On testing for spatial correspondence between maps of human brain structure and function

Alexander-Bloch, Aaron; Shou, Haochang; Liu, Siyuan; Satterthwaite, Theodore D.; Glahn, David C.; Shinohara, Russell T.; Vandekar, Simon; Raznahan, Armin

doi:10.1016/j.neuroimage.2018.05.070

Cited by 472 publications

(660 citation statements)

References 72 publications

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“…We used multiple linear regressions to evaluate the variance explained in externopyramidisation and cell-type specific expression by the two structural manifold eigenvectors. Significance values were corrected to account for spatial autocorrelation in the eigenvectors using spin testing and Moran spectral randomisation, respectively 116,117 , and was operationalised using BrainSpace 92 . Spectral randomisation was initialised using the geodesic distance matrix.…”

Section: Externopyramidisation = Max( ) Mean( ) × 1 − ℎ ℎmentioning

confidence: 99%

A cortical wiring space links cellular architecture, functional dynamics and hierarchies in humans

Paquola

Seidlitz

Benkarim

et al. 2020

Preprint

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The vast net of fibres within and underneath the cortical mantle is optimised to support the convergence of different levels of brain organisation, specifically through linking cellular and architectural features of different cortical areas to give rise to more integrated neural function. Leveraging multimodal neuroimaging and machine learning techniques, we identified a novel manifold space that is governed by geometric, microstructural, and connectional aspects of cortico-cortical wiring. Principal dimensions of this manifold recapitulated established sensory-limbic and anterior-posterior gradients of brain organisation, and were found to reflect neural and glial gradients of cytoarchitectural organisation and gene expression. Manifold features were accurate in predicting cortico-cortical functional interactions derived from resting-state functional neuroimaging. Furthermore, application of this approach to a group of neurological patients, who underwent intracerebral encephalographic recordings, established that manifold features also explained the direction of information flow between different cortical areas. These results advance our understanding of how cell-specific neurobiological gradients produce a hierarchical cortical wiring scheme that is concordant with increasing functional sophistication of human brain organisation. RESULTSA multi-scale model of cortical wiring The wiring model was first derived from a Discovery subset of the Human Connectome Project dataset (n=100 unrelated adults) that offers high resolution structural magnetic resonance imaging (MRI), diffusion MRI, and microstructurally sensitive T1w/T2w maps 38 (Figure 1A, see Methods for details). and diffusion-based tractography strength (TS) were estimated between all pairs of nodes. (B) Normalised matrices were concatenated and transformed into an affinity matrix. Manifold learning identified a lower dimensional representation of cortical wiring. (C) Left. Node positions in this newly-discovered structural manifold, coloured according to proximity to axis limits. Closeness to the maximum of the second eigenvector is redness, towards the minimum of the first eigenvector is greenness and towards the maximum of the first eigenvector is blueness. The first two eigenvectors are shown on the respective axes. Right. Equivalent cortical surface representation. (D) Calculation of inter-regional distances in the structural manifold from specific seeds to other regions of cortex (left). Overall distance to all other nodes can also be quantified to index centrality of different regions, with more integrative areas having shorter distances to nodes (right). Figure 4: Hierarchical information processing is organised by the structural manifold. (A)Intracerebral implantations of ten epileptic patients were mapped to cortical surface. Intracortical EEG recordings were selected across five minutes of rest. (B) Boxplots show the variance explained in coherence by the structural manifold using adaboost machine learning across all nodes. (C) The phase slope ...

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Section: Externopyramidisation = Max( ) Mean( ) × 1 − ℎ ℎmentioning

confidence: 99%

A cortical wiring space links cellular architecture, functional dynamics and hierarchies in humans

Paquola

Seidlitz

Benkarim

et al. 2020

Preprint

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“…Additionally, we examined the relationship between level of laminar differentiation and adolescent development of MT moments. To assess the relative over-or underrepresentation of significant regions per laminar class we generated 10,000 spin permutations of the t-maps, which controls for spatial contiguity and hemispheric symmetry across permutations 21,32,44 . Specifically, we differently rotated the t-maps 10,000 times and for each permutation of this spin or rotation we computed counts per laminar class that passed a false discovery rate (FDR) correction for multiple comparisons 62 to create a null-distribution of the counts table.…”

