Biology subjects

van den Heuvel, M. P.

Publications and source records attributed to van den Heuvel, M. P..

At least 19 recordsLinked to original sources

bioRxiv2026

Regional specificity of neuronal cell types, functional connectivity, and cell type-specific correlation to brain disorders in the human ventral tegmental area

The ventral tegmental area (VTA) in the midbrain is a key reward system hub associated with multiple brain disorders. While rodent studies reveal a diverse neuronal population and distinct connectivity patterns, the architecture of the human VTA remains poorly understood. Here, we generated a transcriptomic reference atlas of the adult human VTA with subregional resolution. We identify multiple neuronal cell types defined by differential transcription factor expression, as well as regionally enriched GABAergic cell types. Functional connectivity analysis with fMRI suggests that this spatial organization corresponds to distinct connectivity profiles. Integration with other human midbrain single-nucleus RNA-seq datasets reveals a VTA-specific combinatorial GABA-dopaminergic cell type and regional differences among dopaminergic neurons. Finally, we find multiple associations between neuronal cell types and genetic risk for psychiatric disorders and body mass index. Altogether, this study provides a foundation for mechanistic and therapeutic studies into VTA-related diseases.

neuroscience↗

bioRxiv2024

Multimodal brain imaging of insomnia, depression and anxiety symptoms: transdiagnostic commonalities and differences

Insomnia disorder, major depressive disorder and anxiety disorders are the most common mental health conditions, with high comorbidity and genetic overlap suggesting shared brain mechanisms. Studies on brain correlates of these disorders have not fully addressed this overlap. Aiming to distinguish shared from specific brain structural and functional properties associated with symptoms of these disorders, this study analyzed multimodal brain imaging data from over 40,000 UK Biobank participants. Functional enrichment analyses were conducted to understand the cognitive-emotional and neurotransmission implications of the identified brain regions and connections. Results showed that smaller cortical surfaces, smaller thalamic volumes, and weaker functional connectivity were linked to more severe symptoms across all symptom types. Several symptom-specific associations were revealed, most commonly in different parts of the amygdala-hippocampal-medial prefrontal circuit. These findings revealed both transdiagnostically shared and unique brain properties that could lead to more directed treatment targets for insomnia, depression, and anxiety.

neuroscience↗

bioRxiv2023

Insomnia subtypes have differentiating deviations in brain structural connectivity

ObjectiveInsomnia disorder is the most common sleep disorder. A better understanding of insomnia-related deviations in the brain could inspire better treatment. Insufficiently recognized heterogeneity within the insomnia population could obscure involved brain circuits. The present study investigated whether structural brain connectivity deviations differ between recently discovered and validated insomnia subtypes. MethodsStructural and diffusion weighted 3-Tesla MRI data of four independent studies were harmonized. The sample consisted of 73 controls without sleep complaints and 204 participants with insomnia grouped into five subtypes based on their fingerprint of personality and mood traits assessed with the Insomnia Type Questionnaire. Linear regression correcting for age, sex, and brain volume evaluated group differences in structural connectivity strength, indicated by fractional anisotropy and mean diffusivity, and evaluated within two different atlases. ResultsInsomnia subtypes showed differentiating profiles of deviating structural connectivity which moreover concentrated in different functional networks. Permutation testing against randomly drawn heterogeneous subsamples indicated significant specificity of deviation profiles in four of the five subtypes: highly distressed (p=0.019), moderately distressed reward insensitive (p=0.014), slightly distressed low reactive (p=0.006) and slightly distressed high reactive (p=0.006). ConclusionsOur results provide a first indication that different insomnia subtypes exhibit distinct profiles of deviations in structural brain connectivity. Subtyping of insomnia could be essential for a better understanding of brain mechanisms that contribute to insomnia vulnerability.

neuroscience↗

bioRxiv2023

AutoMacq: an automatic pipeline to analyse macaque structural MRI data

MRI scanning of rhesus macaques is a growing field due to their evolutionary proximity and similar neuroanatomy to humans. As such, there is a need for automatic macaque MRI processing pipelines. AutoMacq is a pipeline capable of processing rhesus macaque MRI data to produce both voxel-based and surface-based metrics. It involves minimal manual intervention and can be carried out without expert knowledge of macaque neuroanatomy. To test the quality of the pipeline, scans from 74 subjects across 8 different sites were processed. Results indicate that over 87% of tissue segmentations and surfaces were of satisfactory quality to not require additional manual correction. Hemispheric comparisons and analyses of scan-rescan data showed strong reliability of the volumetric and surface-based outputs. Finally, to illustrate potential applications of AutoMacq, the change in grey matter volume with ageing was investigated cross-sectionally using subjects aged 3-15 years (corresponding to adolescence until mid-adulthood). The analysis revealed a linear decrease in grey matter volume with age similar to what has been found in humans, reinforcing the value of rhesus macaques as a model of healthy human ageing.

