal Lobe Structures in Children and Adolescents' Brains

The hippocampus and the adjacent perirhinal, entorhinal, temporopolar, and parahippocampal cortices are interconnected in a hierarchical MTL system crucial for memory processes. A probabilistic description of the anatomical location and spatial variability of MTL cortices in the child and adolescent brain would help to assess structure-function relationships. The rhinal sulcus (RS) and the collateral sulcus (CS) that border MTL cortices and influence their morphology have never been described in these populations. In this study, we identified the aforementioned structures on magnetic resonance images of 38 healthy subjects aged 7-17 years old. Relative to sulcal morphometry in the MTL, we showed RS-CS conformation is an additional factor of variability in the MTL that is not explained by other variables such as age, sex and brain volume; with an innovative method using permutation testing of the extrema of structures of interest, we showed that RS-SC conformation was not associated with differences of location of MTL sulci. Relative to probabilistic maps, we offered for the first time a systematic mapping of MTL structures in children and adolescent, mapping all the structures of the MTL system while taking sulcal morphology into account. Our results, with the probabilistic maps described here being freely available for download, will help to understand the anatomy of this region and help functional and clinical studies to accurately test structure-function hypotheses in the MTL during development. Free access to MTL pediatric atlas: http://neurovault.org/collections/2381/.

SPANOL (SPectral ANalysis of Lobes): A Spectral Clustering Framework for Individual and Group Parcellation of Cortical Surfaces in Lobes

Understanding the link between structure, function and development in the brain is a key topic in neuroimaging that benefits from the tremendous progress of multi-modal MRI and its computational analysis. It implies, inter alia, to be able to parcellate the brain volume or cortical surface into biologically relevant regions. These parcellations may be inferred from existing atlases (e.g., Desikan) or sets of rules, as would do a neuroanatomist for lobes, but also directly driven from the data (e.g., functional or structural connectivity) with minimum a priori. In the present work, we aimed at using the intrinsic geometric information contained in the eigenfunctions of Laplace-Beltrami Operator to obtain parcellations of the cortical surface based only on its description by triangular meshes. We proposed a framework adapted from spectral clustering, which is general in scope and suitable for the co-parcellation of a group of subjects. We applied it to a dataset of 62 adults, optimized it and revealed a striking agreement between parcels produced by this unsupervised clustering and Freesurfer lobes (Desikan atlas), which cannot be explained by chance. Constituting the first reported attempt of spectral-based fully unsupervised segmentation of neuroanatomical regions such as lobes, spectral analysis of lobes (Spanol) could conveniently be fitted into a multimodal pipeline to ease, optimize or speed-up lobar or sub-lobar segmentation. In addition, we showed promising results of Spanol on smoother brains and notably on a dataset of 15 fetuses, with an interest for both the understanding of cortical ontogeny and the applicative field of perinatal computational neuroanatomy.

Mechanical morphogenesis and the development of neocortical organisation

The development of complex neocortical organisations is thought to result from the interaction of genetic and activity-dependent processes. We propose that a third type of process - mechanical morphogenesis - may also play an important role. We review theoretical and experimental results in physics showing how even homogeneous growth can produce a variety of forms, in particular neocortical folding. The mechanical instabilities that produce these forms induce heterogeneous patterns of stress at the scale of the organ. We review the evidence showing how these stresses can influence cell proliferation, migration and apoptosis, cell differentiation and shape, migration and axonal guidance, and could thus be able to influence regional neocortical identity and connectivity.

The dynamics of cortical folding waves and prematurity-related deviations revealed by spatial and spectral analysis of gyrification

In the human brain, the appearance of cortical sulci is a complex process that takes place mostly during the second half of pregnancy, with a relatively stable temporal sequence across individuals. Since deviant gyrification patterns have been observed in many neurodevelopmental disorders, mapping cortical development in vivo from the early stages on is an essential step to uncover new markers for diagnosis or prognosis. Recently this has been made possible by MRI combined with post-processing tools, but the reported results are still fragmented. Here we aimed to characterize the typical folding progression ex utero from the pre- to the post-term period, by considering 58 healthy preterm and full-term newborns and infants imaged between 27 and 62 weeks of post-menstrual age. Using a method of spectral analysis of gyrification (SPANGY), we detailed the spatial-frequency structure of cortical patterns in a quantitative way. The modeling of developmental trajectories revealed three successive waves that might correspond to primary, secondary and tertiary folding. Some deviations were further detected in 10 premature infants without apparent neurological impairment and imaged at term equivalent age, suggesting that our approach is sensitive enough to highlight the subtle impact of preterm birth and extra-uterine life on folding.

