Biology subjects

Jefferies, E.

Publications and source records attributed to Jefferies, E..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Hippocampus responds to mismatches with predictions based on episodic memories but not generalised knowledge

Prediction errors drive learning by signalling a mismatch between our expectations and reality. The hippocampus plays a key role in mismatch detection, but it is not known what information the hippocampus uses to form expectations. Here we show that the human hippocampus bases its expectations on episodic memories and not generalised schematic knowledge. Across three fMRI experiments, we demonstrate that the hippocampus is selectively engaged by mismatches with episodic memories of specific events. In contrast, mismatches with schematic knowledge activate regions of the Semantic Control and Multiple Demand Networks, as well as subcortical regions involved in prediction error signalling. Notably, mismatches with episodic memories also engage the Default Mode Network. Overall, our findings provide direct support for some models of learning via mismatch detection and refute models that propose the hippocampus plays a wider role as a more generalised mismatch detector.

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bioRxiv2024

Feature similarity: a sensitive method to capture the functional interaction of brain regions and networks to support flexible behavior

The brain is a dynamic system where complex behaviours emerge from interactions across distributed regions. Accurately linking brain function to cognition requires tools that are sensitive to these dynamics. We introduce a novel technique, Feature Similarity (FS), which represents a conceptual advancement in measuring brain region interactions by integrating multiple features across various measures, moving beyond traditional methods that focus on a single measure. Our results show that FS can capture functional brain organisation: regions within the same functional network have greater FS compared to those in different networks, and FS also identifies the principal gradient that spans from unimodal to transmodal cortices. FS demonstrated greater sensitivity to task modulation than traditional functional connectivity (FC) and 46 out of 49 statistical measures of pairwise interactions (SPIs). Specifically, FS reveals interaction patterns missed by FC and most SPIs, such as a double dissociation in Dorsal Attention Network: greater interaction with Visual network during working memory tasks and greater interaction with default mode network during long-term memory tasks. These findings position FS as a powerful tool for capturing task-specific brain network dynamics and advancing our understanding of cognitive flexibility. Using FS to reanalyse existing fMRI data could resolve inconsistencies, lead to novel insights, and prompt revisions of existing theories or the development of new theoretical frameworks.

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bioRxiv2024

Controlled retrieval relies on directed interactions between semantic control regions and visual cortex: MEG evidence from oscillatory dynamics

To navigate the world, we store knowledge about relationships between concepts and retrieve this information flexibly to suit our goals. The semantic control network, comprising left inferior frontal gyrus (IFG) and posterior middle temporal gyrus (pMTG), is thought to orchestrate this flexible retrieval by modulating sensory inputs. However, interactions between semantic control and input regions are not sufficiently understood. Moreover, pMTGs well-formed structural connections to IFG and visual cortex suggest it as a candidate region to integrate control and input processes. We used magnetoencephalography to investigate oscillatory dynamics during semantic decisions to pairs of words, when participants (both sexes) did or did not know the type of semantic relation between them. IFG showed increases and decreases in oscillatory activity to prior task knowledge, while pMTG only showed positive task knowledge effects. Furthermore, IFG provided sustained feedback to pMTG when task goals were known, while in the absence of goals this feedback was delayed until receiving bottom-up input from the second word. This goal-dependent feedback coincided with an earlier onset of feedforward signalling from visual cortex to pMTG, indicating rapid retrieval of task-relevant features. This pattern supports a model of semantic cognition in which pMTG integrates top-down control from IFG with bottom-up input from visual cortex to activate task-relevant semantic representations. Our findings elucidate the separate roles of anterior and posterior components of the semantic control network and reveal the spectro-temporal cascade of interactions between semantic and visual regions that underlie our ability to flexibly adapt cognition to the current goals. Significance StatementUsing magnetoencephalography, we characterize the spectro-temporal dynamics that underlie our ability to flexibly adapt semantic cognition to the current context and goals. We find that semantic goals increase oscillatory activity in IFG and pMTG, and ultimately facilitate visual processing. Effective connectivity analyses reveal more sustained feedback from IFG to pMTG, and more rapid feedforward signalling from visual cortex to pMTG, resulting in rapid retrieval when semantic goals are known. Crucially, our findings suggest differential roles for the two semantic control regions: while IFG controls goal-dependent retrieval, pMTG integrates top-down information from IFG with bottom-up visual input.

