Mapping pathways to neuronal atrophy in healthy, mid-aged adults: From chronic stress to systemic inflammation to neurodegeneration?

Growing evidence implicates systemic inflammation in the loss of structural brain integrity in natural ageing and disorder development. Chronic stress and glucocorticoid exposure can potentiate inflammatory processes and may also be linked to neuronal atrophy, particularly in the hippocampus and the human neocortex. To improve understanding of emerging maladaptive interactions between stress and inflammation, this study examined evidence for glucocorticoid- and inflammation-mediated neurodegeneration in healthy mid-aged adults. N = 169 healthy adults (mean age = 39.4, 64.5% female) were sampled from the general population in the context of the ReSource Project. Stress, inflammation and neuronal atrophy were quantified using physiological indices of chronic stress (hair cortisol (HCC) and cortisone (HEC) concentration), systemic inflammation (interleukin-6 (IL-6), high-sensitive C-reactive protein (hs-CRP)), the systemic inflammation index (SII), hippocampal volume (HCV) and cortical thickness (CT) in regions of interest. Structural equation models were used to examine evidence for pathways from stress and inflammation to neuronal atrophy. Model fit indices indicated good representation of stress, inflammation, and neurological data through the constructed models (CT model: robust RMSEA = 0.041, robust χ2 = 910.90; HCV model: robust RMSEA <0.001, robust χ2 = 40.95). Among inflammatory indices, only the SII was positively associated with hair cortisol as one indicator of chronic stress (β = 0.18, p < 0.05). Direct and indirect pathways from chronic stress and systemic inflammation to cortical thickness or hippocampal volume were non-significant. In exploratory analysis, the SII was inversely related to mean cortical thickness. Our results emphasize the importance of considering the multidimensionality of systemic inflammation and chronic stress, with various indicators that may represent different aspects of the systemic reaction. We conclude that inflammation and glucocorticoid-mediated neurodegeneration indicated by IL-6 and hs-CRP and HCC and HEC may only emerge during advanced ageing and disorder processes, still the SII could be a promising candidate for detecting associations between inflammation and neurodegeneration in younger and healthy samples. Future work should examine these pathways in prospective longitudinal designs, for which the present investigation serves as a baseline.

Exploring sex-specific neuroendocrine influences on the sensorimotor-association axis in single individuals

Human neuroimaging studies consistently show multimodal patterns of variability along a key principle of macroscale cortical organization - the sensorimotor-association (S-A) axis. However, little is known about day-to-day fluctuations in functional activity along this axis within an individual, including sex-specific neuroendocrine factors contributing to such transient changes. We leveraged data from two densely sampled healthy young adults, one female and one male, to investigate intra-individual daily variability along the S-A axis, which we computed as our measure of functional cortical organization by reducing the dimensionality of functional connectivity matrices. Daily variability was greatest in temporal limbic and ventral prefrontal regions in both participants, and was more strongly pronounced in the male subject. Next, we probed local- and system-level effects of steroid hormones and self-reported perceived stress on functional organization. Our findings revealed modest effects that differed between participants, hinting at subtle -potentially sex-specific- associations between neuroendocrine fluctuations and intra-individual variability along the S-A axis. In sum, our study points to neuroendocrine factors as possible modulators of intra-individual variability in functional brain organization, highlighting the need for further research in larger samples.

Whole-brain structural connectome asymmetry in autism

Autism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in individuals with autism using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. Comparing the asymmetry index between individuals with autism and neurotypical controls, we found atypical structural connectome asymmetry in the sensory and default-mode regions, particularly showing weaker asymmetry towards the right hemisphere in autism. Network communication provided topological underpinnings by demonstrating that the inferior temporal cortex and limbic and frontoparietal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the inferior temporal and lateral visual cortices in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry could be used as a measure for predicting communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings.

Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

Connectome-wide structure-function coupling models implicate polysynaptic alterations in autism

Autism spectrum disorder (ASD) is one of the most common neurodevelopmental diagnoses. Although incompletely understood, structural and functional network alterations are increasingly recognized to be at the core of the condition. We utilized multimodal imaging and connectivity modeling to study structure-function coupling in ASD and probed mono- and polysynaptic mechanisms on structurally-governed network function. We examined multimodal magnetic resonance imaging data in 80 ASD and 61 neurotypical controls from the Autism Brain Imaging Data Exchange (ABIDE) II initiative. We predicted intrinsic functional connectivity from structural connectivity data in each participant using a Riemannian optimization procedure that varies the times that simulated signals can unfold along tractography-derived personalized connectomes. In both ASD and neurotypical controls, we observed improved structure-function prediction at longer diffusion time scales, indicating better modeling of brain function when polysynaptic mechanisms are accounted for. Prediction accuracy differences (∆prediction accuracy) were marked in transmodal association systems, such as the default mode network, in both neurotypical controls and ASD. Differences were, however, lower in ASD in a polysynaptic regime at higher simulated diffusion times. We compared regional differences in ∆prediction accuracy between both groups to assess the impact of polysynaptic communication on structure-function coupling. This analysis revealed that between-group differences in ∆prediction accuracy followed a sensory-to-transmodal cortical hierarchy, with an increased gap between controls and ASD in transmodal compared to sensory/motor systems. Multivariate associative techniques revealed that structure-function differences reflected inter-individual differences in autistic symptoms and verbal as well as non-verbal intelligence. Our network modeling approach sheds light on atypical structure-function coupling in autism, and suggests that polysynaptic network mechanisms are implicated in the condition and that these can help explain its wide range of associated symptoms.

A Comparative Perspective on the Cerebello-Cerebral System and Its Link to Cognition

The longstanding idea that the cerebral cortex is the main neural correlate of human cognition can be elaborated by comparative analyses along the vertebrate phylogenetic tree that support the view that the cerebello-cerebral system is suited to support non-motor functions more generally. In humans, diverse accounts have illustrated cerebellar involvement in cognitive functions. Although the neocortex, and its transmodal association cortices such as the prefrontal cortex, have become disproportionately large over primate evolution specifically, human neocortical volume does not appear to be exceptional relative to the variability within primates. Rather, several lines of evidence indicate that the exceptional volumetric increase of the lateral cerebellum in conjunction with its connectivity with the cerebral cortical system may be linked to non-motor functions and mental operation in primates. This idea is supported by diverging cerebello-cerebral adaptations that potentially coevolve with cognitive abilities across other vertebrates such as dolphins, parrots, and elephants. Modular adaptations upon the vertebrate cerebello-cerebral system may thus help better understand the neuroevolutionary trajectory of the primate brain and its relation to cognition in humans. Lateral cerebellar lobules crura I-II and their reciprocal connections to the cerebral cortical association areas appear to have substantially expanded in great apes, and humans. This, along with the notable increase in the ventral portions of the dentate nucleus and a shift to increased relative prefrontal-cerebellar connectivity, suggests that modular cerebellar adaptations support cognitive functions in humans. In sum, we show how comparative neuroscience provides new avenues to broaden our understanding of cerebellar and cerebello-cerebral functions in the context of cognition.