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

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.

Cortical gyrification is abnormal in children with prenatal alcohol exposure

OBJECTIVES

Prenatal alcohol exposure (PAE) adversely affects early brain development. Previous studies have shown a wide range of structural and functional abnormalities in children and adolescents with PAE. The current study adds to the existing literature specifically on cortical development by examining cortical gyrification in a large sample of children with PAE compared to controls. Relationships between cortical development and intellectual functioning are also examined.

EXPERIMENTAL DESIGN

Included were 92 children with PAE and 83 controls ages 9-16 from four sites in the Collaborative Initiative on FASD (CIFASD). All PAE participants had documented heavy PAE. All underwent a formal evaluation of physical anomalies and dysmorphic facial features. MRI data were collected using modified matched protocols on three platforms (Siemens, GE, and Philips). Cortical gyrification was examined using a semi-automated procedure.

PRINCIPAL OBSERVATIONS

Whole brain group comparisons using Monte Carlo z-simulation for multiple comparisons showed significantly lower cortical gyrification across a large proportion of the cerebral cortex amongst PAE compared to controls. Whole brain comparisons and ROI based analyses showed strong positive correlations between cortical gyrification and IQ (i.e. less developed cortex was associated with lower IQ).

CONCLUSIONS

Abnormalities in cortical development were seen across the brain in children with PAE compared to controls. Cortical gyrification and IQ were strongly correlated, suggesting that examining mechanisms by which alcohol disrupts cortical formation may yield clinically relevant insights and potential directions for early intervention.

Local Spectral Analysis of the Cerebral Cortex: New Gyrification Indices

Gyrification index (GI) is an appropriate measure to quantify the complexity of the cerebral cortex. There is, however, no universal agreement on the notion of surface complexity and there are various methods in literature that evaluate different aspects of cortical folding. In this paper, we give two intuitive interpretations on folding quantification based on the magnitude and variation of the mean curvature of the cortical surface. We then present a local spectral analysis of the mean curvature to introduce two local gyrification indices that satisfy our interpretations. For this purpose, the graph windowed Fourier transform is extended to the framework of surfaces discretized with triangular meshes. An adaptive window function is also proposed to deal with the intersubject cortical size variability. The intrinsic nature of the method allows us to compute the degree of folding at different spatial scales. Our experiments show that while more classical surface area-based GIs may fail at differentiating deep folds from very convoluted ones, our spectral GIs overcome this issue. The method is applied to the cortical surfaces of 124 healthy adult subjects of OASIS database and average gyrification maps are computed and compared with other GI definitions. In order to illustrate the capacity of our method to capture and quantify important aspects of gyrification, we study the relationship between brain volume and cortical complexity, and design a scaling analysis with a power law model. Results indicate an allometric relation and confirm the well-known observations that larger brains are more folded. We also perform the scaling analysis at the vertex level to investigate how the degree of folding varies locally with the brain volume. Results reveal that in our healthy adult brain database, cortical regions which are the least folded on average show an increased folding complexity when brain size increases.