neuroscience↗

bioRxiv2022

Evolutionary shaping of human brain dynamics

The human brain is distinct from those of other species in terms of size, organization, and connectivity. How do these structural evolutionary differences drive patterns of neural activity enabling brain function? Here, we combine brain imaging and biophysical modeling to show that the anatomical wiring of the human brain distinctly shapes neural dynamics. This shaping is characterized by a narrower distribution of dynamic ranges across brain regions compared with that of chimpanzees, our closest living primate relatives. We find that such a sharp dynamic range distribution supports faster integration between regions, particularly in transmodal systems. Conversely, a broad dynamic range distribution as seen in chimpanzees facilitates brain processes relying more on neural interactions within specialized local brain systems. These findings suggest that human brain dynamics have evolved to foster rapid associative processes in service of complex cognitive functions and behavior.

neuroscience↗

bioRxiv2022

Assortative mixing in micro-architecturally annotated brain connectomes

The wiring of the brain connects micro-architecturally diverse neuronal populations. The conventional graph model encodes macroscale brain connectivity as a network of nodes and edges, but abstracts away the rich biological detail of each regional node. Regions are different in terms of their microscale attributes, many of which are readily available through modern technological advances and data-sharing initiatives. How is macroscale connectivity related to nodal attributes? Here we investigate the systematic arrangement of white-matter connectivity with respect to multiple biological annotations. Namely, we formally study assortative mixing in annotated connectomes by quantifying the tendency for regions to be connected with each other based on the similarity of their micro-architectural attributes. We perform all experiments using four cortico-cortical connectome datasets from three different species (human, macaque and mouse), and consider a range of molecular, cellular and laminar annotations, including gene expression, neurotransmitter receptors, neuron density, laminar thickness and intracortical myelin. Importantly, we disentangle the relationship between neural wiring, regional heterogeneity and spatial embedding using spatial autocorrelation-preserving null models. We show that mixing between micro-architecturally diverse neuronal populations is supported by long-distance connections. Using meta-analytic decoding, we find that the arrangement of connectivity patterns with respect to biological annotations shape patterns of regional functional specialization. Specifically, regions that connect to biologically similar regions are associated with executive function; conversely, regions that connect with biologically dissimilar regions are associated with memory function. By bridging scales of cortical organization, from microscale attributes to macroscale connectivity, this work lays the foundation for next-generation annotated connectomics.

neuroscience↗

bioRxiv2022

Specificity and overlap in the genetic architectures of functional and structural connectivity within cerebral resting-state networks

The functional connectivity and dynamics of resting-state networks (RSN-FC) are vital for cognitive functioning. RSN-FC is heritable and partially translates to the anatomical architecture of white matter, but the genetic component of structural connections of RSNs (RSN-SC) and their potential genetic overlap with RSN-FC remains unknown. Here we perform genome-wide association studies (Ndiscovery=24,336; Nreplication=3,412) and in silico annotation on RSN-SC and RSN-FC. We identify the first genes for visual network-SC, that are involved in axon guidance and synaptic functioning and show that genetic variation in RSN-FC impacts biological processes related to brain disorders that have previously been associated with FC alterations in those same RSNs. Correlations of the genetic components of RSNs are mostly observed within the functional domain, whereas less overlap is observed within the structural domain and between the functional and structural domains. This study advances the understanding of the complex functional organization of the brain and its structural underpinnings from a genetics viewpoint.

genetics↗

bioRxiv2022

The role of preterm birth and postnatal stress in neonatal structural brain development

