Biology subjects

Haak, K. V.

Publications and source records attributed to Haak, K. V..

13 recordsLinked to original sources

bioRxiv2026

Population-wide variation in connectopic organization of cerebral language hubs

The uniquely human capacity for language is supported by a distributed brain network with cerebral cortical hubs in the left inferior frontal gyrus (LIFG) and left superior temporal sulcus (LSTS). Individual differences in the graded spatial organization of function across these regions may provide sensitive phenotypes for behavioural and genetic association analyses, to better understand the biological underpinnings of language. In 41,437 UK Biobank participants we applied connectopic mapping to the LIFG and LSTS. This approach maps spatial changes across a region in terms of connectivity with the rest of the brain, based on resting state functional imaging. On average, we found that Brodmann Area (BA) 44, BA 45 and the posterior LSTS were strongly connected to the superior and inferior parietal lobe and the dorsal attention and frontoparietal networks, whereas BA 47 and the medial LSTS were strongly connected to superior frontal areas BA 8B and BA 9, and the default mode network more broadly. However, there was extensive population-wide variation in these graded connectopic patterns, which significantly mediated the effects of polygenic scores for reading ability and educational attainment on performance on a vocabulary task. Furthermore we identified 3 genomic loci displaying multivariate association patterns with these connectopic maps, one of which coincides with a long non-coding RNA, LINC01165, with potential relevance in human evolution. Overall, connectopic mapping produced fewer significant genetic association findings and lower heritability (range from 0.3 to 9.4%) than previous parcel-based approaches for mapping language network connectivity. These observations suggest higher genetic complexity and/or prominent roles for environmental or random developmental effects on these connectopic maps.

neuroscience↗

bioRxiv2025

Integrating brain structure and function for the neurobiology and genetics of language

Brain structure and function have largely been studied separately in relation to the neurobiology and genetics of language. Here we used linked independent component analysis to integrate language network functional connectivity with brain volumetric and white matter structure in 32,677 UK Biobank participants, followed by analysis of behavioural, neurobiological and genetic correlates of the derived multimodal structure-function imaging components. Stronger functional connectivity between brain language areas was associated with increased volume of parts of the cerebellum and motor cortex, together with smaller ventricles and sensory parietal and occipital areas. The brain structure-function language components mediated an association between vocabulary level and polygenic scores for reading ability. We report 18 genomic loci associated with brain structure-function language components. Single-nucleotide polymorphism (SNP)-based heritability estimates for these components were 23-30%, and there was significant enrichment of heritability in primate-conserved genomic loci and fetal brain human-gained enhancer elements. This study revealed that structural correlates of functional language network connectivity extend well beyond previously defined language areas of the brain, and highlights the value of multimodal brain phenotyping for human neurogenetic discovery.

neuroscience↗

bioRxiv2024

A shifting role of thalamocortical connectivity in the emergence of large-scale functional brain organization across early lifespan development

While cortical patterning has been a perennial research topic in neuroscience, the mechanism for its consequence, namely functional specialization at the macro scale, remains an open question in the human brain. Here, we focused on age-dependent changes of resting-state thalamocortical connectivity to investigate its role in the emergence of large-scale functional networks across infancy, childhood and young adulthood. We found that the thalamocortical connectivity during infancy reflects an early differentiation of sensorimotor networks and genetically-influenced axonal projection. This initial role of the thalamus, however, seems to change during childhood, by establishing connectivity with the salience network and decoupling externally- and internally-oriented functional processes. Developmental simulation and perturbation analyses corroborated these findings, demonstrating the highest contribution of thalamic connectivity, especially in the later age of youth, in the formation of key characteristics of the mature brain, such as functional gradient and cortical hierarchy. Our study highlights a developmentally shifting role of the thalamus in orchestrating complex brain organization and its potential implications for developmental conditions characterized by compromised internal and external processing.

