Deciphering the functional specialization of whole-brain spatiomolecular gradients in the adult brain.

Cortical arealization arises during neurodevelopment from the confluence of molecular gradients representing patterned expression of morphogens and transcription factors. However, whether similar gradients are maintained in the adult brain remains unknown. Here, we uncover three axes of topographic variation in gene expression in the adult human brain that specifically capture previously identified rostral-caudal, dorsal-ventral, and medial-lateral axes of early developmental patterning. The interaction of these spatiomolecular gradients i) accurately reconstructs the position of brain tissue samples, ii) delineates known functional territories, and iii) can model the topographical variation of diverse cortical features. The spatiomolecular gradients are distinct from canonical cortical axes differentiating the primary sensory cortex from the association cortex, but radiate in parallel with the axes traversed by local field potentials along the cortex. We replicate all three molecular gradients in three independent human datasets as well as two nonhuman primate datasets and find that each gradient shows a distinct developmental trajectory across the lifespan. The gradients are composed of several well-known transcription factors (e.g., PAX6 and SIX3), and a small set of genes shared across gradients are strongly enriched for multiple diseases. Together, these results provide insight into the developmental sculpting of functionally distinct brain regions, governed by three robust transcriptomic axes embedded within brain parenchyma.

In vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth.

A balanced excitation-inhibition ratio (E/I ratio) is critical for healthy brain function. Normative development of cortex-wide E/I ratio remains unknown. Here, we noninvasively estimate a putative marker of whole-cortex E/I ratio by fitting a large-scale biophysically plausible circuit model to resting-state functional MRI (fMRI) data. We first confirm that our model generates realistic brain dynamics in the Human Connectome Project. Next, we show that the estimated E/I ratio marker is sensitive to the gamma-aminobutyric acid (GABA) agonist benzodiazepine alprazolam during fMRI. Alprazolam-induced E/I changes are spatially consistent with positron emission tomography measurement of benzodiazepine receptor density. We then investigate the relationship between the E/I ratio marker and neurodevelopment. We find that the E/I ratio marker declines heterogeneously across the cerebral cortex during youth, with the greatest reduction occurring in sensorimotor systems relative to association systems. Importantly, among children with the same chronological age, a lower E/I ratio marker (especially in the association cortex) is linked to better cognitive performance. This result is replicated across North American (8.2 to 23.0 y old) and Asian (7.2 to 7.9 y old) cohorts, suggesting that a more mature E/I ratio indexes improved cognition during normative development. Overall, our findings open the door to studying how disrupted E/I trajectories may lead to cognitive dysfunction in psychopathology that emerges during youth.

A practical evaluation of measures derived from compressed sensing diffusion spectrum imaging.

Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling of q-space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling of q-space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions. However prior studies have mainly evaluated CS-DSI in post-mortem or non-human data. At present, the capacity for CS-DSI to provide accurate and reliable measures of white matter anatomy and microstructure in the living human brain remains unclear. We evaluated the accuracy and inter-scan reliability of 6 different CS-DSI schemes that provided up to 80% reductions in scan time compared to a full DSI scheme. We capitalized on a dataset of 26 participants who were scanned over eight independent sessions using a full DSI scheme. From this full DSI scheme, we subsampled images to create a range of CS-DSI images. This allowed us to compare the accuracy and inter-scan reliability of derived measures of white matter structure (bundle segmentation, voxel-wise scalar maps) produced by the CS-DSI and the full DSI schemes. We found that CS-DSI estimates of both bundle segmentations and voxel-wise scalars were nearly as accurate and reliable as those generated by the full DSI scheme. Moreover, we found that the accuracy and reliability of CS-DSI was higher in white matter bundles that were more reliably segmented by the full DSI scheme. As a final step, we replicated the accuracy of CS-DSI in a prospectively acquired dataset (n = 20, scanned once). Together, these results illustrate the utility of CS-DSI for reliably delineating in vivo white matter architecture in a fraction of the scan time, underscoring its promise for both clinical and research applications.

QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data.

Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for noninvasively studying the organization of white matter in the human brain. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing on a diverse set of software suites to capitalize on their complementary strengths, QSIPrep facilitates the implementation of best practices for processing of diffusion images.

