Brain size and folding of the human cerebral cortex

Development and Maturation of the Human Brain, from Infancy to Adolescence

This chapter describes basic principles and key findings regarding the development and maturation of the human brain, the former referring to the pre-natal and early post-natal periods and the latter concerning childhood and adolescence. In both cases, we focus on brain structure as revealed in vivo with multi-modal magnetic resonance imaging (MRI). We begin with a few numbers about the human brain and its cellular composition and a brief overview of a number of MRI-based metrics used to characterize age-related variations in grey and white matter. We then proceed with synthesizing current knowledge about developmental and maturational changes in the cerebral cortex (its thickness, surface area, and intra-cortical myelination) and the underlying white matter (volume and structural properties). To facilitate biological interpretations of MRI-derived metrics, we introduce the concept of virtual histology. We conclude the chapter with a few notes about future directions in the study of factors shaping the human brain from conception onwards.

Cortical gyrification in women and men and the (missing) link to prenatal androgens

Previous studies have reported sex differences in cortical gyrification. Since most cortical folding is principally defined in utero, sex chromosomes as well as gonadal hormones are likely to influence sex-specific aspects of local gyrification. Classic congenital adrenal hyperplasia (CAH) causes high levels of androgens during gestation in females, whereas levels in males are largely within the typical male range. Therefore, CAH provides an opportunity to study the possible effects of prenatal androgens on cortical gyrification. Here, we examined the vertex-wise absolute mean curvature-a common estimate for cortical gyrification-in individuals with CAH (33 women and 20 men) and pair-wise matched controls (33 women and 20 men). There was no significant main effect of CAH and no significant CAH-by-sex interaction. However, there was a significant main effect of sex in five cortical regions, where gyrification was increased in women compared to men. These regions were located on the lateral surface of the brain, specifically left middle frontal (rostral and caudal), right inferior frontal, left inferior parietal, and right occipital. There was no cortical region where gyrification was increased in men compared to women. Our findings do not only confirm prior reports of increased cortical gyrification in female brains but also suggest that cortical gyrification is not significantly affected by prenatal androgen exposure. Instead, cortical gyrification might be determined by sex chromosomes either directly or indirectly-the latter potentially by affecting the underlying architecture of the cortex or the size of the intracranial cavity, which is smaller in women.

The Contribution of Explainable Machine Learning Algorithms Using ROI-based Brain Surface Morphology Parameters in Distinguishing Early-onset Schizophrenia From Bipolar Disorder

RATIONALE AND OBJECTIVES

To differentiate early-onset schizophrenia (EOS) from early-onset bipolar disorder (EBD) using surface-based morphometry measurements and brain volumes using machine learning (ML) algorithms.

METHOD

High-resolution T1-weighted images were obtained to measure cortical thickness (CT), gyrification, gyrification index (GI), sulcal depth (SD), fractal dimension (FD), and brain volumes. After the feature selection step, ML classifiers were applied for each feature set and the combination of them. The SHapley Additive exPlanations (SHAP) technique was implemented to interpret the contribution of each feature.

FINDINGS

144 adolescents (16.2 ± 1.4 years, female=39%) with EOS (n = 81) and EBD (n = 63) were included. The Adaptive Boosting (AdaBoost) algorithm had the highest accuracy (82.75%) in the whole dataset that includes all variables from Destrieux atlas. The best-performing algorithms were K-nearest neighbors (KNN) for FD subset, support vector machine (SVM) for SD subset, and AdaBoost for GI subset. The KNN algorithm had the highest accuracy (accuracy=79.31%) in the whole dataset from the Desikan-Killiany-Tourville atlas.

CONCLUSION

This study demonstrates the use of ML in the differential diagnosis of EOS and EBD using surface-based morphometry measurements. Future studies could focus on multicenter data for the validation of these results.

Scaling patterns of cortical folding and thickness in early human brain development in comparison with primates

Across mammalia, brain morphology follows specific scaling patterns. Bigger bodies have bigger brains, with surface area outpacing volume growth, resulting in increased foldedness. We have recently studied scaling rules of cortical thickness, both local and global, finding that the cortical thickness difference between thick gyri and thin sulci also increases with brain size and foldedness. Here, we investigate early brain development in humans, using subjects from the Developing Human Connectome Project, scanned shortly after pre-term or full-term birth, yielding magnetic resonance images of the brain from 29 to 43 postmenstrual weeks. While the global cortical thickness does not change significantly during this development period, its distribution does, with sulci thinning, while gyri thickening. By comparing our results with our recent work on humans and 11 non-human primate species, we also compare the trajectories of primate evolution with human development, noticing that the 2 trends are distinct for volume, surface area, cortical thickness, and gyrification index. Finally, we introduce the global shape index as a proxy for gyrification index; while correlating very strongly with gyrification index, it offers the advantage of being calculated only from local quantities without generating a convex hull or alpha surface.

Loss of control eating in children is associated with altered cortical and subcortical brain structure

Introduction

Loss of control (LOC) eating is the perceived inability to control how much is eaten, regardless of actual amount consumed. Childhood LOC-eating is a risk factor for the development of binge-eating disorder (BED), but its neurobiological basis is poorly understood. Studies in children with BED have shown both increased gray matter volume in regions related to top-down cognitive control (e.g., dorsolateral prefrontal cortex) and reward-related decision making (e.g., orbital frontal cortex) relative to healthy controls. However, no studies have examined brain structure in children with LOC-eating. To identify potential neurobiological precursors of BED, we conducted secondary analysis of five studies that conducted T1 MPRAGE scans.

Methods

A total of 143, 7-12-year-old children (M = 8.9 years, 70 boys) were included in the study, 26% of which (n = 37) reported LOC-eating (semi-structured interview). Age, sex, and obesity status did not differ by LOC-eating. Differences between children with and without LOC were examined for gray matter volume, cortical thickness, gyrification, sulci depth, and cortical complexity after adjusting for age, sex, total intercranial volume, weight status, and study.

Results

Children with LOC, relative to those without, had greater gray matter volume in right orbital frontal cortex but lower gray matter volume in right parahippocampal gyrus, left CA4/dentate gyrus, and left cerebellar lobule VI. While there were no differences in cortical thickness or gyrification, children with LOC-eating had great sulci depth in left anterior cingulate cortex and cuneus and greater cortical complexity in right insular cortex.

Discussion

Together, this indicates that children with LOC-eating have structural differences in regions related to cognitive control, reward-related decision-making, and regulation of eating behaviors.

CAT: a computational anatomy toolbox for the analysis of structural MRI data

A large range of sophisticated brain image analysis tools have been developed by the neuroscience community, greatly advancing the field of human brain mapping. Here we introduce the Computational Anatomy Toolbox (CAT)-a powerful suite of tools for brain morphometric analyses with an intuitive graphical user interface but also usable as a shell script. CAT is suitable for beginners, casual users, experts, and developers alike, providing a comprehensive set of analysis options, workflows, and integrated pipelines. The available analysis streams-illustrated on an example dataset-allow for voxel-based, surface-based, and region-based morphometric analyses. Notably, CAT incorporates multiple quality control options and covers the entire analysis workflow, including the preprocessing of cross-sectional and longitudinal data, statistical analysis, and the visualization of results. The overarching aim of this article is to provide a complete description and evaluation of CAT while offering a citable standard for the neuroscience community.

