Biology subjects

Smallwood, J.

Publications and source records attributed to Smallwood, J..

At least 73 records · Page 4Linked to original sources

bioRxiv2020

Distinct and Common Neural Coding of Semantic and Non-semantic Control Demands

The flexible retrieval of knowledge is critical in everyday situations involving problem solving, reasoning and social interaction. Current theories emphasise the importance of a left-lateralised semantic control network (SCN) in supporting flexible semantic behaviour, while a bilateral multiple-demand network (MDN) is implicated in executive functions across domains. No study, however, has examined whether semantic and non-semantic demands are reflected in a common neural code within regions specifically implicated in semantic control. Using functional MRI and univariate parametric modulation analysis as well as multivariate pattern analysis, we found that semantic and non-semantic demands gave rise to both similar and distinct neural responses across control-related networks. Though activity patterns in SCN and MDN could decode the difficulty of both semantic and verbal working memory decisions, there was no shared common neural coding of cognitive demands in SCN regions. In contrast, regions in MDN showed common patterns across manipulations of semantic and working memory control demands, with successful cross-classification of difficulty across tasks. Therefore, SCN and MDN can be dissociated according to the information they maintain about cognitive demands.

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bioRxiv2020

Neuroimaging: Into the Multiverse

AO_SCPLOWBSTRACTC_SCPLOWFor most neuroimaging questions the huge range of possible analytic choices leads to the possibility that conclusions from any single analytic approach may be misleading. Examples of possible choices include the motion regression approach used and smoothing and threshold factors applied during the processing pipeline. Although it is possible to perform a multiverse analysis that evaluates all possible analytic choices, this can be computationally challenging and repeated sequential analyses on the same data can compromise inferential and predictive power. Here, we establish how active learning on a low-dimensional space that captures the inter-relationships between analysis approaches can be used to efficiently approximate the whole multiverse of analyses. This approach balances the benefits of a multiverse analysis without the accompanying cost to statistical power, computational power and the integrity of inferences. We illustrate this approach with a functional MRI dataset of functional connectivity across adolescence, demonstrating how a multiverse of graph theoretic and simple pre-processing steps can be efficiently navigated using active learning. Our study shows how this approach can identify the subset of analysis techniques (i.e., pipelines) which are best able to predict participants ages, as well as allowing the performance of different approaches to be quantified.

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bioRxiv2020

A structure-function substrate of memory for spatial configurations in medial and lateral temporal cortices

AO_SCPLOWBSTRACTC_SCPLOWPrior research has shown that structures of the mesiotemporal lobe, particularly the hippocampal-parahippocampal complex, are engaged in different forms of spatial cognition. Here, we developed a new paradigm, the Conformational Shift Spatial task (CSST), which examines the ability to encode and retrieve spatial relations between three unrelated items. This task is short, uses symbolic cues, and incorporates two difficulty levels and can be administered inside and outside the scanner. A cohort of 48 healthy young adults underwent the CSST, together with a set of validated behavioral measures and multimodal magnetic resonance imaging (MRI). Interindividual differences in CSST performance correlated with scores on an established spatial memory paradigm, but neither with episodic memory nor pattern separation performance, highlighting the specificity of the new measure. Analyzing high resolution structural MRI data, individuals with better spatial memory showed thicker medial as well as lateral temporal cortices. Functional relevance of these findings was supported by task-based functional MRI analysis in the same participants and ad hoc meta-analysis. Exploratory resting-state functional MRI analyses centered on clusters of morphological effects revealed additional modulation of intrinsic network integration, particularly between lateral and medial temporal structures. Our work presents a novel spatial memory paradigm and supports an integrated structure-function substrate in the human temporal lobe. Task paradigms are programmed in python and made open access.