Section: Longitudinal Assessment Of Age-related Changes In Mt Momentsmentioning

confidence: 99%

A moment of change: shifts in myeloarchitecture characterise adolescent development of cortical gradients

Paquola

Bethlehem

Seidlitz

et al. 2019

Preprint

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The biological processes underpinning adolescent brain maturation remain elusive. Expanding on previous work showing age-related changes in cortical morphology, we studied an accelerated longitudinal cohort of adolescents and young adults (n=223, two time points) to investigate dynamic reconfigurations in myeloarchitecture. Intracortical profiles were generated using magnetization transfer (MT) data, a myelinsensitive magnetic resonance imaging contrast. Mixed-effect models of depth specific intracortical profiles demonstrated two separate processes i) related to overall increases in MT, and ii) showing a flattening of the MT profile related to enhanced signal in mid-to-deeper layers, especially in heteromodal and unimodal association cortices. This development was independent of morphological changes, and enhanced MT in mid-to-deeper layers was found to spatially co-localise specifically with gene expression markers of oligodendrocytes. Covariance analysis between all pairs of intracortical profiles revealed that these intracortical changes contributed to a gradual and dynamic differentiation from higher-order to lower-order systems. Depth-dependent trajectories of intracortical myeloarchitectural development contribute to the maturation of structural hierarchies in the human neocortex, providing a model for adolescent development that bridges microstructural and macroscopic scales of brain organization.Intracortical myelin imposes a spatial structure on cortico-cortical connections, yet little is known about how myeloarchitecture develops throughout youth. We formulated a novel approach to study cortical myeloarchitecture in individual humans and leveraged an accelerated longitudinal design to track agerelated changes from 14-27 years. We discovered two unique processes: one involving increasing mean myelin and another characterised by the preferential accumulation of myelin in mid-to-deeper cortical layers. Both processes contributed to an increasing segregation of lower-order from higher-order systems along the macroscale cortical hierarchy. These findings illustrate how layer specific microstructural changes contribute to the maturation of cortical organization and suggest adolescent fine tuning of hierarchical gradients of cortical networks.

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“…To explore how compression efficiency might relate to patterns of cortical myelination and areal scaling, we assessed the Spearman's correlation coefficient between myelination or scaling and send or receive compression efficiency. To further test correspondence between brain maps, we used a spatial permutation test, which generates a null distribution of randomly rotated brain maps that preserve the spatial covariance structure of the original data [79]. We refer to the p-value of this statistical test as p SP IN .…”

Section: Compression Efficiency and Patterns Of Neurodevelopmentmentioning

confidence: 99%

Efficient Coding in the Economics of Human Brain Connectomics

Zhou

Lynn

Cui

et al. 2020

Preprint

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In systems neuroscience, most models posit that brain regions communicate information under constraints of efficiency. Yet, metabolic and information transfer efficiency across structural networks are not understood. In a large cohort of youth, we find metabolic costs associated with structural path strengths supporting information diffusion. Metabolism is balanced with the coupling of structures supporting diffusion and network modularity. To understand efficient network communication, we develop a theory specifying minimum rates of message diffusion that brain regions should transmit for an expected fidelity, and we test five predictions from the theory. We introduce compression efficiency, which quantifies differing trade-offs between lossy compression and communication fidelity in structural networks. Compression efficiency evolves with development, heightens when metabolic gradients guide diffusion, constrains network complexity, explains how rich-club hubs integrate information, and correlates with cortical areal scaling, myelination, and speed-accuracy trade-offs. Our findings elucidate how network structures and metabolic resources support efficient neural communication.

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On testing for spatial correspondence between maps of human brain structure and function

Cited by 472 publications

References 72 publications

A cortical wiring space links cellular architecture, functional dynamics and hierarchies in humans

A cortical wiring space links cellular architecture, functional dynamics and hierarchies in humans

A moment of change: shifts in myeloarchitecture characterise adolescent development of cortical gradients

Efficient Coding in the Economics of Human Brain Connectomics

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