Gradients of connectivity distance in the cerebral cortex of the macaque monkey

Oligschläger, Sabine; Xu, Ting; Bączkowski, Błażej M.; Falkiewicz, Marcel; Falchier, Arnaud; Linn, Gary; Margulies, Daniel S.

doi:10.1007/s00429-018-1811-1

Cited by 48 publications

(42 citation statements)

References 68 publications

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“…This is in line with a previous study that used a similar approach (39). It is further in line with organizing principles of the brain that regions tend to be more interconnected when they are located close to each other (40,41). However, when we compared the regions loading on the two components, the covarying regions of each component distribute in different brain locations.…”

Section: Discussionsupporting

confidence: 89%

Gray matter covariations and core symptoms of autism. The EU-AIMS Longitudinal European Autism Project

Mei

Llera

Floris

et al. 2020

Preprint

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BackgroundVoxel-based Morphometry (VBM) studies in Autism Spectrum Disorder (autism) have yielded diverging results. This might partly be attributed to structural alterations being associating with the combined influence of several regions rather than with a single region. Further, these structural covariation differences may relate to continuous measures of autism rather than with categorical case-control contrasts. The current study aimed to identify structural covariation alterations in autism, and assessed canonical correlations between brain covariation patterns and core autism symptoms.MethodsWe studied 347 individuals with autism and 252 typically developing individuals, aged between 6 and 30 years, who have been deeply phenotyped in the Longitudinal European Autism Project (LEAP). All participants’ VBM maps were decomposed into spatially independent components using Independent Component Analysis. A Generalized Linear Model (GLM) was used to examine case-control differences. Next, Canonical Correlation Analysis (CCA) was performed to separately explore the integrated effects between all the brain sources of gray matter variation and two sets of core autism symptoms.ResultsGLM analyses showed significant case-control differences for two independent components. The first component was primarily associated with decreased density of bilateral insula, inferior frontal gyrus, orbitofrontal cortex, and increased density of caudate nucleus in the autism group relative to typically developing individuals. The second component was related to decreased densities of the bilateral amygdala, hippocampus, and parahippocampal gyrus in the autism group relative to typically developing individuals. The CCA results showed significant correlations between components that involved variation of thalamus, putamen, precentral gyrus, frontal, parietal, and occipital lobes, and the cerebellum, and repetitive, rigid and stereotyped behaviors and abnormal sensory behaviors in autism individuals.LimitationsOnly 55.9% of the participants with autism had complete questionnaire data on continuous parent-reported symptom measures.ConclusionsCovaried areas associated with autism diagnosis and/or symptoms are scattered across the whole brain and include the limbic system, basal ganglia, thalamus, cerebellum, precentral gyrus, and parts of the frontal, parietal, and occipital lobes. Some of these areas potentially subserve social-communicative behavior whereas others may underpin sensory processing and integration, and motor behavior.

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Section: Discussionsupporting

confidence: 89%

Gray matter covariations and core symptoms of autism. The EU-AIMS Longitudinal European Autism Project

Mei

Llera

Floris

et al. 2020

Preprint

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“…The functional affinity matrix was built using the same steps described by 23 . In reporting the results we explicitly looked for gradients capturing the polymodal-unimodal differentiation as well as the modality specific organization of cortical connectivity as described in recent human and primate work 23,64 . In line with human results, we found that the dominant gradient of both SC and FC recapitulates the unimodal-polymodal continuum (Gradient A in Figure 5A and 5B), whereas the second ranked functional and the third ranked structural gradients delineate comparable modality specific spatial configuration of cortical connectivity (Gradient B).…”