neuroscience↗

bioRxiv2023

The effect of long-term sleep disruption on the brain - looking beyond amyloid

The mechanism underlying the possible causal association between long-term sleep disruption and Alzheimers disease remains unclear [1]. A hypothesised pathway through increased brain amyloid load was not confirmed in previous work in our cohort of maritime pilots with long-term work-related sleep disruption [2]. Here, using functional MRI, T2-FLAIR and Arterial Spin Labeling MRI scans, we explored alternative neuroimaging biomarkers related to both sleep disruption and AD: resting-state network co-activation and between-network connectivity of the default mode network (DMN), salience network (SAL) and frontoparietal network (FPN), vascular damage and cerebral blood flow (CBF). We acquired data of 16 maritime pilots (56 {+/-} 2.3 years old) with work-related long-term sleep disruption (23 {+/-} 4.8 working years) and 16 healthy controls (59 {+/-} 3.3 years old), with normal sleep patterns (Pittsburgh Sleep Quality Index [≤] 5). Maritime pilots did not show altered co-activation in either the DMN, FPN, or SAL and no differences in between-network connectivity. We did not detect increased markers of vascular damage in maritime pilots, and additionally, maritime pilots did not show altered CBF-patterns compared to healthy controls. In summary, maritime pilots with long-term sleep disruption did not show neuroimaging markers indicative of preclinical AD compared to healthy controls. These findings do not resemble those of short-term sleep deprivation studies. This could be due to resiliency to sleep disruption or selection bias, as participants have already been exposed to and were able to deal with sleep disruption for multiple years, or to compensatory mechanisms [3]. This suggests the relationship between sleep disruption and AD is not as strong as previously implied in studies on short-term sleep deprivation, which would be beneficial for all shift workers suffering from work-related sleep disruptions.

neuroscience↗

bioRxiv2022

Association of Striatal Connectivity Gradients to Functional Domains Across Psychiatric Disorders

ObjectiveTo uncover transdiagnostic domains of functioning across stress- and neurodevelopmental disorders, and to map these on to the topographic functional organization of cortico-striatal circuitry. MethodsIn a clinical sample (n=186) of subjects with high rates of comorbidity of major depressive disorder, anxiety disorder, attention-deficit/hyperactivity disorder and/or autism spectrum disorder, we use exploratory factor analysis on a wide range of clinical questionnaires to identify consistent functional domains of symptomatology across disorders, then replicate these functional domains in an independent dataset (n=188). Then, we use canonical correlation analysis link these functional domains to the topographic organization of the striatum as represented by connectopic maps. ResultsWe reveal four functional domains that transcend current diagnostic categories relating to negative valence, cognition, social functioning and inhibition/arousal. These functional domains are replicated in an independent sample and are associated with the fine-grained topographical organization of functional connectivity in the striatum (out of sample r=0.20, p=0.026), a central hub in motor, cognitive, affective and reward-related brain circuits. Conclusions and relevanceFunctional domains across stress- and neurodevelopmental disorders are associated with the functional organization of the striatum. We propose that investigating psychiatric symptoms across disorders is a promising path to linking them to underlying biology, and can help bridge the gap between neuroscience and clinical psychiatry.

neuroscience↗

bioRxiv2022

Fine-grained topographic organization within somatosensory cortex during resting-state and emotional face-matching task and its association with ASD traits

BACKGROUNDSensory atypicalities are particularly common in autism spectrum disorders (ASD). Nevertheless, our knowledge about the divergence of the underlying somatosensory region and its association with ASD phenotype features is limited. METHODSWe applied a data-driven approach to map the fine-grained variations in functional connectivity of the primary somatosensory cortex (S1) to the rest of the brain in 240 autistic and 164 neurotypical individuals from the EU-AIMS LEAP dataset, aged between 7 and 30. We estimated the S1 connection topography ( connectopy) during rest and during the emotional face-matching (Hariri) task, an established measure of emotion reactivity, and accessed its association with a set of clinical and behavioral variables. RESULTSWe demonstrated that the S1 connectopy is organized along a dorsoventral axis, mapping onto the somatotopic organization of S1. We found that its spatial characteristics were linked to the individuals adaptive functioning skills, as measured by the Vineland Adaptive Behavior Scales, across the whole sample. Higher functional differentiation characterized the S1 connectopies of individuals with higher daily life adaptive skills. Notably, we detected significant differences between rest and the Hariri task in the S1 connectopies, as well as their projection maps onto the rest of the brain suggesting a task-modulating effect on S1 due to emotion processing. CONCLUSIONSVariation of daily life adaptive skills appears to be reflected in the brains mesoscale neural circuitry, as shown by the S1 connectivity profile, which is also differentially modulated during rest and emotional processing.