Sex differences in intrinsic functional cortical organization reflect differences in network topology rather than cortical morphometry

Brain size robustly differs between sexes. However, the consequences of this anatomical dimorphism on sex differences in intrinsic brain function remain unclear. We investigated the extent to which sex differences in intrinsic cortical functional organization may be explained by differences in cortical morphometry, namely brain size, microstructure, and the geodesic distances of connectivity profiles. For this, we computed a low dimensional representation of functional cortical organization, the sensory-association axis, and identified widespread sex differences. Contrary to our expectations, observed sex differences in functional organization were not fundamentally associated with differences in brain size, microstructural organization, or geodesic distances, despite these morphometric properties being per se associated with functional organization and differing between sexes. Instead, functional sex differences in the sensory-association axis were associated with differences in functional connectivity profiles and network topology. Collectively, our findings suggest that sex differences in functional cortical organization extend beyond sex differences in cortical morphometry.

Teaser

Investigating sex differences in functional cortical organization and their association to differences in cortical morphometry.

Phylogenetic comparative analysis of the cerebello-cerebral system in 34 species highlights primate-general expansion of cerebellar crura I-II

The reciprocal connections between the cerebellum and the cerebrum have been suggested to simultaneously play a role in brain size increase and to support a broad array of brain functions in primates. The cerebello-cerebral system has undergone marked functionally relevant reorganization. In particular, the lateral cerebellar lobules crura I-II (the ansiform) have been suggested to be expanded in hominoids. Here, we manually segmented 63 cerebella (34 primate species; 9 infraorders) and 30 ansiforms (13 species; 8 infraorders) to understand how their volumes have evolved over the primate lineage. Together, our analyses support proportional cerebellar-cerebral scaling, whereas ansiforms have expanded faster than the cerebellum and cerebrum. We did not find different scaling between strepsirrhines and haplorhines, nor between apes and non-apes. In sum, our study shows primate-general structural reorganization of the ansiform, relative to the cerebello-cerebral system, which is relevant for specialized brain functions in an evolutionary context.

The regional variation of laminar thickness in the human isocortex is related to cortical hierarchy and interregional connectivity

The human isocortex consists of tangentially organized layers with unique cytoarchitectural properties. These layers show spatial variations in thickness and cytoarchitecture across the neocortex, which is thought to support function through enabling targeted corticocortical connections. Here, leveraging maps of the 6 cortical layers based on 3D human brain histology, we aimed to quantitatively characterize the systematic covariation of laminar structure in the cortex and its functional consequences. After correcting for the effect of cortical curvature, we identified a spatial pattern of changes in laminar thickness covariance from lateral frontal to posterior occipital regions, which differentiated the dominance of infra- versus supragranular layer thickness. Corresponding to the laminar regularities of cortical connections along cortical hierarchy, the infragranular-dominant pattern of laminar thickness was associated with higher hierarchical positions of regions, mapped based on resting-state effective connectivity in humans and tract-tracing of structural connections in macaques. Moreover, we show that regions with similar laminar thickness patterns have a higher likelihood of structural connections and strength of functional connections. In sum, here we characterize the organization of laminar thickness in the human isocortex and its association with cortico-cortical connectivity, illustrating how laminar organization may provide a foundational principle of cortical function.

Diverging asymmetry of intrinsic functional organization in autism

Autism is a neurodevelopmental condition involving atypical sensory-perceptual functions together with language and socio-cognitive deficits. Previous work has reported subtle alterations in the asymmetry of brain structure and reduced laterality of functional activation in individuals with autism relative to non-autistic individuals (NAI). However, whether functional asymmetries show altered intrinsic systematic organization in autism remains unclear. Here, we examined inter- and intra-hemispheric asymmetry of intrinsic functional gradients capturing connectome organization along three axes, stretching between sensory-default, somatomotor-visual, and default-multiple demand networks, to study system-level hemispheric imbalances in autism. We observed decreased leftward functional asymmetry of language network organization in individuals with autism, relative to NAI. Whereas language network asymmetry varied across age groups in NAI, this was not the case in autism, suggesting atypical functional laterality in autism may result from altered developmental trajectories. Finally, we observed that intra- but not inter-hemispheric features were predictive of the severity of autistic traits. Our findings illustrate how regional and patterned functional lateralization is altered in autism at the system level. Such differences may be rooted in atypical developmental trajectories of functional organization asymmetry in autism.

Lack of structural brain alterations associated with insomnia: findings from the ENIGMA-Sleep Working Group

Existing neuroimaging studies have reported divergent structural alterations in insomnia disorder (ID). In the present study, we performed a large-scale coordinated meta-analysis by pooling structural brain measures from 1085 subjects (mean [SD] age 50.5 [13.9] years, 50.2% female, 17.4% with insomnia) across three international Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA)-Sleep cohorts. Two sites recruited patients with ID/controls: Freiburg (University of Freiburg Medical Center, Freiburg, Germany) 42/43 and KUMS (Kermanshah University of Medical Sciences, Kermanshah, Iran) 42/49, while the Study of Health in Pomerania (SHIP-Trend, University Medicine Greifswald, Greifswald, Germany) recruited population-based individuals with/without insomnia symptoms 75/662. The influence of insomnia on magnetic resonance imaging-based brain morphometry using an insomnia brain score was then assessed. Within each cohort, we used an ordinary least-squares linear regression to investigate the link between the individual regional cortical and subcortical volumes and the presence of insomnia symptoms. Then, we performed a fixed-effects meta-analysis across cohorts based on the first-level results. For the insomnia brain score, weighted logistic ridge regression was performed on one sample (Freiburg), which separated patients with ID from controls to train a model based on the segmentation measurements. Afterward, the insomnia brain scores were validated using the other two samples. The model was used to predict the log-odds of the subjects with insomnia given individual insomnia-related brain atrophy. After adjusting for multiple comparisons, we did not detect any significant associations between insomnia symptoms and cortical or subcortical volumes, nor could we identify a global insomnia-related brain atrophy pattern. Thus, we observed inconsistent brain morphology differences between individuals with and without insomnia across three independent cohorts. Further large-scale cross-sectional/longitudinal studies using both structural and functional neuroimaging are warranted to decipher the neurobiology of insomnia.