ModelArray: An R package for statistical analysis of fixel-wise data.

Diffusion MRI is the dominant non-invasive imaging method used to characterize white matter organization in health and disease. Increasingly, fiber-specific properties within a voxel are analyzed using fixels. While tools for conducting statistical analyses of fixel-wise data exist, currently available tools support only a limited number of statistical models. Here we introduce ModelArray, an R package for mass-univariate statistical analysis of fixel-wise data. At present, ModelArray supports linear models as well as generalized additive models (GAMs), which are particularly useful for studying nonlinear effects in lifespan data. In addition, ModelArray also aims for scalable analysis. With only several lines of code, even large fixel-wise datasets can be analyzed using a standard personal computer. Detailed memory profiling revealed that ModelArray required only limited memory even for large datasets. As an example, we applied ModelArray to fixel-wise data derived from diffusion images acquired as part of the Philadelphia Neurodevelopmental Cohort (n = 938). ModelArray revealed anticipated nonlinear developmental effects in white matter. Moving forward, ModelArray is supported by an open-source software development model that can incorporate additional statistical models and other imaging data types. Taken together, ModelArray provides a flexible and efficient platform for statistical analysis of fixel-wise data.

Retinal ganglion cell endowment is correlated with optic tract fiber cross section, not density.

There is substantial variation between healthy individuals in the number of retinal ganglion cells (RGC) in the eye, with commensurate variation in the number of axons in the optic tracts. Fixel-based analysis of diffusion MR produces estimates of fiber density (FD) and cross section (FC). Using these fixel measurements along with retinal imaging, we asked if individual differences in RGC tissue volume are correlated with individual differences in FD and FC measurements obtained from the optic tracts, and subsequent structures along the cortical visual pathway. We find that RGC endowment is correlated with optic tract FC, but not with FD. RGC volume had a decreasing relationship with measurements from subsequent regions of the visual system (LGN volume, optic radiation FC/FD, and V1 surface area). However, we also found that the variations in each visual area were correlated with the variations in its immediately adjacent visual structure. We only observed these serial correlations when FC is used as the measure of interest for the optic tract and radiations, but no significant relationship was found when FD represented these white matter structures. From these results, we conclude that the variations in RGC endowment, LGN volume, and V1 surface area are better predicted by the overall cross section of the optic tract and optic radiations as compared to the intra-axonal restricted signal component of these white matter pathways. Additionally, the presence of significant correlations between adjacent, but not distant, anatomical structures suggests that there are multiple, local sources of anatomical variation along the visual pathway.

Diminished reward responsiveness is associated with lower reward network GluCEST: an ultra-high field glutamate imaging study.

Low reward responsiveness (RR) is associated with poor psychological well-being, psychiatric disorder risk, and psychotropic treatment resistance. Functional MRI studies have reported decreased activity within the brain's reward network in individuals with RR deficits, however the neurochemistry underlying network hypofunction in those with low RR remains unclear. This study employed ultra-high field glutamate chemical exchange saturation transfer (GluCEST) imaging to investigate the hypothesis that glutamatergic deficits within the reward network contribute to low RR. GluCEST images were acquired at 7.0 T from 45 participants (ages 15-29, 30 females) including 15 healthy individuals, 11 with depression, and 19 with psychosis spectrum symptoms. The GluCEST contrast, a measure sensitive to local glutamate concentration, was quantified in a meta-analytically defined reward network comprised of cortical, subcortical, and brainstem regions. Associations between brain GluCEST contrast and Behavioral Activation System Scale RR scores were assessed using multiple linear regressions. Analyses revealed that reward network GluCEST contrast was positively and selectively associated with RR, but not other clinical features. Follow-up investigations identified that this association was driven by the subcortical reward network and network areas that encode the salience of valenced stimuli. We observed no association between RR and the GluCEST contrast within non-reward cortex. This study thus provides new evidence that reward network glutamate levels contribute to individual differences in RR. Decreased reward network excitatory neurotransmission or metabolism may be mechanisms driving reward network hypofunction and RR deficits. These findings provide a framework for understanding the efficacy of glutamate-modulating psychotropics such as ketamine for treating anhedonia.