Allometric scaling of brain regions to intra-cranial volume: An epidemiological MRI study

There is growing evidence that sub-structures of the brain scale allometrically to total brain size, that is, in a non-proportional and non-linear way. Here, scaling of different volumes of interest (VOI) to intra-cranial volume (ICV) was examined. It was assessed whether scaling was allometric or isometric and whether scaling coefficients significantly differed from each other. We also tested to what extent allometric scaling of VOI was introduced by the automated segmentation technique. Furthermore, reproducibility of allometric scaling was studied different age groups and study populations. Study samples included samples of cognitively healthy adults from the community-based Age Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik Study) (N = 3,883), the Coronary Artery Risk Development in Young Adults Study (CARDIA) (N =709), and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 180). Data encompassed participants with different age, ethnicity, risk factor profile, and ICV and VOI obtained with different automated MRI segmentation techniques. Our analysis showed that (1) allometric scaling is a trait of all parts of the brain, (2) scaling of neo-cortical white matter, neo-cortical gray matter, and deep gray matter structures including the cerebellum are significantly different from each other, and (3) allometric scaling of brain structures cannot solely be explained by age-associated atrophy, sex, ethnicity, or a systematic bias from study-specific segmentation algorithm, but appears to be a true feature of brain geometry. Hum Brain Mapp 38:151-164, 2017. © 2016 Wiley Periodicals, Inc.

Micro- and nano-technologies to probe the mechano-biology of the brain

Biomechanical forces have been demonstrated to influence a plethora of neuronal functions across scales including gene expression, mechano-sensitive ion channels, neurite outgrowth and folding of the cortices in the brain. However, the detailed roles biomechanical forces may play in brain development and disorders has seen limited study, partly due to a lack of effective methods to probe the mechano-biology of the brain. Current techniques to apply biomechanical forces on neurons often suffer from low throughput and poor spatiotemporal resolution. On the other hand, newly developed micro- and nano-technologies can overcome these aforementioned limitations and offer advantages such as lower cost and possibility of non-invasive control of neuronal circuits. This review compares the range of conventional, micro- and nano-technological techniques that have been developed and how they have been or can be used to understand the effect of biomechanical forces on neuronal development and homeostasis.

Insights into the Brain: Neuroimaging of Brain Development and Maturation

The study of how the human brain develops has always been a challenge and an interest to the scientific community. In recent years, new evidence has suggested that many neuropsychiatric disorders may originate from aberrations early in development. This discovery necessitates the application of methodologies that make possible the investigation of human brain development in vivo and across the lifespan. In this commentary, we present evidence that the advent of structural neuroimaging has specifically and significantly contributed critical information about the developmental trajectories of postnatal human brain development that would otherwise not have been possible. We believe that this is particularly relevant to present day research as it has become increasingly clear that growth trajectories within the brain might serve as an endophenotype for a number of factors, ranging from IQ to psychiatric illness. We highlight seminal early works that helped to jumpstart the field of developmental neuroimaging and which inspired incredible new advances in neuroimaging methodologies that are being developed and applied in the field today.

Comparison of cortical folding measures for evaluation of developing human brain

We evaluated 22 measures of cortical folding, 20 derived from local curvature (curvature-based measures) and two based on other features (sulcal depth and gyrification index), for their capacity to distinguish between normal and aberrant cortical development. Cortical surfaces were reconstructed from 12 term-born control and 63 prematurely-born infants. Preterm infants underwent 2-4 MR imaging sessions between 27 and 42weeks postmenstrual age (PMA). Term infants underwent a single MR imaging session during the first postnatal week. Preterm infants were divided into two groups. One group (38 infants) had no/minimal abnormalities on qualitative assessment of conventional MR images. The second group (25 infants) consisted of infants with injury on conventional MRI at term equivalent PMA. For both preterm infant groups, all folding measures increased or decreased monotonically with increasing PMA, but only sulcal depth and gyrification index differentiated preterm infants with brain injury from those without. We also compared scans obtained at term equivalent PMA (36-42weeks) for all three groups. No curvature-based measured distinguished between the groups, whereas sulcal depth distinguished term control from injured preterm infants and gyrification index distinguished all three groups. When incorporating total cerebral volume into the statistical model, sulcal depth no longer distinguished between the groups, though gyrification index distinguished between all three groups and positive shape index distinguished between the term control and uninjured preterm groups. We also analyzed folding measures averaged over brain lobes separately. These results demonstrated similar patterns to those obtained from the whole brain analyses. Overall, though the curvature-based measures changed during this period of rapid cerebral development, they were not sensitive for detecting the differences in folding associated with brain injury and/or preterm birth. In contrast, gyrification index was effective in differentiating these groups.