Macroscale Thalamic Functional Organization Disturbances and Underlying Core Cytoarchitecture in Early-Onset Schizophrenia

BACKGROUND AND HYPOTHESIS

Schizophrenia is a polygenetic mental disorder with heterogeneous positive and negative symptom constellations, and is associated with abnormal cortical connectivity. The thalamus has a coordinative role in cortical function and is key to the development of the cerebral cortex. Conversely, altered functional organization of the thalamus might relate to overarching cortical disruptions in schizophrenia, anchored in development.

STUDY DESIGN

Here, we contrasted resting-state fMRI in 86 antipsychotic-naive first-episode early-onset schizophrenia (EOS) patients and 91 typically developing controls to study whether macroscale thalamic organization is altered in EOS. Employing dimensional reduction techniques on thalamocortical functional connectome (FC), we derived lateral-medial and anterior-posterior thalamic functional axes.

STUDY RESULTS

We observed increased segregation of macroscale thalamic functional organization in EOS patients, which was related to altered thalamocortical interactions both in unimodal and transmodal networks. Using an ex vivo approximation of core-matrix cell distribution, we found that core cells particularly underlie the macroscale abnormalities in EOS patients. Moreover, the disruptions were associated with schizophrenia-related gene expression maps. Behavioral and disorder decoding analyses indicated that the macroscale hierarchy disturbances might perturb both perceptual and abstract cognitive functions and contribute to negative syndromes in patients.

CONCLUSIONS

These findings provide mechanistic evidence for disrupted thalamocortical system in schizophrenia, suggesting a unitary pathophysiological framework.

Genetic insights into human cortical organization and development through genome-wide analyses of 2,347 neuroimaging phenotypes

Our understanding of the genetics of the human cerebral cortex is limited both in terms of the diversity and the anatomical granularity of brain structural phenotypes. Here we conducted a genome-wide association meta-analysis of 13 structural and diffusion magnetic resonance imaging-derived cortical phenotypes, measured globally and at 180 bilaterally averaged regions in 36,663 individuals and identified 4,349 experiment-wide significant loci. These phenotypes include cortical thickness, surface area, gray matter volume, measures of folding, neurite density and water diffusion. We identified four genetic latent structures and causal relationships between surface area and some measures of cortical folding. These latent structures partly relate to different underlying gene expression trajectories during development and are enriched for different cell types. We also identified differential enrichment for neurodevelopmental and constrained genes and demonstrate that common genetic variants associated with cortical expansion are associated with cephalic disorders. Finally, we identified complex interphenotype and inter-regional genetic relationships among the 13 phenotypes, reflecting the developmental differences among them. Together, these analyses identify distinct genetic organizational principles of the cortex and their correlates with neurodevelopment.

Atypical structural connectome asymmetry and associations with network communication in autism spectrum disorder

Autism spectrum disorder is a common neurodevelopmental condition showing connectome disorganization in sensory and transmodal cortices. However, alterations in the inter-hemispheric asymmetry of structural connectome are remained to be investigated. Here, we studied structural connectome asymmetry in individuals with autism using dimensionality reduction techniques and assessed its topological underpinnings by associating with network communication measures. We found that the sensory and heteromodal association regions showed significant between-group differences in inter-hemispheric asymmetry between individuals with autism and neurotypical controls. In addition, the network communication ability was particularly altered between visual and limbic areas. Our findings provide insights for understanding structural connectome alteration in autism and its topological underpinnings.Clinical Relevance- This study provides insights into the understanding of atypical macroscale structural connectome organization in individuals with autism.

Associations between mental health, blood pressure and the development of hypertension

Multiple studies have reported a link between mental health and high blood pressure with mixed or even contradictory findings. Here, we resolve those contradictions and further dissect the cross-sectional and longitudinal relationship between mental health, systolic blood pressure, and hypertension using extensive psychological, medical and neuroimaging data from the UK Biobank. We show that higher systolic blood pressure is associated with fewer depressive symptoms, greater well-being, and lower emotion-related brain activity. Interestingly, impending hypertension is associated with poorer mental health years before HTN is diagnosed. In addition, a stronger baseline association between systolic blood pressure and better mental health was observed in individuals who develop hypertension until follow-up. Overall, our findings offer insights on the complex relationship between mental health, blood pressure, and hypertension, suggesting that-via baroreceptor mechanisms and reinforcement learning-the association of higher blood pressure with better mental health may ultimately contribute to the development of hypertension.

A convergent structure-function substrate of cognitive imbalances in autism

BACKGROUND

Autism spectrum disorder (ASD) is a common neurodevelopmental diagnosis showing substantial phenotypic heterogeneity. A leading example can be found in verbal and nonverbal cognitive skills, which vary from elevated to impaired compared with neurotypical individuals. Moreover, deficits in verbal profiles often coexist with normal or superior performance in the nonverbal domain.

METHODS

To study brain substrates underlying cognitive imbalance in ASD, we capitalized categorical and dimensional IQ profiling as well as multimodal neuroimaging.

RESULTS

IQ analyses revealed a marked verbal to nonverbal IQ imbalance in ASD across 2 datasets (Dataset-1: 155 ASD, 151 controls; Dataset-2: 270 ASD, 490 controls). Neuroimaging analysis in Dataset-1 revealed a structure-function substrate of cognitive imbalance, characterized by atypical cortical thickening and altered functional integration of language networks alongside sensory and higher cognitive areas.

CONCLUSION

Although verbal and nonverbal intelligence have been considered as specifiers unrelated to autism diagnosis, our results indicate that intelligence disparities are accentuated in ASD and reflected by a consistent structure-function substrate affecting multiple brain networks. Our findings motivate the incorporation of cognitive imbalances in future autism research, which may help to parse the phenotypic heterogeneity and inform intervention-oriented subtyping in ASD.

Long-range functional connections mirror and link microarchitectural and cognitive hierarchies in the human brain

BACKGROUND

Higher-order cognition is hypothesized to be implemented via distributed cortical networks that are linked via long-range connections. However, it is unknown how computational advantages of long-range connections reflect cortical microstructure and microcircuitry.

METHODS

We investigated this question by (i) profiling long-range cortical connectivity using resting-state functional magnetic resonance imaging (MRI) and cortico-cortical geodesic distance mapping, (ii) assessing how long-range connections reflect local brain microarchitecture, and (iii) examining the microarchitectural similarity of regions connected through long-range connections.