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bioRxiv2024

Patterns of Ongoing Thought in the Real World and Their Link to Mental Health and Well-Being

The thoughts we experience in daily life have implications for our mental health and well-being. However, it is often difficult to measure thought patterns outside of laboratory conditions due to concerns about the voracity of measurements taken in daily life. To address this gap in the literature, our study set out to measure patterns of thought as they occur in daily life and assess the robustness of these measures and their associations with trait measurements of mental health and well-being. A sample of undergraduate participants completed multi-dimensional experience sampling surveys eight times per day for five days as they went around their normal lives. Principal component analysis reduced these data to identify the dimensions that explained the patterns of thought reported by our participants. We used linear modelling to map how these thought patterns related to the activities taking place at the time of the probe, highlighting good consistency within the sample, as well as substantial overlap with prior work. Multiple regression was used to examine associations between patterns of ongoing thought and aspects of mental health and well-being, highlighting a pattern of "Intrusive Distraction" that had a positive association with anxiety, and a negative association with social well-being. Notably, this thought pattern tended to be most prevalent in solo activities and was relatively suppressed when interacting with other people (either in person or virtually). Our study, therefore, highlights the use of multi-dimensional experience sampling as a tool to understand how ongoing thoughts in daily life impact on our mental health and well-being, and establishes the important role social connectedness plays in the etiology of intrusive thinking.

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bioRxiv2024

The spatial layout of antagonistic brain regions are explicable based on geometric principles

Brain activity emerges in a dynamic landscape of regional increases and decreases that span the cortex. Increases in activity during a cognitive task are often assumed to reflect the processing of task-relevant information, while reductions can be interpreted as suppression of irrelevant activity to facilitate task goals. Here, we explore the relationship between task-induced increases and decreases in activity from a geometric perspective. Using a technique known as kriging, developed in earth sciences, we examined whether the spatial organisation of brain regions showing positive activity could be predicted based on the spatial layout of regions showing activity decreases (and vice versa). Consistent with this hypothesis we established the spatial distribution of regions showing reductions in activity could predict (i) regions showing task-relevant increases in activity in both groups of humans and single individuals; (ii) patterns of neural activity captured by calcium imaging in mice; and, (iii) showed a high degree of generalisability across task contexts. Our analysis, therefore, establishes that antagonistic relationships between brain regions are topographically determined, a spatial analog for the well documented anti-correlation between brain systems over time. Significance StatementIt is well documented that brain activity changes in response to the demands of different situations, although what gives rise to the observed cortical activity patterns remains poorly understood. Using analytic tools from earth sciences, we examined whether the landscape of regional changes in activity emerge from a set of common topographical causes. Using only regions showing decreases in activity, we could predict the landscape of regions showing increases in activity using fMRI in humans and calcium imaging in mice. Our results suggest topographical principles determine the landscape of peaks and valleys in brain activity -- a spatial analog for the well documented anti-correlation between sets of brain regions over time.

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bioRxiv2024

The impact of heterogeneous spatial autocorrelation on comparisons of brain maps

It is increasingly common to statistically compare brain maps to assess how spatially similar they are. However, statistical inference can be challenging due to the presence of spatial autocorrelation. Therefore, random permutation approaches based on null models are widely used to address this concern. Here, we show how that the presence of heterogeneity in the spatial autocorrelation across brain maps impacts the validity of statistical inference in common approaches for spatially correlated maps. Furthermore, we illustrate how a Bayesian spatial regression approach can be applied to compare functional and structural cortical brain maps, yielding valid statistical inferences even in the presence of heterogeneity. Explicitly modelling spatial properties provides more valid inferences about whole brain spatial maps allowing a wider and more sophisticated range of neurobiological questions to be answered about the relationship between brain maps than are possible with current approaches.