From Black Holes Entropy to Consciousness: The Dimensions of the Brain Connectome

It has been shown that the theory of relativity can be applied physically to the functioning brain, so that the brain connectome should be considered as a four-dimensional spacetime entity curved by brain activity, just as gravity curves the four-dimensional spacetime of the physical world. Following the most recent developments in modern theoretical physics (black hole entropy, holographic principle, AdS/CFT duality), we conjecture that consciousness can naturally emerge from this four-dimensional brain connectome when a fifth dimension is considered, in the same way that gravity emerges from a 'flat' four-dimensional quantum world, without gravitation, present at the boundaries of a five-dimensional spacetime. This vision makes it possible to envisage quantitative signatures of consciousness based on the entropy of the connectome and the curvature of spacetime estimated from data obtained by fMRI in the resting state (nodal activity and functional connectivity) and constrained by the anatomical connectivity derived from diffusion tensor imaging.

Orbitofrontal sulcal patterns in catatonia

BACKGROUND

Catatonia is a psychomotor syndrome frequently observed in disorders with neurodevelopmental impairments, including psychiatric disorders such as schizophrenia. The orbitofrontal cortex (OFC) has been repeatedly associated with catatonia. It presents with an important interindividual morphological variability, with three distinct H-shaped sulcal patterns, types I, II, and III, based on the continuity of the medial and lateral orbital sulci. Types II and III have been identified as neurodevelopmental risk factors for schizophrenia. The sulcal pattern of the OFC has never been investigated in catatonia despite the role of the OFC in the pathophysiology and the neurodevelopmental component of catatonia.

METHODS

In this context, we performed a retrospective analysis of the OFC sulcal pattern in carefully selected homogeneous and matched subgroups of schizophrenia patients with catatonia (N = 58) or without catatonia (N = 65), and healthy controls (N = 82).

RESULTS

Logistic regression analyses revealed a group effect on OFC sulcal pattern in the left (χ2 = 18.1; p < .001) and right (χ2 = 28.3; p < .001) hemispheres. Catatonia patients were found to have more type III and less type I in both hemispheres compared to healthy controls and more type III on the left hemisphere compared to schizophrenia patients without catatonia.

CONCLUSION

Because the sulcal patterns are indirect markers of early brain development, our findings support a neurodevelopmental origin of catatonia and may shed light on the pathophysiology of this syndrome.

Variants in PTEN Are Associated With a Diverse Spectrum of Cortical Dysplasia

BACKGROUND

Inactivating mutations in PTEN are among the most common causes of megalencephaly. Activating mutations in other nodes of the PI3K/AKT/MTOR signaling pathway are recognized as a frequent cause of cortical brain malformations. Only recently has PTEN been associated with cortical malformations, and analyses of their prognostic significance have been limited.

METHODS

Retrospective neuroimaging analysis and detailed chart review were conducted on 20 participants identified with pathogenic or likely pathogenic mutations in PTEN and a cortical brain malformation present on brain magnetic resonance imaging.

RESULTS

Neuroimaging analysis revealed four main cerebral phenotypes-hemimegalencephaly, focal cortical dysplasia, polymicrogyria (PMG), and a less severe category, termed "macrocephaly with complicated gyral pattern" (MCG). Although a high proportion of participants (90%) had neurodevelopmental findings on presentation, outcomes varied and were favorable in over half of participants. Consistent with prior work, 39% of participants had autism spectrum disorder and 19% of participants with either pure-PMG or pure-MCG phenotypes had epilepsy. Megalencephaly and systemic overgrowth were common, but other systemic features of PTEN-hamartoma tumor syndrome were absent in over one-third of participants.

CONCLUSIONS

A spectrum of cortical dysplasias is present in individuals with inactivating mutations in PTEN. Future studies are needed to clarify the prognostic significance of each cerebral phenotype, but overall, we conclude that despite a high burden of neurodevelopmental disease, long-term outcomes may be favorable. Germline testing for PTEN mutations should be considered in cases of megalencephaly and cortical brain malformations even in the absence of other findings, including cognitive impairment.

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.

Cortical and subcortical brain morphometry abnormalities in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia

Neuroimaging studies have documented morphometric brain abnormalities in schizophrenia, but less is known about them in individuals at clinical high-risk for psychosis (CHR-P), including how they compare with those observed in early schizophrenia (ESZ). Accordingly, we implemented multivariate profile analysis of regional morphometric profiles in CHR-P (n = 89), ESZ (n = 93) and healthy controls (HC; n = 122). ESZ profiles differed from HC and CHR-P profiles, including 1) cortical thickness: significant level reduction and regional non-parallelism reflecting widespread thinning, except for entorhinal and pericalcarine cortex, 2) basal ganglia volume: significant level increase and regional non-parallelism reflecting larger caudate and pallidum, and 3) ventricular volume: significant level increase with parallel regional profiles. CHR-P and ESZ cerebellar profiles showed significant non-parallelism with HC profiles. Regional profiles did not significantly differ between groups for cortical surface area or subcortical volume. Compared to CHR-P followed for ≥18 months without psychosis conversion (n = 31), CHR-P converters (n = 17) showed significant non-parallel ventricular volume expansion reflecting specific enlargement of lateral and inferolateral regions. Antipsychotic dosage in ESZ was significantly correlated with frontal cortical thinning. Results suggest that morphometric abnormalities in ESZ are not present in CHR-P, except for ventricular enlargement, which was evident in CHR-P who developed psychosis.

From fossils to mind

Fossil endocasts record features of brains from the past: size, shape, vasculature, and gyrification. These data, alongside experimental and comparative evidence, are needed to resolve questions about brain energetics, cognitive specializations, and developmental plasticity. Through the application of interdisciplinary techniques to the fossil record, paleoneurology has been leading major innovations. Neuroimaging is shedding light on fossil brain organization and behaviors. Inferences about the development and physiology of the brains of extinct species can be experimentally investigated through brain organoids and transgenic models based on ancient DNA. Phylogenetic comparative methods integrate data across species and associate genotypes to phenotypes, and brains to behaviors. Meanwhile, fossil and archeological discoveries continuously contribute new knowledge. Through cooperation, the scientific community can accelerate knowledge acquisition. Sharing digitized museum collections improves the availability of rare fossils and artifacts. Comparative neuroanatomical data are available through online databases, along with tools for their measurement and analysis. In the context of these advances, the paleoneurological record provides ample opportunity for future research. Biomedical and ecological sciences can benefit from paleoneurology's approach to understanding the mind as well as its novel research pipelines that establish connections between neuroanatomy, genes and behavior.

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.