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bioRxiv2020

Distinct default mode network subsystems show similarities and differences in the effect of task focus across reading and autobiographical memory

While reading, the mind can wander to unrelated autobiographical information, creating a perceptually-decoupled state detrimental to narrative comprehension. To understand how this mind-wandering state emerges, we asked whether retrieving autobiographical content necessitates functional disengagement from visual input. In Experiment 1, brain activity was recorded using functional magnetic resonance imaging (fMRI) in an experimental situation mimicking naturally occurring mind-wandering, allowing us to precisely delineate neural regions involved in memory and reading. Individuals read expository texts and ignored personally relevant autobiographical memories, as well as the opposite situation. Medial regions of the default mode network (DMN) were recruited during memory retrieval. In contrast, left temporal and lateral prefrontal regions of the DMN, as well as ventral visual cortex, were recruited when reading for comprehension. Experiment 2 used functional connectivity at rest to establish that (i) DMN regions linked to memory are more functionally decoupled from regions of ventral visual cortex than regions in the same network engaged when reading, and (ii) individuals reporting more mind-wandering and worse comprehension, while reading in the lab, showed increased functional decoupling between visually-connected DMN sites important for reading and a region of dorsal occipital cortex linked to autobiographical memory in Experiment 1. These data suggest we lose track of the narrative when our mind wanders because the generation of autobiographical mental content relies on cortical regions within the DMN which are functionally decoupled from ventral visual regions engaged during reading. Significance statementWhen the mind wanders during reading, we lose track of information from the narrative. We hypothesised that poor comprehension occurs because retrieving autobiographical memories reduces the perceptual coupling necessary to understand written words. We show that default mode network (DMN) areas involved in reading are functionally more connected to ventral visual regions than DMN regions important for autobiographical memory. Furthermore, individuals who mind-wander more, and comprehend less, have weaker connectivity between visually-coupled DMN regions linked to reading and dorsal occipital areas linked to autobiographical memory. These data suggest that when our minds wander during reading, retrieval of personally-relevant information activates DMN regions that are functionally disconnected from visual input, creating a perceptually decoupled state detrimental to comprehension.

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bioRxiv2020

Exploring patterns of ongoing thought under naturalistic and task-based conditions

Previous research suggests that patterns of ongoing thought are heterogeneous, varying across situations and individuals. The current study investigated the influence of a wide range of tasks and individual affective style on ongoing patterns of thought. In total, we used 9 different tasks and measured ongoing thought using multidimensional experience sampling. A Principle Component Analysis of the experience sampling data revealed four patterns of ongoing thought. Linear Mixed Modelling was used to examine the contextual distribution of the thought patterns. Different thought patterns were found to relate to different types of conditions. Intrusive and negative thought pattern expression was found to be influenced by individual affective style (depression level). Overall, these data show that patterns of thought are subject to both contextual and intrinsic variation, suggesting that understanding these important features of experience across a broad range of situations will be useful in understanding their role in human experience. HighlightsO_LIPatterns of thought vary across different task contexts C_LIO_LIThought pattern expression is influenced by individual affective style C_LIO_LIThere is a need to broaden the tasks used to study ongoing thought C_LI

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bioRxiv2020

Individual Differences in the Connectivity of Left and Right Anterior Temporal Lobes Relate to Modality and Category Effects in Semantic Categorisation

Contemporary neuroscientific accounts suggest that ventral anterior temporal lobe (ATL) regions act as a bilateral heteromodal semantic hub. However, research also shows graded functional differences between the hemispheres relating to linguistic versus non-linguistic semantic tasks and to knowledge of objects versus people. Individual differences in connectivity from bilateral ATL and between left and right ATL might therefore give rise to differences in function within this system. We investigated whether the relative strength of intrinsic connectivity from left and right ATL would relate to differences in performance on semantic tasks. We examined resting-state fMRI in 74 individuals and, in a separate session, examined semantic categorisation, manipulating stimulus type (famous faces versus landmarks) and modality of presentation (visual versus verbal). We found that people with greater connectivity between left and right ATL were more efficient at categorising landmarks, especially when these were presented visually. In addition, participants who showed stronger connectivity from right than left ATL to medial occipital cortex showed more efficient semantic categorisation of landmarks regardless of modality of presentation. These findings show that individual differences in the intrinsic connectivity of left and right ATL are associated with effects of category and modality in semantic categorisation. The results can be interpreted in terms of graded differences in the strengths of inputs from spoke regions, such as regions of visual cortex, to a bilateral yet partially segregated semantic hub, encompassing left and right ATL.