neuroscience↗

bioRxiv2020

Assessing uncertainty in connective field estimations from resting state fMRI activity

Connective Field (CF) modeling estimates the local spatial integration between signals in distinct cortical visual field areas. As we have shown previously using 7T data, CF can reveal the visuotopic organization of visual cortical areas even when applied to BOLD activity recorded in the absence of external stimulation. This indicates that CF modeling can be used to evaluate cortical processing in participants in which the visual input may be compromised. Furthermore, by using Bayesian CF modelling it is possible to estimate the co-variability of the parameter estimates and therefore, apply CF modeling to single cases. However, no previous studies evaluated the (Bayesian) CF model using 3T resting-state fMRI data, although this is important since 3T scanners are much more abundant and more often used in clinical research than 7T ones. In this study, we investigate whether it is possible to obtain meaningful CF estimates from 3T resting state (RS) fMRI data. To do so, we applied the standard and Bayesian CF modeling approaches on two RS scans interleaved by the acquisition of visual stimulation in 12 healthy participants. Our results show that both approaches reveal good agreement between RS- and visual field (VF)-based maps. Moreover, the 3T observations were similar to those previously reported at 7T. In addition, to quantify the uncertainty associated with each estimate in both RS and VF data, we applied our Bayesian CF framework to provide the underlying marginal distribution of the CF parameters. Finally, we show how an additional CF parameter, beta, can be used as a data-driven threshold on the RS data to further improve CF estimates. We conclude that Bayesian CF modeling can characterize local functional connectivity between visual cortical areas from RS data at 3T. In particular, we expect the ability to assess parameter uncertainty in individual participants will be important for future clinical studies. HighlightsO_LILocal functional connectivity between visual cortical areas can be estimated from RS-fMRI data at 3T using both standard CF and Bayesian CF modelling. C_LIO_LIBayesian CF modelling quantifies the model uncertainty associated with each CF parameter on RS and VF data, important in particular for future studies on clinical populations. C_LIO_LI3T observations were qualitatively similar to those previously reported at 7T. C_LI

neuroscience↗

bioRxiv2020

Bayesian Connective Field Modeling: a Markov Chain Monte Carlo approach.

The majority of neurons in the human brain process signals from neurons elsewhere in the brain. Connective Field (CF) modeling is a biologically-grounded method to describe this essential aspect of the brains circuitry. It allows characterizing the response of a population of neurons in terms of the activity in another part of the brain. CF modeling translates the concept of the receptive field (RF) into the domain of connectivity by assessing the spatial dependency between signals in distinct cortical visual field areas. Standard CF model estimation has some intrinsic limitations in that it cannot estimate the uncertainty associated with each of its parameters. Obtaining the uncertainty will allow identification of model biases, e.g. related to an over- or under-fitting or a co-dependence of parameters, thereby improving the CF prediction. To enable this, here we present a Bayesian framework for the CF model. Using a Markov Chain Monte Carlo (MCMC) approach, we estimate the underlying posterior distribution of the CF parameters and consequently, quantify the uncertainty associated with each estimate. We applied the method and its new Bayesian features to characterize the cortical circuitry of the early human visual cortex of 12 healthy participants that were assessed using 3T fMRI. In addition, we show how the MCMC approach enables the use of effect size (beta) as a data-driven parameter to retain relevant voxels for further analysis. Finally, we demonstrate how our new method can be used to compare different CF models. Our results show that single Gaussian models are favoured over differences of Gaussians (i.e. center-surround) models, suggesting that the cortico-cortical connections of the early visual system do not possess center-surround organisation. We conclude that our new Bayesian CF framework provides a comprehensive tool to improve our fundamental understanding of the human cortical circuitry in health and disease. Highlights{square} We present and validate a Bayesian CF framework based on a MCMC approach. {square}The MCMC CF approach quantifies the model uncertainty associated with each CF parameter. {square}We show how to use effect size beta as a data-driven threshold to retain relevant voxels. {square}The cortical connective fields of the human early visual system are best described by a single, circular symmetric, Gaussian.