Accurate localization and coactivation profiles of the frontal eye field and inferior frontal junction: an ALE and MACM fMRI meta-analysis

The frontal eye field (FEF) and the inferior frontal junction (IFJ) are prefrontal structures involved in mediating multiple aspects of goal-driven behavior. Despite being recognized as prominent nodes of the networks underlying spatial attention and oculomotor control, and working memory and cognitive control, respectively, the limited quantitative evidence on their precise localization has considerably impeded the detailed understanding of their structure and connectivity. In this study, we performed an activation likelihood estimation (ALE) fMRI meta-analysis by selecting studies that employed standard paradigms to accurately infer the localization of these regions in stereotaxic space. For the FEF, we found the highest spatial convergence of activations for prosaccade and antisaccade paradigms at the junction of the precentral sulcus and superior frontal sulcus. For the IFJ, we found consistent activations across oddball/attention, working memory, task-switching and Stroop paradigms at the junction of the inferior precentral sulcus and inferior frontal sulcus. We related these clusters to previous meta-analyses, sulcal/gyral neuroanatomy, and a comprehensive brain parcellation, highlighting important differences compared to their results and taxonomy. Finally, we leveraged the ALE peak coordinates as seeds to perform a meta-analytic connectivity modeling (MACM) analysis, which revealed systematic coactivation patterns spanning the frontal, parietal, and temporal cortices. We decoded the behavioral domains associated with these coactivations, suggesting that these may allow FEF and IFJ to support their specialized roles in flexible behavior. Our study provides the meta-analytic groundwork for investigating the relationship between functional specialization and connectivity of two crucial control structures of the prefrontal cortex.

Psychotic Like Experiences in Healthy Adolescents are Underpinned by Lower Fronto-Temporal Cortical Gyrification: a Study from the IMAGEN Consortium

BACKGROUND AND HYPOTHESIS

Psychotic Like Experiences (PLEs) are widely prevalent in children and adolescents and increase the risk of developing psychosis. Cortical gyrification characterizes brain development from in utero till about the first 2 years of life and can be measured in later years as static gyrification changes demonstrating neurodevelopment and dynamic gyrification changes reflecting brain maturation during adolescence. We hypothesized that PLEs would be associated with static cortical gyrification changes reflecting a neurodevelopmental abnormality.

STUDY DESIGN

We studied 1252 adolescents recruited in the IMAGEN consortium. We used a longitudinal study design, with Magnetic Resonance Imaging measurements at age 14 years and age 19 years; measurement of PLEs using the Community Assessment of Psychic Experiences (CAPE) questionnaire at age 19 years; and clinical diagnoses at age 23 years.

STUDY RESULTS

Our results show static gyrification changes in adolescents with elevated PLEs on 3 items of the CAPE-voice hearing, unusual experiences of receiving messages, and persecutory ideas-with lower cortical gyrification in fronto-temporal regions in the left hemisphere. This group also demonstrated dynamic gyrification changes with higher cortical gyrification in right parietal cortex in late adolescence; a finding that we replicated in an independent sample of patients with first-episode psychosis. Adolescents with high PLEs were also 5.6 times more likely to transition to psychosis in adulthood by age 23 years.

CONCLUSIONS

This is the largest study in adolescents that demonstrates fronto-temporal abnormality of cortical gyrification as a potential biomarker for vulnerability to PLEs and transition to psychosis.

A cross-sectional and longitudinal study of human brain development: The integration of cortical thickness, surface area, gyrification index, and cortical curvature into a unified analytical framework

Brain maturation studies typically examine relationships linking a single morphometric feature with cognition, behavior, age, or other demographic characteristics. However, the coordinated spatiotemporal arrangement of morphological features across development and their associations with behavior are unclear. Here, we examine covariation across multiple cortical features (cortical thickness [CT], surface area [SA], local gyrification index [GI], and mean curvature [MC]) using magnetic resonance images from the NIMH developmental cohort (ages 5-25). Neuroanatomical covariance was examined using non-negative matrix factorization (NMF), which decomposes covariance resulting in a parts-based representation. Cross-sectionally, we identified six components of covariation which demonstrate differential contributions of CT, GI, and SA in hetero- vs. unimodal areas. Using this technique to examine covariance in rates of change to identify longitudinal sources of covariance highlighted preserved SA in unimodal areas and changes in CT and GI in heteromodal areas. Using behavioral partial least squares (PLS), we identified a single latent variable (LV) that recapitulated patterns of reduced CT, GI, and SA related to older age, with limited contributions of IQ and SES. Longitudinally, PLS revealed three LVs that demonstrated a nuanced developmental pattern that highlighted a higher rate of maturational change in SA and CT in higher IQ and SES females. Finally, we situated the components in the changing architecture of cortical gradients. This novel characterization of brain maturation provides an important understanding of the interdependencies between morphological measures, their coordinated development, and their relationship to biological sex, cognitive ability, and the resources of the local environment.

Ensemble learning for the detection of pli-de-passages in the superior temporal sulcus

The surface of the cerebral cortex is very convoluted, with a large number of folds, the cortical sulci. These folds are extremely variable from one individual to another, and this large variability is a problem for many applications in neuroscience and brain imaging. In particular, sulcal geometry (shape) and sulcal topology (branches, number of pieces) are very variable. "Plis de passages" (PPs) or "annectant gyri" can explain part of the topological variability, namely why sulci have a variable number of pieces across subjects. The concept of PPs was first introduced by Gratiolet (1854) to describe transverse gyri that interconnect both sides of a sulcus, that are frequently buried in the depth of sulci, and that are sometimes apparent on the cortical surface, hence seemingly interrupting the course of sulci and separating them in several pieces. Nevertheless, the difficulty of identifying PPs and the lack of systematic methods to automatically detect them has limited their use. However, based on a recent characterization of PPs in the superior temporal sulcus, we present here a method to automatically detect PPs in the superior temporal sulcus. Local morphology within the sulcus is characterized using cortical surface profiling, and the three-dimensional PP recognition problem is performed as a two-dimensional image classification problem with class-imbalance. This is solved by using an ensemble support vector machine model (EnsSVM) with a rebalancing strategy. Cross validation and quantitative experimental results on an external dataset show the effectiveness and robustness of our approach.

The neural coding of tonal working memory load: An functional magnetic resonance imaging study

Tonal working memory load refers to the number of pitches held in working memory. It has been found that different verbal working memory loads have different neural coding (local neural activity pattern). However, whether there exists a comparable phenomenon for tonal working memory load remains unclear. In this study, we used a delayed match-to-sample paradigm to evoke tonal working memory. Neural coding of different tonal working memory loads was studied with a surface space and convolution neural network (CNN)-based multivariate pattern analysis (SC-MVPA) method. We found that first, neural coding of tonal working memory was significantly different from that of the control condition in the bilateral superior temporal gyrus (STG), supplement motor area (SMA), and precentral gyrus (PCG). Second, neural coding of nonadjacent tonal working memory loads was distinguishable in the bilateral STG and PCG. Third, neural coding is gradually enhanced as the memory load increases. Finally, neural coding of tonal working memory was encoded in the bilateral STG in the encoding phase and shored in the bilateral PCG and SMA in the maintenance phase.