Preterm birth disrupts the emerging foundations of the brains architecture, and the continuum of early-life stress-provoked alterations reaches from a healthy adaptation with resilience to severe vulnerability and maladjustment with psychopathology. The current study examined how structural brain development is affected by a stressful extra-uterine environment and whether changes in topological architecture at term-equivalent age could explain the increased vulnerability for behavioral symptoms during early childhood. Longitudinal changes in structural brain connectivity were quantified using diffusion-weighted imaging (DWI) and tractography in preterm born infants (gestational age <28 weeks), imaged at 30 and/or 40 weeks of gestation (N=145, 43.5% female). A global index of postnatal stress was based on invasive procedures during hospitalization (e.g., heel lance). Infants were classified as vulnerable and resilient based on having more or less internalizing symptoms at 2-5 years of age (n=71). Findings were replicated in an independent validation sample (N=123, 39.8% female, n=91 with follow-up). Higher stress levels impaired structural connectivity growth in the amygdala, insula, hippocampus, and posterior cingulate cortex. The hippocampus, amygdala, and subthalamic nucleus showed lower global connectivity in vulnerable relative to resilient individuals. The distinct characteristics of the resilient brain allowed for a good predictive accuracy of group membership using local network measures (80%, p<10-5, {kappa}=0.61). These findings emphasize the detrimental impact of postnatal stress and, more importantly, the relative plasticity of the preterm brain. Resilience following postnatal stress appertains to a potential compensatory or innate ability to propagate global information flow. Significance StatementThe underdeveloped preterm brain is exposed to various external stimuli following birth. Although the importance of early adversity has been widely recognized, the essential understanding of the effects of early chronic stress on neonatal brain networks as well as the remarkable degree of resilience is not well understood. We aim to provide an increased understanding of the impact of postnatal stress on brain development between 30 and 40 weeks of gestation and describe the topological architecture of a resilient brain. We observed global alteration in neonatal brain networks following postnatal stress and identified key contributive regions conferring resilience to the development of future internalizing symptoms.

neuroscience↗

bioRxiv2021

Trajectory of rich club properties in structural brain networks

Many organizational principles of structural brain networks are established before birth and undergo considerable developmental changes afterwards. These include the topologically central hub regions and a densely connected rich club. While several studies have mapped developmental trajectories of brain connectivity and brain network organization across childhood and adolescence, comparatively little is known about subsequent development over the course of the lifespan. Here, we present a cross-sectional analysis of structural brain network development in N = 8,066 participants aged 5 to 80 years. Across all brain regions, structural connectivity strength followed an inverted-U-shaped trajectory with vertex in the early 30s. Connectivity strength of hub regions showed a similar trajectory and the identity of hub regions remained stable across all age groups. While connectivity strength declined with advancing age, the organization of hub regions into a rich club did not only remain intact but became more pronounced, presumingly through a selected sparing of relevant connections from age-related connectivity loss. The stability of rich club organization in the face of overall age-related decline is consistent with a "first come, last served" model of neurodevelopment, where the first principles to develop are the last to decline with age. Rich club organization has been shown to be highly beneficial for communicability and higher cognition. A resilient rich club might thus be protective of a functional loss in late adulthood and represent a neural reserve to sustain cognitive functioning in the aging brain.

neuroscience↗

bioRxiv2021

Genome-wide association study of cerebellar volume

Cerebellar volume is highly heritable and associated with neurodevelopmental and neurodegenerative disorders. Understanding the genetic architecture of cerebellar volume may improve our insight into these disorders. This study aims to investigate the convergence of cerebellar volume genetic associations in close detail. A genome-wide associations study for cerebellar volume was performed in a sample of 27,486 individuals from UK Biobank, resulting in 29 genome-wide significant loci and a SNP heritability of 39.82%. We pinpoint variants that have effects on amino acid sequence or cerebellar gene-expression. Additionally, 85 genome-wide significant genes were detected and tested for convergence onto biological pathways, cerebellar cell types or developmental stages. Local genetic correlations between cerebellar volume and neurodevelopmental and neurodegenerative disorders reveal shared loci with Parkinsons disease, Alzheimers disease and schizophrenia. These results provide insights into the heritable mechanisms that contribute to developing a brain structure important for cognitive functioning and mental health.