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bioRxiv2020

Topographic profiling of memory-related pattern separation processes in humans

AO_SCPLOWBSTRACTC_SCPLOWEpisodic memory is our ability to remember past events accurately. Pattern separation, the process of of orthogonalizing similar aspects of external information into nonoverlapping representations, is one of its mechanisms. Converging evidence suggests a pivotal role of the hippocampus, in concert with neocortical areas, in this process. The current study aimed to identify principal dimensions of functional activation associated with pattern separation in hippocampal and neocortical areas, in both healthy individuals and patients with lesions to the hippocampus. Administering a pattern separation fMRI paradigm to a group of healthy adults, we detected task-related activation in bilateral hippocampal and distributed neocortical areas. Capitalizing on manifold learning techniques applied to parallel resting-state fMRI data, we could identify that hippocampal and neocortical activity patterns were efficiently captured by their principal gradients of intrinsic functional connectivity, which follows the hippocampal long axis and sensory-fugal cortical organization. Functional activation patterns and their alignment with these principal dimensions were altered in patients. Notably, inter-individual differences in the concordance between task-related activity and intrinsic functional gradients were correlated with pattern separation performance in both patients and controls. Our work outlines a parsimonious approach to capture the functional underpinnings of episodic memory processes at the systems level, and to decode functional reorganization in clinical populations.

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bioRxiv2020

Convergence of cortical types and functional motifs in the mesiotemporal lobe

AO_SCPLOWBSTRACTC_SCPLOWThe parahippocampus-hippocampus complex in the mesiotemporal lobe (MTL) is implicated in many different cognitive processes, is compromised in numerous disorders, and exhibits a unique cytoarchitectural transition from six-layered isocortex to three-layered allocortex. Our study leveraged an ultra-high-resolution histological reconstruction of a human brain to (i) develop a continuous surface model of the MTL iso-to-allocortex transition and (ii) quantitatively characterise the regions cytoarchitecture. We projected the model into the native space of in vivo functional magnetic resonance imaging of healthy adults to (iii) construct a generative model of its intrinsic circuitry and (iv) determine its relationship with distributed functional dynamics of macroscale isocortical fluctuations. We provide evidence that the most prominent axis of cytoarchitectural differentiation of the MTL follows infolding from iso-to-allocortex and is defined by depth-specific variations in neuron density. Intrinsic effective connectivity exhibited a more complex relationship to MTL geometry, varying across both iso-to-allocortical and anterior-posterior axes. Variation along the long axis of the MTL was associated with differentiation between transmodal and unimodal systems, with anterior regions linked to transmodal cortex. In contrast, the iso-to-allocortical gradient was associated with the multiple demand system, with isocortex linked to regions activated when task demands prohibit the use of prior knowledge. Our findings establish a novel model of the MTL, in which its broad influence on neural function emerges through the combination micro- and macro-scale structural features. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/148643v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@48dbc7org.highwire.dtl.DTLVardef@15500a2org.highwire.dtl.DTLVardef@19c99b2org.highwire.dtl.DTLVardef@2eab49_HPS_FORMAT_FIGEXP M_FIG C_FIG

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bioRxiv2020

Connectome and microcircuit models implicate atypical subcortico-cortical interactions in autism pathophysiology

AO_SCPLOWBSTRACTC_SCPLOWBoth macroscale connectome miswiring and microcircuit anomalies have been suggested to play a role in the pathophysiology of autism. However, an overarching framework that consolidates these macro and microscale perspectives of the condition is lacking. Here, we combined connectome-wide manifold learning and biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. Our analysis established that autism showed significant differences in structural connectome organization relative to neurotypical controls, with strong effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models revealed that the degree of macroscale anomalies was related to atypical increases of subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic decoding and developmental gene enrichment analyses provided biological context and pointed to genes expressed in cortical and thalamic areas during childhood and adolescence. Supervised machine learning showed the macroscale perturbations predicted socio-cognitive symptoms and repetitive behaviors. Our analyses provide convergent support that atypical subcortico-cortical interactions may contribute to both microcircuit and macroscale connectome anomalies in autism.