Brain gyrification in bipolar disorder: a systematic review of neuroimaging studies

Bipolar disorder (BD) is a severe mental illness with a strong genetic component. Genetic variations have been involved in the risk of this disorder, including those mediating brain function and neurodevelopment. Early neurodevelopment and neuroprogression processes could be reflected in brain gyrification patterns and help optimize the prediction and diagnosis of such disorders that is often delayed. Previous neuroimaging studies using this measure in patients with bipolar disorder revealed controversial results. This systematic review aimed to summarize available neuroimaging investigations on gyrification in BD compared to healthy controls (HC) and/or other psychiatric groups. Fourteen studies including 733 patients with BD, 585 patients with schizophrenia (SCZ), 90 with schizoaffective disorder (SZA), and 1380 healthy subjects were identified. Overall, a heterogeneous pattern of gyrification emerged between patients with BD and HC. Interestingly, increased gyrification or no differences were also observed in patients with BD compared to those with the schizophrenia-spectrum disorders. Furthermore, relatives of patients with BD showed lower or no differences in gyrification compared to healthy subjects without a family history of affective illness. Differences in the design and in methodological approaches could have contributed to the heterogeneity of the findings. The current review supports an altered brain gyrification pattern that underlies the pathophysiology of BD spanning large anatomical and functional neural networks, associated with altered cognitive functioning, difficulties in processing and affective regulation, and clinical symptoms. Longitudinal studies are needed to test different bipolar phenotypes and pharmacological effects on gyrification.

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.

Quantitative Structural Brain Magnetic Resonance Imaging Analyses: Methodological Overview and Application to Rett Syndrome

Congenital genetic disorders often present with neurological manifestations such as neurodevelopmental disorders, motor developmental retardation, epilepsy, and involuntary movement. Through qualitative morphometric evaluation of neuroimaging studies, remarkable structural abnormalities, such as lissencephaly, polymicrogyria, white matter lesions, and cortical tubers, have been identified in these disorders, while no structural abnormalities were identified in clinical settings in a large population. Recent advances in data analysis programs have led to significant progress in the quantitative analysis of anatomical structural magnetic resonance imaging (MRI) and diffusion-weighted MRI tractography, and these approaches have been used to investigate psychological and congenital genetic disorders. Evaluation of morphometric brain characteristics may contribute to the identification of neuroimaging biomarkers for early diagnosis and response evaluation in patients with congenital genetic diseases. This mini-review focuses on the methodologies and attempts employed to study Rett syndrome using quantitative structural brain MRI analyses, including voxel- and surface-based morphometry and diffusion-weighted MRI tractography. The mini-review aims to deepen our understanding of how neuroimaging studies are used to examine congenital genetic disorders.

Cortical and Subcortical Structural Morphometric Profiles in Individuals with Nonaffective and Affective Early Illness Psychosis

Research has found strong evidence for common and distinct morphometric brain abnormality profiles in nonaffective psychosis (NAff-P) and affective psychosis (Aff-P). Due to chronicity and prolonged medication exposure confounds, it is crucial to examine structural morphometry early in the course of psychosis. Using Human Connectome Project-Early Psychosis data, multivariate profile analyses were implemented to examine regional profiles for cortical thickness, cortical surface area, subcortical volume, and ventricular volume in healthy control (HC; n = 56), early illness NAff-P (n = 83), and Aff-P (n = 30) groups after accounting for normal aging. Associations with symptom severity, functioning, and cognition were also examined. Group regional profiles were significantly nonparallel and differed in level for cortical thickness (P < .001), with NAff-P having widespread cortical thinning relative to HC and Aff-P and some regions showing greater deficits than others. Significant nonparallelism of group regional profiles was also evident for cortical surface area (P < .006), with Aff-P and N-Aff-P differing from HC and from each other (P < .001). For subcortical volume, there was significant profile nonparallelism with NAff-P having an enlarged left pallidum and smaller accumbens and hippocampus (P < .028), and Aff-P having a smaller accumbens and amygdala (P < .006), relative to HC. NAff-P also had larger basal ganglia compared to Aff-P. Furthermore, NAff-P had enlarged ventricles (P < .055) compared to HC and Aff-P. Additionally, greater ventricular volume was associated with increased manic symptoms in NAff-P and Aff-P. Overall, this study found common and distinct regional morphometric profile abnormalities in early illness NAff-P and Aff-P, providing evidence for both shared and disease-specific pathophysiological processes.

Associations between Brain Reserve Proxies and Clinical Progression in Alzheimer's Disease Dementia

The purpose of this study was to investigate whether brain and cognitive reserves were associated with the clinical progression of AD dementia. We included participants with AD dementia from the Alzheimer’s Disease Neuroimaging Initiative, provided they were followed up at least once, and candidate proxies for cognitive (education for early-life reserve and Adult Reading Test for late-life reserve) or brain reserve (intracranial volume [ICV] for early-life reserve and the composite value of [¹⁸F] fluorodeoxyglucose positron emission tomography regions of interest (FDG-ROIs) for late-life reserve) were available. The final analysis included 120 participants. Cox proportional hazards model revealed that FDG-ROIs were the only significant predictor of clinical progression. Subgroup analysis revealed a significant association between FDG-ROIs and clinical progression only in the larger ICV group (HR = 0.388, p = 0.028, 95% CI 0.167–0.902). Our preliminary findings suggest that relatively preserved cerebral glucose metabolism might delay further clinical progression in AD dementia, particularly in the greater ICV group. In addition to ICV, cerebral glucose metabolism could play an important role as a late-life brain reserve in the process of neurodegeneration. Distinguishing between early- and late-life reserves, and considering both proxies simultaneously, would provide a wider range of factors associated with the prognosis of AD dementia.

Hierarchical Self-Assembly of Metal-Ion-Modulated Chitosan Tubules

Soft materials such as gels or biological tissues can develop via self-assembly under chemo-mechanical forces. Here, we report the instantaneous formation of soft tubular structures with a two-level hierarchy by injecting a mixture of inorganic salt and chitosan (CS) solution from below into a reactor filled with alkaline solution. Folding and wrinkling instabilities occur on the originally smooth surface controlled by the salt composition and concentration. Liesegang-like precipitation patterns develop on the outer surface on a μm length scale in the presence of calcium chloride, while the precipitate particles are distributed evenly in the bulk as corroborated by X-ray μ-CT. On the other hand, barium hydroxide precipitates out only in the thin outer layer of the CS tubule when barium chloride is introduced into the CS solution. Independent of the concentration of the weakly interacting salt, an electric potential gradient across the CS membrane develops, which vanishes when the pH difference between the two sides of the membrane diminishes.

Consistency in Geometry Among Coronary Atherosclerotic Plaques Extracted From Computed Tomography Angiography

Background: The three-dimensional (3D) geometry of coronary atherosclerotic plaques is associated with plaque growth and the occurrence of coronary artery disease. However, there is a lack of studies on the 3D geometric properties of coronary plaques. We aim to investigate if coronary plaques of different sizes are consistent in geometric properties.

Methods: Nineteen cases with symptomatic stenosis caused by atherosclerotic plaques in the left coronary artery were included. Based on attenuation values on computed tomography angiography images, coronary atherosclerotic plaques and calcifications were identified, 3D reconstructed, and manually revised. Multidimensional geometric parameters were measured on the 3D models of plaques and calcifications. Linear and non-linear (i.e., power function) fittings were used to investigate the relationship between multidimensional geometric parameters (length, surface area, volume, etc.). Pearson correlation coefficient (r), R-squared, and p-values were used to evaluate the significance of the relationship. The analysis was performed based on cases and plaques, respectively. Significant linear relationship was defined as R-squared > 0.25 and p < 0.05.