genetics↗

bioRxiv2021

Common micro- and macroscale principles of connectivity in the human brain

The brain requires efficient information transfer between neurons and between large-scale brain regions. Brain connectivity follows predictable organizational principles: at the cellular level, larger supragranular pyramidal neurons have larger dendritic trees, more synapses, more complex branching and perform more complex neuronal computations; at the macro-scale, region-to-region connections are suggested to display a diverse architecture with highly connected hub-areas facilitating complex information integration and computation. Here, we explore the hypothesis that the branching structure of large-scale region-to-region connectivity follows similar organizational principles as known for the neuronal scale. We examine microscale connectivity of basal dendritic trees of supragranular pyramidal neurons (300+) across ten cortical areas in five human donor brains (1M/4F). Dendritic complexity was quantified as the number of branch points, tree length, spine count, spine density and overall branching complexity. High-resolution diffusion-weighted MRI was used to construct white matter trees of cortico-cortical wiring. Examining the complexity of the resulting white matter trees using the same measures as for dendritic trees shows multimodal association areas to have larger, more complexly branched white matter trees than primary areas (all p<0.0001) and regional macroscale complexity to run in parallel with microscale measures, in terms of number of inputs (r=0.677, p=0.032), branch points (r=0.790, p=0.006), total tree length (r=0.664, p=0.036) and branching complexity (r=0.724, p=0.018). Our findings support the integrative theory that brain connectivity is structured following similar principles of connectivity at the neuronal and macroscale level, and provide a framework to study connectivity changes in brain conditions at multiple levels of brain organization.

neuroscience↗

bioRxiv2021

Scaling principles of white matter brain connectivity

Brains come in many shapes and sizes. Nature has endowed big-brained primate species like humans with a proportionally large cerebral cortex. White matter connectivity - the brains infrastructure for long-range communication - might not always scale at the same pace as the cortex. We investigated the consequences of this allometric scaling for white matter brain network connectivity. Structural T1 and diffusion MRI data were collated across fourteen primate species, describing a comprehensive 350-fold range in brain volume. We report volumetric scaling relationships that point towards a restriction in macroscale connectivity in larger brains. Building on previous findings, we show cortical surface to outpace white matter volume and the corpus callosum, suggesting the emergence of a white matter bottleneck of lower levels of connectedness through the corpus callosum in larger brains. At the network level, we find a potential consequence of this bottleneck in shaping connectivity patterns, with homologous regions in the left and right hemisphere showing more divergent connectivity in larger brains. Our findings show conserved scaling relationships of major brain components and their consequence for macroscale brain circuitry, providing a comparative framework for expected connectivity architecture in larger brains such as the human brain.

neuroscience↗

bioRxiv2021

Structural and functional connectivity reconstruction with CATO - A Connectivity Analysis TOolbox

We describe a Connectivity Analysis TOolbox (CATO) for the reconstruction of structural and functional brain connectivity based on diffusion weighted imaging and resting-state functional MRI data. CATO is a multimodal software package that enables researchers to run end-to-end reconstructions from MRI data to structural and functional connectome maps, customize their analyses and utilize various software packages to preprocess data. Structural and functional connectome maps can be reconstructed with respect to user-defined (sub)cortical atlases providing aligned connectivity matrices for integrative multimodal analyses. We outline the implementation and usage of the structural and functional processing pipelines in CATO. Performance was calibrated with respect to simulated diffusion weighted imaging from the ITC2015 challenge, test-retest diffusion weighted imaging data and resting-state functional MRI data from the Human Connectome Project. CATO is open-source software distributed under the MIT License and available as a MATLAB toolbox and as a stand-alone application at www.dutchconnectomelab.nl/CATO.

neuroscience↗

bioRxiv2021

Pipeline for 4D whole-brain microscopy preprocessing and analysis.

Acute stress leads to sequential activation of functional brain networks. The challenge is to get insight in whole brain activity at multiple scales, beyond the level of (networks of) nuclei. We developed a novel pre-processing and analytical pipeline to chart whole-brain immediate early genes expression - as proxy for cellular activity - after a single stressful foot-shock in 4 dimensions; that is, from functional networks up to 3D single-cell resolution, and over time. The pipeline is available as R-package. Most brain areas (96%) showed increased numbers of c-fos+ cells after foot-shock, yet hypothalamic areas stood out as being most active and prompt in their activation, followed by amygdalar, prefrontal, hippocampal and finally thalamic areas. At the cellular level, c-fos+ density clearly shifted over time across subareas, as illustrated for the basolateral amygdala. Moreover, some brain areas showed increased numbers of c-fos+ cells, while others dramatically increased c-fos intensity in just a subset of cells; this strategy changed after foot-shock in half of the brain areas. All single-cell data can be visualized for each of the 90 brain areas examined through our interactive web-portal.

