Connectivity optimization and the positioning of cortical areas

Noncoding variants and sulcal patterns in congenital heart disease: Machine learning to predict functional impact

Neurodevelopmental impairments associated with congenital heart disease (CHD) may arise from perturbations in brain developmental pathways, including the formation of sulcal patterns. While genetic factors contribute to sulcal features, the association of noncoding de novo variants (ncDNVs) with sulcal patterns in people with CHD remains poorly understood. Leveraging deep learning models, we examined the predicted impact of ncDNVs on gene regulatory signals. Predicted impact was compared between participants with CHD and a jointly called cohort without CHD. We then assessed the relationship of the predicted impact of ncDNVs with their sulcal folding patterns. ncDNVs predicted to increase H3K9me2 modification were associated with larger disruptions in right parietal sulcal patterns in the CHD cohort. Genes predicted to be regulated by these ncDNVs were enriched for functions related to neuronal development. This highlights the potential of deep learning models to generate hypotheses about the role of noncoding variants in brain development.

Brain-inspired wiring economics for artificial neural networks

Wiring patterns of brain networks embody a trade-off between information transmission, geometric constraints, and metabolic cost, all of which must be balanced to meet functional needs. Geometry and wiring economy are crucial in the development of brains, but their impact on artificial neural networks (ANNs) remains little understood. Here, we adopt a wiring cost-controlled training framework that simultaneously optimizes wiring efficiency and task performance during structural evolution of sparse ANNs whose nodes are located at arbitrary but fixed positions. We show that wiring cost control improves performance across a wide range of tasks, ANN architectures and training methods, and can promote task-specific structural modules. An optimal wiring cost range provides both enhanced predictive performance and high values of topological properties, such as modularity and clustering, which are observed in real brain networks and known to improve robustness, interpretability, and performance of ANNs. In addition, ANNs trained using wiring cost can emulate the connection distance distribution observed in the brains of real organisms (such as Ciona intestinalis and Caenorhabditis elegans), especially when achieving high task performance, offering insights into biological organizing principles. Our results shed light on the relationship between topology and task specialization of ANNs trained within biophysical constraints, and their geometric resemblance to real neuronal-level brain maps.

Patterns of the left thalamus embedding into the connectome associated with reading skills in children with reading disabilities

We examined how thalamocortical connectivity structure reflects children's reading performance. Diffusion-weighted MRI at 3 T and a series of reading measures were collected from 64 children (33 girls) ages 8-14 years with and without dyslexia. The topological properties of the left and right thalamus were computed based on the whole-brain white matter network and a hub-attached reading network, and were correlated with scores on several tests of children's reading and reading-related abilities. Significant correlations between topological metrics of the left thalamus and reading scores were observed only in the hub-attached reading network. Local efficiency was negatively correlated with rapid automatized naming. Transmission cost was positively correlated with phonemic decoding, and this correlation was independent of network efficiency scores; follow-up analyses further demonstrated that this effect was specific to the pulvinar and mediodorsal nuclei of the left thalamus. We validated these results using an independent dataset and demonstrated that that the relationship between thalamic connectivity and phonemic decoding was specifically robust. Overall, the results highlight the role of the left thalamus and thalamocortical network in understanding the neurocognitive bases of skilled reading and dyslexia in children.

The Control of Cortical Folding: Multiple Mechanisms, Multiple Models

The cerebral cortex develops through a carefully conscripted series of cellular and molecular events that culminate in the production of highly specialized neuronal and glial cells. During development, cortical neurons and glia acquire a precise cellular arrangement and architecture to support higher-order cognitive functioning. Decades of study using rodent models, naturally gyrencephalic animal models, human pathology specimens, and, recently, human cerebral organoids, reveal that rodents recapitulate some but not all the cellular and molecular features of human cortices. Whereas rodent cortices are smooth-surfaced or lissencephalic, larger mammals, including humans and nonhuman primates, have highly folded/gyrencephalic cortices that accommodate an expansion in neuronal mass and increase in surface area. Several genes have evolved to drive cortical gyrification, arising from gene duplications or de novo origins, or by alterations to the structure/function of ancestral genes or their gene regulatory regions. Primary cortical folds arise in stereotypical locations, prefigured by a molecular "blueprint" that is set up by several signaling pathways (e.g., Notch, Fgf, Wnt, PI3K, Shh) and influenced by the extracellular matrix. Mutations that affect neural progenitor cell proliferation and/or neurogenesis, predominantly of upper-layer neurons, perturb cortical gyrification. Below we review the molecular drivers of cortical folding and their roles in disease.

Surface-Based Morphometry Analysis of the Cerebral Cortex in Patients With Probable Idiopathic Rapid Eye Movement Sleep Behavior Disorder

INTRODUCTION

Strong indications support the notion that idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) acts as a precursor to multiple α-synucleinopathies, including Parkinson's disease and dementia with Lewy bodies. Despite numerous investigations into the alterations in cortical thickness and the volume of subcortical areas associated with this condition, comprehensive studies on the cortical surface morphology, focusing on gyrification and sulcal depth changes, are scarce. The purpose of this research was to explore the cortical surface morphology in individuals with probable iRBD (piRBD), to pinpoint early-phase diagnostic markers.

METHODS

This study included 30 piRBD patients confirmed using the RBD Screening Questionnaire (RBDSQ) and 33 control individuals selected from the Parkinson's Progression Markers Initiative (PPMI) database. They underwent neurophysiological tests and MRI scans. The FreeSurfer software was utilized to estimate cortical thickness (CTH), cortical and subcortical volumetry, local gyrification index (LGI), and sulcus depth (SD). Subsequently, these parameters were compared between the two groups. Additionally, linear correlation analysis was employed to estimate the relationship between brain morphological parameters and clinical parameters.

RESULTS

Compared to the healthy control (HC), piRBD patients exhibited a significant reduction in CTH, LGI, and cortical volume in the bilateral superior parietal, lateral occipital, orbitofrontal, temporo-occipital, bilateral rostral middle frontal, inferior parietal, and precentral brain regions. Moreover, a significant and notable correlation was observed between CTH and Geriatric Depression Scale (GDS), letter-number sequencing (LTNS), the Benton Judgment of Line Orientation (BJLO) test, and the symbol digit modalities test (SDMT) in several brain regions encompassing the motor cortex.

CONCLUSION

Patients with piRBD displayed widespread atrophy in various brain regions, predominantly covering the motor and sensory cortex. Furthermore, LGI could serve as a prognostic biomarker of disease's progression in piRBD.

Maintenance of delay-period activity in working memory task is modulated by local network structure

Revealing the relationship between neural network structure and function is one central theme of neuroscience. In the context of working memory (WM), anatomical data suggested that the topological structure of microcircuits within WM gradient network may differ, and the impact of such structural heterogeneity on WM activity remains unknown. Here, we proposed a spiking neural network model that can replicate the fundamental characteristics of WM: delay-period neural activity involves association cortex but not sensory cortex. First, experimentally observed receptor expression gradient along the WM gradient network is reproduced by our network model. Second, by analyzing the correlation between different local structures and duration of WM activity, we demonstrated that small-worldness, excitation-inhibition balance, and cycle structures play crucial roles in sustaining WM-related activity. To elucidate the relationship between the structure and functionality of neural networks, structural circuit gradients in brain should also be subject to further measurement. Finally, combining anatomical data, we simulated the duration of WM activity across different brain regions, its maintenance relies on the interaction between local and distributed networks. Overall, network structural gradient and interaction between local and distributed networks are of great significance for WM.