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bioRxiv2024

Personality traits vary in their association with brain activity across situations.

Human cognition supports complex behaviour across a range of situations, and traits (such as personality) influence how we react in these different contexts. Although viewing traits as situationally grounded is common in social sciences it is often overlooked in neuroscience. Often studies focus on linking brain activity to trait descriptions of humans examine brain-trait associations in a single task, or, under passive conditions like wakeful rest. These studies, often referred to as brain wide association studies (BWAS) have recently become the subject of controversy because results are often unreliable even with large sample sizes. Although there are important statistical reasons why BWAS yield inconsistent results, we hypothesised that results are inconsistent because the situation in which brain activity is measured will impact the power in detecting a reliable link to a specific trait. To examine this possibility, we performed a state-space analysis in which tasks from the Human Connectome Project (HCP) were organized into a low-dimensional space based on how they activated different large-scale neural systems. We examined how individuals observed brain activity across these different contexts related to their personality. Our analysis found that for multiple personality traits (including Agreeableness, Openness to Experience and Conscientiousness) stronger associations with brain activity emerge in some tasks than others. These data establish that for specific personality traits there are situations in which reliable associations with brain activity can be identified with greater accuracy, highlighting the importance of context-bound views of understanding how brain activity links to trait variation in human behaviour. Significance statementAs a species humans act efficiently in many contexts, however, as individuals our personality makes us more specialised in some situations than others. This "if-then" view of personality is widely accepted in the social sciences but is often overlooked in neuroscience. Here we show adopting a situationally bound view of human traits provides more meaningful descriptions of a brain-trait associations than are possible in traditional brain wide association studies (BWAS) that measure brain activity in a single situation. Our results demonstrate multiple personality traits (including Agreeableness, Openness to Experience and Conscientiousness) show stronger associations with brain activity in some tasks than others, explaining why studies focusing on changes in brain activity at rest can lead to weak or contradictory results.

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bioRxiv2024

Functional divergence between the two cerebral hemispheres contributes to human fluid intelligence

Hemispheric lateralization is linked to potential cognitive advantages. It is considered a driving force behind the generation of human intelligence. However, establishing quantitative links between the degree of lateralization and intelligence in humans remains elusive. In this study, we propose a framework that utilizes the functional aligned multidimensional representation space derived from hemispheric functional gradients to compute between-hemisphere distances within this space. Applying this framework to a large cohort (N=777 from the Human Connectome Project), we identified high functional divergence across the two hemispheres within the frontoparietal control network. We found that both global divergence between the cerebral hemispheres and regional divergence within the multiple demand network were positively associated with fluid composite score and partially mediated the influence of brain size on individual differences in fluid intelligence. Together, these findings illuminate the profound significance of brain lateralization as a fundamental organizational principle of the human brain, providing direct evidence that hemispheric lateralization supports human fluid intelligence.

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bioRxiv2024

Macroscale brain states support the control of semantic cognition

Understanding how the human brain adapts to varying cognitive demands is crucial in neuroscience. Here, we examined how networks involved in controlled semantic retrieval reconfigure themselves to generate neurocognitive states appropriate to different task contexts. We parametrically varied the demands of two semantic tasks - global association and feature matching judgments - and contrasted these effects of cognitive control with those of non-semantic tasks. We then characterized these effects on the cortical surface and within a whole-brain state space, anchored by the top three dimensions of intrinsic connectivity. Our results revealed that demanding semantic association tasks elicited more activation in the anterior regions of the prefrontal and temporal cortex. In contrast, difficult semantic feature matching tasks produced more posterior activation, aligning closely with regions engaged during multiple demanding non-semantic tasks. In both semantic feature matching and non-semantic contexts, the difficulty effects were situated towards the controlled end of a dimension capturing functional separation between cognitive control and default mode regions. Conversely, in semantic association tasks, the difficulty effects elicited similar responses across both cognitive control and default mode networks. Furthermore, controlled association and non-semantic control were located towards the heteromodal end of a heteromodal- unimodal dimension, while semantic feature matching involved a brain state that was more visual and unimodal. These findings demonstrate that a variety of brain states underpin controlled cognition. Specifically, cognitive control regions interact with heteromodal semantic knowledge system to identify contextually relevant conceptual overlaps (e.g., associating DOG with BEACH), and separate from heteromodal memory regions for modality-specific conceptual overlaps (e.g., connecting DALMATIAN with BLACK AND WHITE).