Results: In total, 49 atherosclerotic plaques and 56 calcifications were extracted. In the case-based analysis, significant linear relationships were found between number of plaques and number of calcifications (r = 0.650, p = 0.003) as well as total volume of plaques (r = 0.538, p = 0.018), between number of calcifications and total volume of plaques (r = 0.703, p = 0.001) as well as total volume of calcification (r = 0.646, p = 0.003), and between the total volumes of plaques and calcifications (r = 0.872, p < 0.001). In plaque-based analysis, the power function showed higher R-squared values than the linear function in fitting the relationships of multidimensional geometric parameters. Two presumptions of plaque geometry in different growth stages were proposed with simplified geometric models developed. In the proposed models, the exponents in the power functions of geometric parameters were in accordance with the fitted values.

Conclusion: In patients with coronary artery disease, coronary plaques and calcifications are positively related in number and volume. Different coronary plaques are consistent in the relationship between geometry parameters in different dimensions.

Impact of Cardiopulmonary Bypass on Neurogenesis and Cortical Maturation

OBJECTIVE

Neurodevelopmental delays and frontal lobe cortical dysmaturation are widespread among children with congenital heart disease (CHD). The subventricular zone (SVZ) is the largest pool of neural stem/progenitor cells in the postnatal brain. Our aim is to determine the effects of cardiopulmonary bypass (CPB) on neurogenesis and cortical maturation in piglets whose SVZ development is similar to human infants.

METHODS

Three-week-old piglets (n = 29) were randomly assigned to control (no surgery), mild-CPB (34°C full flow for 60 minutes) and severe-CPB groups (25°C circulatory-arrest for 60 minutes). The SVZ and frontal lobe were analyzed with immunohistochemistry 3 days and 4 weeks postoperatively. MRI of the frontal lobe was used to assess cortical development.

RESULTS

SVZ neurogenic activity was reduced up to 4 weeks after both mild and severe CPB-induced insults. CPB also induced decreased migration of young neurons to the frontal lobe, demonstrating that CPB impairs postnatal neurogenesis. MRI 4 weeks after CPB displayed a decrease in gyrification index and cortical volume of the frontal lobe. Cortical fractional anisotropy was increased after severe CPB injury, indicating a prolonged deleterious impact of CPB on cortical maturation. Both CPB-induced insults displayed a significant change in densities of three major inhibitory neurons, suggesting excitatory-inhibitory imbalance in the frontal cortex. In addition, different CPB insults altered different subpopulations of inhibitory neurons.

INTERPRETATION

Our results provide novel insights into cellular mechanisms contributing to CHD-induced neurological impairments. Further refinement of CPB hardware and techniques is necessary to improve long-term frontal cortical dysmaturation observed in children with CHD. ANN NEUROL 2021.

Neuroanatomical norms in the UK Biobank: The impact of allometric scaling, sex, and age

Few neuroimaging studies are sufficiently large to adequately describe population‐wide variations. This study's primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40,028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry—the nonlinear scaling relationship between a region and brain size (e.g., total brain volume)—across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |β| = .13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. Finally, we contribute to the reproducibility of research on sex differences in the brain by replicating previous studies examining cerebral sex differences. This large‐scale study advances our understanding of age, sex, and brain allometry's impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size.

Associations between long-term psychosis risk, probabilistic category learning, and attenuated psychotic symptoms with cortical surface morphometry

Neuroimaging studies have consistently found structural cortical abnormalities in individuals with schizophrenia, especially in structural hubs. However, it is unclear what abnormalities predate psychosis onset and whether abnormalities are related to behavioral performance and symptoms associated with psychosis risk. Using surface-based morphometry, we examined cortical volume, gyrification, and thickness in a psychosis risk group at long-term risk for developing a psychotic disorder (n = 18; i.e., extreme positive schizotypy plus interview-rated attenuated psychotic symptoms [APS]) and control group (n = 19). Overall, the psychosis risk group exhibited cortical abnormalities in multiple structural hub regions, with abnormalities associated with poorer probabilistic category learning, a behavioral measure strongly associated with psychosis risk. For instance, the psychosis risk group had hypogyria in a right posterior midcingulate cortical hub and left superior parietal cortical hub, as well as decreased volume in a right pericalcarine hub. Morphometric measures in all of these regions were also associated with poorer probabilistic category learning. In addition to decreased right pericalcarine volume, the psychosis risk group exhibited a number of other structural abnormalities in visual network structural hub regions, consistent with previous evidence of visual perception deficits in psychosis risk. Further, severity of APS hallucinations, delusional ideation, and suspiciousness/persecutory ideas were associated with gyrification abnormalities, with all domains associated with hypogyria of the right lateral orbitofrontal cortex. Thus, current results suggest that structural abnormalities, especially in structural hubs, are present in psychosis risk and are associated both with poor learning on a psychosis risk-related task and with APS severity.

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.

New insights into the dynamic development of the cerebral cortex in childhood and adolescence: Integrating macro- and microstructural MRI findings

Through dynamic transactional processes between genetic and environmental factors, childhood and adolescence involve reorganization and optimization of the cerebral cortex. The cortex and its development plays a crucial role for prototypical human cognitive abilities. At the same time, many common mental disorders appear during these critical phases of neurodevelopment. Magnetic resonance imaging (MRI) can indirectly capture several multifaceted changes of cortical macro- and microstructure, of high relevance to further our understanding of the neural foundation of cognition and mental health. Great progress has been made recently in mapping the typical development of cortical morphology. Moreover, newer less explored MRI signal intensity and specialized quantitative T2 measures have been applied to assess microstructural cortical development. We review recent findings of typical postnatal macro- and microstructural development of the cerebral cortex from early childhood to young adulthood. We cover studies of cortical volume, thickness, area, gyrification, T1-weighted (T1w) tissue contrasts such a grey/white matter contrast, T1w/T2w ratio, magnetization transfer and myelin water fraction. Finally, we integrate imaging studies with cortical gene expression findings to further our understanding of the underlying neurobiology of the developmental changes, bridging the gap between ex vivo histological- and in vivo MRI studies.

