Towards Deciphering the Fetal Foundation of Normal Cognition and Cognitive Symptoms From Sulcation of the Cortex.

Growing evidence supports that prenatal processes play an important role for cognitive ability in normal and clinical conditions. In this context, several neuroimaging studies searched for features in postnatal life that could serve as a proxy for earlier developmental events. A very interesting candidate is the sulcal, or sulco-gyral, patterns, macroscopic features of the cortex anatomy related to the fold topology-e.g., continuous vs. interrupted/broken fold, present vs. absent fold-or their spatial organization. Indeed, as opposed to quantitative features of the cortical sheet (e.g., thickness, surface area or curvature) taking decades to reach the levels measured in adult, the qualitative sulcal patterns are mainly determined before birth and stable across the lifespan. The sulcal patterns therefore offer a window on the fetal constraints on specific brain areas on cognitive abilities and clinical symptoms that manifest later in life. After a global review of the cerebral cortex sulcation, its mechanisms, its ontogenesis along with methodological issues on how to measure the sulcal patterns, we present a selection of studies illustrating that analysis of the sulcal patterns can provide information on prenatal dispositions to cognition (with a focus on cognitive control and academic abilities) and cognitive symptoms (with a focus on schizophrenia and bipolar disorders). Finally, perspectives of sulcal studies are discussed

A functional polymorphism of the brain derived neurotrophic factor gene and cortical anatomy in autism spectrum disorder

Autism Spectrum Disorder (ASD) is associated with both (i) post-mortem and neuroimaging evidence of abnormal cortical development, and (ii) altered signalling in Brain Derived Neurotrophic Factor (BDNF) pathways - which regulate neuroproliferative and neuroplastic processes. In healthy controls genotype at a single nucleotide polymorphism that alters BDNF signalling (Val66met) has been related to regional cortical volume. It is not known however if this influence on brain development is intact in ASD. Therefore we compared the relationship between genotype and cortical anatomy (as measured using in vivo Magnetic Resonance Imaging) in 41 people with ASD and 30 healthy controls. We measured cortical volume, and its two sole determinants - cortical thickness and surface area - which reflect differing neurodevelopmental processes. We found “Group-by-Genotype” interactions for cortical volume in medial (caudal anterior cingulate, posterior cingulate) and lateral (rostral middle, lateral orbitofrontal, pars orbitalis and pars triangularis) frontal cortices. Furthermore, within (only) these regions “Group-by-Genotype” interactions were also found for surface area. No effects were found for cortical thickness in any region. Our preliminary findings suggest that people with ASD have differences from controls in the relationship between BDNF val66met genotype and regional (especially frontal) cortical volume and surface area, but not cortical thickness. Therefore alterations in the relationship between BDNF val66met genotype and surface area in ASD may drive the findings for volume. If correct, this suggests ASD is associated with a distorted relationship between BDNF val66met genotype and the determinants of regional cortical surface area – gyrification and/or sulcal positioning

Mapping cortical anatomy in preschool aged children with autism using surface-based morphometry☆

The challenges of gathering in-vivo measures of brain anatomy from young children have limited the number of independent studies examining neuroanatomical differences between children with autism and typically developing controls (TDCs) during early life, and almost all studies in this critical developmental window focus on global or lobar measures of brain volume. Using a novel cohort of young males with Autistic Disorder and TDCs aged 2 to 5 years, we (i) tested for group differences in traditional measures of global anatomy (total brain, total white, total gray and total cortical volume), and (ii) employed surface-based methods for cortical morphometry to directly measure the two biologically distinct sub-components of cortical volume (CV) at high spatial resolution—cortical thickness (CT) and surface area (SA). While measures of global brain anatomy did not show statistically significant group differences, children with autism showed focal, and CT-specific anatomical disruptions compared to TDCs, consisting of relative cortical thickening in regions with central roles in behavioral regulation, and the processing of language, biological movement and social information. Our findings demonstrate the focal nature of brain involvement in early autism, and provide more spatially and morphometrically specific anatomical phenotypes for subsequent translational study

The variegation of human brain vulnerability to rare genetic disorders and convergence with behaviorally defined disorders

BACKGROUND: Diverse gene dosage disorders (GDDs) increase risk for psychiatric impairment, but characterization of GDD effects on the human brain has so far been piecemeal with few simultaneous analyses of multiple brain features across different GDDs. METHODS: Here, through multimodal neuroimaging of 3 aneuploidy syndromes [XXY (total n = 191, 92 controls), XYY (total n=81, 47 controls) , trisomy 21 (total n=69, 41 controls)], we systematically map the effects of supernumerary X, Y and chromosome 21 dosage across a breadth of 15 different macrostructural, microstructural, and functional imaging derived phenotypes (IDPs). RESULTS: We reveal considerable diversity in cortical changes across GDDs and IDPs. This variegation of IDP change underlines the limitations of studying GDD effects unimodally. Integration across all IDP change maps reveals highly distinct architectures of cortical change in each GDD along with partial coalescence onto a common spatial axis of cortical vulnerability that is evident in all three GDDs. This common axis shows strong alignment with shared cortical changes in behaviorally defined psychiatric disorders and is enriched for specific molecular and cellular signatures. CONCLUSION: Use of multimodal neuroimaging data in three aneuploidies indicates that different GDDs impose unique fingerprints of change in the human brain that differ widely depending on the imaging modality being considered. Embedded in this variegation is a spatial axis of shared multimodal change that aligns with shared brain changes across psychiatric disorders and therefore represents a major high-priority target for future translational research in neuroscience