RESULTS

Analysis of 2 independent datasets indicated that sensory/motor areas had more clustered short-range connections, while transmodal association systems hosted distributed, long-range connections. Meta-analytical decoding suggested that this topographical difference mirrored shifts in cognitive function, from perception/action towards emotional/social processing. Analysis of myelin-sensitive in vivo MRI as well as postmortem histology and transcriptomics datasets established that gradients in functional connectivity distance are paralleled by those present in cortical microarchitecture. Notably, long-range connections were found to link spatially remote regions of association cortex with an unexpectedly similar microarchitecture.

CONCLUSIONS

By mapping covarying topographies of long-range functional connections and cortical microcircuits, the current work provides insights into structure-function relations in human neocortex.

BrainStat: A toolbox for brain-wide statistics and multimodal feature associations

Analysis and interpretation of neuroimaging datasets has become a multidisciplinary endeavor, relying not only on statistical methods, but increasingly on associations with respect to other brain-derived features such as gene expression, histological data, and functional as well as cognitive architectures. Here, we introduce BrainStat - a toolbox for (i) univariate and multivariate linear models in volumetric and surface-based brain imaging datasets, and (ii) multidomain feature association of results with respect to spatial maps of post-mortem gene expression and histology, task-based fMRI meta-analysis, as well as resting-state fMRI motifs across several common surface templates. The combination of statistics and feature associations into a turnkey toolbox streamlines analytical processes and accelerates cross-modal research. The toolbox is implemented in both Python and MATLAB, two widely used programming languages in the neuroimaging and neuroinformatics communities. BrainStat is openly available and complemented by an expandable documentation.

Heritability of hippocampal functional and microstructural organisation

The hippocampus is a uniquely infolded allocortical structure in the medial temporal lobe that consists of the microstructurally and functionally distinct subregions: subiculum, cornu ammonis, and dentate gyrus. The hippocampus is a remarkably plastic region that is implicated in learning and memory. At the same time it has been shown that hippocampal subregion volumes are heritable, and that genetic expression varies along a posterior to anterior axis. Here, we studied how a heritable, stable, hippocampal organisation may support its flexible function in healthy adults. Leveraging the twin set-up of the Human Connectome Project with multimodal neuroimaging, we observed that the functional connectivity between hippocampus and cortex was heritable and that microstructure of the hippocampus genetically correlated with cortical microstructure. Moreover, both functional and microstructural organisation could be consistently captured by anterior-to-posterior and medial-to-lateral axes across individuals. However, heritability of functional, relative to microstructural, organisation was found reduced, suggesting individual variation in functional organisation may be explained by experience-driven factors. Last, we demonstrate that structure and function couple along an inherited macroscale organisation, suggesting an interplay of stability and plasticity within the hippocampus. Our study provides new insights on the heritability of the hippocampal of the structure and function within the hippocampal organisation.

A cross-cohort replicable and heritable latent dimension linking behaviour to multi-featured brain structure

Identifying associations between interindividual variability in brain structure and behaviour requires large cohorts, multivariate methods, out-of-sample validation and, ideally, out-of-cohort replication. Moreover, the influence of nature vs nurture on brain-behaviour associations should be analysed. We analysed associations between brain structure (grey matter volume, cortical thickness, and surface area) and behaviour (spanning cognition, emotion, and alertness) using regularized canonical correlation analysis and a machine learning framework that tests the generalisability and stability of such associations. The replicability of brain-behaviour associations was assessed in two large, independent cohorts. The load of genetic factors on these associations was analysed with heritability and genetic correlation. We found one heritable and replicable latent dimension linking cognitive-control/executive-functions and positive affect to brain structural variability in areas typically associated with higher cognitive functions, and with areas typically associated with sensorimotor functions. These results revealed a major axis of interindividual behavioural variability linking to a whole-brain structural pattern.

Genetic and phylogenetic uncoupling of structure and function in human transmodal cortex

Brain structure scaffolds intrinsic function, supporting cognition and ultimately behavioral flexibility. However, it remains unclear how a static, genetically controlled architecture supports flexible cognition and behavior. Here, we synthesize genetic, phylogenetic and cognitive analyses to understand how the macroscale organization of structure-function coupling across the cortex can inform its role in cognition. In humans, structure-function coupling was highest in regions of unimodal cortex and lowest in transmodal cortex, a pattern that was mirrored by a reduced alignment with heritable connectivity profiles. Structure-function uncoupling in macaques had a similar spatial distribution, but we observed an increased coupling between structure and function in association cortices relative to humans. Meta-analysis suggested regions with the least genetic control (low heritable correspondence and different across primates) are linked to social-cognition and autobiographical memory. Our findings suggest that genetic and evolutionary uncoupling of structure and function in different transmodal systems may support the emergence of complex forms of cognition.

Diagnosis-informed connectivity subtyping discovers subgroups of autism with reproducible symptom profiles

Clinical heterogeneity has been one of the main barriers to develop effective biomarkers and therapeutic strategies in autism spectrum disorder (ASD). Recognizing this challenge, much effort has been made in recent neuroimaging studies to find biologically more homogeneous subgroups (called 'neurosubtypes') in autism. However, most approaches have rarely evaluated how much the employed features in subtyping represent the core anomalies of ASD, obscuring its utility in actual clinical diagnosis. To address this, we combined two data-driven methods, 'connectome-based gradient' and 'functional random forest', collectively allowing to discover reproducible neurosubtypes based on resting-state functional connectivity profiles that are specific to ASD. Indeed, the former technique provides the features (as input for subtyping) that effectively summarize whole-brain connectome variations in both normal and ASD conditions, while the latter leverages a supervised random forest algorithm to inform diagnostic labels to clustering, which makes neurosubtyping driven by the features of ASD core anomalies. Applying this framework to the open-sharing Autism Brain Imaging Data Exchange repository data (discovery, n = 103/108 for ASD/typically developing [TD]; replication, n = 44/42 for ASD/TD), we found three dominant subtypes of functional gradients in ASD and three subtypes in TD. The subtypes in ASD revealed distinct connectome profiles in multiple brain areas, which are associated with different Neurosynth-derived cognitive functions previously implicated in autism studies. Moreover, these subtypes showed different symptom severity, which degree co-varies with the extent of functional gradient changes observed across the groups. The subtypes in the discovery and replication datasets showed similar symptom profiles in social interaction and communication domains, confirming a largely reproducible brain-behavior relationship. Finally, the connectome gradients in ASD subtypes present both common and distinct patterns compared to those in TD, reflecting their potential overlap and divergence in terms of developmental mechanisms involved in the manifestation of large-scale functional networks. Our study demonstrated a potential of the diagnosis-informed subtyping approach in developing a clinically useful brain-based classification system for future ASD research.

