Dissociation of Reliability, Heritability, and Predictivity in Coarse- and Fine-Scale Functional Connectomes during Development.

The functional connectome supports information transmission through the brain at various spatial scales, from exchange between broad cortical regions to finer-scale, vertex-wise connections that underlie specific information processing mechanisms. In adults, while both the coarse- and fine-scale functional connectomes predict cognition, the fine scale can predict up to twice the variance as the coarse-scale functional connectome. Yet, past brain-wide association studies, particularly using large developmental samples, focus on the coarse connectome to understand the neural underpinnings of individual differences in cognition. Using a large cohort of children (age 9-10 years; n = 1,115 individuals; both sexes; 50% female, including 170 monozygotic and 219 dizygotic twin pairs and 337 unrelated individuals), we examine the reliability, heritability, and behavioral relevance of resting-state functional connectivity computed at different spatial scales. We use connectivity hyperalignment to improve access to reliable fine-scale (vertex-wise) connectivity information and compare the fine-scale connectome with the traditional parcel-wise (coarse scale) functional connectomes. Though individual differences in the fine-scale connectome are more reliable than those in the coarse-scale, they are less heritable. Further, the alignment and scale of connectomes influence their ability to predict behavior, whereby some cognitive traits are equally well predicted by both connectome scales, but other, less heritable cognitive traits are better predicted by the fine-scale connectome. Together, our findings suggest there are dissociable individual differences in information processing represented at different scales of the functional connectome which, in turn, have distinct implications for heritability and cognition.

Heritability of individualized cortical network topography.

Human cortex is patterned by a complex and interdigitated web of large-scale functional networks. Recent methodological breakthroughs reveal variation in the size, shape, and spatial topography of cortical networks across individuals. While spatial network organization emerges across development, is stable over time, and is predictive of behavior, it is not yet clear to what extent genetic factors underlie interindividual differences in network topography. Here, leveraging a nonlinear multidimensional estimation of heritability, we provide evidence that individual variability in the size and topographic organization of cortical networks are under genetic control. Using twin and family data from the Human Connectome Project (n = 1,023), we find increased variability and reduced heritability in the size of heteromodal association networks (h2 : M = 0.34, SD = 0.070), relative to unimodal sensory/motor cortex (h2 : M = 0.40, SD = 0.097). We then demonstrate that the spatial layout of cortical networks is influenced by genetics, using our multidimensional estimation of heritability (h2-multi; M = 0.14, SD = 0.015). However, topographic heritability did not differ between heteromodal and unimodal networks. Genetic factors had a regionally variable influence on brain organization, such that the heritability of network topography was greatest in prefrontal, precuneus, and posterior parietal cortex. Taken together, these data are consistent with relaxed genetic control of association cortices relative to primary sensory/motor regions and have implications for understanding population-level variability in brain functioning, guiding both individualized prediction and the interpretation of analyses that integrate genetics and neuroimaging.

Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder.

Major depressive disorder emerges from the complex interactions of biological systems that span genes and molecules through cells, networks, and behavior. Establishing how neurobiological processes coalesce to contribute to depression requires a multiscale approach, encompassing measures of brain structure and function as well as genetic and cell-specific transcriptional data. Here, we examine anatomical (cortical thickness) and functional (functional variability, global brain connectivity) correlates of depression and negative affect across three population-imaging datasets: UK Biobank, Brain Genomics Superstruct Project, and Enhancing NeuroImaging through Meta Analysis (ENIGMA; combined n ≥ 23,723). Integrative analyses incorporate measures of cortical gene expression, postmortem patient transcriptional data, depression genome-wide association study (GWAS), and single-cell gene transcription. Neuroimaging correlates of depression and negative affect were consistent across three independent datasets. Linking ex vivo gene down-regulation with in vivo neuroimaging, we find that transcriptional correlates of depression imaging phenotypes track gene down-regulation in postmortem cortical samples of patients with depression. Integrated analysis of single-cell and Allen Human Brain Atlas expression data reveal somatostatin interneurons and astrocytes to be consistent cell associates of depression, through both in vivo imaging and ex vivo cortical gene dysregulation. Providing converging evidence for these observations, GWAS-derived polygenic risk for depression was enriched for genes expressed in interneurons, but not glia. Underscoring the translational potential of multiscale approaches, the transcriptional correlates of depression-linked brain function and structure were enriched for disorder-relevant molecular pathways. These findings bridge levels to connect specific genes, cell classes, and biological pathways to in vivo imaging correlates of depression.