Are Developmental Trajectories of Cortical Folding Comparable Between Cross-sectional Datasets of Fetuses and Preterm Newborns?

Magnetic resonance imaging has proved to be suitable and efficient for in vivo investigation of the early process of brain gyrification in fetuses and preterm newborns but the question remains as to whether cortical-related measurements derived from both cases are comparable or not. Indeed, the developmental folding trajectories drawn up from both populations have not been compared so far, neither from cross-sectional nor from longitudinal datasets. The present study aimed to compare features of cortical folding between healthy fetuses and early imaged preterm newborns on a cross-sectional basis, over a developmental period critical for the folding process (21-36 weeks of gestational age [GA]). A particular attention was carried out to reduce the methodological biases between the 2 populations. To provide an accurate group comparison, several global parameters characterizing the cortical morphometry were derived. In both groups, those metrics provided good proxies for the dramatic brain growth and cortical folding over this developmental period. Except for the cortical volume and the rate of sulci appearance, they depicted different trajectories in both groups suggesting that the transition from into ex utero has a visible impact on cortical morphology that is at least dependent on the GA at birth in preterm newborns.

Shape analysis of the human brain: a brief survey

The survey outlines and compares popular computational techniques for quantitative description of shapes of major structural parts of the human brain, including medial axis and skeletal analysis, geodesic distances, Procrustes analysis, deformable models, spherical harmonics, and deformation morphometry, as well as other less widely used techniques. Their advantages, drawbacks, and emerging trends, as well as results of applications, in particular, for computer-aided diagnostics, are discussed.

BrainPrint: a discriminative characterization of brain morphology

We introduce BrainPrint, a compact and discriminative representation of brain morphology. BrainPrint captures shape information of an ensemble of cortical and subcortical structures by solving the eigenvalue problem of the 2D and 3D Laplace-Beltrami operator on triangular (boundary) and tetrahedral (volumetric) meshes. This discriminative characterization enables new ways to study the similarity between brains; the focus can either be on a specific brain structure of interest or on the overall brain similarity. We highlight four applications for BrainPrint in this article: (i) subject identification, (ii) age and sex prediction, (iii) brain asymmetry analysis, and (iv) potential genetic influences on brain morphology. The properties of BrainPrint require the derivation of new algorithms to account for the heterogeneous mix of brain structures with varying discriminative power. We conduct experiments on three datasets, including over 3000 MRI scans from the ADNI database, 436 MRI scans from the OASIS dataset, and 236 MRI scans from the VETSA twin study. All processing steps for obtaining the compact representation are fully automated, making this processing framework particularly attractive for handling large datasets.

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

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.

A method for assessing nonlinear growth in the fetal cortex

The cerebral cortex is folded into gyri and sulci in the brains of higher mammals. Quantitative study of the process by which the cortex folds during brain development is critical to a complete understanding of normal brain development and neuro-developmental disorders. In this work, we propose a new method by which to localise nonlinearities in the cortical folding process, and thereby identify regions of differential growth across the cortex. Our method is based on spherical harmonic (SPHARM) representation of the cortical surface. Linearity is assessed by comparison of each SPHARM reconstructed surface with an artificial surface constructed using a linear combination of SPHARM coefficients from data at adjoining developmental time points. The resultant quantification of cortical folding development is easy to interpret, and the method has low computational cost. We demonstrate application to a set of experimental MRI data of fetal sheep brains, across key developmental timepoints as the cortex first folds during development.

1910s' brains revisited. Cortical complexity in early 20th century patients with intellectual disability or with dementia praecox

OBJECTIVE

The idea of cortical surface anomalies in subjects with intellectual disability (mental retardation) and schizophrenia can be traced back to early 20th century qualitative observations. Since it is unknown whether modern quantitative measures of cortical complexity and folding would retrieve those early empirical observations, we measured fractal dimension and sulcal span index in photographs of human brains taken in the 1910's.