Imaging local genetic influences on cortical folding

Recent progress in deciphering mechanisms of human brain cortical folding leave unexplained whether spatially patterned genetic influences contribute to this folding. High-resolution in vivo brain MRI can be used to estimate genetic correlations (covariability due to shared genetic factors) in interregional cortical thickness, and biomechanical studies predict an influence of cortical thickness on folding patterns. However, progress has been hampered because shared genetic influences related to folding patterns likely operate at a scale that is much more local (cm) than that addressed in prior imaging studies. Here, we develop methodological approaches to examine local genetic influences on cortical thickness and apply these methods to two large, independent samples. We find that such influences are markedly heterogeneous in strength, and in some cortical areas are notably stronger in specific orientations relative to gyri or sulci. The overall, phenotypic local correlation has a significant basis in shared genetic factors and is highly symmetric between left and right cortical hemispheres. Furthermore, the degree of local cortical folding relates systematically with the strength of local correlations, which tends to be higher in gyral crests and lower in sulcal fundi. The relationship between folding and local correlations is stronger in primary sensorimotor areas and weaker in association areas such as prefrontal cortex, consistent with reduced genetic constraints on the structural topology of association cortex. Collectively, our results suggest that patterned genetic influences on cortical thickness, measurable at the scale of in vivo MRI, may be a causal factor in the development of cortical folding

Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes.

Schizophrenia has been conceived as a disorder of brain connectivity, but it is unclear how this network phenotype is related to the underlying genetics. We used morphometric similarity analysis of MRI data as a marker of interareal cortical connectivity in three prior case-control studies of psychosis: in total, n = 185 cases and n = 227 controls. Psychosis was associated with globally reduced morphometric similarity in all three studies. There was also a replicable pattern of case-control differences in regional morphometric similarity, which was significantly reduced in patients in frontal and temporal cortical areas but increased in parietal cortex. Using prior brain-wide gene expression data, we found that the cortical map of case-control differences in morphometric similarity was spatially correlated with cortical expression of a weighted combination of genes enriched for neurobiologically relevant ontology terms and pathways. In addition, genes that were normally overexpressed in cortical areas with reduced morphometric similarity were significantly up-regulated in three prior post mortem studies of schizophrenia. We propose that this combined analysis of neuroimaging and transcriptional data provides insight into how previously implicated genes and proteins as well as a number of unreported genes in their topological vicinity on the protein interaction network may drive structural brain network changes mediating the genetic risk of schizophrenia.This study was supported by grants from the European Commission (PSYSCAN - Translating neuroimaging findings from research into clinical practice; ID: 603196) and the NIHR Cambridge Biomedical Research Centre (Mental Health). SEM holds a Henslow Fellowship at Lucy Cavendish College, University of Cambridge, funded by the Cambridge Philosophical Society. PEV was supported by the Medical Research Council (MR/K020706/1) and an MQ fellowship (MQF17_24) and is a Fellow of the Alan Turing Institute funded under the EPSRC grant EP/N510129/1. KJW was funded by an Alan Turing Institute Research Fellowship under EPSRC Research grant TU/A/000017. ETB is supported by a NIHR Senior Investigator Award

Studying neuroanatomy using MRI

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works

Author Correction: Transcriptomic and cellular decoding of regional brain vulnerability to neurogenetic disorders

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Morphometric Similarity Networks Detect Microscale Cortical Organization and Predict Inter-Individual Cognitive Variation.

Macroscopic cortical networks are important for cognitive function, but it remains challenging to construct anatomically plausible individual structural connectomes from human neuroimaging. We introduce a new technique for cortical network mapping based on inter-regional similarity of multiple morphometric parameters measured using multimodal MRI. In three cohorts (two human, one macaque), we find that the resulting morphometric similarity networks (MSNs) have a complex topological organization comprising modules and high-degree hubs. Human MSN modules recapitulate known cortical cytoarchitectonic divisions, and greater inter-regional morphometric similarity was associated with stronger inter-regional co-expression of genes enriched for neuronal terms. Comparing macaque MSNs with tract-tracing data confirmed that morphometric similarity was related to axonal connectivity. Finally, variation in the degree of human MSN nodes accounted for about 40% of between-subject variability in IQ. Morphometric similarity mapping provides a novel, robust, and biologically plausible approach to understanding how human cortical networks underpin individual differences in psychological functions