Proportional intracranial volume correction differentially biases behavioral predictions across neuroanatomical features, sexes, and development.

Individual differences in brain anatomy can be used to predict variations in cognitive ability. Most studies to date have focused on broad population-level trends, but the extent to which the observed predictive features are shared across sexes and age groups remains to be established. While it is standard practice to account for intracranial volume (ICV) using proportion correction in both regional and whole-brain morphometric analyses, in the context of brain-behavior predictions the possible differential impact of ICV correction on anatomical features and subgroups within the population has yet to be systematically investigated. In this work, we evaluate the effect of proportional ICV correction on sex-independent and sex-specific predictive models of individual cognitive abilities across multiple anatomical properties (surface area, gray matter volume, and cortical thickness) in healthy young adults (Human Connectome Project; n = 1013, 548 females) and typically developing children (Adolescent Brain Cognitive Development study; n = 1823, 979 females). We demonstrate that ICV correction generally reduces predictive accuracies derived from surface area and gray matter volume, while increasing predictive accuracies based on cortical thickness in both adults and children. Furthermore, the extent to which predictive models generalize across sexes and age groups depends on ICV correction: models based on surface area and gray matter volume are more generalizable without ICV correction, while models based on cortical thickness are more generalizable with ICV correction. Finally, the observed neuroanatomical features predictive of cognitive abilities are unique across age groups regardless of ICV correction, but whether they are shared or unique across sexes (within age groups) depends on ICV correction. These findings highlight the importance of considering individual differences in ICV, and show that proportional ICV correction does not remove the effects of cranial volume from anatomical measurements and can introduce ICV bias where previously there was none. ICV correction choices affect not just the strength of the relationships captured, but also the conclusions drawn regarding the neuroanatomical features that underlie those relationships.

Behavioral and Neural Signatures of Working Memory in Childhood.

Working memory function changes across development and varies across individuals. The patterns of behavior and brain function that track individual differences in working memory during human development, however, are not well understood. Here, we establish associations between working memory, other cognitive abilities, and functional MRI (fMRI) activation in data from over 11,500 9- to 10-year-old children (both sexes) enrolled in the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing longitudinal study in the United States. Behavioral analyses reveal robust relationships between working memory, short-term memory, language skills, and fluid intelligence. Analyses relating out-of-scanner working memory performance to memory-related fMRI activation in an emotional n-back task demonstrate that frontoparietal activity during a working memory challenge indexes working memory performance. This relationship is domain specific, such that fMRI activation related to emotion processing during the emotional n-back task, inhibitory control during a stop-signal task (SST), and reward processing during a monetary incentive delay (MID) task does not track memory abilities. Together, these results inform our understanding of individual differences in working memory in childhood and lay the groundwork for characterizing the ways in which they change across adolescence.SIGNIFICANCE STATEMENT Working memory is a foundational cognitive ability that changes over time and varies across individuals. Here, we analyze data from over 11,500 9- to 10-year-olds to establish relationships between working memory, other cognitive abilities, and frontoparietal brain activity during a working memory challenge, but not during other cognitive challenges. Our results lay the groundwork for assessing longitudinal changes in working memory and predicting later academic and other real-world outcomes.

Local and distributed cortical markers of effort expenditure during sustained goal pursuit.