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bioRxiv2024

The dimensionality of neural coding for cognitive control is gradually transformed within the lateral prefrontal cortex

Implementing cognitive control relies on neural representations that are inherently high-dimensional and distribute across multiple subregions in the prefrontal cortex (PFC). Traditional approaches tackle prefrontal representations by reducing them into a unidimensional measure (univariate amplitude) or using them to distinguish a limited number of alternatives (pattern classification). By contrast, representational similarity analysis (RSA) enables flexibly formulating various hypotheses about informational contents underlying the neural codes, explicitly comparing hypotheses, and examining the representational alignment between brain regions. Here, we used a multifaceted paradigm wherein the difficulty of cognitive control was manipulated separately for five cognitive tasks. We used RSA to unveil representational contents, measure the representational alignment between regions, and quantify representational generality vs. specificity. We found a graded transition in the lateral PFC: The dorsocaudal PFC was tuned to the information about behavioural effort, preferentially connected with the parietal cortex, and representationally generalisable across domains. The ventrorostral PFC was tuned to the abstract structure of tasks, preferentially connected with the temporal cortex, and representationally specific. The middle PFC (interposed between dorsocaudal and ventrorostral PFC) was tuned to individual task-sets, ranked in the middle in terms of connectivity and generalisability. Furthermore, whether a region was dimensionally rich or thin co-varied with its functional profile: Low dimensionality (only gist) in the dorsocaudal PFC dovetailed with better generality, whereas high dimensionality (gist plus details) in the ventrorostral PFC corresponded with better ability to encode subtleties. Our findings, collectively, demonstrate how cognitive control is decomposed into distinct facets that transition steadily along prefrontal subregions. SignificanceCognitive control is known to be a high-dimensional construct, implemented along the dorsocaudal-ventrorostral subregions of PFC. However, it remains unclear how prefrontal representations could be dissected in a multivariate fashion to reveal (1) what information is encoded in each subregion, (2) whether information systematically transforms across contiguous PFC subregions as a gradient, (3) how this transformation is affected by functional connectivity. Here we shed light on these issues by using RSA to decode informational composition in the PFC while using participant-specific localisers to facilitate individually-tailored precision. Our findings elucidate the functional organisation of PFC by revealing how a trade-off between dimensionality and generalisability unfolds in the PFC and highlight the strength of RSA in deciphering the coding of cognitive control.

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bioRxiv2023

Visual to default network pathways: A double dissociation between semantic and spatial cognition

Processing pathways between sensory and default mode network (DMN) regions support recognition, navigation, and memory but their organisation is not well understood. We show that functional subdivisions of visual cortex and DMN sit at opposing ends of parallel streams of information processing that support visually-mediated semantic and spatial cognition, providing convergent evidence from univariate and multivariate task responses, intrinsic functional and structural connectivity. Participants learned virtual environments consisting of buildings populated with objects, drawn from either a single semantic category or multiple categories. Later, they made semantic and spatial context decisions about these objects and buildings during functional magnetic resonance imaging. A lateral ventral occipital to frontotemporal DMN pathway was primarily engaged by semantic judgements, while a medial visual to medial temporal DMN pathway supported spatial context judgements. These pathways had distinctive locations in functional connectivity space: the semantic pathway was both further from unimodal systems and more balanced between visual and auditory-motor regions compared with the spatial pathway. When semantic and spatial context information could be integrated (in buildings containing objects from a single category), regions at the intersection of these pathways responded, suggesting that parallel processing streams interact at multiple levels of the cortical hierarchy to produce coherent memory-guided cognition.