Multimodal neuroimaging fusion unravel structural-functional-neurotransmitter change in Parkinson's disease with impulse control disorders

BACKGROUND

Impulse control disorders (ICD) in Parkinson's disease (PD) is highly multifactorial in etiology and has intricate neural mechanisms. Our multimodal neuroimaging study aimed to investigate the specific patterns of structure-function-neurotransmitter interactions underlying ICD.

METHODS

Thirty PD patients with ICD (PD-ICD), 30 without ICD (PD-NICD) and 32 healthy controls (HCs) were recruited. Gyrification and perivascular spaces (PVS) were computed to capture the alternations of cortical surface morphology and glymphatic function. Seed-based functional connectivity (FC) were performed to identify the corresponding functional changes. Further, JuSpace toolbox were employed for cross-modal correlations to evaluate whether the spatial patterns of functional alterations in ICD patients were associated with specific neurotransmitter system.

RESULTS

Compared to PD-NICD, PD-ICD patients showed hypogyrification and enlarged PVS volume fraction in the left orbitofrontal gyrus (OFG), as well as decreased FC between interhemispheric OFG. The interhemispheric OFG connectivity reduction was associated with spatial distribution of μ-opioid pathway (r = -0.186, p = 0.029, false discovery rate corrected). ICD severity was positively associated with the PVS volume fraction of left OFG (r = 0.422, p = 0.032). Furthermore, gyrification index (LGI) and percent PVS (pPVS) in OFG and their combined indicator showed good performance in differentiating PD-ICD from PD-NICD.

CONCLUSIONS

Our findings indicated that the co-altered structure-function-neurotransmitter interactions of OFG might be involved in the pathogenesis of ICD.

Gene regulatory landscape of cerebral cortex folding

Folding of the cerebral cortex is a key aspect of mammalian brain development and evolution, and defects are linked to severe neurological disorders. Primary folding occurs in highly stereotyped patterns that are predefined in the cortical germinal zones by a transcriptomic protomap. The gene regulatory landscape governing the emergence of this folding protomap remains unknown. We characterized the spatiotemporal dynamics of gene expression and active epigenetic landscape (H3K27ac) across prospective folds and fissures in ferret. Our results show that the transcriptomic protomap begins to emerge at early embryonic stages, and it involves cell-fate signaling pathways. The H3K27ac landscape reveals developmental cell-fate restriction and engages known developmental regulators, including the transcription factor Cux2. Manipulating Cux2 expression in cortical progenitors changed their proliferation and the folding pattern in ferret, caused by selective transcriptional changes as revealed by single-cell RNA sequencing analyses. Our findings highlight the key relevance of epigenetic mechanisms in defining the patterns of cerebral cortex folding.

Association between placental oxygen transport and fetal brain cortical development: a study in monochorionic diamniotic twins

Normal cortical growth and the resulting folding patterns are crucial for normal brain function. Although cortical development is largely influenced by genetic factors, environmental factors in fetal life can modify the gene expression associated with brain development. As the placenta plays a vital role in shaping the fetal environment, affecting fetal growth through the exchange of oxygen and nutrients, placental oxygen transport might be one of the environmental factors that also affect early human cortical growth. In this study, we aimed to assess the placental oxygen transport during maternal hyperoxia and its impact on fetal brain development using MRI in identical twins to control for genetic and maternal factors. We enrolled 9 pregnant subjects with monochorionic diamniotic twins (30.03 ± 2.39 gestational weeks [mean ± SD]). We observed that the fetuses with slower placental oxygen delivery had reduced volumetric and surface growth of the cerebral cortex. Moreover, when the difference between placenta oxygen delivery increased between the twin pairs, sulcal folding patterns were more divergent. Thus, there is a significant relationship between placental oxygen transport and fetal brain cortical growth and folding in monochorionic twins.

Shaping the brain: The emergence of cortical structure and folding

The cerebral cortex-the brain's covering and largest region-has increased in size and complexity in humans and supports higher cognitive functions such as language and abstract thinking. There is a growing understanding of the human cerebral cortex, including the diversity and number of cell types that it contains, as well as of the developmental mechanisms that shape cortical structure and organization. In this review, we discuss recent progress in our understanding of molecular and cellular processes, as well as mechanical forces, that regulate the folding of the cerebral cortex. Advances in human genetics, coupled with experimental modeling in gyrencephalic species, have provided insights into the central role of cortical progenitors in the gyrification and evolutionary expansion of the cerebral cortex. These studies are essential for understanding the emergence of structural and functional organization during cortical development and the pathogenesis of neurodevelopmental disorders associated with cortical malformations.

Improved brain community structure detection by two-step weighted modularity maximization

The human brain can be regarded as a complex network with interacting connections between brain regions. Complex brain network analyses have been widely applied to functional magnetic resonance imaging (fMRI) data and have revealed the existence of community structures in brain networks. The identification of communities may provide insight into understanding the topological functions of brain networks. Among various community detection methods, the modularity maximization (MM) method has the advantages of model conciseness, fast convergence and strong adaptability to large-scale networks and has been extended from single-layer networks to multilayer networks to investigate the community structure changes of brain networks. However, the problems of MM, suffering from instability and failing to detect hierarchical community structure in networks, largely limit the application of MM in the community detection of brain networks. In this study, we proposed the weighted modularity maximization (WMM) method by using the weight matrix to weight the adjacency matrix and improve the performance of MM. Moreover, we further proposed the two-step WMM method to detect the hierarchical community structures of networks by utilizing node attributes. The results of the synthetic networks without node attributes demonstrated that WMM showed better partition accuracy than both MM and robust MM and better stability than MM. The two-step WMM method showed better accuracy of community partitioning than WMM for synthetic networks with node attributes. Moreover, the results of resting state fMRI (rs-fMRI) data showed that two-step WMM had the advantage of detecting the hierarchical communities over WMM and was more insensitive to the density of the rs-fMRI networks than WMM.

Cortical gyrification pattern of depression in Parkinson's disease: a neuroimaging marker for disease severity?

Background

Although the study of the neuroanatomical correlates of depression in Parkinson's Disease (PD) is gaining increasing interest, up to now the cortical gyrification pattern of PD-related depression has not been reported. This study was conducted to investigate the local gyrification index (LGI) in PD patients with depression, and its associations with the severity of depression.

Methods

LGI values, as measured using FreeSurfer software, were compared between 59 depressed PD (dPD), 27 non-depressed PD (ndPD) patients and 43 healthy controls. The values were also compared between ndPD and mild-depressed PD (mi-dPD), moderate-depressed PD (mo-dPD) and severe-depressed PD (se-dPD) patients as sub-group analyses. Furthermore, we evaluated the correlation between LGI values and depressive symptom scores within dPD group.

Results

Compared to ndPD, the dPD patients exhibited decreased LGI in the left parietal, the right superior-frontal, posterior cingulate and paracentral regions, and the LGI values within these areas negatively correlated with the severity of depression. Specially, reduced gyrification was observed in mo-dPD and involving a larger region in se-dPD, but not in mi-dPD group.

Conclusion

The present study demonstrated that cortical gyrification is decreased within specific brain regions among PD patients with versus without depression, and those changes were associated with the severity of depression. Our findings suggested that cortical gyrification might be a potential neuroimaging marker for the severity of depression in patients with PD.