Geometric deep learning on brain shape predicts sex and age

The complex relationship between the shape and function of the human brain remains elusive despite extensive studies of cortical folding over many decades. The analysis of cortical gyrification presents an opportunity to advance our knowledge about this relationship, and better understand the etiology of a variety of pathologies involving diverse degrees of cortical folding abnormalities. Hypothesis-driven surface-based approaches have been shown to be particularly efficient in their ability to accurately describe unique features of the folded sheet topology of the cortical ribbon. However, the utility of these approaches has been blunted by their reliance on manually defined features aiming to capture the relevant geometric properties of cortical folding. In this paper, we propose an entirely novel, data-driven deep-learning based method to analyze the brain's shape that eliminates this reliance on manual feature definition. This method builds on the emerging field of geometric deep-learning and uses traditional convolutional neural network architecture uniquely adapted to the surface representation of the cortical ribbon. This method is a complete departure from prior brain MRI CNN investigations, all of which have relied on three dimensional MRI data and interpreted features of the MRI signal for prediction. MRI data from 6410 healthy subjects obtained from 11 publicly available data repositories were used for analysis. Ages ranged from 6 to 89 years. Both inner and outer cortical surfaces were extracted using Freesurfer and then registered into MNI space. For purposes of method development, both a classification and regression challenge were introduced for network learning including sex and age prediction, respectively. Two independent graph convolutional neural networks (gCNNs) were trained, the first of which to predict subject's self-identified sex, the second of which to predict subject's age. Class Activation Maps (CAM) and Regression Activation Maps (RAM) were constructed respectively to map the topographic distribution of the most influential brain regions involved in the decision process for each gCNN. Using this approach, the gCNN was able to predict a subject's sex with an average accuracy of 87.99 % and achieved a Person's coefficient of correlation of 0.93 with an average absolute error 4.58 years when predicting a subject's age. We believe this shape-based convolutional classifier offers a novel, data-driven approach to define biomedically relevant features from the brain at both the population and single subject levels and therefore lays a critical foundation for future precision medicine applications.

Multimodal prognosis of negative symptom severity in individuals at increased risk of developing psychosis

Negative symptoms occur frequently in individuals at clinical high risk (CHR) for psychosis and contribute to functional impairments. The aim of this study was to predict negative symptom severity in CHR after 9 months. Predictive models either included baseline negative symptoms measured with the Structured Interview for Psychosis-Risk Syndromes (SIPS-N), whole-brain gyrification, or both to forecast negative symptoms of at least moderate severity in 94 CHR. We also conducted sequential risk stratification to stratify CHR into different risk groups based on the SIPS-N and gyrification model. Additionally, we assessed the models' ability to predict functional outcomes in CHR and their transdiagnostic generalizability to predict negative symptoms in 96 patients with recent-onset psychosis (ROP) and 97 patients with recent-onset depression (ROD). Baseline SIPS-N and gyrification predicted moderate/severe negative symptoms with significant balanced accuracies of 68 and 62%, while the combined model achieved 73% accuracy. Sequential risk stratification stratified CHR into a high (83%), medium (40-64%), and low (19%) risk group regarding their risk of having moderate/severe negative symptoms at 9 months follow-up. The baseline SIPS-N model was also able to predict social (61%), but not role functioning (59%) at above-chance accuracies, whereas the gyrification model achieved significant accuracies in predicting both social (76%) and role (74%) functioning in CHR. Finally, only the baseline SIPS-N model showed transdiagnostic generalization to ROP (63%). This study delivers a multimodal prognostic model to identify those CHR with a clinically relevant negative symptom severity and functional impairments, potentially requiring further therapeutic consideration.

The social brain in female autism: a structural imaging study of twins

A female advantage in social cognition (SoC) might contribute to women's underrepresentation in autism spectrum disorder (ASD). The latter could be underpinned by sex differences in social brain structure. This study investigated the relationship between structural social brain networks and SoC in females and males in relation to ASD and autistic traits in twins. We used a co-twin design in 77 twin pairs (39 female) aged 12.5 to 31.0 years. Twin pairs were discordant or concordant for ASD or autistic traits, discordant or concordant for other neurodevelopmental disorders or concordant for neurotypical development. They underwent structural magnetic resonance imaging and were assessed for SoC using the naturalistic Movie for the Assessment of Social Cognition. Autistic traits predicted reduced SoC capacities predominantly in male twins, despite a comparable extent of autistic traits in each sex, although the association between SoC and autistic traits did not differ significantly between the sexes. Consistently, within-pair associations between SoC and social brain structure revealed that lower SoC ability was associated with increased cortical thickness of several brain regions, particularly in males. Our findings confirm the notion that sex differences in SoC in association with ASD are underpinned by sex differences in brain structure.

Growth and form, Lie algebras and special functions

The formation of a biological organism, or an organ within it, can often be regarded as the unfolding of successive equilibria of a mechanical system. In a mathematical model, these changes of equilibria may be considered to be responses of mechanically constrained systems to a change of a reference configuration and of a reference metric, which are in turn driven by genes and their expression. This paper brings together three major threads of research. These are: Lie-type symmetries of equations; models as well as data on growth and pattern formation; and the relation between Lie algebras (and groups) and special functions associated with them. We show that symmetry methods can be generalized to map between solutions to models with different reference metrics. In the case in which we attempt to obtain such equations, they seem too complicated to be of any immediate service to the community of researchers on cortical growth. However, models and data on growth may be used to obtain generators of these Lie algebras empirically and numerically. These generators result in new classes of special functions. The paper is an invitation to develop what we may call empirical Lie algebras and associated functions. The hypothesis that remains to be tested is whether the confluence of ideas described in the paper, namely the Lie algebraic-related consequences of pattern formation and growth, prove useful for deepened understanding of biological growth patterns.

Application of transcranial magnetic stimulation for major depression: Coil design and neuroanatomical variability considerations

High-frequency repeated transcranial magnetic stimulation (rTMS) as a treatment for major depressive disorder (MDD) has received FDA clearance for both the figure-of-8 coil (figure-8 coil) and the H1 coil. The FDA-cleared MDD protocols for both coils include high frequency (10-18 Hz) stimulation targeting the dorsolateral prefrontal cortex (dlPFC) at an intensity that is 120% of the right-hand resting motor threshold. Despite these similar parameters, the two coils generate distinct electrical fields (e-fields) which result in differences in the cortical stimulation they produce. Due to the differences in coil designs, the H1 coil induces a stimulation e-field that is broader and deeper than the one induced by the figure-8 coil. In this paper we review theoretical and clinical implications of these differences between the two coils and compare evidence of their safety and efficacy in treating MDD. We present the design principles of the coils, the challenges of identifying, finding, and stimulating the optimal brain target of each individual (both from functional and connectivity perspectives), and the possible implication of stimulating outside that target. There is only one study that performed a direct comparison between clinical effectiveness of the two coils, using the standard FDA-approved protocols in MDD patients. This study indicated clinical superiority of the H1 coil but did not measure long-term effects. Post-marketing data suggest that both coils have a similar safety profile in clinical practice, whereas effect size comparisons of the two respective FDA pivotal trials suggests that the H1 coil may have an advantage in efficacy. We conclude that further head-to-head experiments are needed, especially ones that will compare long-term effects and usage of similar temporal stimulation parameters and similar number of pulses.

Boys with autism spectrum disorder have distinct cortical folding patterns underpinning impaired self-regulation: a surface-based morphometry study

Although impaired self-regulation (dysregulation) in autism spectrum disorder (ASD) garnered increasing awareness, the neural mechanism of dysregulation in ASD are far from conclusive. To complement our previous voxel-based morphometry findings, we estimated the cortical thickness, surface area, and local gyrification index based on the surface-based morphometry from structural MRI images in 85 ASD and 65 typically developing control (TDC) boys, aged 7-17 years. Levels of dysregulation were measured by the sum of T-scores of Attention, Aggression, and Anxiety/Depression subscales on the Child Behavior Checklist. We found both ASD and TDC shared similar relationships between dysregulation and cortical folding patterns in the left superior and inferior temporal gyri and the left premotor cortex. Significant diagnosis by dysregulation interactions in cortical folding patterns were identified over the right middle frontal and right lateral orbitofrontal regions. The statistical significance of greater local gyrification index in ASD than TDC in several brain regions disappeared when the level of dysregulation was considered. The findings of shared and distinct neural correlates underpinning dysregulation between ASD and TDC may facilitate the development of targeted interventions in the future. The present work also demonstrates that inter-subject variations in self-regulation may explain some extents of ASD-associated brain morphometric differences, likely suggesting that dysregulation is one of the yardsticks for dissecting the heterogeneity of ASD.