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bioRxiv2023

Distinctive and complementary roles of default mode network subsystems in semantic cognition

The default mode network (DMN) typically deactivates to external tasks, yet supports semantic cognition. It comprises medial temporal (MT), core, and fronto-temporal (FT) subsystems, but its functional organisation is unclear: the requirement for perceptual coupling versus decoupling, input modality (visual/verbal), type of information (social/spatial) and control demands all potentially affect its recruitment. We examined the effect of these factors on activation and deactivation of DMN subsystems during semantic cognition, across four task-based functional magnetic resonance imaging (fMRI) datasets, and localised these responses in whole-brain state space defined by gradients of intrinsic connectivity. FT showed activation consistent with a central role across domains, tasks and modalities, although it was most responsive to abstract, verbal tasks; this subsystem uniquely showed more tuned states characterised by increases in both activation and deactivation when semantic retrieval demands were higher. MT also activated to both perceptually-coupled (scenes) and decoupled (autobiographical memory) tasks, and showed stronger responses to picture associations, consistent with a role in scene construction. Core DMN consistently showed deactivation, especially to externally-oriented tasks. These diverse contributions of DMN subsystems to semantic cognition were related to their location on intrinsic connectivity gradients: activation was closer to sensory-motor cortex than deactivation, particularly for FT and MT, while activation for core DMN was distant from both visual cortex and cognitive control. These results reveal distinctive yet complementary DMN responses: MT and FT support different memory-based representations that are accessed externally and internally, while deactivation in core DMN is associated with demanding, external semantic tasks. Significance StatementWe delineate the functional organisation of DMN in semantic cognition, examining effects of perceptual coupling versus decoupling, input modality (visual/verbal), domain (social/spatial) and control demands across DMN subsystems in four fMRI datasets. These subsystems played complementary roles in semantic cognition related to their locations on gradients of intrinsic connectivity. Medial temporal and frontotemporal subsystems supported visuospatial and abstract conceptual information respectively, across both internally and externally-focussed tasks, while deactivation in core DMN was associated with focussed and externally-oriented semantic states. We conclude that both content and process are relevant to the functional architecture of DMN in semantic cognition.

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bioRxiv2023

Default mode network shows distinct emotional and contextual responses yet common effects of retrieval demands across tasks

The default mode network (DMN) lies towards the heteromodal end of the principal gradient of intrinsic connectivity, maximally separated from sensory-motor cortex. It supports memory-based cognition, including the capacity to retrieve conceptual and evaluative information from sensory inputs, and to generate meaningful states internally; however, the functional organisation of DMN that can support these distinct modes of retrieval remains unclear. We used fMRI to examine whether activation within subsystems of DMN differed as a function of retrieval demands, or the type of information to be retrieved, or both. In a picture association task, participants retrieved two types of semantic features about contexts and emotions: in the generate phase, these associations were retrieved from a novel picture, while in a switch phase, participants retrieved a new association for the same image. Semantic context and emotion trials were associated with dissociable DMN subnetworks, indicating that a key dimension of DMN organisation relates to the type of information being accessed. The fronto-temporal and medial temporal DMN showed a preference for emotional and contextual associations, respectively. Relative to the generate phase, the switch phase recruited clusters closer to the heteromodal apex of the principal gradient - a cortical hierarchy separating unimodal and heteromodal regions. There were no differences in this effect between association types. Instead, memory switching was associated with a distinct subnetwork associated with controlled internal cognition. These findings delineate distinct patterns of DMN recruitment for different kinds of associations yet common responses across tasks that reflect retrieval demands. Key pointsO_LIRetrieval of contextual and emotional features relies on distinct default mode subnetworks. C_LIO_LINovelty of visual input has an equivalent effect across default mode subnetworks. C_LIO_LISecondary associations retrieved from re-presented pictures activate heteromodal end of the principal gradient. C_LI