Postnatal growth and spatial conformity of the cranium, brain, eyeballs and masseter muscles in the macaque (Macaca mulatta)

Spatial growth constraints in the head region can lead to coordinated patterns of morphological variation that pleiotropically modify genetically defined phenotypes as the tissues compete for space. Here we test for such architectural modifications during rhesus macaque (Macaca mulatta) postnatal ontogeny. We captured cranium and brain shape from 153 MRI datasets spanning 13 to 1090 postnatal days and tested for patterns of covariation with measurements of relative brain, eyeball, and masseter muscle size as well as callosal tract length. We find that the shape of the infant (<365 days) macaque cranium was most closely aligned to masseter muscle and brain size measured relative to face size. Infant brain and juvenile (365-1090 days) cranium shape were more closely linked with brain size relative to basicranium and face size. Meanwhile, the juvenile macaque brain shape was dominated by the size of the brain relative to that of the basicranium. Associations with relative eyeball size and commissural tract lengths were weaker. Our results are consistent with a spatial-packing regime operating during postnatal macaque ontogeny, in which relative growth of the masseter, face and basicranium have a greater influence than brain growth on the overall shape of the cranium and brain.

Subcortico-amygdala pathway processes innate and learned threats

Behavioral flexibility and timely reactions to salient stimuli are essential for survival. The subcortical thalamic-basolateral amygdala (BLA) pathway serves as a shortcut for salient stimuli ensuring rapid processing. Here, we show that BLA neuronal and thalamic axonal activity in mice mirror the defensive behavior evoked by an innate visual threat as well as an auditory learned threat. Importantly, perturbing this pathway compromises defensive responses to both forms of threats, in that animals fail to switch from exploratory to defensive behavior. Despite the shared pathway between the two forms of threat processing, we observed noticeable differences. Blocking β-adrenergic receptors impairs the defensive response to the innate but not the learned threats. This reduced defensive response, surprisingly, is reflected in the suppression of the activity exclusively in the BLA as the thalamic input response remains intact. Our side-by-side examination highlights the similarities and differences between innate and learned threat-processing, thus providing new fundamental insights.

Association of Cortical Gyrification With Imaging and Serum Biomarkers in Patients With Parkinson Disease

BACKGROUND AND OBJECTIVES

Pathologic progression across the cortex is a key feature of Parkinson disease (PD). Cortical gyrification is a morphologic feature of human cerebral cortex that is tightly linked to the integrity of underlying axonal connectivity. Monitoring cortical gyrification reductions may provide a sensitive marker of progression through structural connectivity, preceding the progressive stages of PD pathology. We aimed to examine the progressive cortical gyrification reductions and their associations with overlying cortical thickness, white matter (WM) integrity, striatum dopamine availability, serum neurofilament light (NfL) chain, and CSF α-synuclein levels in PD.

METHODS

This study included a longitudinal dataset with baseline (T0), 1-year (T1), and 4-year (T4) follow-ups and 2 cross-sectional datasets. Local gyrification index (LGI) was computed from T1-weighted MRI data to measure cortical gyrification. Fractional anisotropy (FA) was computed from diffusion-weighted MRI data to measure WM integrity. Striatal binding ratio (SBR) was measured from 123Ioflupane SPECT scans. Serum NfL and CSF α-synuclein levels were also measured.

RESULTS

The longitudinal dataset included 113 patients with de novo PD and 55 healthy controls (HCs). The cross-sectional datasets included 116 patients with relatively more advanced PD and 85 HCs. Compared with HCs, patients with de novo PD showed accelerated LGI and FA reductions over 1-year period and a further decline at 4-year follow-up. Across the 3 time points, the LGI paralleled and correlated with FA (p = 0.002 at T0, p = 0.0214 at T1, and p = 0.0037 at T4) and SBR (p = 0.0095 at T0, p = 0.0035 at T1, and p = 0.0096 at T4) but not with overlying cortical thickness in patients with PD. Both LGI and FA correlated with serum NfL level (LGI: p < 0.0001 at T0, p = 0.0043 at T1; FA: p < 0.0001 at T0, p = 0.0001 at T1) but not with CSF α-synuclein level in patients with PD. In the 2 cross-sectional datasets, we revealed similar patterns of LGI and FA reductions and associations between LGI and FA in patients with more advanced PD.

DISCUSSION

We demonstrated progressive reductions in cortical gyrification that were robustly associated with WM microstructure, striatum dopamine availability, and serum NfL level in PD. Our findings may contribute biomarkers for PD progression and potential pathways for early interventions of PD.

Trade-offs among cost, integration, and segregation in the human connectome

The human brain structural network is thought to be shaped by the optimal trade-off between cost and efficiency. However, most studies on this problem have focused on only the trade-off between cost and global efficiency (i.e., integration) and have overlooked the efficiency of segregated processing (i.e., segregation), which is essential for specialized information processing. Direct evidence on how trade-offs among cost, integration, and segregation shape the human brain network remains lacking. Here, adopting local efficiency and modularity as segregation factors, we used a multiobjective evolutionary algorithm to investigate this problem. We defined three trade-off models, which represented trade-offs between cost and integration (Dual-factor model), and trade-offs among cost, integration, and segregation (local efficiency or modularity; Tri-factor model), respectively. Among these, synthetic networks with optimal trade-off among cost, integration, and modularity (Tri-factor model [Q]) showed the best performance. They had a high recovery rate of structural connections and optimal performance in most network features, especially in segregated processing capacity and network robustness. Morphospace of this trade-off model could further capture the variation of individual behavioral/demographic characteristics in a domain-specific manner. Overall, our results highlight the importance of modularity in the formation of the human brain structural network and provide new insights into the original cost-efficiency trade-off hypothesis.

Biomechanical models and mechanisms of cellular morphogenesis and cerebral cortical expansion and folding

Morphogenesis of the nervous system involves a highly complex spatio-temporal pattern of physical forces (mainly tension and pressure) acting on cells and tissues that are pliable but have an intricately organized cytoskeletal infrastructure. This review begins by covering basic principles of biomechanics and the core cytoskeletal toolkit used to regulate the shapes of cells and tissues during embryogenesis and neural development. It illustrates how the principle of 'tensegrity' provides a useful conceptual framework for understanding how cells dynamically respond to forces that are generated internally or applied externally. The latter part of the review builds on this foundation in considering the development of mammalian cerebral cortex. The main focus is on cortical expansion and folding - processes that take place over an extended period of prenatal and postnatal development. Cortical expansion and folding are likely to involve many complementary mechanisms, some related to regulating cell proliferation and migration and others related to specific types and patterns of mechanical tension and pressure. Three distinct multi-mechanism models are evaluated in relation to a set of 18 key experimental observations and findings. The Composite Tension Plus (CT+) model is introduced as an updated version of a previous multi-component Differential Expansion Sandwich Plus (DES+) model (Van Essen, 2020); the new CT+ model includes 10 distinct mechanisms and has the greatest explanatory power among published models to date. Much needs to be done in order to validate specific mechanistic components and to assess their relative importance in different species, and important directions for future research are suggested.