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bioRxiv2020

LSD flattens the functional hierarchy of the human brain

LSD and psilocybin are serotonergic psychedelic compounds with potential in the treatment of mental health disorders. Past neuroimaging investigations have revealed that both compounds can elicit significant changes to whole-brain functional organization and dynamics. A recent proposal linked past findings into a unified model and hypothesized reduced whole-brain hierarchical organization as a key mechanism underlying the psychedelic state, but this has yet to be directly tested. We applied a non-linear dimensionality reduction technique previously used to map hierarchical connectivity gradients to pharmacological resting-state fMRI data to assess cortical organization in the LSD and psilocybin state. Results supported our primary hypothesis: The principal gradient of cortical connectivity, describing a hierarchy from unimodal to transmodal cortex, was significantly flattened under both drugs relative to their respective placebo conditions. Between-condition contrasts revealed that this was driven by a reduction of functional differentiation at both hierarchical extremes - default and frontoparietal networks at the upper end, and somatomotor at the lower. Gradient-based connectivity mapping confirmed that this was underpinned by increased unimodal-transmodal crosstalk. In addition, LSD-dependent principal gradient changes tracked changes in self-reported ego-dissolution. Results involving the second and third gradient, which respectively represent axes of sensory and executive differentiation, also showed significant alterations across both drugs. These findings provide support for a recent mechanistic model of the psychedelic state relevant to therapeutic applications of psychedelics. More fundamentally, we provide the first evidence that macroscale connectivity gradients are sensitive to a pharmacological manipulation, specifically highlighting an important relationship between cortical organization and serotonergic modulation.

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bioRxiv2020

TOWARD A CONNECTIVITY GRADIENT-BASED FRAMEWORK FOR REPRODUCIBLE BIOMARKER DISCOVERY

AO_SCPLOWBSTRACTC_SCPLOWDespite myriad demonstrations of feasibility, the high dimensionality of fMRI data remains a critical barrier to its utility for reproducible biomarker discovery. Recent studies applying dimensionality reduction techniques to resting-state fMRI (R-fMRI) have unveiled neurocognitively meaningful connectivity gradients that are present in both human and primate brains, and appear to differ meaningfully among individuals and clinical populations. Here, we provide a critical assessment of the suitability of connectivity gradients for biomarker discovery. Using the Human Connectome Project (discovery subsample=209; two replication subsamples= 209x2) and the Midnight scan club (n=9), we tested the following key biomarker traits - reliability, reproducibility and predictive validity - of functional gradients. In doing so, we systematically assessed the effects of three analytical settings, including i) dimensionality reduction algorithms (i.e., linear vs. non-linear methods), ii) input data types (i.e., raw time series, [un-]thresholded functional connectivity), and iii) amount of the data (R-fMRI time-series lengths). We found that the reproducibility of functional gradients across algorithms and subsamples is generally higher for those explaining more variances of whole-brain connectivity data, as well as those having higher reliability. Notably, among different analytical settings, a linear dimensionality reduction (principal component analysis in our study), more conservatively thresholded functional connectivity (e.g., 95-97%) and longer time-series data (at least [≥]20mins) was found to be preferential conditions to obtain higher reliability. Those gradients with higher reliability were able to predict unseen phenotypic scores with a higher accuracy, highlighting reliability as a critical prerequisite for validity. Importantly, prediction accuracy with connectivity gradients exceeded that observed with more traditional edge-based connectivity measures, suggesting the added value of a low-dimensional gradient approach. Finally, the present work highlights the importance and benefits of systematically exploring the parameter space for new imaging methods before widespread deployment. HO_SCPLOWIGHLIGHTSC_SCPLOW- There is a growing need to identify benchmark parameters in advancing functional connectivity gradients into a reliable biomarker. - Here, we explored multidimensional parameter space in calculating functional gradients to improve their reproducibility, reliability and predictive validity. - We demonstrated that more reproducible and reliable gradient markers tend to have higher predictive power for unseen phenotypic scores across various cognitive domains. - We showed that the low-dimensional connectivity gradient approach could outperform raw edge-based analyses in terms of predicting phenotypic scores. - We highlight the necessity of optimizing parameters for new imaging methods before their widespread deployment.

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bioRxiv2020

Shaping Brain Structure: Genetic and Phylogenetic Axes of Macro Scale Organization of Cortical Thickness