The adaptive adjustment of behavior in pursuit of desired goals is critical for survival. To accomplish this complex feat, individuals must weigh the potential benefits of a given action against time, energy, and resource costs. Here, we examine brain responses associated with willingness to exert physical effort during the sustained pursuit of desired goals. Our analyses reveal a distributed pattern of brain activity in aspects of ventral medial prefrontal cortex that tracks with trial-level variability in effort expenditure. Indicating the brain represents echoes of effort at the point of feedback, whole-brain searchlights identified signals reflecting past effort expenditure in medial and lateral prefrontal cortices, encompassing broad swaths of frontoparietal and dorsal attention networks. These data have important implications for our understanding of how the brain's valuation mechanisms contend with the complexity of real-world dynamic environments with relevance for the study of behavior across health and disease.

Oxytocin under opioid antagonism leads to supralinear enhancement of social attention.

To provide new preclinical evidence toward improving the efficacy of oxytocin (OT) in treating social dysfunction, we tested the benefit of administering OT under simultaneously induced opioid antagonism during dyadic gaze interactions in monkeys. OT coadministered with a µ-opioid receptor antagonist, naloxone, invoked a supralinear enhancement of prolonged and selective social attention, producing a stronger effect than the summed effects of each administered separately. These effects were consistently observed when averaging over entire sessions, as well as specifically following events of particular social importance, including mutual eye contact and mutual reward receipt. Furthermore, attention to various facial regions was differentially modulated depending on social context. Using the Allen Institute's transcriptional atlas, we further established the colocalization of µ-opioid and κ-opioid receptor genes and OT genes at the OT-releasing sites in the human brain. These data across monkeys and humans support a regulatory relationship between the OT and opioid systems and suggest that administering OT under opioid antagonism may boost the therapeutic efficacy of OT for enhancing social cognition.

Individual differences in intrinsic brain connectivity predict decision strategy.

When humans are provided with ample time to make a decision, individual differences in strategy emerge. Using an adaptation of a well-studied decision making paradigm, motion direction discrimination, we probed the neural basis of individual differences in strategy. We tested whether strategies emerged from moment-to-moment reconfiguration of functional brain networks involved in decision making with task-evoked functional MRI (fMRI) and whether intrinsic properties of functional brain networks, measured at rest with functional connectivity MRI (fcMRI), were associated with strategy use. We found that human participants reliably selected one of two strategies across 2 days of task performance, either continuously accumulating evidence or waiting for task difficulty to decrease. Individual differences in decision strategy were predicted both by the degree of task-evoked activation of decision-related brain regions and by the strength of pretask correlated spontaneous brain activity. These results suggest that spontaneous brain activity constrains strategy selection on perceptual decisions.

Cortical gene expression architecture links healthy neurodevelopment to the imaging, transcriptomics and genetics of autism and schizophrenia.

Human brain organization involves the coordinated expression of thousands of genes. For example, the first principal component (C1) of cortical transcription identifies a hierarchy from sensorimotor to association regions. In this study, optimized processing of the Allen Human Brain Atlas revealed two new components of cortical gene expression architecture, C2 and C3, which are distinctively enriched for neuronal, metabolic and immune processes, specific cell types and cytoarchitectonics, and genetic variants associated with intelligence. Using additional datasets (PsychENCODE, Allen Cell Atlas and BrainSpan), we found that C1-C3 represent generalizable transcriptional programs that are coordinated within cells and differentially phased during fetal and postnatal development. Autism spectrum disorder and schizophrenia were specifically associated with C1/C2 and C3, respectively, across neuroimaging, differential expression and genome-wide association studies. Evidence converged especially in support of C3 as a normative transcriptional program for adolescent brain development, which can lead to atypical supragranular cortical connectivity in people at high genetic risk for schizophrenia.

The Cellular Underpinnings of the Human Cortical Connectome.

The functional properties of the human brain arise, in part, from the vast assortment of cell types that pattern the cortex. The cortical sheet can be broadly divided into distinct networks, which are further embedded into processing streams, or gradients, that extend from unimodal systems through higher-order association territories. Here, using transcriptional data from the Allen Human Brain Atlas, we demonstrate that imputed cell type distributions are spatially coupled to the functional organization of cortex, as estimated through fMRI. Cortical cellular profiles follow the macro-scale organization of the functional gradients as well as the associated large-scale networks. Distinct cellular fingerprints were evident across networks, and a classifier trained on post-mortem cell-type distributions was able to predict the functional network allegiance of cortical tissue samples. These data indicate that the in vivo organization of the cortical sheet is reflected in the spatial variability of its cellular composition.