Parameter estimation for connectome generative models: Accuracy, reliability, and a fast parameter fitting method

Generative models of the human connectome enable in silico generation of brain networks based on probabilistic wiring rules. These wiring rules are governed by a small number of parameters that are typically fitted to individual connectomes and quantify the extent to which geometry and topology shape the generative process. A significant shortcoming of generative modeling in large cohort studies is that parameter estimation is computationally burdensome, and the accuracy and reliability of current estimation methods remain untested. Here, we propose a fast, reliable, and accurate parameter estimation method for connectome generative models that is scalable to large sample sizes. Our method achieves improved estimation accuracy and reliability and reduces computational cost by orders of magnitude, compared to established methods. We demonstrate an inherent tradeoff between accuracy, reliability, and computational expense in parameter estimation and provide recommendations for leveraging this tradeoff. To enable power analyses in future studies, we empirically approximate the minimum sample size required to detect between-group differences in generative model parameters. While we focus on the classic two-parameter generative model based on connection length and the topological matching index, our method can be generalized to other growth-based generative models. Our work provides a statistical and practical guide to parameter estimation for connectome generative models.

Longitudinal changes in surface based brain morphometry measures in amnestic mild cognitive impairment and Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is associated with marked brain atrophy. While commonly used structural MRI imaging methods do not account for the complexity of human brain morphology, little is known about the longitudinal changes of cortical geometry and their relationship with cognitive decline in subjects with AD.

METHODS

Data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used to perform two-sample t-tests to investigate longitudinal changes of cortical thickness (CTh) and three surface-based morphometry measures: fractal dimension (i.e. cortical complexity; FD), gyrification index (GI), and sulcal depth (SD) in subjects with AD, amnestic mild cognitive impairment (aMCI) in comparison to cognitively unimpaired controls (CU) in baseline and 2-year follow-up sMRI scans. In addition, correlations of the morphological measures with two-year cognitive decline as assessed by the modified AD Assessment Scale-Cognitive Subscale (ADAS-Cog 11) were calculated via regression analyses.

RESULTS

Compared to CU, both AD and aMCI showed marked decreases in CTh. In contrast, analyses of FD and GI yielded a more nuanced decline of the respective measures with some areas showing increases in FD and GI. Overall changes in FD and GI were more pronounced in AD as compared to aMCI. Analyses of SD yielded widespread decreases. Interestingly, cognitive decline corresponded well with CTh declines in aMCI but not AD, whereas changes in FD corresponded with AD only but not aMCI, whereas GI and SD were associated with cognitive decline in aMCI and AD.

CONCLUSION

Patterns of longitudinal changes in FD, GI and SD were only partially overlapping with CTh reductions. In AD, surface-based morphometry measures for brain-surface complexity showed better correspondence than CTh with cognitive decline over a two-year period of time. Being drawn from measures reflecting changes in more intricate aspects of human brain morphology, these data provide new insight into the complexity of AD-related brain atrophy and its relationship with cognitive decline.

The effect of early trauma on suicidal vulnerability depends on fronto-insular sulcation

Improving our understanding of pathophysiology of suicidal behavior (SB) is an important step for prevention. Assessment of suicide risk is based on socio-demographic and clinical risk factors with a poor predictivity. Current understanding of SB is based on a stress-vulnerability model, whereby early-life adversities are predominant. SB may thus result from a cascade of developmental processes stemming from early-life abuse and/or neglect. Some cerebral abnormalities, particularly in fronto-limbic regions, might also provide vulnerability to develop maladaptive responses to stress, leading to SB. We hypothesized that SB is associated with interactions between early trauma and neurodevelopmental deviations of the frontal and insular cortices. We recruited 86 euthymic women, including 44 suicide attempters (history of depression and SB) and 42 affective controls (history of depression without SB). The early development of prefrontal cortex (PFC) and insula was inferred using 3D magnetic resonance imaging-derived regional sulcation indices, which are indirect markers of early neurodevelopment. The insula sulcation index was higher in emotional abused subjects; among those patients, PFC sulcation index was reduced in suicide attempters, but not in affective controls. Such findings provide evidence that SB likely traced back to early stages of brain development in interaction with later environmental factors experienced early in life.

High-throughput sequencing of single neuron projections reveals spatial organization in the olfactory cortex

In most sensory modalities, neuronal connectivity reflects behaviorally relevant stimulus features, such as spatial location, orientation, and sound frequency. By contrast, the prevailing view in the olfactory cortex, based on the reconstruction of dozens of neurons, is that connectivity is random. Here, we used high-throughput sequencing-based neuroanatomical techniques to analyze the projections of 5,309 mouse olfactory bulb and 30,433 piriform cortex output neurons at single-cell resolution. Surprisingly, statistical analysis of this much larger dataset revealed that the olfactory cortex connectivity is spatially structured. Single olfactory bulb neurons targeting a particular location along the anterior-posterior axis of piriform cortex also project to matched, functionally distinct, extra-piriform targets. Moreover, single neurons from the targeted piriform locus also project to the same matched extra-piriform targets, forming triadic circuit motifs. Thus, as in other sensory modalities, olfactory information is routed at early stages of processing to functionally diverse targets in a coordinated manner.

Structural-Functional Connectivity Bandwidth of the Human Brain

BACKGROUND

The human brain is a complex network that seamlessly manifests behaviour and cognition. This network comprises neurons that directly, or indirectly mediate communication between brain regions. Here, we show how multilayer/multiplex network analysis provides a suitable framework to uncover the throughput of structural connectivity (SC) to mediate information transfer-giving rise to functional connectivity (FC).

METHOD

We implemented a novel method to reconcile SC and FC using diffusion and resting-state functional MRI connectivity data from 484 subjects (272 females, 212 males; age = 29.15 ± 3.47) from the Human Connectome Project. First, we counted the number of direct and indirect structural paths that mediate FC. FC nodes with indirect SC paths were then weighted according to their least restrictive SC path. We refer to this as SC-FC Bandwidth. We then mapped paths with the highest SC-FC Bandwidth across 7 canonical resting-state networks.

FINDINGS

We found that most pairs of FC nodes were connected by SC paths of length two and three (SC paths of length >5 were virtually non-existent). Direct SC-FC connections accounted for only 10% of all SC-FC connections. The majority of FC nodes without a direct SC path were mediated by a proportion of two (44%) or three SC path lengths (39%). Only a small proportion of FC nodes were mediated by SC path lengths of four (5%). We found high-bandwidth direct SC-FC connections show dense intra- and sparse inter-network connectivity, with a bilateral, anteroposterior distribution. High bandwidth SC-FC triangles have a right superomedial distribution within the somatomotor network. High-bandwidth SC-FC quads have a superoposterior distribution within the default mode network.

CONCLUSION

Our method allows the measurement of indirect SC-FC using undirected, weighted graphs derived from multimodal MRI data in order to map the location and throughput of SC to mediate FC. An extension of this work may be to explore how SC-FC Bandwidth changes over time, relates to cognition/behavior, and if this measure reflects a marker of neurological injury or psychiatric disorders.

Quantification of sulcal emergence timing and its variability in early fetal life: Hemispheric asymmetry and sex difference

Human fetal brains show regionally different temporal patterns of sulcal emergence following a regular timeline, which may be associated with spatiotemporal patterns of gene expression among cortical regions. This study aims to quantify the timing of sulcal emergence and its temporal variability across typically developing fetuses by fitting a logistic curve to presence or absence of sulcus. We found that the sulcal emergence started from the central to the temporo-parieto-occipital lobes and frontal lobe, and the temporal variability of emergence in most of the sulci was similar between 1 and 2 weeks. Small variability (< 1 week) was found in the left central and postcentral sulci and larger variability (>2 weeks) was shown in the bilateral occipitotemporal and left superior temporal sulci. The temporal variability showed a positive correlation with the emergence timing that may be associated with differential contributions between genetic and environmental factors. Our statistical analysis revealed that the right superior temporal sulcus emerged earlier than the left. Female fetuses showed a trend of earlier sulcal emergence in the right superior temporal sulcus, lower temporal variability in the right intraparietal sulcus, and higher variability in the right precentral sulcus compared to male fetuses. Our quantitative and statistical approach quantified the temporal patterns of sulcal emergence in detail that can be a reference for assessing the normality of developing fetal gyrification.