METHOD

Brain photographs were compared between 36 patients with mental retardation and 21 patients with dementia praecox for the fractal dimension and sulcal span index. Also, a mental retardation subgroup with no-or-non-understandable speech (n = 12) was compared with a subgroup with comprehensible speech (n = 23).

RESULTS

Mental retardation group had a lower whole-brain fractal dimension than dementia praecox, and a higher sulcal span index in left posterior cortex. The mental retardation subgroup with comprehensible speech had a lower fractal dimension in left hemisphere than the subgroup with no-or-non-understandable speech and a lower sulcal index in left posterior cortex.

CONCLUSION

Measures of cortical complexity and folding suggest differences between mental retardation and dementia praecox, and regional variations according to language abilities in mental retardation. The findings provide a unique picture of cortical surface changes in their original untreated form, one century ago.

Simplified gyral pattern in severe developmental microcephalies? New insights from allometric modeling for spatial and spectral analysis of gyrification

The strong positive-allometric relationship between brain size, cortical extension and gyrification complexity, recently highlighted in the general population, could be modified by brain developmental disorders. Indeed, in case of brain growth insufficiency, the pathophysiological relevance of the "simplified gyral pattern" phenotype is strongly disputed since almost no genotype-phenotype correlations have been found in primary microcephalies. Using surface scaling analysis and newly-developed spectral analysis of gyrification (Spangy), we tested whether the gyral simplification in groups of severe microcephalies related to ASPM, PQBP1 or fetal-alcohol-syndrome could be fully explained by brain size reduction according to the allometric scaling law established in typically-developing control groups, or whether an additional disease effect was to be suspected. We found the surface area reductions to be fully explained by scaling effect, leading to predictable folding intensities measured by gyrification indices. As for folding pattern assessed by spectral analysis, scaling effect also accounted for the majority of the variations, but an additional negative or positive disease effect was found in the case of ASPM and PQBP1-linked microcephalies, respectively. Our results point out the necessity of taking allometric scaling into account when studying the gyrification variability in pathological conditions. They also show that the quantitative analysis of gyrification complexity through spectral analysis can enable distinguishing between even (predictable, non-specific) and uneven (unpredictable, maybe disease-specific) gyral simplifications.

Spatial distribution and longitudinal development of deep cortical sulcal landmarks in infants

Sulcal pits, the locally deepest points in sulci of the highly convoluted and variable cerebral cortex, are found to be spatially consistent across human adult individuals. It is suggested that sulcal pits are genetically controlled and have close relationships with functional areas. To date, the existing imaging studies of sulcal pits are mainly focused on adult brains, yet little is known about the spatial distribution and temporal development of sulcal pits in the first 2 years of life, which is the most dynamic and critical period of postnatal brain development. Studying sulcal pits during this period would greatly enrich our limited understandings of the origins and developmental trajectories of sulcal pits, and would also provide important insights into many neurodevelopmental disorders associated with abnormal cortical foldings. In this paper, by using surface-based morphometry, for the first time, we systemically investigated the spatial distribution and temporal development of sulcal pits in major cortical sulci from 73 healthy infants, each with three longitudinal 3T MR scans at term birth, 1 year, and 2 years of age. Our results suggest that the spatially consistent distributions of sulcal pits in major sulci across individuals have already existed at term birth and this spatial distribution pattern keeps relatively stable in the first 2 years of life, despite that the cerebral cortex expands dramatically and the sulcal depth increases considerably during this period. Specially, the depth of sulcal pits increases regionally heterogeneously, with more rapid growth in the high-order association cortex, including the prefrontal and temporal cortices, than the sensorimotor cortex in the first 2 years of life. Meanwhile, our results also suggest that there exist hemispheric asymmetries of the spatial distributions of sulcal pits in several cortical regions, such as the central, superior temporal and postcentral sulci, consistently from birth to 2 years of age, which likely has close relationships with the lateralization of brain functions of these regions. This study provides detailed insights into the spatial distribution and temporal development of deep sulcal landmarks in infants.