Structural and functional characteristics of the cortex systematically vary along global axes as a function of cytoarchitecture, gene expression, and connectivity. The topology of the cerebral cortex has been proposed to be a prerequisite for the emergence of human cognition and explain both the impact and progression of pathology. However, the neurogenetic origin of these organizational axes in humans remains incompletely understood. To address this gap in the literature our current study assessed macro scale cortical organization through an unsupervised machine learning analysis of cortical thickness covariance patterns and used converging methods to evaluate its genetic basis. In a large-scale sample of twins (n=899) we found structural covariance of thickness to be organized along both an anterior-to-posterior and inferior-to-superior axis. We found that both axes showed a high degree of correspondence in pairs of identical twins, suggesting a strong heritable component in humans. Furthermore, comparing these dimensions in macaques and humans highlighted similar organizational principles in both species demonstrating that these axes of cortical organization are phylogenetically conserved within primate species. Finally, we found that in both humans and macaques the inferior-superior dimension of cortical organization was aligned with the predictions of the dual-origin theory, highlighting the possibility that the macroscale organization of primate brain structure is subject to multiple distinct neurodevelopmental trajectories. Together, our study establishes the genetic basis of natural axes in the cerebral cortex along which structure is organized and so provides important insights into the organization of human cognition that will inform both our understanding of how structure guides function and for the progression of pathology in diseases.

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bioRxiv2020

A gradient from long-term memory to novel cognition: graded transitions through default mode and executive cortex

Human cognition flexibly guides decision-making in familiar and novel situations. Although these decisions are often treated as dichotomous, in reality, situations are neither completely familiar, nor entirely new. Contemporary accounts of brain organization suggest that neural function is organized along a gradient from unimodal regions of sensorimotor cortex, through executive regions to transmodal default network. We examined whether this graded view of neural organization helps to explain how decision-making changes across situations that vary in their alignment with long-term knowledge. Functional magnetic resonance imaging found that as decisions are made in an increasingly familiar context, the BOLD signal follows this neural gradient, with stronger responses in default regions when items are linked in long-term memory. In this way, neural organization is optimized to support decision-making in both highly familiar and less familiar situations.

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bioRxiv2020

The cortical wiring scheme of hierarchical information processing

AO_SCPLOWBSTRACTC_SCPLOWThe vast net of fibres within and underneath the cortex is optimised to support the convergence of different levels of brain organisation. Here we propose a novel coordinate system of the human cortex based on an advanced model of its connectivity. Our approach is inspired by seminal, but so far largely neglected models of cortico-cortical wiring established by post mortem anatomical studies and capitalizes on cutting-edge neuroimaging and machine learning. The new model expands the currently prevailing diffusion MRI tractography approach by incorporation of additional features of cortical microstructure and cortico-cortical proximity. Studying several datasets, we could show that our coordinate system robustly recapitulates established sensory-limbic and anterior-posterior dimensions of brain organisation. A series of validation experiments showed that the new wiring space reflects cortical microcircuit features (including pyramidal neuron depth and glial expression) and allowed for competitive simulations of functional connectivity and dynamics across a broad range contexts (based on resting-state fMRI, task-based fMRI, and human intracranial EEG coherence). Our 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. Our evaluations demonstrate the cortical wiring space bridges across scales of neural organisation and can be easily translated to single individuals. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=148 SRC="FIGDIR/small/899583v4_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1b1c601org.highwire.dtl.DTLVardef@3e76c7org.highwire.dtl.DTLVardef@e828e5org.highwire.dtl.DTLVardef@1d4f8ce_HPS_FORMAT_FIGEXP M_FIG C_FIG

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bioRxiv2020

Missing the forest because of the trees: Slower alternations during binocular rivalry are associated with lower levels of visual detail

Conscious awareness of the world fluctuates, either through variation in the quality with which we perceive the environment, or, when attention switches to information generated using imagination rather than the external environment. Our study combined individual differences in experience sampling, psychophysical reports of perception, and neuroimaging descriptions of structural connectivity, to better understand these changes in conscious awareness. In particular, we (a) examined if aspects of ongoing thought, as measured by multi-dimensional experience sampling during a sustained attention task, are associated with the white matter fibre organization of the cortex as reflected by their relative degree of anisotropic diffusion, and (b) whether these neuro-cognitive descriptions of ongoing experience are related to a more constrained measure of visual consciousness provided by the analysis of bistable perception during binocular rivalry. Individuals with greater fractional anisotropy (FA) in right hemisphere white matter regions involving the inferior fronto-occipital fasciculus, the superior longitudinal fasciculus and the cortico-spinal tract, described their ongoing thoughts as lacking external details. Subsequent analysis indicated that the combination of low FA in these right hemisphere regions, with reports of high level external details, was associated with the shortest periods of dominance during binocular rivalry. Since variation in binocular rivalry reflects differences between bottom-up and top-down influences on vision, our study suggests that reports of ongoing thoughts with vivid external details may occur when conscious precedence is given to bottom-up representation of perceptual information and that this may partly be rooted in the white matter fibre organization of the cortex.