Advances in microstructural diffusion neuroimaging for psychiatric disorders.

Understanding the neuropathological underpinnings of mental disorders such as schizophrenia, major depression, and bipolar disorder is an essential step towards the development of targeted treatments. Diffusion MRI studies utilizing the diffusion tensor imaging (DTI) model have been extremely successful to date in identifying microstructural brain abnormalities in individuals suffering from mental illness, especially in regions of white matter, although identified abnormalities have been biologically non-specific. Building on DTI's success, in recent years more advanced diffusion MRI methods have been developed and applied to the study of psychiatric populations, with the aim of offering increased sensitivity to subtle neurological abnormalities, as well as improved specificity to candidate pathologies such as demyelination and neuroinflammation. These advanced methods, however, usually come at the cost of prolonged imaging sequences or reduced signal to noise, and they are more difficult to evaluate compared with the more simplified approach taken by the now common DTI model. To date, a limited number of advanced diffusion MRI methods have been employed to study schizophrenia, major depression and bipolar disorder populations. In this review we survey these studies, compare findings across diverse methods, discuss the main benefits and limitations of the different methods, and assess the extent to which the application of more advanced diffusion imaging approaches has led to novel and transformative information with regards to our ability to better understand the etiology and pathology of mental disorders.

A comparison of three fiber tract delineation methods and their impact on white matter analysis.

Diffusion magnetic resonance imaging (dMRI) is an important method for studying white matter connectivity in the brain in vivo in both healthy and clinical populations. Improvements in dMRI tractography algorithms, which reconstruct macroscopic three-dimensional white matter fiber pathways, have allowed for methodological advances in the study of white matter; however, insufficient attention has been paid to comparing post-tractography methods that extract white matter fiber tracts of interest from whole-brain tractography. Here we conduct a comparison of three representative and conceptually distinct approaches to fiber tract delineation: 1) a manual multiple region of interest-based approach, 2) an atlas-based approach, and 3) a groupwise fiber clustering approach, by employing methods that exemplify these approaches to delineate the arcuate fasciculus, the middle longitudinal fasciculus, and the uncinate fasciculus in 10 healthy male subjects. We enable qualitative comparisons across methods, conduct quantitative evaluations of tract volume, tract length, mean fractional anisotropy, and true positive and true negative rates, and report measures of intra-method and inter-method agreement. We discuss methodological similarities and differences between the three approaches and the major advantages and drawbacks of each, and review research and clinical contexts for which each method may be most apposite. Emphasis is given to the means by which different white matter fiber tract delineation approaches may systematically produce variable results, despite utilizing the same input tractography and reliance on similar anatomical knowledge.

Complex Polypharmacy in Patients With Schizophrenia-Spectrum Disorders Before a Psychiatric Hospitalization: Prescribing Patterns and Associated Clinical Features.

BACKGROUND: Current evidence-based guidelines provide unclear support for many common polypharmacy practices in schizophrenia. Excessive or complex polypharmacy (≥4 psychotropics) has been studied in patients with bipolar disorder, but not in schizophrenia to date. METHODS: We conducted a digital medical record data extraction of 829 patients consecutively admitted to a psychiatric hospital and diagnosed as having schizophrenia-spectrum disorders. RESULTS: In those prescribed psychiatric medication preadmission, 28.1% (n = 169) met the criteria for complex polypharmacy. Complex polypharmacy patients were older, female, white, and disabled, and had more comorbidities compared with those without complex polypharmacy. In multivariable analysis, complex polypharmacy was specifically associated with being white and disabled, and having a comorbid anxiety disorder, tobacco use disorder, metabolic condition, and neurological condition compared with noncomplex polypharmacy patients. CONCLUSIONS: Although there is little evidence to support complex polypharmacy in schizophrenia, rates were relatively high in patients requiring hospitalization, especially when they are also diagnosed as having comorbid psychiatric and medical conditions. Future research is needed to study the risk-benefit profile for these patients, especially considering their higher medical burden and related health risks.