The Influence of Neural Activity and Neural Cytoarchitecture on Cerebrovascular Arborization: A Computational Model

Normal functioning of the brain relies on a continual and efficient delivery of energy by a vast network of cerebral blood vessels. The bidirectional coupling between neurons and blood vessels consists of vasodilatory energy demand signals from neurons to blood vessels, and the retrograde flow of energy substrates from the vessels to neurons, which fuel neural firing, growth and other housekeeping activities in the neurons. Recent works indicate that, in addition to the functional coupling observed in the adult brain, the interdependence between the neural and vascular networks begins at the embryonic stage, and continues into subsequent developmental stages. The proposed Vascular Arborization Model (VAM) captures the effect of neural cytoarchitecture and neural activity on vascular arborization. The VAM describes three important stages of vascular tree growth: (i) The prenatal growth phase, where the vascular arborization depends on the cytoarchitecture of neurons and non-neural cells, (ii) the post-natal growth phase during which the further arborization of the vasculature depends on neural activity in addition to neural cytoarchitecture, and (iii) the settling phase, where the fully grown vascular tree repositions its vascular branch points or nodes to ensure minimum path length and wire length. The vasculature growth depicted by VAM captures structural characteristics like vascular volume density, radii, mean distance to proximal neurons in the cortex. VAM-grown vasculature agrees with the experimental observation that the neural densities do not covary with the vascular density along the depth of the cortex but predicts a high correlation between neural areal density and microvascular density when compared over a global scale (across animals and regions). To explore the influence of neural activity on vascular arborization, the VAM was used to grow the vasculature in neonatal rat whisker barrel cortex under two conditions: (i) Control, where the whiskers were intact and (ii) Lesioned, where one row of whiskers was cauterized. The model captures a significant reduction in vascular branch density in lesioned animals compared to control animals, concurring with experimental observation.

Individualized Functional Subnetworks Connect Human Striatum and Frontal Cortex

The striatum and cerebral cortex are interconnected via multiple recurrent loops that play a major role in many neuropsychiatric conditions. Primate corticostriatal connections can be precisely mapped using invasive tract-tracing. However, noninvasive human research has not mapped these connections with anatomical precision, limited in part by the practice of averaging neuroimaging data across individuals. Here we utilized highly sampled resting-state functional connectivity MRI for individual-specific precision functional mapping (PFM) of corticostriatal connections. We identified ten individual-specific subnetworks linking cortex-predominately frontal cortex-to striatum, most of which converged with nonhuman primate tract-tracing work. These included separable connections between nucleus accumbens core/shell and orbitofrontal/medial frontal gyrus; between anterior striatum and dorsomedial prefrontal cortex; between dorsal caudate and lateral prefrontal cortex; and between middle/posterior putamen and supplementary motor/primary motor cortex. Two subnetworks that did not converge with nonhuman primates were connected to cortical regions associated with human language function. Thus, precision subnetworks identify detailed, individual-specific, neurobiologically plausible corticostriatal connectivity that includes human-specific language networks.

The roles of inter-tissue adhesion in development and morphological evolution

The study of how neighboring tissues physically interact with each other, inter-tissue adhesion, is an emerging field at the interface of cell biology, biophysics and developmental biology. Inter-tissue adhesion can be mediated by either cell-extracellular matrix adhesion or cell-cell adhesion, and both the mechanisms and consequences of inter-tissue adhesion have been studied in vivo in numerous vertebrate and invertebrate species. In this Review, we discuss recent progress in understanding the many functions of inter-tissue adhesion in development and evolution. Inter-tissue adhesion can couple the motion of adjacent tissues, be the source of mechanical resistance that constrains morphogenesis, and transmit tension required for normal development. Tissue-tissue adhesion can also create mechanical instability that leads to tissue folding or looping. Transient inter-tissue adhesion can facilitate tissue invasion, and weak tissue adhesion can generate friction that shapes and positions tissues within the embryo. Lastly, we review studies that reveal how inter-tissue adhesion contributes to the diversification of animal morphologies.

Optimality of syntactic dependency distances

It is often stated that human languages, as other biological systems, are shaped by cost-cutting pressures but, to what extent? Attempts to quantify the degree of optimality of languages by means of an optimality score have been scarce and focused mostly on English. Here we recast the problem of the optimality of the word order of a sentence as an optimization problem on a spatial network where the vertices are words, arcs indicate syntactic dependencies, and the space is defined by the linear order of the words in the sentence. We introduce a score to quantify the cognitive pressure to reduce the distance between linked words in a sentence. The analysis of sentences from 93 languages representing 19 linguistic families reveals that half of languages are optimized to a 70% or more. The score indicates that distances are not significantly reduced in a few languages and confirms two theoretical predictions: that longer sentences are more optimized and that distances are more likely to be longer than expected by chance in short sentences. We present a hierarchical ranking of languages by their degree of optimization. The score has implications for various fields of language research (dependency linguistics, typology, historical linguistics, clinical linguistics, and cognitive science). Finally, the principles behind the design of the score have implications for network science.

Three-dimensional anatomy of the anterior commissure: A tractography and anatomical study

The anterior commissure (AC) is one of the main commissural fibers of the brain. Commissural fibers are involved in bilateral integration and coordination of any normal brain activity. The AC is an important interhemispheric structure which forms a bidirectional communication channel between the frontal, temporal, parietal and occipital lobes bilaterally. In this article, we focus on describing the morphology, relations, and distribution of the AC through diffusion spectrum imaging (DSI) DSI-based fiber tracking. Tractographies were compared with gross anatomical dissection of the anterior commissure of adult's brains. Our study suggests that the AC found by tracking methods is bigger in comparison to the one found by dissection. In summary, the tractography added extensions to the main AC structure.

Gyral Hinges Account for the Highest Cost and the Highest Communication Capacity in a Corticocortical Network

Prior studies reported the global structure of brain networks exhibits the "small-world" and "rich-world" attributes. However, the underlying structural and functional architecture highlighted by these graph theory findings hasn't been explicitly related to the morphology of the cortex. This could be attributed to the lower resolution of used folding patterns, such as gyro-sulcal patterns. By defining a novel gyral folding pattern, termed gyral hinge (GH), which is the conjunction of ordinary gyri from multiple directions, we found GHs possess the highest length and cost in the white matter fiber connective network, and the shortest paths in the network tend to travel through GHs in their middle part. Based on these findings, we would hypothesize GHs could reside in the centers of a network core, thereby accounting for the highest cost and the highest communication capacity in a corticocortical network. The following results further support our hypothesis: 1) GHs possess stronger functional network integration capacity. 2) Higher cost is found on the connection with GHs to hinges and GHs to GHs. 3) Moving GHs introduces higher extra network cost. Our findings and hypotheses could reveal a profound relationship among the cortical folding patterns, axonal wiring architectures, and brain functions.