Atypical sulcal anatomy in young children with autism spectrum disorder

Autism spectrum disorder is associated with an altered early brain development. However, the specific cortical structure abnormalities underlying this disorder remain largely unknown. Nonetheless, atypical cortical folding provides lingering evidence of early disruptions in neurodevelopmental processes and identifying changes in the geometry of cortical sulci is of primary interest for characterizing these structural abnormalities in autism and their evolution over the first stages of brain development. Here, we applied state-of-the-art sulcus-based morphometry methods to a large highly-selective cohort of 73 young male children of age spanning from 18 to 108 months. Moreover, such large cohort was selected through extensive behavioral assessments and stringent inclusion criteria for the group of 59 children with autism. After manual labeling of 59 different sulci in each hemisphere, we computed multiple shape descriptors for each single sulcus element, hereby separating the folding measurement into distinct factors such as the length and depth of the sulcus. We demonstrated that the central, intraparietal and frontal medial sulci showed a significant and consistent pattern of abnormalities across our different geometrical indices. We also found that autistic and control children exhibited strikingly different relationships between age and structural changes in brain morphology. Lastly, the different measures of sulcus shapes were correlated with the CARS and ADOS scores that are specific to the autistic pathology and indices of symptom severity. Inherently, these structural abnormalities are confined to regions that are functionally relevant with respect to cognitive disorders in ASD. In contrast to those previously reported in adults, it is very unlikely that these abnormalities originate from general compensatory mechanisms unrelated to the primary pathology. Rather, they most probably reflect an early disruption on developmental trajectory that could be part of the primary pathology.

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A new single-site cohort of 73 young children (1.5–11 years) with autism and controls

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State-of-the-art methodology used to compare geometrical attributes of sulci

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Combination of automatic extraction of descriptors with manual identification of sulci

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Clearly evidence localized sulcal shape abnormalities in the autism group

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Different relationships between age and structural changes in brain morphology

A study of cortical morphology in children with fetal alcohol spectrum disorders

Prenatal alcohol exposure is responsible for a broad range of brain structural malformations, which can be studied using magnetic resonance imaging (MRI). Advanced MRI methods have emerged to characterize brain abnormalities, but the teratogenic effects of alcohol on cortical morphology have received little attention to date. Twenty-four 9-year-old children with fetal alcohol spectrum disorders (9 with fetal alcohol syndrome, 15 heavy exposed nonsyndromal children) and 16 age-matched controls were studied to assess the effect of alcohol consumption during pregnancy on cortical morphology. An automated method was applied to 3D T1-weighted images to assess cortical gyrification using global and regional sulcal indices and two region-based morphological measurements, mean sulcal depth and fold opening. Increasing levels of alcohol exposure were related to reduced cortical folding complexity, even among children with normal brain size, indicating a reduction of buried cortical surface. Fold opening was the strongest anatomical correlate of prenatal alcohol intake, indicating a widening of sulci in all regions that were examined. These data identify cortical morphology as a suitable marker for further investigation of brain damage associated with prenatal alcohol exposure.

Reconsidering the evolution of brain, cognition, and behavior in birds and mammals

Despite decades of research, some of the most basic issues concerning the extraordinarily complex brains and behavior of birds and mammals, such as the factors responsible for the diversity of brain size and composition, are still unclear. This is partly due to a number of conceptual and methodological issues. Determining species and group differences in brain composition requires accounting for the presence of taxon-cerebrotypes and the use of precise statistical methods. The role of allometry in determining brain variables should be revised. In particular, bird and mammalian brains appear to have evolved in response to a variety of selective pressures influencing both brain size and composition. “Brain” and “cognition” are indeed meta-variables, made up of the variables that are ecologically relevant and evolutionarily selected. External indicators of species differences in cognition and behavior are limited by the complexity of these differences. Indeed, behavioral differences between species and individuals are caused by cognitive and affective components. Although intra-species variability forms the basis of species evolution, some of the mechanisms underlying individual differences in brain and behavior appear to differ from those between species. While many issues have persisted over the years because of a lack of appropriate data or methods to test them; several fallacies, particularly those related to the human brain, reflect scientists' preconceptions. The theoretical framework on the evolution of brain, cognition, and behavior in birds and mammals should be reconsidered with these biases in mind.