Comorbid Cannabis and Tobacco Use Disorders in Hospitalized Patients with Psychotic-Spectrum Disorders.

OBJECTIVE: Individuals with psychotic-spectrum disorders use tobacco and cannabis at higher rates than the general population and individuals with other psychiatric disorders, which may contribute to increased rates of medical problems and mortality. The present study examined whether individuals with psychosis and comorbid tobacco and/or cannabis use disorders exhibit differing clinical characteristics in terms of their sociodemographic, mental health, substance use, physical health, and medication use patterns. Elucidation of these profiles, and determining their relative severity, has important implications for treatment, including offering more targeted interventions based on type of comorbidity pattern. METHODS: We examined the electronic medical records of 829 patients with psychotic-spectrum disorders admitted to a psychiatric hospital and categorized them as having: (1) cannabis use disorder (CUD); (2) tobacco use disorder (TUD); (3) comorbid cannabis and tobacco use disorders (CUD + TUD); or (4) neither disorder (no CUD/TUD). Multinomial logistic regression was used to compare the aforementioned groups on multiple variables controlling for age and sex. RESULTS: Alcohol and stimulant use disorder diagnoses were each related to higher odds of having a CUD and CUD + TUD, relative to no CUD/TUD. Stimulant and polysubstance use disorder diagnoses were each related to higher odds of having a TUD compared to no CUD/TUD. Greater number of prescribed psychotropic medications was related to higher odds of a TUD compared to no CUD/TUD. CONCLUSIONS: Although several differences between groups were accounted for by age of cannabis versus tobacco users, findings point to the importance of considering comorbid alcohol and substance use disorders among those with psychosis and CUD/TUD, as these comorbidities have important implications for screening and treatment selection during and following acute hospitalization.

Adolescent-to-adult gains in cognitive flexibility are adaptively supported by reward sensitivity, exploration, and neural variability.

Cognitive flexibility exhibits dynamic changes throughout development, with different forms of flexibility showing dissociable developmental trajectories. In this review, we propose that an adolescent-specific mode of flexibility in the face of changing environmental contingencies supports the emergence of adolescent-to-adult gains in cognitive shifting efficiency. We first describe how cognitive shifting abilities monotonically improve from childhood to adulthood, accompanied by increases in brain state flexibility, neural variability, and excitatory/inhibitory balance. We next summarize evidence supporting the existence of a dopamine-driven, adolescent peak in flexible behavior that results in reward seeking, undirected exploration, and environmental sampling. We propose a neurodevelopmental framework that relates these adolescent behaviors to the refinement of neural phenotypes relevant to mature cognitive flexibility, and thus highlight the importance of the adolescent period in fostering healthy neurocognitive trajectories.

Intimate partner violence perpetration among veterans: associations with neuropsychiatric symptoms and limbic microstructure.

Background: Intimate partner violence (IPV) perpetration is highly prevalent among veterans. Suggested risk factors of IPV perpetration include combat exposure, post-traumatic stress disorder (PTSD), depression, alcohol use, and mild traumatic brain injury (mTBI). While the underlying brain pathophysiological characteristics associated with IPV perpetration remain largely unknown, previous studies have linked aggression and violence to alterations of the limbic system. Here, we investigate whether IPV perpetration is associated with limbic microstructural abnormalities in military veterans. Further, we test the effect of potential risk factors (i.e., PTSD, depression, substance use disorder, mTBI, and war zone-related stress) on the prevalence of IPV perpetration. Methods: Structural and diffusion-weighted magnetic resonance imaging (dMRI) data were acquired from 49 male veterans of the Iraq and Afghanistan wars (Operation Enduring Freedom/Operation Iraqi Freedom; OEF/OIF) of the Translational Research Center for TBI and Stress Disorders (TRACTS) study. IPV perpetration was assessed using the psychological aggression and physical assault sub-scales of the Revised Conflict Tactics Scales (CTS2). Odds ratios were calculated to assess the likelihood of IPV perpetration in veterans with either of the following diagnoses: PTSD, depression, substance use disorder, or mTBI. Fractional anisotropy tissue (FA) measures were calculated for limbic gray matter structures (amygdala-hippocampus complex, cingulate, parahippocampal gyrus, entorhinal cortex). Partial correlations were calculated between IPV perpetration, neuropsychiatric symptoms, and FA. Results: Veterans with a diagnosis of PTSD, depression, substance use disorder, or mTBI had higher odds of perpetrating IPV. Greater war zone-related stress, and symptom severity of PTSD, depression, and mTBI were significantly associated with IPV perpetration. CTS2 (psychological aggression), a measure of IPV perpetration, was associated with higher FA in the right amygdala-hippocampus complex (r = 0.400, p = 0.005). Conclusion: Veterans with psychiatric disorders and/or mTBI exhibit higher odds of engaging in IPV perpetration. Further, the more severe the symptoms of PTSD, depression, or TBI, and the greater the war zone-related stress, the greater the frequency of IPV perpetration. Moreover, we report a significant association between psychological aggression against an intimate partner and microstructural alterations in the right amygdala-hippocampus complex. These findings suggest the possibility of a structural brain correlate underlying IPV perpetration that requires further research.