Transcriptome-based polygenic score links depression-related corticolimbic gene expression changes to sex-specific brain morphology and depression risk

Studies in post-mortem human brain tissue have associated major depressive disorder (MDD) with cortical transcriptomic changes, whose potential in vivo impact remains unexplored. To address this translational gap, we recently developed a transcriptome-based polygenic risk score (T-PRS) based on common functional variants capturing 'depression-like' shifts in cortical gene expression. Here, we used a non-clinical sample of young adults (n = 482, Duke Neurogenetics Study: 53% women; aged 19.8 ± 1.2 years) to map T-PRS onto brain morphology measures, including Freesurfer-derived subcortical volume, cortical thickness, surface area, and local gyrification index, as well as broad MDD risk, indexed by self-reported family history of depression. We conducted side-by-side comparisons with a PRS independently derived from a Psychiatric Genomics Consortium (PGC) MDD GWAS (PGC-PRS), and sought to link T-PRS with diagnosis and symptom severity directly in PGC-MDD participants (n = 29,340, 59% women; 12,923 MDD cases, 16,417 controls). T-PRS was associated with smaller amygdala volume in women (t = -3.478, p = 0.001) and lower prefrontal gyrification across sexes. In men, T-PRS was associated with hypergyrification in temporal and occipital regions. Prefrontal hypogyrification mediated a male-specific indirect link between T-PRS and familial depression (b = 0.005, p = 0.029). PGC-PRS was similarly associated with lower amygdala volume and cortical gyrification; however, both effects were male-specific and hypogyrification emerged in distinct parietal and temporo-occipital regions, unassociated with familial depression. In PGC-MDD, T-PRS did not predict diagnosis (OR = 1.007, 95% CI = [0.997-1.018]) but correlated with symptom severity in men (rho = 0.175, p = 7.957 × 10-4) in one cohort (N = 762, 48% men). Depression-like shifts in cortical gene expression have sex-specific effects on brain morphology and may contribute to broad depression vulnerability in men.

Digital Reconstruction of the Neuro-Glia-Vascular Architecture

Astrocytes connect the vasculature to neurons mediating the supply of nutrients and biochemicals. They are involved in a growing number of physiological and pathophysiological processes that result from biophysical, physiological, and molecular interactions in this neuro-glia-vascular ensemble (NGV). The lack of a detailed cytoarchitecture severely restricts the understanding of how they support brain function. To address this problem, we used data from multiple sources to create a data-driven digital reconstruction of the NGV at micrometer anatomical resolution. We reconstructed 0.2 mm3 of the rat somatosensory cortex with 16 000 morphologically detailed neurons, 2500 protoplasmic astrocytes, and its microvasculature. The consistency of the reconstruction with a wide array of experimental measurements allows novel predictions of the NGV organization, allowing the anatomical reconstruction of overlapping astrocytic microdomains and the quantification of endfeet connecting each astrocyte to the vasculature, as well as the extent to which they cover the latter. Structural analysis showed that astrocytes optimize their positions to provide uniform vascular coverage for trophic support and signaling. However, this optimal organization rapidly declines as their density increases. The NGV digital reconstruction is a resource that will enable a better understanding of the anatomical principles and geometric constraints, which govern how astrocytes support brain function.

Folding brains: from development to disease modeling

The human brain is characterized by the large size and intricate folding of its cerebral cortex, which are fundamental for our higher cognitive function and frequently altered in pathological dysfunction. Cortex folding is not unique to humans, nor even to primates, but is common across mammals. Cortical growth and folding are the result of complex developmental processes that involve neural stem and progenitor cells and their cellular lineages, the migration and differentiation of neurons, and the genetic programs that regulate and fine-tune these processes. All these factors combined generate mechanical stress and strain on the developing neural tissue, which ultimately drives orderly cortical deformation and folding. In this review we examine and summarize the current knowledge on the molecular, cellular, histogenic and mechanical mechanisms that are involved in and influence folding of the cerebral cortex, and how they emerged and changed during mammalian evolution. We discuss the main types of pathological malformations of human cortex folding, their specific developmental origin, and how investigating their genetic causes has illuminated our understanding of key events involved. We close our review by presenting the state-of-the-art animal and in vitro models of cortex folding that are currently used to study these devastating developmental brain disorders in children, and what are the main challenges that remain ahead of us to fully understand brain folding.

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.

Cortical Gyrification Morphology in ASD and ADHD: Implication for Further Similarities or Disorder-Specific Features?

Shared etiological pathways are suggested in ASD and ADHD given high rates of comorbidity, phenotypic overlap and shared genetic susceptibility. Given the peak of cortical gyrification expansion and emergence of ASD and ADHD symptomology in early development, we investigated gyrification morphology in 539 children and adolescents (6–17 years of age) with ASD (n=197) and ADHD (n=96) compared to typically developing controls (n=246) using the local Gyrification Index (lGI) to provide insight into contributing etiopathological factors in these two disorders. We also examined IQ effects and functional implications of gyrification by exploring the relation between lGI and ASD and ADHD symptomatology beyond diagnosis. General Linear Models yielded no group differences in lGI, and across groups, we identified an age-related decrease of lGI and greater lGI in females compared to males. No diagnosis-by-age interactions were found. Accounting for IQ variability in the model (n=484) yielded similar results. No significant associations were found between lGI and social communication deficits, repetitive and restricted behaviours, inattention or adaptive functioning. By examining both disorders and controls using shared methodology, we found no evidence of atypicality in gyrification as measured by the lGI in these conditions.

Abnormal Right-Hemispheric Sulcal Patterns Correlate with Executive Function in Adolescents with Tetralogy of Fallot

Neurodevelopmental disabilities are the most common noncardiac conditions in patients with congenital heart disease (CHD). Executive function skills have been frequently observed to be decreased among children and adults with CHD compared with peers, but a neuroanatomical basis for the association is yet to be identified. In this study, we quantified sulcal pattern features from brain magnetic resonance imaging data obtained during adolescence among 41 participants with tetralogy of Fallot (ToF) and 49 control participants using a graph-based pattern analysis technique. Among patients with ToF, right-hemispheric sulcal pattern similarity to the control group was decreased (0.7514 vs. 0.7553, P = 0.01) and positively correlated with neuropsychological testing values including executive function (r = 0.48, P < 0.001). Together these findings suggest that sulcal pattern analysis may be a useful marker of neurodevelopmental risk in patients with CHD. Further studies may elucidate the mechanisms leading to different alterations in sulcal patterning.

Sulcation of the intraparietal sulcus is related to symbolic but not non-symbolic number skills

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The horizontal segment of intraparietal sulcus (HIPS) is one of the key functional regions for processing numbers.

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Sulcal morphology is a qualitative feature of the brain determined in-utero and not affected by brain maturation and learning.

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The HIPS sulcal pattern explains part of the variance in participant’s symbolic number comparison and math fluency abilities.

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Participant’s non-symbolic number comparison abilities was not explained by HIPS sulcal pattern.

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This association between HIPS sulcal pattern and symbolic number abilities was stable from childhood to young adulthood.