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

ENIGMA-Sleep: Challenges, opportunities, and the road map

Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine.

Recent developments in representations of the connectome

Research into the human connectome (i.e., all connections in the human brain) with the use of resting state functional MRI has rapidly increased in popularity in recent years, especially with the growing availability of large-scale neuroimaging datasets. The goal of this review article is to describe innovations in functional connectome representations that have come about in the past 8 years, since the 2013 NeuroImage special issue on 'Mapping the Connectome'. In the period, research has shifted from group-level brain parcellations towards the characterization of the individualized connectome and of relationships between individual connectomic differences and behavioral/clinical variation. Achieving subject-specific accuracy in parcel boundaries while retaining cross-subject correspondence is challenging, and a variety of different approaches are being developed to meet this challenge, including improved alignment, improved noise reduction, and robust group-to-subject mapping approaches. Beyond the interest in the individualized connectome, new representations of the data are being studied to complement the traditional parcellated connectome representation (i.e., pairwise connections between distinct brain regions), such as methods that capture overlapping and smoothly varying patterns of connectivity ('gradients'). These different connectome representations offer complimentary insights into the inherent functional organization of the brain, but challenges for functional connectome research remain. Interpretability will be improved by future research towards gaining insights into the neural mechanisms underlying connectome observations obtained from functional MRI. Validation studies comparing different connectome representations are also needed to build consensus and confidence to proceed with clinical trials that may produce meaningful clinical translation of connectome insights.

Behavioral, Anatomical and Heritable Convergence of Affect and Cognition in Superior Frontal Cortex

Cognitive abilities and affective experience are key human traits that are interrelated in behavior and brain. Individual variation of cognitive and affective traits, as well as brain structure, has been shown to partly underlie genetic effects. However, to what extent affect and cognition have a shared genetic relationship with local brain structure is incompletely understood. Here we studied phenotypic and genetic correlations of cognitive and affective traits in behavior and brain structure (cortical thickness, surface area and subcortical volumes) in the pedigree-based Human Connectome Project sample (N = 1091). Both cognitive and affective trait scores were highly heritable and showed significant phenotypic correlation on the behavioral level. Cortical thickness in the left superior frontal cortex showed a phenotypic association with both affect and cognition. Decomposing the phenotypic correlations into genetic and environmental components showed that the associations were accounted for by shared genetic effects between the traits. Quantitative functional decoding of the left superior frontal cortex further indicated that this region is associated with cognitive and emotional functioning. This study provides a multi-level approach to study the association between affect and cognition and suggests a convergence of both in superior frontal cortical thickness.

The BigBrainWarp toolbox for integration of BigBrain 3D histology with multimodal neuroimaging

Neuroimaging stands to benefit from emerging ultrahigh-resolution 3D histological atlases of the human brain; the first of which is 'BigBrain'. Here, we review recent methodological advances for the integration of BigBrain with multi-modal neuroimaging and introduce a toolbox, 'BigBrainWarp', that combines these developments. The aim of BigBrainWarp is to simplify workflows and support the adoption of best practices. This is accomplished with a simple wrapper function that allows users to easily map data between BigBrain and standard MRI spaces. The function automatically pulls specialised transformation procedures, based on ongoing research from a wide collaborative network of researchers. Additionally, the toolbox improves accessibility of histological information through dissemination of ready-to-use cytoarchitectural features. Finally, we demonstrate the utility of BigBrainWarp with three tutorials and discuss the potential of the toolbox to support multi-scale investigations of brain organisation.

Centering inclusivity in the design of online conferences-An OHBM-Open Science perspective

As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.

Atypical Integration of Sensory-to-Transmodal Functional Systems Mediates Symptom Severity in Autism

A notable characteristic of autism spectrum disorder (ASD) is co-occurring deficits in low-level sensory processing and high-order social interaction. While there is evidence indicating detrimental cascading effects of sensory anomalies on the high-order cognitive functions in ASD, the exact pathological mechanism underlying their atypical functional interaction across the cortical hierarchy has not been systematically investigated. To address this gap, here we assessed the functional organisation of sensory and motor areas in ASD, and their relationship with subcortical and high-order trandmodal systems. In a resting-state fMRI data of 107 ASD and 113 neurotypical individuals, we applied advanced connectopic mapping to probe functional organization of primary sensory/motor areas, together with targeted seed-based intrinsic functional connectivity (iFC) analyses. In ASD, the connectopic mapping revealed topological anomalies (i.e., excessively more segregated iFC) in the motor and visual areas, the former of which patterns showed association with the symptom severity of restricted and repetitive behaviors. Moreover, the seed-based analysis found diverging patterns of ASD-related connectopathies: decreased iFCs within the sensory/motor areas but increased iFCs between sensory and subcortical structures. While decreased iFCs were also found within the higher-order functional systems, the overall proportion of this anomaly tends to increase along the level of cortical hierarchy, suggesting more dysconnectivity in the higher-order functional networks. Finally, we demonstrated that the association between low-level sensory/motor iFCs and clinical symptoms in ASD was mediated by the high-order transmodal systems, suggesting pathogenic functional interactions along the cortical hierarchy. Findings were largely replicated in the independent dataset. These results highlight that atypical integration of sensory-to-high-order systems contributes to the complex ASD symptomatology.

Association between hippocampal structure and serum Brain-Derived Neurotrophic Factor (BDNF) in healthy adults: A registered report

The hippocampus is a highly plastic brain structure supporting functions central to human cognition. Morphological changes in the hippocampus have been implicated in development, aging, as well as in a broad range of neurological and psychiatric disorders. A growing body of research suggests that hippocampal plasticity is closely linked to the actions of brain-derived neurotrophic factor (BDNF). However, evidence on the relationship between hippocampal volume (HCV) and peripheral BDNF levels is scarce and limited to elderly and patient populations. Further, despite evidence that BDNF expression differs throughout the hippocampus and is implicated in adult neurogenesis specifically in the dentate gyrus, no study has so far related peripheral BDNF levels to the volumes of individual hippocampal subfields. Besides its clinical implications, BDNF-facilitated hippocampal plasticity plays an important role in regulating cognitive and affective processes. In the current registered report, we investigated how serum BDNF (sBDNF) levels relate to volumes of the hippocampal formation and its subfields in a large sample of healthy adults (N = 279, 160 f) with a broad age range (20-55 years, mean 40.5) recruited in the context of the ReSource Project. We related HCV to basal sBDNF and, in a subsample (n = 103, 57 f), to acute stress-reactive change in sBDNF. We further tested the role of age as a moderator of both associations. Contrary to our hypotheses, neither basal sBDNF levels nor stress-reactive sBDNF change were associated with total HCV or volume of the dentate gyrus/cornu ammonis 4 (DG/CA4) subfield. We also found no evidence for a moderating effect of age on any of these associations. Our null results provide a first point of reference on the relationship between sBDNF and HCV in healthy mid-age, in contrast to patient or aging populations. We suggest that sBDNF levels have limited predictive value for morphological differences of the hippocampal structure when notable challenge to its neuronal integrity or to neurotrophic capacity is absent.