In-vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth.

A balanced excitation-inhibition ratio (E/I ratio) is critical for healthy brain function. Normative development of cortex-wide E/I ratio remains unknown. Here we non-invasively estimate a putative marker of whole-cortex E/I ratio by fitting a large-scale biophysically-plausible circuit model to resting-state functional MRI (fMRI) data. We first confirm that our model generates realistic brain dynamics in the Human Connectome Project. Next, we show that the estimated E/I ratio marker is sensitive to the GABA-agonist benzodiazepine alprazolam during fMRI. Alprazolam-induced E/I changes are spatially consistent with positron emission tomography measurement of benzodiazepine receptor density. We then investigate the relationship between the E/I ratio marker and neurodevelopment. We find that the E/I ratio marker declines heterogeneously across the cerebral cortex during youth, with the greatest reduction occurring in sensorimotor systems relative to association systems. Importantly, among children with the same chronological age, a lower E/I ratio marker (especially in association cortex) is linked to better cognitive performance. This result is replicated across North American (8.2 to 23.0 years old) and Asian (7.2 to 7.9 years old) cohorts, suggesting that a more mature E/I ratio indexes improved cognition during normative development. Overall, our findings open the door to studying how disrupted E/I trajectories may lead to cognitive dysfunction in psychopathology that emerges during youth.

Posttraumatic survivor guilt is associated with white matter microstructure alterations.

BACKGROUND: Military veterans with posttraumatic stress disorder (PTSD) commonly experience posttraumatic guilt. Guilt over commission or omission evolves when responsibility is assumed for an unfortunate outcome (e.g., the death of a fellow combatant). Survivor guilt is a state of intense emotional distress experienced by the weight of knowing that one survived while others did not. METHODS: This study of the Translational Research Center for TBI and Stress Disorders (TRACTS) analyzed structural and diffusion-weighted magnetic resonance imaging data from 132 male Iraq/Afghanistan veterans with PTSD. The Clinician-Administered PTSD Scale for DSM-IV (CAPS-IV) was employed to classify guilt. Thirty (22.7 %) veterans experienced guilt over acts of commission or omission, 34 (25.8 %) experienced survivor guilt, and 68 (51.5 %) had no posttraumatic guilt. White matter microstructure (fractional anisotropy, FA), cortical thickness, and cortical volume were compared between veterans with guilt over acts of commission or omission, veterans with survivor guilt, and veterans without guilt. RESULTS: Veterans with survivor guilt had significantly lower white matter FA compared to veterans who did not experience guilt (p < .001), affecting several regions of major white matter fiber bundles. There were no significant differences in white matter FA, cortical thickness, or volumes between veterans with guilt over acts of commission or omission and veterans without guilt (p > .050). LIMITATIONS: This cross-sectional study with exclusively male veterans precludes inferences of causality between the studied variables and generalizability to the larger veteran population that includes women. CONCLUSION: Survivor guilt may be a particularly impactful form of posttraumatic guilt that requires specific treatment efforts targeting brain health.

Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy.

Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3355; ages 5-23 years): the Philadelphia Neurodevelopmental Cohort (n = 1207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.