Vaping disrupts ventilation-perfusion matching in asymptomatic users.

Inhalation of e-cigarette's aerosols (vaping) has the potential to disrupt pulmonary gas exchange, but the effects in asymptomatic users are unknown. We assessed ventilation-perfusion (V̇A/Q̇) mismatch in asymptomatic e-cigarette users, using magnetic resonance imaging (MRI). We hypothesized that vaping induces V̇A/Q̇ mismatch through alterations in both ventilation and perfusion distributions. Nine young, asymptomatic "Vapers" with >1-yr vaping history, and no history of cardiopulmonary disease, were imaged supine using proton MRI, to assess the right lung at baseline and immediately after vaping. Seven young "Controls" were imaged at baseline only. Relative dispersion (SD/means) was used to quantify the heterogeneity of the individual ventilation and perfusion distributions. V̇A/Q̇ mismatch was quantified using the second moments of the ventilation and perfusion versus V̇A/Q̇ ratio distributions, log scale, LogSDV̇, and LogSDQ̇, respectively, analogous to the multiple inert gas elimination technique. Spirometry was normal in both groups. Ventilation heterogeneity was similar between groups at baseline (Vapers, 0.43 ± 0.13; Controls, 0.51 ± 0.11; P = 0.13) but increased after vaping (to 0.57 ± 0.17; P = 0.03). Perfusion heterogeneity was greater (P = 0.04) in Vapers at baseline (0.53 ± 0.06) compared with Controls (0.44 ± 0.10) but decreased after vaping (to 0.42 ± 0.07; P = 0.005). Vapers had greater (P = 0.01) V̇A/Q̇ mismatch at baseline compared with Controls (LogSDQ̇ = 0.61 ± 0.12 vs. 0.43 ± 0.12), which was increased after vaping (LogSDQ̇ = 0.73 ± 0.16; P = 0.03). V̇A/Q̇ mismatch is greater in Vapers and worsens after vaping. This suggests subclinical alterations in lung function not detected by spirometry.NEW & NOTEWORTHY This research provides evidence of vaping-induced disruptions in ventilation-perfusion matching in young, healthy, asymptomatic adults with normal spirometry who habitually vape. The changes in ventilation and perfusion distributions, both at baseline and acutely after vaping, and the potential implications on hypoxic vasoconstriction are particularly relevant in understanding the pathogenesis of vaping-induced dysfunction. Our imaging-based approach provides evidence of potential subclinical alterations in lung function below thresholds of detection using spirometry.

Transcriptional and imaging-genetic association of cortical interneurons, brain function, and schizophrenia risk.

Inhibitory interneurons orchestrate information flow across the cortex and are implicated in psychiatric illness. Although interneuron classes have unique functional properties and spatial distributions, the influence of interneuron subtypes on brain function, cortical specialization, and illness risk remains elusive. Here, we demonstrate stereotyped negative correlation of somatostatin and parvalbumin transcripts within human and non-human primates. Cortical distributions of somatostatin and parvalbumin cell gene markers are strongly coupled to regional differences in functional MRI variability. In the general population (n = 9,713), parvalbumin-linked genes account for an enriched proportion of heritable variance in in-vivo functional MRI signal amplitude. Single-marker and polygenic cell deconvolution establish that this relationship is spatially dependent, following the topography of parvalbumin expression in post-mortem brain tissue. Finally, schizophrenia genetic risk is enriched among interneuron-linked genes and predicts cortical signal amplitude in parvalbumin-biased regions. These data indicate that the molecular-genetic basis of brain function is shaped by interneuron-related transcripts and may capture individual differences in schizophrenia risk.

Heavy upright exercise increases ventilation-perfusion mismatch in the basal lung: indirect evidence for interstitial pulmonary edema.