Travelling waves reveal a dynamic seizure source in human focal epilepsy

Treatment of patients with drug-resistant focal epilepsy relies upon accurate seizure localization. Ictal activity captured by intracranial EEG has traditionally been interpreted to suggest that the underlying cortex is actively involved in seizures. Here, we hypothesize that such activity instead reflects propagated activity from a relatively focal seizure source, even during later time points when ictal activity is more widespread. We used the time differences observed between ictal discharges in adjacent electrodes to estimate the location of the hypothesized focal source and demonstrated that the seizure source, localized in this manner, closely matches the clinically and neurophysiologically determined brain region giving rise to seizures. Moreover, we determined this focal source to be a dynamic entity that moves and evolves over the time course of a seizure. Our results offer an interpretation of ictal activity observed by intracranial EEG that challenges the traditional conceptualization of the seizure source.

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.

Parameter-robust multiphysics algorithms for Biot model with application in brain edema simulation

In this paper, we develop parameter-robust numerical algorithms for Biot model and apply the algorithms in brain edema simulations. By introducing an intermediate variable, we derive a multiphysics reformulation of the Biot model. Based on the reformulation, the Biot model is viewed as a generalized Stokes subproblem combining with a reaction-diffusion subproblem. Solving the two subproblems together or separately leads to a coupled or a decoupled algorithm. We conduct extensive numerical experiments to show that the two algorithms are robust with respect to the key physical parameters. The algorithms are applied to study the brain swelling caused by abnormal accumulation of cerebrospinal fluid in injured areas. The effects of the key physical parameters on brain swelling are carefully investigated. It is observed that the permeability has the biggest influence on intracranial pressure (ICP) and tissue deformation; the Young's modulus and the Poisson ratio do not affect the maximum value of ICP too much but have big influence on the tissue deformation and the developing speed of brain swelling.

Folding drives cortical thickness variations

The cortical thickness is a characteristic biomarker for a wide variety of neurological disorders. While the structural organization of the cerebral cortex is tightly regulated and evolutionarily preserved, its thickness varies widely between 1.5 and 4.5 mm across the healthy adult human brain. It remains unclear whether these thickness variations are a cause or consequence of cortical development. Recent studies suggest that cortical thickness variations are primarily a result of genetic effects. Previous studies showed that a simple homogeneous bilayered system with a growing layer on an elastic substrate undergoes a unique symmetry breaking into a spatially heterogeneous system with discrete gyri and sulci. Here, we expand on that work to explore the evolution of cortical thickness variations over time to support our finding that cortical pattern formation and thickness variations can be explained - at least in part - by the physical forces that emerge during cortical folding. Strikingly, as growth progresses, the developing gyri universally thicken and the sulci thin, even in the complete absence of regional information. Using magnetic resonance images, we demonstrate that these naturally emerging thickness variations agree with the cortical folding pattern in n = 9 healthy adult human brains, in n = 564 healthy human brains ages 7-64, and in n = 73 infant brains scanned at birth, and at ages one and two. Additionally, we show that cortical organoids develop similar patterns throughout their growth. Our results suggest that genetic, geometric, and physical events during brain development are closely interrelated. Understanding regional and temporal variations in cortical thickness can provide insight into the evolution and causative factors of neurological disorders, inform the diagnosis of neurological conditions, and assess the efficacy of treatment options.

The Subplate: A Potential Driver of Cortical Folding?

In many species of Mammalia, the surface of the brain develops from a smooth structure to one with many fissures and folds, allowing for vast expansion of the surface area of the cortex. The importance of understanding what drives cortical folding extends beyond mere curiosity, as conditions such as preterm birth, intrauterine growth restriction, and fetal alcohol syndrome are associated with impaired folding in the infant and child. Despite being a key feature of brain development, the mechanisms driving cortical folding remain largely unknown. In this review we discuss the possible role of the subplate, a developmentally transient compartment, in directing region-dependent development leading to sulcal and gyral formation. We discuss the development of the subplate in species with lissencephalic and gyrencephalic cortices, the characteristics of the cells found in the subplate, and the possible presence of molecular cues that guide axons into, and out of, the overlying and multilayered cortex before the appearance of definitive cortical folds. An understanding of what drives cortical folding is likely to help in understanding the origins of abnormal folding patterns in clinical pathologies.

High-Expanding Regions in Primate Cortical Brain Evolution Support Supramodal Cognitive Flexibility

Primate cortical evolution has been characterized by massive and disproportionate expansion of a set of specific regions in the neocortex. The associated increase in neocortical neurons comes with a high metabolic cost, thus the functions served by these regions must have conferred significant evolutionary advantage. In the present series of analyses, we show that evolutionary high-expanding cortex - as estimated from patterns of surface growth from several primate species - shares functional connections with different brain networks in a context-dependent manner. Specifically, we demonstrate that high-expanding cortex is characterized by high internetwork functional connectivity; is recruited flexibly over many different cognitive tasks; and changes its functional coupling pattern between rest and a multimodal task-state. The capacity of high-expanding cortex to connect flexibly with various specialized brain networks depending on particular cognitive requirements suggests that its selective growth and sustainment in evolution may have been linked to an involvement in supramodal cognition. In accordance with an evolutionary-developmental view, we find that this observed ability of high-expanding regions - to flexibly modulate functional connections as a function of cognitive state - emerges gradually through childhood, with a prolonged developmental trajectory plateauing in young adulthood.

Cortical gyrification and its relationships with molecular measures and cognition in children with the FMR1 premutation

Neurobiological basis for cognitive development and psychiatric conditions remains unexplored in children with the FMR1 premutation (PM). Knock-in mouse models of PM revealed defects in embryonic cortical development that may affect cortical folding. Cortical-folding complexity quantified using local gyrification index (LGI) was examined in 61 children (age 8–12 years, 19/14 male/female PM carriers, 15/13 male/female controls). Whole-brain vertex-wise analysis of LGI was performed for group comparisons and correlations with IQ. Individuals with aberrant gyrification in 68 cortical areas were identified using Z-scores of LGI (hyper: Z ≥ 2.58, hypo: Z ≤ − 2.58). Significant group-by-sex-by-age interaction in LGI was detected in right inferior temporal and fusiform cortices, which correlated negatively with CGG repeat length in the PM carriers. Sixteen PM boys (hyper/hypo: 7/9) and 10 PM girls (hyper/hypo: 2/5, 3 both) displayed aberrant LGI in 1–17 regions/person while 2 control boys (hyper/hypo: 0/2) and 2 control girls (hyper/hypo: 1/1) met the same criteria in only 1 region/person. LGI in the precuneus and cingulate cortices correlated positively with IQ scores in PM and control boys while negatively in PM girls and no significant correlation in control girls. These findings reveal aberrant gyrification, which may underlie cognitive performance in children with the PM.