neuroscience↗

bioRxiv2021

Statistical testing and annotation of gene transcriptomic-neuroimaging associations

Multiscale integration of gene transcriptomic and neuroimaging data is becoming a widely used approach for exploring the molecular underpinnings of large-scale brain structure and function. Proper statistical evaluation of computed associations between imaging-based phenotypic and transcriptomic data is key in these explorations, in particular to establish whether observed associations exceed chance level of random, non-specific effects. Recent approaches have shown the importance of spatial null models to test for spatial specificity of effects to avoid serious inflation of reported statistics. Here, we discuss the need for examination of the second category of specificity in transcriptomic-neuroimaging analyses, namely that of gene specificity, examined using null models built upon effects that occur from sets of random genes. Through simple examples of commonly performed transcriptomic-neuroimaging analyses, we show that providing additional gene specificity on observed transcriptomic-neuroimaging effects is of high importance to avoid non-specific (potentially false-positive) effects. Through simulations we further show that the rate of reported non-specific effects (i.e., effects that are generally observed and cannot be specifically linked to a gene-set of interest) can run as high as 60%, with only less than 5% of transcriptomic-neuroimaging associations observed through ordinary linear regression analyses showing spatial and gene specificity. We explain that using proper null models that test for both spatial specificity and gene specificity is warranted.

neuroscience↗

bioRxiv2019

Genetic correlates of evolutionary adaptations in cognitive functional brain networks and their relationship to human cognitive functioning and disease

Cognitive functional networks such as the default-mode network (DMN), frontal-parietal network (FPN), and salience network (SN), are key networks of the human brain. Here, we show that the distinct rapid evolutionary cortical expansion of cognitive networks in the human brain, and most pronounced the DMN, runs parallel with high expression of genes important for human evolution (so-called HAR genes). Comparative gene expression examination then shows that HAR genes are more differentially expressed in cognitive networks in humans compared to the chimpanzee and macaque. Genes with distinct high expression in the DMN display broad involvement in the formation of synapses and dendrites. Next, we performed a genome-wide association analysis on functional MRI data, and show that HAR genes are associated with individual variations in DMN functional connectivity in todays human population. Finally, gene-set analysis suggests associations of HAR genes with intelligence, social cognition, and mental conditions such as schizophrenia and autism. Taken together, our results indicate that the expansion of higher-order functional networks and their cognitive properties have been an important locus of change in recent human brain evolution.

neuroscience↗

bioRxiv2018

Evolutionarily developed connections compromised in schizophrenia

The genetic basis and uniquely human character of schizophrenia has led to the notion of human brain evolution to have resulted in vulnerability to the disorder. We examined schizophrenia-related changes in brain connectivity in the context of evolutionary changes in human brain wiring by comparing in-vivo neuroimaging data from humans, chimpanzees and macaque monkeys. We find that evolutionary changes in human connectome organization overlap with the pattern of schizophrenia-related changes in brain connectivity, with connections evolutionary enhanced in the human brain showing significantly more involvement in schizophrenia pathology than connections shared between humans and non-human primates (effects shown in three independent patient-control datasets). Our findings suggest that the evolution of brain wiring in support of complex brain function in humans may have come at the cost of an increased vulnerability to brain dysfunction in disease.

neuroscience↗

bioRxiv2018

Shared vulnerability for connectome alterations across psychiatric and neurological brain disorders

Macroscale white matter pathways form the infrastructure for large-scale communication in the human brain, a prerequisite for healthy brain function. Conversely, disruptions in the brains connectivity architecture are thought to play an important role in a wide range of psychiatric and neurological brain disorders. Here we show that especially connections important for global communication and network integration are involved in a wide range of brain disorders. We report on a meta-analytic connectome study comprising in total 895 patients and 1,016 controls across twelve neurological and psychiatric disorders. We extracted disorder connectome fingerprints for each of these twelve disorders, which were then combined into a cross-disorder disconnectivity involvement map, representing the involvement of each brain pathway across brain disorders. Our findings show connections central to the brains infrastructure are disproportionally involved across a wide range of disorders. Connections critical for global network communication and integration display high disturbance across disorders, suggesting a general cross-disorder involvement and importance of these pathways in normal function. Taken together, our cross-disorder study suggests a convergence of disconnectivity across disorders to a partially shared disconnectivity substrate of central connections.

neuroscience↗