Structural Connectivity Gradients of the Temporal Lobe Serve as Multiscale Axes of Brain Organization and Cortical Evolution

The temporal lobe is implicated in higher cognitive processes and is one of the regions that underwent substantial reorganization during primate evolution. Its functions are instantiated, in part, by the complex layout of its structural connections. Here, we identified low-dimensional representations of structural connectivity variations in human temporal cortex and explored their microstructural underpinnings and associations to macroscale function. We identified three eigenmodes which described gradients in structural connectivity. These gradients reflected inter-regional variations in cortical microstructure derived from quantitative magnetic resonance imaging and postmortem histology. Gradient-informed models accurately predicted macroscale measures of temporal lobe function. Furthermore, the identified gradients aligned closely with established measures of functional reconfiguration and areal expansion between macaques and humans, highlighting their potential role in shaping temporal lobe function throughout primate evolution. Findings were replicated in several datasets. Our results provide robust evidence for three axes of structural connectivity in human temporal cortex with consistent microstructural underpinnings and contributions to large-scale brain network function.

Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism

The pathophysiology of autism has been suggested to involve a combination of both macroscale connectome miswiring and microcircuit anomalies. Here, we combine connectome-wide manifold learning with biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. We studied neuroimaging and phenotypic data in 47 individuals with autism and 37 typically developing controls obtained from the Autism Brain Imaging Data Exchange initiative. Our analysis establishes significant differences in structural connectome organization in individuals with autism relative to controls, with strong between-group effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models reveal that the degree of macroscale anomalies is related to atypical increases of recurrent excitation/inhibition, as well as subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic association analysis based on postmortem datasets identifies genes expressed in cortical and thalamic areas from childhood to young adulthood. Finally, supervised machine learning finds that the macroscale perturbations are associated with symptom severity scores on the Autism Diagnostic Observation Schedule. Together, our analyses suggest that atypical subcortico-cortical interactions are associated with both microcircuit and macroscale connectome differences in autism.

Signal diffusion along connectome gradients and inter-hub routing differentially contribute to dynamic human brain function

Human cognition is dynamic, alternating over time between externally-focused states and more abstract, often self-generated, patterns of thought. Although cognitive neuroscience has documented how networks anchor particular modes of brain function, mechanisms that describe transitions between distinct functional states remain poorly understood. Here, we examined how time-varying changes in brain function emerge within the constraints imposed by macroscale structural network organization. Studying a large cohort of healthy adults (n = 326), we capitalized on manifold learning techniques that identify low dimensional representations of structural connectome organization and we decomposed neurophysiological activity into distinct functional states and their transition patterns using Hidden Markov Models. Structural connectome organization predicted dynamic transitions anchored in sensorimotor systems and those between sensorimotor and transmodal states. Connectome topology analyses revealed that transitions involving sensorimotor states traversed short and intermediary distances and adhered strongly to communication mechanisms of network diffusion. Conversely, transitions between transmodal states involved spatially distributed hubs and increasingly engaged long-range routing. These findings establish that the structure of the cortex is optimized to allow neural states the freedom to vary between distinct modes of processing, and so provides a key insight into the neural mechanisms that give rise to the flexibility of human cognition.

Shaping brain structure: Genetic and phylogenetic axes of macroscale organization of cortical thickness

The topology of the cerebral cortex has been proposed to provide an important source of constraint for the organization of cognition. In a sample of twins (n = 1113), we determined structural covariance of thickness to be organized along both a posterior-to-anterior and an inferior-to-superior axis. Both organizational axes were present when investigating the genetic correlation of cortical thickness, suggesting a strong genetic component in humans, and had a comparable organization in macaques, demonstrating they are phylogenetically conserved in primates. In both species, the inferior-superior dimension of cortical organization aligned with the predictions of dual-origin theory, and in humans, we found that the posterior-to-anterior axis related to a functional topography describing a continuum of functions from basic processes involved in perception and action to more abstract features of human cognition. Together, our study provides important insights into how functional and evolutionary patterns converge at the level of macroscale cortical structural organization.

Effective Self-Management for Early Career Researchers in the Natural and Life Sciences

Early career researchers (ECRs) are faced with a range of competing pressures in academia, making self-management key to building a successful career. The Organization for Human Brain Mapping undertook a group effort to gather helpful advice for ECRs in self-management.

Influence of Processing Pipeline on Cortical Thickness Measurement

In recent years, replicability of neuroscientific findings, specifically those concerning correlates of morphological properties of gray matter (GM), have been subject of major scrutiny. Use of different processing pipelines and differences in their estimates of the macroscale GM may play an important role in this context. To address this issue, here, we investigated the cortical thickness estimates of three widely used pipelines. Based on analyses in two independent large-scale cohorts, we report high levels of within-pipeline reliability of the absolute cortical thickness-estimates and comparable spatial patterns of cortical thickness-estimates across all pipelines. Within each individual, absolute regional thickness differed between pipelines, indicating that in-vivo thickness measurements are only a proxy of actual thickness of the cortex, which shall only be compared within the same software package and thickness estimation technique. However, at group level, cortical thickness-estimates correlated strongly between pipelines, in most brain regions. The smallest between-pipeline correlations were observed in para-limbic areas and insula. These regions also demonstrated the highest interindividual variability and the lowest reliability of cortical thickness-estimates within each pipeline, suggesting that structural variations within these regions should be interpreted with caution.

Multidimensional Neuroanatomical Subtyping of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders with multiple biological etiologies and highly variable symptoms. Using a novel analytical framework that integrates cortex-wide MRI markers of vertical (i.e., thickness, tissue contrast) and horizontal (i.e., surface area, geodesic distance) cortical organization, we could show that a large multi-centric cohort of individuals with ASD falls into 3 distinctive anatomical subtypes (ASD-I: cortical thickening, increased surface area, tissue blurring; ASD-II: cortical thinning, decreased distance; ASD-III: increased distance). Bootstrap analysis indicated a high consistency of these biotypes across thousands of simulations, while analysis of behavioral phenotypes and resting-state fMRI showed differential symptom load (i.e., Autism Diagnostic Observation Schedule; ADOS) and instrinsic connectivity anomalies in communication and social-cognition networks. Notably, subtyping improved supervised learning approaches predicting ADOS score in single subjects, with significantly increased performance compared to a subtype-blind approach. The existence of different subtypes may reconcile previous results so far not converging on a consistent pattern of anatomical anomalies in autism, and possibly relate the presence of diverging corticogenic and maturational anomalies. The high accuracy for symptom severity prediction indicates benefits of MRI biotyping for personalized diagnostics and may guide the development of targeted therapeutic strategies.