Section: Functional and Structural Gradientsmentioning

confidence: 99%

Network structure of the mouse brain connectome with voxel resolution

Coletta

Pagani

Whitesell

et al. 2020

Preprint

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Fine-grained descriptions of brain connectivity are fundamental for understanding how neural information is processed and relayed across spatial scales. Prior investigations of the mouse brain connectome have employed discrete anatomical parcellations, limiting spatial resolution and potentially concealing network attributes critical to the organization of the mammalian connectome.Here we provide a voxel-level description of the network and hierarchical structure of the directed mouse connectome, unconstrained by regional partitioning. We show that integrative hub regions can be directionally segregated into neural sinks and sources, defining a hierarchical axis. We describe a set of structural communities that spatially reconstitute previously described fMRI networks of the mouse brain, and document that neuromodulatory nuclei are strategically wired as critical orchestrators of inter-modular and network communicability. Notably, like in primates, the directed mouse connectome is organized along two superimposed cortical gradients reflecting unimodaltransmodal functional processing and a modality-specific sensorimotor axis. These structural features can be related to patterns of intralaminar connectivity and to the spatial topography of dynamic fMRI brain states, respectively. Together, our results reveal a high-resolution structural scaffold linking mesoscale connectome topography to its macroscale functional organization, and create opportunities for identifying targets of interventions to modulate brain function in a physiologicallyaccessible species.

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“…Degree centrality is defined as the row-wise sum of the weighted connectivity matrix, representing the connection strength of a given node 70 . Connectivity distance is a given brain region's geodesic distance to its structurally connected brain areas within the cortex 134 , and it is defined as the multiplication between the geodesic distance and the binarized structural connectome 10,134 . Within-module degree and participation coefficient are nodal measures reflecting different facets of community organization 70,[135][136][137] .…”

Section: Association With Connectome Topologymentioning

confidence: 99%

An expanding manifold in transmodal regions characterizes adolescent reconfiguration of structural connectome organization

Park

Bethlehem

Paquola

et al. 2020

Preprint

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Adolescence is a critical time for the continued maturation of brain networks, and the current work assessed longitudinal reconfigurations of diffusion MRI derived connectomes in a large sample (n = 208). We identified an expansion of structural network representations in lower dimensional manifold spaces, with strongest effects in transmodal cortices and indicative of an increasing differentiation of these networks from the rest of the brain. Findings were shown to relate to mainly an increase in within-module connectivity and increased segregation during adolescence. Connectome findings were consistent when additionally controlling for regional changes in MRI measures of cortical morphology and myelin, despite reductions in effect sizes. On the other hand, cortical areas showing manifold expansion were found to become more closely embedded with subcortical targets, notably the striatum. Identified networks were also found to harbor genes significantly expressed in both cortical and subcortical regions. Using supervised machine learning with cross-validation, we demonstrated that cortico-subcortical manifold features at baseline and their maturational change predicted measures of intelligence at follow-up. Our findings chart adolescent connectome development and suggest that brain-wide network reconfigurations offer intermediary phenotypes between genetic-microstructural processes and cognitive-behavioral outcomes.We explored how whole-brain structural networks reconfigure during adolescence, using a novel analysis that simultaneously interrogates network and regional features. Our approach revealed an increasing differentiation of the connectome during this critical period, particularly in higher-order prefrontal and parietal regions. We could show that while this effect was only partially related to developmental trajectories of intracortical microstructure and morphology, but rather to changes in connectivity to subcortical areas, particularly the striatum. Cortico-subcortical network effects were also supported by transcriptomics and phenotype prediction, which suggested that cognitive function in adulthood was most effectively predicted when combining cortical and subcortical features. Our findings shed new light on adolescence and support a key role of cortico-subcortical integration in shaping macroscale structural networks. Park et al. | Structural connectome maturation during adolescence 3 3

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Gradients of connectivity distance in the cerebral cortex of the macaque monkey

Cited by 48 publications

References 68 publications

Gray matter covariations and core symptoms of autism. The EU-AIMS Longitudinal European Autism Project

Gray matter covariations and core symptoms of autism. The EU-AIMS Longitudinal European Autism Project

Network structure of the mouse brain connectome with voxel resolution

An expanding manifold in transmodal regions characterizes adolescent reconfiguration of structural connectome organization

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