Sex Differences Along the Autism Continuum: A Twin Study of Brain Structure

Females might possess protective mechanisms regarding autism spectrum disorder (ASD) and require a higher detrimental load, including structural brain alterations, before developing clinically relevant levels of autistic traits. This study examines sex differences in structural brain morphology in autism and autistic traits using a within-twin pair approach. Twin design inherently controls for shared confounders and enables the study of gene-independent neuroanatomical variation. N = 148 twins (62 females) from 49 monozygotic and 25 dizygotic same-sex pairs were included. Participants were distributed along the whole continuum of autism including twin pairs discordant and concordant for clinical ASD. Regional brain volume, surface area, and cortical thickness were computed. Within-twin pair increases in autistic traits were related to decreases in cortical volume and surface area of temporal and frontal regions specifically in female twin pairs, in particular regions involved in social communication, while only two regions were associated with autistic traits in males. The same pattern was detected in the monozygotic twin pairs only. Thus, non-shared environmental factors seem to impact female more than male cerebral architecture associated with autistic traits. Our results are in line with the hypothesis of a female protective effect in autism and highlights the need to study ASD in females separately from males.

Intrathecal drug delivery in the era of nanomedicine

Administration of substances directly into the cerebrospinal fluid (CSF) that surrounds the brain and spinal cord is one approach that can circumvent the blood-brain barrier to enable drug delivery to the central nervous system (CNS). However, molecules that have been administered by intrathecal injection, which includes intraventricular, intracisternal, or lumbar locations, encounter new barriers within the subarachnoid space. These barriers include relatively high rates of turnover as CSF clears and potentially inadequate delivery to tissue or cellular targets. Nanomedicine could offer a solution. In contrast to the fate of freely administered drugs, nanomedicine systems can navigate the subarachnoid space to sustain delivery of therapeutic molecules, genes, and imaging agents within the CNS. Some evidence suggests that certain nanomedicine agents can reach the parenchyma following intrathecal administration. Here, we will address the preclinical and clinical use of intrathecal nanomedicine, including nanoparticles, microparticles, dendrimers, micelles, liposomes, polyplexes, and other colloidalal materials that function to alter the distribution of molecules in tissue. Our review forms a foundational understanding of drug delivery to the CSF that can be built upon to better engineer nanomedicine for intrathecal treatment of disease.

Daily-life affective instability in emotional distress disorders is associated with function and structure of posterior parietal cortex

Affective instability (i.e., large and frequent shifts in negative emotions) is a key emotion dysregulation symptom in emotional distress disorders and can be reliably and validly assessed using ambulatory assessment. However, no study has examined whether affective instability is associated with brain function and structure. Using multimodal neuroimaging and ambulatory assessment, we examined associations between functional activation and cortical structure with ambulatory-assessed affective instability in emotional distress disorders (n = 27). Increased daily life-affective instability was associated with decreased neural activation on an emotion regulation task in a left inferior parietal region consistently associated with emotion regulation. Daily-life affective instability was also associated with hypogyria in this same left inferior parietal region, with hypogyria extending into additional posterior parietal regions. This study found evidence that daily-life affective instability was associated with both functionstructure of the posterior parietal cortex, a key attentional control region involved in emotion regulation.

Global Perturbation of Initial Geometry in a Biomechanical Model of Cortical Morphogenesis

Cortical folding pattern is a main characteristic of the geometry of the human brain which is formed by gyri (ridges) and sulci (grooves). Several biological hypotheses have suggested different mechanisms that attempt to explain the development of cortical folding and its abnormal evolutions. Based on these hypotheses, biomechanical models of cortical folding have been proposed. In this work, we compare biomechanical simulations for several initial conditions by using an adaptive spherical parameterization approach. Our approach allows us to study and explore one of the most potential sources of reproducible cortical folding pattern: the specification of initial geometry of the brain.

Multiscale Structure-Function Gradients in the Neonatal Connectome

The adult functional connectome is well characterized by a macroscale spatial gradient of connectivity traversing from unimodal toward higher-order transmodal cortices that recapitulates known principles of hierarchical organization and myelination patterns. Despite an emerging literature assessing connectome properties in neonates, the presence of connectome gradients and particularly their correspondence to microstructure remains largely unknown. We derived connectome gradients using unsupervised techniques applied to functional connectivity data from 40 term-born neonates. A series of cortex-wide analysis examined associations to magnetic resonance imaging-derived morphological parameters (cortical thickness, sulcal depth, curvature), measures of tissue microstructure (intracortical T1w/T2w intensity, superficial white matter diffusion parameters), and subcortico-cortical functional connectivity. Our findings indicate that the primary neonatal connectome gradient runs between sensorimotor and visual anchors and captures specific associations to cortical and superficial white matter microstructure as well as thalamo-cortical connectivity. A second gradient indicated an anterior-to-posterior asymmetry in macroscale connectivity alongside an immature differentiation between unimodal and transmodal areas, indicating a connectome-level circuitry en route to an adult-like organization. Our findings reveal an important coordination of structural and functional interactions in the neonatal connectome across spatial scales. Observed associations were replicable across individual neonates, suggesting consistency and generalizability.

Sex differences in brain structure: a twin study on restricted and repetitive behaviors in twin pairs with and without autism

Background

Females with autism spectrum disorder have been reported to exhibit fewer and less severe restricted and repetitive behaviors and interests compared to males. This difference might indicate sex-specific alterations of brain networks involved in autism symptom domains, especially within cortico-striatal and sensory integration networks. This study used a well-controlled twin design to examine sex differences in brain anatomy in relation to repetitive behaviors.

Methods

In 75 twin pairs (n = 150, 62 females, 88 males) enriched for autism spectrum disorder (n = 32), and other neurodevelopmental disorders (n = 32), we explored the association of restricted and repetitive behaviors and interests—operationalized by the Autism Diagnostic Interview-Revised (C domain) and the Social Responsiveness Scale-2 (Restricted Interests and Repetitive Behavior subscale)—with cortical volume, surface area and thickness of neocortical, sub-cortical, and cerebellar networks.

Results

Co-twin control analyses revealed within-pair associations between RRBI symptoms and increased thickness of the right intraparietal sulcus and reduced volume of the right orbital gyrus in females only, even though the mean number of RRBIs did not differ between the sexes. In a sub-sample of ASD-discordant pairs, increased thickness in association with RRBIs was found exclusively in females in the orbitofrontal regions, superior frontal gyrus, and intraparietal sulcus, while in males RRBIs tended to be associated with increased volume of the bilateral pallidum.

Limitations

However, due to a small sample size and the small difference in RRBI symptoms within pairs, the results of this exploratory study need to be interpreted with caution.

Conclusions

Our findings suggest that structural alterations of fronto-parietal networks in association with RRBIs are found mostly in females, while striatal networks are more affected in males. These results endorse the importance of investigating sex differences in the neurobiology of autism symptoms, and indicate different etiological pathways underlying restricted and repetitive behaviors and interests in females and males.