Association of Short-term Change in Leukocyte Telomere Length With Cortical Thickness and Outcomes of Mental Training Among Healthy Adults: A Randomized Clinical Trial

Importance

Telomere length is associated with the development of age-related diseases and structural differences in multiple brain regions. It remains unclear, however, whether change in telomere length is linked to brain structure change, and to what extent telomere length can be influenced through mental training.

Objectives

To assess the dynamic associations between leukocyte telomere length (LTL) and cortical thickness (CT), and to determine whether LTL is affected by a longitudinal contemplative mental training intervention.

Design, Setting, and Participants

An open-label efficacy trial of three 3-month mental training modules with healthy, meditation-naive adults was conducted. Data on LTL and CT were collected 4 times over 9 months between April 22, 2013, and March 31, 2015, as part of the ReSource Project. Data analysis was performed between September 23, 2016, and June 21, 2019. Of 1582 eligible individuals, 943 declined to participate; 362 were randomly selected for participation and assigned to training or retest control cohorts, with demographic characteristics matched. The retest control cohorts underwent all testing but no training. Intention-to-treat analysis was performed.

Interventions

Training cohort participants completed 3 modules cultivating interoception and attention (Presence), compassion (Affect), or perspective taking (Perspective).

Main Outcomes and Measures

Change in LTL and CT.

Results

Of the 362 individuals randomized, 30 participants dropped out before study initiation (initial sample, 332). Data were available for analysis of the training intervention in 298 participants (n = 222 training; n = 76 retest control) (175 women [58.7%]; mean [SD] age, 40.5 [9.3] years). The training modules had no effect on LTL. In 699 observations from all 298 participants, mean estimated changes in the relative ratios of telomere repeat copy number to single-copy gene (T/S) were for no training, 0.004 (95% CI, -0.010 to 0.018); Presence, -0.007 (95% CI, -0.025 to 0.011); Affect, -0.005 (95% CI, -0.019 to 0.010); and Perspective, -0.001 (95% CI, -0.017 to 0.016). Cortical thickness change data were analyzed in 167 observations from 67 retest control participants (37 women [55.2%], mean [SD] age, 39.6 [9.0] years). In this retest control cohort subsample, naturally occurring LTL change was related to CT change in the left precuneus extending to the posterior cingulate cortex (mean t161 = 3.22; P < .001; r = 0.246). At the individual participant level, leukocyte telomere shortening as well as lengthening were observed. Leukocyte telomere shortening was related to cortical thinning (t77 = 2.38; P = .01; r = 0.262), and leukocyte telomere lengthening was related to cortical thickening (t77 = 2.42; P = .009; r = 0.266). All analyses controlled for age, sex, and body mass index.

Conclusions and Relevance

The findings of this trial indicate an association between short-term change in LTL and concomitant change in plasticity of the left precuneus extending to the posterior cingulate cortex. This result contributes to the evidence that LTL changes more dynamically on the individual level than previously thought. Further studies are needed to determine potential long-term implications of such change in relation to cellular aging and the development of neurodegenerative disorders. No effect of contemplative mental training was noted in what may be, to date, the longest intervention with healthy adults.

Trial Registration

ClinicalTrials.gov identifier: NCT01833104.

10Kin1day: A Bottom-Up Neuroimaging Initiative

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.

Atypical functional connectome hierarchy in autism

One paradox of autism is the co-occurrence of deficits in sensory and higher-order socio-cognitive processing. Here, we examined whether these phenotypical patterns may relate to an overarching system-level imbalance-specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. Combining connectome gradient and stepwise connectivity analysis based on task-free functional magnetic resonance imaging (fMRI), we demonstrated atypical connectivity transitions between sensory and higher-order default mode regions in a large cohort of individuals with autism relative to typically-developing controls. Further analyses indicated that reduced differentiation related to perturbed stepwise connectivity from sensory towards transmodal areas, as well as atypical long-range rich-club connectivity. Supervised pattern learning revealed that hierarchical features predicted deficits in social cognition and low-level behavioral symptoms, but not communication-related symptoms. Our findings provide new evidence for imbalances in network hierarchy in autism, which offers a parsimonious reference frame to consolidate its diverse features.

Change in emotional self-concept following socio-cognitive training relates to structural plasticity of the prefrontal cortex

INTRODUCTION

Self-referential processing is a key component of the emotional self-concept. Previous studies have shown that emotional self-referential processing is related to structure and function of cortical midline areas such as medial prefrontal cortex (mPFC), and that it can be altered on a behavioral level by specific mental training practices. However, it remains unknown how behavioral training-related change in emotional self-concept content relates to structural plasticity.

METHODS

To address this issue, we examined the relationship between training-induced change in participant's emotional self-concept measured through emotional word use in the Twenty Statement Test and change in cortical thickness in the context of a large-scale longitudinal mental training study called the ReSource Project.

RESULTS

Based on prior behavioral findings showing increased emotional word use particularly after socio-cognitive training targeting perspective-taking capacities, this study extended these results by revealing that individual differences in the degree to which participants changed their emotional self-concept after training was positively related to cortical thickness change in right mPFC extending to dorsolateral PFC (dlPFC). Furthermore, increased self-related negative emotional word use after training was positively associated with cortical thickness change in left pars orbitalis and bilateral dlPFC.

CONCLUSIONS

Our findings reveal training-related structural brain change in regions known to be involved in self-referential processing and cognitive control, and could indicate a relationship between restructuring of the emotional self-concept content as well as reappraisal of negative aspects and cortical thickness change. As such, our findings can guide the development of psychological interventions targeted to alter specific facets of the self-concept.