Understanding the constraints, including biological ones, that may influence mathematical development is of great importance because math ability is a key predictor of career success, income and even psychological well-being. While research in developmental cognitive neuroscience of mathematics has extensively studied the key functional regions for processing numbers, particularly the horizontal segment of intraparietal sulcus (HIPS), few studies have investigated the effects of early cerebral constraints on later mathematical abilities. In this pre-registered study, we investigated whether variability of the sulcal pattern of the HIPS, a qualitative feature of the brain determined in-utero and not affected by brain maturation and learning, accounts for individual difference in symbolic and non-symbolic number abilities. Seventy-seven typically developing school-aged children and 21 young adults participated in our study. We found that the HIPS sulcal pattern, (a) explains part of the variance in participant’s symbolic number comparison and math fluency abilities, and (b) that this association between HIPS sulcal pattern and symbolic number abilities was found to be stable from childhood to young adulthood. However, (c) we did not find an association between participant’s non-symbolic number abilities and HIPS sulcal morphology. Our findings suggest that early cerebral constraints may influence individual difference in math abilities, in addition to the well-established neuroplastic factors.

Morphological and Age-Related Changes in the Narcolepsy Brain

Morphological changes in the cortex of narcolepsy patients were investigated by surface-based morphometry analysis in this study. Fifty-one type 1 narcolepsy patients and 60 demographically group-matched healthy controls provided resting-state functional and high-resolution 3T anatomical magnetic resonance imaging scans. Vertex-level cortical thickness (CT), gyrification, and voxel-wise functional connectivity were calculated. Adolescent narcolepsy patients showed decreased CT in bilateral frontal cortex and left precuneus. Adolescent narcolepsy demonstrated increased gyrification in left occipital lobe, left precuneus, and right fusiform but decreased gyrification in left postcentral gyrus, whereas adult narcolepsy exhibited increased gyrification in left temporal lobe and right frontal cortex. Furthermore, sleepiness severity was associated with altered CT and gyrification. Increased gyrification was associated with reduced long-range functional connectivity. In adolescent patients, those with more severe sleepiness showed increased right postcentral gyrification. Decreased frontal and occipital gyrification was found in cases with hallucination. In adult patients, a wide range of regions showed reduced gyrification in those with adolescence-onset compared adult-onset narcolepsy patients. Particularly the frontal lobes showed altered brain morphology, being a thinner cortex and more gyri. The impact of narcolepsy on age-related brain morphological changes may remain from adolescence to young adulthood, and it was especially exacerbated in adolescence.

Cost-efficiency trade-offs of the human brain network revealed by a multiobjective evolutionary algorithm

It is widely believed that the formation of brain network architecture is under the pressure of optimal trade-off between reducing wiring cost and promoting communication efficiency. However, the questions of whether this trade-off exists in empirical human brain structural networks and, if so, how it takes effect are still not well understood. Here, we employed a multiobjective evolutionary algorithm to directly and quantitatively explore the cost-efficiency trade-off in human brain structural networks. Using this algorithm, we generated a population of synthetic networks with optimal but diverse cost-efficiency trade-offs. It was found that these synthetic networks could not only reproduce a large portion of connections in the empirical brain structural networks but also embed a resembling small-world organization. Moreover, the synthetic and empirical brain networks were found similar in terms of the spatial arrangement of hub regions and the modular structure, which are two important topological features widely assumed to be outcomes of cost-efficiency trade-offs. The synthetic networks had high robustness against random attacks as the empirical brain networks did. Additionally, we also revealed some differences between the synthetic networks and the empirical brain networks, including lower segregated processing capacity and weaker robustness against targeted attacks in the synthetic networks. These findings provide direct and quantitative evidence that the structure of human brain networks is indeed largely influenced by optimal cost-efficiency trade-offs. We also suggest that some additional factors (e.g., segregated processing capacity) might jointly determine the network organization with cost and efficiency.

Intergenerational Transmission of Cortical Sulcal Patterns from Mothers to their Children

Intergenerational effects are described as the genetic, epigenetic, as well as pre- and postnatal environmental influence parents have on their offspring's behavior, cognition, and brain. During fetal brain development, the primary cortical sulci emerge with a distinctive folding pattern that are under strong genetic influence and show little change of this pattern throughout postnatal brain development. We examined intergenerational transmission of cortical sulcal patterns by comparing primary sulcal patterns between children (N = 16, age 5.5 ± 0.81 years, 8 males) and their biological mothers (N = 15, age 39.72 ± 4.68 years) as well as between children and unrelated adult females. Our graph-based sulcal pattern comparison method detected stronger sulcal pattern similarity for child-mother pairs than child-unrelated pairs, where higher similarity between child-mother pairs was observed mostly for the right lobar regions. Our results also show that child-mother versus child-unrelated pairs differ for daughters and sons with a trend toward significance, particularly for the left hemisphere lobar regions. This is the first study to reveal significant intergenerational transmission of cortical sulcal patterns, and our results have important implications for the study of the heritability of complex behaviors, brain-based disorders, the identification of biomarkers, and targets for interventions.

The Heritability of Cortical Folding: Evidence from the Human Connectome Project

The mechanisms underlying cortical folding are incompletely understood. Prior studies have suggested that individual differences in sulcal depth are genetically mediated, with deeper and ontologically older sulci more heritable than others. In this study, we examine FreeSurfer-derived estimates of average convexity and mean curvature as proxy measures of cortical folding patterns using a large (N = 1096) genetically informative young adult subsample of the Human Connectome Project. Both measures were significantly heritable near major sulci and primary fissures, where approximately half of individual differences could be attributed to genetic factors. Genetic influences near higher order gyri and sulci were substantially lower and largely nonsignificant. Spatial permutation analysis found that heritability patterns were significantly anticorrelated to maps of evolutionary and neurodevelopmental expansion. We also found strong phenotypic correlations between average convexity, curvature, and several common surface metrics (cortical thickness, surface area, and cortical myelination). However, quantitative genetic models suggest that correlations between these metrics are largely driven by nongenetic factors. These findings not only further our understanding of the neurobiology of gyrification, but have pragmatic implications for the interpretation of heritability maps based on automated surface-based measurements.

Early-Emerging Sulcal Patterns Are Atypical in Fetuses with Congenital Heart Disease

Fetuses with congenital heart disease (CHD) have third trimester alterations in cortical development on brain magnetic resonance imaging (MRI). However, the intersulcal relationships contributing to global sulcal pattern remain unknown. This study applied a novel method for examining the geometric and topological relationships between sulci to fetal brain MRIs from 21-30 gestational weeks in CHD fetuses (n = 19) and typically developing (TD) fetuses (n = 17). Sulcal pattern similarity index (SI) to template fetal brain MRIs was determined for the position, area, and depth for corresponding sulcal basins and intersulcal relationships for each subject. CHD fetuses demonstrated altered global sulcal patterns in the left hemisphere compared with TD fetuses (TD [SI, mean ± SD]: 0.822 ± 0.023, CHD: 0.795 ± 0.030, P = 0.002). These differences were present in the earliest emerging sulci and were driven by differences in the position of corresponding sulcal basins (TD: 0.897 ± 0.024, CHD: 0.878 ± 0.019, P = 0.006) and intersulcal relationships (TD: 0.876 ± 0.031, CHD: 0.857 ± 0.018, P = 0.033). No differences in cortical gyrification index, mean curvature, or surface area were present. These data suggest our methods may be more sensitive than traditional measures for evaluating cortical developmental alterations early in gestation.

Conservation of brain connectivity and wiring across the mammalian class

Over 100 years ago, Ramon y Cajal hypothesized that two forces played a role in the evolution of mammalian brain connectivity: minimizing wiring costs and maximizing conductivity speed. Using diffusion MRI, we reconstructed the brain connectomes of 123 mammalian species. Network analysis revealed that both connectivity and the wiring cost are conserved across mammals. We describe a conservation principle that maintains the overall connectivity: species with fewer interhemispheric connections exhibit better intrahemispheric connectivity.