A sensorimotor-association axis of thalamocortical connection development.

Human cortical development follows a sensorimotor-to-association sequence during childhood and adolescence1-6. The brain's capacity to enact this sequence over decades indicates that it relies on intrinsic mechanisms to regulate inter-regional differences in the timing of cortical maturation, yet regulators of human developmental chronology are not well understood. Given evidence from animal models that thalamic axons modulate windows of cortical plasticity7-12, here we evaluate the overarching hypothesis that structural connections between the thalamus and cortex help to coordinate cortical maturational heterochronicity during youth. We first introduce, cortically annotate, and anatomically validate a new atlas of human thalamocortical connections using diffusion tractography. By applying this atlas to three independent youth datasets (ages 8-23 years; total N = 2,676), we reproducibly demonstrate that thalamocortical connections develop along a maturational gradient that aligns with the cortex's sensorimotor-association axis. Associative cortical regions with thalamic connections that take longest to mature exhibit protracted expression of neurochemical, structural, and functional markers indicative of higher circuit plasticity as well as heightened environmental sensitivity. This work highlights a central role for the thalamus in the orchestration of hierarchically organized and environmentally sensitive windows of cortical developmental malleability.

A critical period plasticity framework for the sensorimotor-association axis of cortical neurodevelopment.

To understand human brain development it is necessary to describe not only the spatiotemporal patterns of neurodevelopment but also the neurobiological mechanisms that underlie them. Human neuroimaging studies have provided evidence for a hierarchical sensorimotor-to-association (S-A) axis of cortical neurodevelopment. Understanding the biological mechanisms that underlie this program of development using traditional neuroimaging approaches has been challenging. Animal models have been used to identify periods of enhanced experience-dependent plasticity - 'critical periods' - that progress along cortical hierarchies and are governed by a conserved set of neurobiological mechanisms that promote and then restrict plasticity. In this review we hypothesize that the S-A axis of cortical development in humans is partly driven by the cascading maturation of critical period plasticity mechanisms. We then describe how recent advances in in vivo neuroimaging approaches provide a promising path toward testing this hypothesis by linking signals derived from non-invasive imaging to critical period mechanisms.

Hierarchical functional system development supports executive function.

In this perspective, we describe how developmental improvements in youth executive function (EF) are supported by hierarchically organized maturational changes in functional brain systems. We first highlight evidence that functional brain systems are embedded within a hierarchical sensorimotor-association axis of cortical organization. We then review data showing that functional system developmental profiles vary along this axis: systems near the associative end become more functionally segregated, while those in the middle become more integrative. Developmental changes that strengthen the hierarchical organization of the cortex may support EF by facilitating top-down information flow and balancing within- and between-system communication. We propose a central role for attention and frontoparietal control systems in the maturation of healthy EF and suggest that reduced functional system differentiation across the sensorimotor-association axis contributes to transdiagnostic EF deficits.

Connectional Hierarchy in Human Brain Revealed by Individual Variability of Functional Network Edges.

The human cerebral cortex is connected by intricate inter-areal wiring at the macroscale. The cortical hierarchy from primary sensorimotor to higher-order association areas is a unifying organizational principle across various neurobiological properties; however, previous studies have not clarified whether the connections between cortical regions exhibit a similar hierarchical pattern. Here, we identify a connectional hierarchy indexed by inter-individual variability of functional connectivity edges, which continuously progresses along a hierarchical gradient from within-network connections to between-network edges connecting sensorimotor and association networks. We found that this connectional hierarchy of variability aligns with both hemodynamic and electromagnetic connectivity strength and is constrained by structural connectivity strength. Moreover, the patterning of connectional hierarchy is related to inter-regional similarity in transcriptional and neurotransmitter receptor profiles. Using the Neurosynth cognitive atlas and cortical vulnerability maps in 13 brain disorders, we found that the connectional hierarchy of variability is associated with similarity networks of cognitive relevance and that of disorder vulnerability. Finally, we found that the prominence of this hierarchical gradient of connectivity variability declines during youth. Together, our results reveal a novel hierarchal organizational principle at the connectional level that links multimodal and multiscale human connectomes to individual variability in functional connectivity.