Structural plasticity of the social brain: Differential change after socio-affective and cognitive mental training

Although neuroscientific research has revealed experience-dependent brain changes across the life span in sensory, motor, and cognitive domains, plasticity relating to social capacities remains largely unknown. To investigate whether the targeted mental training of different cognitive and social skills can induce specific changes in brain morphology, we collected longitudinal magnetic resonance imaging (MRI) data throughout a 9-month mental training intervention from a large sample of adults between 20 and 55 years of age. By means of various daily mental exercises and weekly instructed group sessions, training protocols specifically addressed three functional domains: (i) mindfulness-based attention and interoception, (ii) socio-affective skills (compassion, dealing with difficult emotions, and prosocial motivation), and (iii) socio-cognitive skills (cognitive perspective-taking on self and others and metacognition). MRI-based cortical thickness analyses, contrasting the different training modules against each other, indicated spatially diverging changes in cortical morphology. Training of present-moment focused attention mostly led to increases in cortical thickness in prefrontal regions, socio-affective training induced plasticity in frontoinsular regions, and socio-cognitive training included change in inferior frontal and lateral temporal cortices. Module-specific structural brain changes correlated with training-induced behavioral improvements in the same individuals in domain-specific measures of attention, compassion, and cognitive perspective-taking, respectively, and overlapped with task-relevant functional networks. Our longitudinal findings indicate structural plasticity in well-known socio-affective and socio-cognitive brain networks in healthy adults based on targeted short daily mental practices. These findings could promote the development of evidence-based mental training interventions in clinical, educational, and corporate settings aimed at cultivating social intelligence, prosocial motivation, and cooperation.

Neuroimaging-Based Phenotyping of the Autism Spectrum

Recent advances in neuroimaging have offered a rich array of structural and functional markers to probe the organization of regional and large-scale brain networks. The current chapter provides a brief introduction into these techniques and overviews their contribution to the understanding of autism spectrum disorder (ASD), a neurodevelopmental condition associated with atypical social cognition, language function, and repetitive behaviors/interests. While it is generally recognized that ASD relates to structural and functional network anomalies, the extent and overall pattern of reported findings have been rather heterogeneous. Indeed, while several attempts have been made to label the main neuroimaging phenotype of ASD (e.g., 'early brain overgrowth hypothesis', 'amygdala theory', 'disconnectivity hypothesis'), none of these frameworks has been without controversy. Methodological sources of inconsistent results may include differences in subject inclusion criteria, variability in image processing, and analysis methodology. However, inconsistencies may also relate to high heterogeneity across the autism spectrum itself. It, therefore, remains to be investigated whether a consistent imaging phenotype that adequately describes the entire autism spectrum can, in fact, be established. On the other hand, as previous findings clearly emphasize the value of neuroimaging in identifying atypical brain morphology, function, and connectivity, they ultimately support its high potential to identify biologically and clinically relevant endophenotypes.

Substrates of metacognition on perception and metacognition on higher-order cognition relate to different subsystems of the mentalizing network

Humans have the ability to reflect upon their perception, thoughts, and actions, known as metacognition (MC). The brain basis of MC is incompletely understood, and it is debated whether MC on different processes is subserved by common or divergent networks. We combined behavioral phenotyping with multi-modal neuroimaging to investigate whether structural substrates of individual differences in MC on higher-order cognition (MC-C) are dissociable from those underlying MC on perceptual accuracy (MC-P). Motivated by conceptual work suggesting a link between MC and cognitive perspective taking, we furthermore tested for overlaps between MC substrates and mentalizing networks. In a large sample of healthy adults, individual differences in MC-C and MC-P did not correlate. MRI-based cortical thickness mapping revealed a structural basis of this independence, by showing that individual differences in MC-P related to right prefrontal cortical thickness, while MC-C scores correlated with measures in lateral prefrontal, temporo-parietal, and posterior midline regions. Surface-based superficial white matter diffusivity analysis revealed substrates resembling those seen for cortical thickness, confirming the divergence of both MC faculties using an independent imaging marker. Despite their specificity, substrates of MC-C and MC-P fell clearly within networks known to participate in mentalizing, confirmed by task-based fMRI in the same subjects, previous meta-analytical findings, and ad-hoc Neurosynth-based meta-analyses. Our integrative multi-method approach indicates domain-specific substrates of MC; despite their divergence, these nevertheless likely rely on component processes mediated by circuits also involved in mentalizing. Hum Brain Mapp 37:3388-3399, 2016. © 2016 Wiley Periodicals, Inc.

Multicenter mapping of structural network alterations in autism

Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions primarily characterized by abnormalities in social cognition. Abundant previous functional MRI studies have shown atypical activity in networks encompassing medial prefrontal cortex (mPFC) and medial parietal regions corresponding to posterior cingulate cortex and precuneus (PCC/PCU). Conversely, studies assessing structural brain anomalies in ASD have been rather inconsistent. The current work evaluated whether structural changes in ASD can be reliability detected in a large multicenter dataset. Our comprehensive structural MRI framework encompassed cortical thickness mapping and structural covariance analysis based on three independent samples comprising individuals with ASD and controls (n = 220), selected from the Autism Brain Imaging Data Exchange open-access database. Surface-based analysis revealed increased cortical thickness in ASD relative to controls in mPFC and lateral prefrontal cortex. Clusters encompassing mPFC were embedded in altered inter-regional covariance networks, showing decreased covariance in ASD relative to controls primarily to PCC/PCU and inferior parietal regions. Cortical thickness increases and covariance reductions in ASD were consistent, yet of variable effect size, across the different sites evaluated and measurable both in children and adults. Our multisite study shows regional and network-level structural alterations in mPFC in ASD that, possibly, relate to atypical socio-cognitive functions in this condition.

Selective disruption of sociocognitive structural brain networks in autism and alexithymia

Autism spectrum conditions (ASC) are neurodevelopmental disorders characterized by abnormal social cognition. A core feature of ASC is disrupted Theory of Mind (ToM), our ability to take the mental perspective of others. ASC is also associated with alexithymia, a trait characterized by altered emotional interoception and empathy. Here, we applied structural MRI covariance analysis to assess whether ASC and alexithymia differentially affect structural brain networks associated with sociocognitive and socioaffective functions. Based on previous functional MRI findings, we expected disrupted ToM networks (centered on dorsomedial prefontal cortex [dmPFC], and temporo-parietal junction [TPJ]) in ASC, while alexithymia would affect networks centered on fronto-insular cortex (FI), regions associated with interoception of emotion and empathy. Relative to controls, ASC indeed showed reduced covariance in networks centered on dmPFC and TPJ, but not within FI networks. Irrespective of ASC, covariance was negatively modulated by alexithymia in networks extending from FI to posterior regions. Network findings were complemented by self-reports, indicating decreased perspective taking but normal empathic concern in ASC. Our results show divergent effects of ASC and alexithymia on inter-regional structural networks, suggesting that networks mediating socioaffective processes may be separable from networks mediating sociocognitive processing.