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bioRxiv2023

Differential reorganization of episodic and semantic memory systems in epilepsy-related mesiotemporal pathology

Declarative memory encompasses episodic and semantic divisions. Episodic memory captures singular events with specific spatiotemporal relationships, while semantic memory houses context-independent knowledge. Behavioural and functional neuroimaging studies have revealed common and distinct neural substrates of both memory systems, implicating mesiotemporal lobe (MTL) regions such as the hippocampus and distributed neocortices. Here, we explored declarative memory system reorganization in patients with unilateral temporal lobe epilepsy (TLE), as a human disease model to test the impact of variable degrees of MTL pathology on memory function. Our cohort included 31 patients with TLE as well as 60 age and sex-matched healthy controls and all participants underwent episodic and semantic retrieval tasks during a multimodal MRI session. The functional MRI tasks were closely matched in terms of stimuli and trial design. Capitalizing on non-linear connectome gradient mapping techniques, we derived task-based functional topographies during episodic and semantic memory states, both in the MTL and in neocortical networks. Comparing neocortical and hippocampal functional gradients between TLE patients and healthy controls, we observed a marked topographic reorganization of both neocortical and MTL systems during episodic memory states. In the neocortex, alterations were characterized by reduced functional differentiation in patients in lateral temporal and midline parietal cortices in both hemispheres. In the MTL, on the other hand, patients presented with a more marked functional differentiation of posterior and anterior hippocampal segments ipsilateral to the seizure focus and pathological core, indicating perturbed intrahippocampal connectivity. Semantic memory reorganization was also found in bilateral lateral temporal and ipsilateral angular regions, while hippocampal functional topographies were unaffected. Leveraging MRI proxies of MTL pathology, we furthermore observed alterations in hippocampal microstructure and morphology are associated with TLE-related functional reorganization during episodic memory. Moreover, correlation analysis and statistical mediation models revealed that these functional alterations contributed to behavioural deficits in episodic, but again not semantic memory in patients. Altogether, our findings suggest that semantic processes rely on distributed neocortical networks, while episodic processes are supported by a network involving both the hippocampus and neocortex. Alterations of such networks can provide a compact signature of state-dependent reorganization in conditions associated with MTL damage, such as TLE.

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bioRxiv2023

The brain's topographical organization shapes dynamic interaction patterns to support flexible behavior

Understanding how human cognition flexibly supports distinct forms of behavior is a key goal of neuroscience. Adaptive behavior relies on context-specific rules that vary across situations, as well as on stable knowledge gained from experience. However, the mechanisms that allow these influences to be appropriately balanced remain elusive. Here, we show that this cognitive flexibility is partly supported by the topographical organization of the cortex. The frontoparietal control network (FPCN) is located between regions implicated in top-down attention and memory-guided cognition. We hypothesized that the FPCN is topographically divided into discrete systems that support these distinct forms of behavior. These FPCN subsystems exhibit multiple anatomical and functional similarities to their neighboring systems (the dorsal attention network and default mode network respectively). This topographic architecture is also mirrored in the functional patterns that emerge in different situations: the FPCN subnetworks act as a unified system when long-term memory can support behavior, but they segregate into discrete units when working memory, rather than long term memory, is necessary for behavioral control. In this way, the topographic organization of brain function provides crucial insights into how the human cortex supports flexible behavior.

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bioRxiv2023

Graded functional changes in ATL reflect both semantic content and process.

Recent work has focussed on how patterns of functional change within the temporal lobe relate to whole-brain dimensions of intrinsic connectivity variation (Margulies et al., 2016). We examined two such connectivity gradients reflecting the separation of (i) unimodal versus heteromodal and (ii) visual versus auditory-motor cortex, examining visually presented verbal associative and feature judgments, plus picture-based context and emotion generation. Functional responses along the first dimension sometimes showed graded change between modality-tuned and heteromodal cortex (in the verbal matching task), and other times showed sharp functional transitions, with deactivation at the extremes and activation in the middle of this gradient (internal generation). The second gradient revealed more visual than auditory-motor activation, regardless of content (associative, feature, context, emotion) or task process (matching/generation). We also uncovered subtle differences across each gradient for content type, which predominantly manifested as differences in relative magnitude of activation or deactivation.