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bioRxiv2019

Emergence of neural dynamics within a co-ordinate space of large-scale neural hierarchies

When unoccupied by an explicit external task, humans engage in a wide range of different types of self-generated thinking. These are often unrelated to the immediate environment and have unique psychological features. Although contemporary perspectives on ongoing thought recognise the heterogeneity of these self-generated states, we lack both a clear understanding of how to classify the specific states, and how they can be mapped empirically. In the current study, we capitalise on advances in machine learning that allow continuous neural data to be divided into a set of distinct temporally re-occurring patterns, or states. We applied this technique to a large set of resting state data in which we also acquired retrospective descriptions of the participants experiences during the scan. We found that two of the identified states were predictive of patterns of thinking at rest. One state highlighted a pattern of neural activity commonly seen during demanding tasks, and the time individuals spent in this state was associated with descriptions of experience focused on problem solving in the future. A second state was associated with patterns of activity that are commonly seen under less demanding conditions, and the time spent in it was linked to reports of negative rumination. Finally, we found that these two neural states tended to fall at either end of a neural hierarchy that is thought to reflect the brains response to cognitive demands. Together, these results demonstrate that approaches which take advantage of time-varying changes in neural function can play an important role in understanding the repertoire of self-generated states. Moreover, they establish that important features of self-generated ongoing experience are related to variation along a similar vein to those seen when the brain responds to cognitive task demands.

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bioRxiv2019

Population level interactions between the neural correlates of dispositional internal thought and visual imagery

Cognition is not always directed to the events in the here and now and we often self-generate thoughts and images in imagination. Important aspects of these self-generated experiences are associated with various dispositional traits. In this study, we explored whether these psychological associations relate to a common underlying neurocognitive mechanism. We acquired resting state functional magnetic resonance imaging data from a large cohort of participants and asked them to retrospectively report their experience during the scan. Participants also completed questionnaires reflecting a range of dispositional traits. We found thoughts emphasising visual imagery at rest were associated with dispositional tendency towards internally directed attention (self-consciousness and attentional problems) and linked to a stronger correlation between a posterior parietal network and a lateral fronto-temporal network. Furthermore, decoupling between the brainstem and a lateral visual network was associated with dispositional internally directed attention. Critically, these brain-cognition associations were related: the correlation between parietal-frontal regions and reports of visual imagery was stronger for individuals with increased connectivity between brainstem and visual cortex. Our results highlight neural mechanisms linked to the dispositional basis for patterns of self-generated thought, and suggest that accounting for dispositional traits is important when exploring the neural substrates of self-generated experience (and vice versa).

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bioRxiv2019

Myeloarchitecture gradients in the human insula serve as blueprints for its diverse connectivity and function

AO_SCPLOWBSTRACTC_SCPLOWInsular cortex is a core hub involved in multiple cognitive and socio-affective processes. Yet, the anatomical mechanisms that explain how it is involved in such a diverse array of functions remain incompletely understood. Here, we define a novel framework to test the hypothesis that changes in myeloarchitecture across the insular cortex explain how it can be involved in many different facets of cognitive function. Detailed intracortical profiling, performed across hundreds of insular locations on the basis of myelin-sensitive magnetic resonance imaging (MRI), was compressed into a lower-dimensional space uncovering principal axes of myeloarchitectonic variation. Leveraging two datasets with different high-resolution MRI contrasts, we obtained robust support for two principal dimensions of insular myeloarchitectonic differentiation in vivo, one running from ventral anterior to posterior banks and one radiating from dorsal anterior towards both ventral anterior and posterior subregions. Analyses of post mortem 3D histological data showed that the antero-posterior axis was mirrored in cytoarchitectural markers, even when controlling for anatomical landmarks and sulco-gyral folding. Resting-state functional connectomics in the same individuals and ad hoc meta-analyses showed that myelin gradients in the insula constrained affiliation to macroscale intrinsic functional systems, showing differential shifts in functional network embedding across each myelin-derived gradient. Collectively, our findings offer a novel approach to capture structure-function interactions of a key node of the limbic system, and suggest a multidimensional structural basis underlying the diverse functional roles of the insula.

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