Reliability of multimodal MRI brain measures in youth at risk for mental illness

INTRODUCTION

A new generation of large-scale studies is using neuroimaging to investigate adolescent brain development across health and disease. However, imaging artifacts such as head motion remain a challenge and may be exacerbated in pediatric clinical samples. In this study, we assessed the scan-rescan reliability of multimodal MRI in a sample of youth enriched for risk of mental illness.

METHODS

We obtained repeated MRI scans, an average of 2.7 ± 1.4 weeks apart, from 50 youth (mean age 14.7 years, SD = 4.4). Half of the sample (52%) had a diagnosis of an anxiety disorder; 22% had attention-deficit/hyperactivity disorder (ADHD). We quantified reliability with the test-retest intraclass correlation coefficient (ICC).

RESULTS

Gray matter measurements were highly reliable with mean ICCs as follows: cortical volume (ICC = 0.90), cortical surface area (ICC = 0.89), cortical thickness (ICC = 0.82), and local gyrification index (ICC = 0.85). White matter volume reliability was excellent (ICC = 0.98). Diffusion tensor imaging (DTI) components were also highly reliable. Fractional anisotropy was most consistently measured (ICC = 0.88), followed by radial diffusivity (ICC = 0.84), mean diffusivity (ICC = 0.81), and axial diffusivity (ICC = 0.78). We also observed regional variability in reconstruction, with some brain structures less reliably reconstructed than others.

CONCLUSIONS

Overall, we showed that developmental MRI measures are highly reliable, even in youth at risk for mental illness and those already affected by anxiety and neurodevelopmental disorders. Yet, caution is warranted if patterns of results cluster within regions of lower reliability.

Relationship between white matter glucose metabolism and fractional anisotropy in healthy and schizophrenia subjects

Decreased fractional anisotropy and increased glucose utilization in the white matter have been reported in schizophrenia. These findings may be indicative of an inverse relationship between these measures of white matter integrity and metabolism. We used ¹⁸F-fluorodeoxyglucose positron emission tomography and diffusion-tensor imaging in 19 healthy and 25 schizophrenia subjects to assess and compare coterritorial correlation patterns between glucose utilization and fractional anisotropy on a voxel-by-voxel basis and across a range of automatically placed representative white matter regions of interest. We found a pattern of predominantly negative correlations between white matter metabolism and fractional anisotropy in both healthy and schizophrenia subjects. The overall strength of the relationship was attenuated in subjects with schizophrenia, who displayed significantly fewer and weaker correlations in all regions assessed with the exception of the corpus callosum. This attenuation was most prominent in the left prefrontal white matter and this region also best predicted the diagnosis of schizophrenia. There exists an inverse relationship between the measures of white matter integrity and metabolism, which may therefore be physiologically linked. In subjects with schizophrenia, hypermetabolism in the white matter may be a function of lower white matter integrity, with lower efficiency and increased energetic cost of task-related computations.

An Atypical Sulcal Pattern in Children with Disorders of the Corpus Callosum and Its Relation to Behavioral Outcomes

Hypogenesis (hCC) and dysgenesis (dCC) of the corpus callosum (CC) are characterized by its smaller size or absence. The outcomes of these patients vary considerably and are unrelated to the size of the CC abnormality. The aim of the current study was to characterize the sulcal pattern in children with hCC and dCC and to explore its relation to clinical outcome. We used quantitative sulcal pattern analysis that measures deviation (similarity index, SI) of the composite or individual sulcal features (position, depth, area, and graph topology) compared to the control group. We calculated SI for each hemisphere and lobe in 11 children with CC disorder (hCC = 4, dCC = 7) and 15 controls. hCC and dCC had smaller hemispheric SI compared to controls. dCC subjects had smaller regional SI in the frontal and occipital lobes, which were driven by a smaller SI in a position or a graph topology. The significantly decreased SI gradient was found across groups only in the sulcal graph topology of the temporal lobes (controls > hCC > dCC) and was related to clinical outcome. Our results suggest that careful examination of sulcal pattern in hCC and dCC patients could be a useful biomarker of outcome.

Abnormal Left-Hemispheric Sulcal Patterns Correlate with Neurodevelopmental Outcomes in Subjects with Single Ventricular Congenital Heart Disease

Neurodevelopmental abnormalities are the most common noncardiac complications in patients with congenital heart disease (CHD). Prenatal brain abnormalities may be due to reduced oxygenation, genetic factors, or less commonly, teratogens. Understanding the contribution of these factors is essential to improve outcomes. Because primary sulcal patterns are prenatally determined and under strong genetic control, we hypothesized that they are influenced by genetic variants in CHD. In this study, we reveal significant alterations in sulcal patterns among subjects with single ventricle CHD (n = 115, 14.7 ± 2.9 years [mean ± standard deviation]) compared with controls (n = 45, 15.5 ± 2.4 years) using a graph-based pattern-analysis technique. Among patients with CHD, the left hemisphere demonstrated decreased sulcal pattern similarity to controls in the left temporal and parietal lobes, as well as the bilateral frontal lobes. Temporal and parietal lobes demonstrated an abnormally asymmetric left-right pattern of sulcal basin area in CHD subjects. Sulcal pattern similarity to control was positively correlated with working memory, processing speed, and executive function. Exome analysis identified damaging de novo variants only in CHD subjects with more atypical sulcal patterns. Together, these findings suggest that sulcal pattern analysis may be useful in characterizing genetically influenced, atypical early brain development and neurodevelopmental risk in subjects with CHD.

Psychotic symptoms are associated with lower cortical folding in youth at risk for mental illness

BACKGROUND

Cortical folding is essential for healthy brain development. Previous studies have found regional reductions in cortical folding in adult patients with psychotic illness. It is unknown whether these neuroanatomical markers are present in youth with subclinical psychotic symptoms.

METHODS

We collected MRIs and examined the local gyrification index in a sample of 110 youth (mean age ± standard deviation 14.0 ± 3.7 yr; range 9–25 yr) with a family history of severe mental illness: 48 with psychotic symptoms and 62 without. Images were processed using the Human Connectome Pipeline and FreeSurfer. We tested for group differences in local gyrification index using mixed-effects generalized linear models controlling for age, sex and familial clustering. Sensitivity analysis further controlled for intracranial volume, IQ, and stimulant and cannabis use.

RESULTS

Youth with psychotic symptoms displayed an overall trend toward lower cortical folding across all brain regions. After adjusting for multiple comparisons and confounders, regional reductions were localized to the frontal and occipital lobes. Specifically, the medial (B = –0.42, pFDR = 0.04) and lateral (B = –0.39, pFDR = 0.04) orbitofrontal cortices as well as the cuneus (B = –0.47, pFDR = 0.03) and the pericalcarine (B = –0.45, pFDR = 0.03) and lingual (B = –0.38, pFDR = 0.04) gyri.

LIMITATIONS

Inference about developmental trajectories was limited by the cross-sectional data.

CONCLUSION

Psychotic symptoms in youth are associated with cortical folding deficits, even in the absence of psychotic illness. The current study helps clarify the neurodevelopmental basis of psychosis at an early stage, before medication, drug use and other confounds have had a persistent effect on the brain.