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bioRxiv2023

Individual word representations dissociate from linguistic context along a cortical unimodal to heteromodal gradient

Language comprehension involves multiple hierarchical processing stages across time, space, and levels of representation. When processing a word, the sensory input is transformed into increasingly abstract representations that need to be integrated with the linguistic context. Thus, language comprehension involves both input-driven as well as context-dependent processes. While neuroimaging research has traditionally focused on mapping individual brain regions to the distinct underlying processes, recent studies indicate that whole-brain distributed patterns of cortical activation might be highly relevant for cognitive functions, including language. One such pattern, based on resting-state connectivity, is the principal cortical gradient, which dissociates sensory from heteromodal brain regions. The present study investigated the extent to which this gradient provides an organizational principle underlying language function, using a multimodal neuroimaging dataset of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) recordings from 102 participants during sentence reading. We found that the brain response to individual representations of a word (word length, orthographic distance and word frequency), which reflect visual, orthographic, and lexical properties, gradually increases towards the sensory end of the gradient. Although these properties showed opposite effect directions in fMRI and MEG, their association with the sensory end of the gradient was consistent across both neuroimaging modalities. In contrast, MEG revealed that properties reflecting a words relation to its linguistic context (semantic similarity and position within the sentence) involve the heteromodal end of the gradient to a stronger extent. This dissociation between individual word and contextual properties was stable across earlier and later time windows during word presentation, indicating interactive processing of word representations and linguistic context at opposing ends of the principal gradient. To conclude, our findings indicate that the principal gradient underlies the organization of a range of linguistic representations while supporting a gradual distinction between context-independent and context-dependent representations. Furthermore, the gradient reveals convergent patterns across neuroimaging modalities (similar location along the gradient) in the presence of divergent responses (opposite effect directions).

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bioRxiv2023

Variation in spatial dependencies across the cortical mantle discriminates the functional behaviour of primary and association cortex

Recent theories of cortical organisation maintain that important features of brain function emerge through the spatial arrangement of regions of cortex. For example, areas of association cortex are located in regions of cortex furthest from sensory and motor cortex. Association cortex is also interdigitated since adjacent regions can have relatively different patterns of functional connectivity. It is assumed that topographic properties such as distance between cortical regions constrain their functions. For example, large distances between association and sensory and motor systems may enable these areas of cortex to maintain differentiable neural patterns, while an interdigitated organisation may enable association cortex to contain many functional systems in a relatively compact space. We currently lack a formal understanding of how spatial organisation impacts brain function, limiting the ability to leverage cortical topography to facilitate better interpretations of a regions function. Here we use variograms, a quantification of spatial autocorrelation, to develop a cortex-wide profile of how functional similarity changes as a function of the distance between regions. We establish that function changes gradually within sensory and motor cortex as the distance between regions increases, while in association cortex function changes rapidly over shorter distances. Subsequent analysis suggests these differential classes of spatial dependency are related to variation in intracortical myelin between sensory motor and association cortex. Our study suggests primary and association cortex are differentiated by the degree to which function varies over space, emphasising the need to formally account for spatial properties when estimating a systems contribution to cognition and behaviour. Significance statementThe spatial arrangements of regions in the human brain are hypothesised to underpin important features of a brain regions function. Currently, however, we lack a formal understanding of how topography shapes brain function, limiting our ability to leverage topographical perspectives to inform better theories of brain function. Here we use a formal mathematical approach to establish that in regions of association cortex function varies across the cortex more rapidly than in sensory and motor cortex, a phenomenon linked to levels of intracortical myelin. This result highlights how topographical features distinguish between cortical regions with different functional profiles and provides a formal account of how spatial differences support different features of brain function.

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