Ventilation-perfusion (V̇a/Q̇) mismatch during exercise may result from interstitial pulmonary edema if increased pulmonary vascular pressure causes fluid efflux into the interstitium. If present, the increased fluid may compress small airways or blood vessels, disrupting V̇a/Q̇ matching, but this is unproven. We hypothesized that V̇a/Q̇ mismatch would be greatest in basal lung following heavy upright exercise, consistent with hydrostatic forces favoring edema accumulation in the gravitationally dependent lung. We applied new tools to reanalyze previously published magnetic resonance imaging data to determine regional V̇a/Q̇ mismatch following 45 min of heavy upright exercise in six athletes (V̇o2max = 61 ± 7 mL·kg-1·min-1). In the supine posture, regional alveolar ventilation and local perfusion were quantified from specific ventilation imaging, proton density, and arterial spin labeling data in a single sagittal slice of the right lung before exercise (PRE), 15 min after exercise (POST), and in recovery 60 min after exercise (REC). Indices of V̇a/Q̇ mismatch [second moments (log scale) of ventilation (LogSDV) and perfusion (LogSDQ) vs. V̇a/Q̇ distributions] were calculated for apical, middle, and basal lung thirds, which represent gravitationally nondependent, middle, and dependent regions, respectively, during upright exercise. LogSDV increased after exercise only in the basal lung (PRE 0.46 ± 0.06, POST 0.57 ± 0.14, REC 0.55 ±0.14, P = 0.01). Similarly, LogSDQ increased only in the basal lung (PRE 0.40 ± 0.06, POST 0.51 ± 0.10, REC 0.44 ± 0.09, P = 0.04). Increased V̇a/Q̇ mismatch in the basal lung after exercise is potentially consistent with interstitial pulmonary edema accumulating in gravitationally dependent lung during exercise.NEW & NOTEWORTHY We reanalyzed previously published MRI data with new tools and found increased ventilation-perfusion mismatch only in the basal lung of athletes following 45 min of cycling exercise. This is consistent with the development of interstitial edema in the gravitationally dependent lung during heavy exercise.

Gene expression links functional networks across cortex and striatum.

The human brain is comprised of a complex web of functional networks that link anatomically distinct regions. However, the biological mechanisms supporting network organization remain elusive, particularly across cortical and subcortical territories with vastly divergent cellular and molecular properties. Here, using human and primate brain transcriptional atlases, we demonstrate that spatial patterns of gene expression show strong correspondence with limbic and somato/motor cortico-striatal functional networks. Network-associated expression is consistent across independent human datasets and evolutionarily conserved in non-human primates. Genes preferentially expressed within the limbic network (encompassing nucleus accumbens, orbital/ventromedial prefrontal cortex, and temporal pole) relate to risk for psychiatric illness, chloride channel complexes, and markers of somatostatin neurons. Somato/motor associated genes are enriched for oligodendrocytes and markers of parvalbumin neurons. These analyses indicate that parallel cortico-striatal processing channels possess dissociable genetic signatures that recapitulate distributed functional networks, and nominate molecular mechanisms supporting cortico-striatal circuitry in health and disease.

The human cortex possesses a reconfigurable dynamic network architecture that is disrupted in psychosis.

Higher-order cognition emerges through the flexible interactions of large-scale brain networks, an aspect of temporal coordination that may be impaired in psychosis. Here, we map the dynamic functional architecture of the cerebral cortex in healthy young adults, leveraging this atlas of transient network configurations (states), to identify state- and network-specific disruptions in patients with schizophrenia and psychotic bipolar disorder. We demonstrate that dynamic connectivity profiles are reliable within participants, and can act as a fingerprint, identifying specific individuals within a larger group. Patients with psychotic illness exhibit intermittent disruptions within cortical networks previously associated with the disease, and the individual connectivity profiles within specific brain states predict the presence of active psychotic symptoms. Taken together, these results provide evidence for a reconfigurable dynamic architecture in the general population and suggest that prior reports of network disruptions in psychosis may reflect symptom-relevant transient abnormalities, rather than a time-invariant global deficit.