neuroscience↗

bioRxiv2020

Overlapping connectivity gradients in the anterior temporal lobe underlie semantic cognition

Convergent evidence from neuroimaging, computational, and clinical research has shown that the anterior temporal lobe (ATL) is critically involved in two key aspects of semantic cognition: the representation of semantic knowledge, and the executive regulation of this knowledge. Both are necessary for integrating features to understand concepts, and to integrate concepts to understand discourse. Here, we tested the hypothesis that these differential aspects of integration map onto different patterns of ATL connectivity. Specifically, we hypothesized that there are two overlapping modes of functional connectivity of the ATL that each predict distinct aspects of semantic cognition on an individual level. We used a novel analytical approach (connectopic mapping) to identify the first two dominant modes connection topographies (i.e. maps of spatially varying connectivity) in the ATL in 766 participants (Human Connectome Project), and summarized these into 16 parameters that reflect inter-individual differences in their functional organization. If these connection topographies reflect the ATLs functional multiplicity, then we would expect to find a dissociation where one mode (but not the other) correlates with cross-modal matching of verbal and visual information (picture vocabulary naming), and the other (but not the former) correlates with how quickly and accurately relevant semantic information is retrieved (story comprehension). Our analysis revealed a gradient of spatially varying connectivity along the inferior-superior axis, and secondly, an anterior to posterior gradient. Multiple regression analyses revealed a double dissociation such that individual differences in the inferior-superior gradient are predictive of differences in story comprehension, whereas the anterior-posterior gradient maps onto differences in picture vocabulary naming, but not vice versa. These findings indicate that overlapping gradients of functional connectivity in the ATL are related to differential behaviors, which is important for understanding how its functional organization underlies its multiple functions.

neuroscience↗

bioRxiv2020

Functional Connectivity of the Precuneus Reflects Effectiveness of Visual Restitution Training in Chronic Hemianopia

Visual field defects in chronic hemianopia can improve through visual restitution training, yet not all patients benefit equally from this long and exhaustive process. Here, we asked if resting-state functional connectivity prior to visual restitution could predict training success. In two training sessions of eight weeks each, 20 patients with chronic hemianopia performed a visual discrimination task by directing spatial attention towards stimuli presented in either hemifield, while suppressing eye movements. We examined two effects: a sensitivity change in the attended (trained) minus the unattended (control) hemifield (i.e., a training-specific improvement), and an overall improvement (i.e., a total change in sensitivity after both sessions). We then identified five visual resting-state networks and evaluated their functional connectivity in relation to both training effects. We found that the functional connectivity strength between the anterior Precuneus and the Occipital Pole Network was positively related to the attention modulated (i.e., training-specific) improvement. No such relationship was found for the overall improvement or for the other visual networks of interest. Our finding suggests that the anterior Precuneus plays a role in training-induced visual field improvements. The resting-state functional connectivity between the anterior Precuneus and the Occipital Pole Network may thus serve as an imaging-based biomarker that quantifies a patients potential capacity to direct spatial attention. This may help to identify hemianopia patients that are most likely to benefit from visual restitution training.

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bioRxiv2019

Plasticity versus stability across the human cortical visual connectome

Whether and how the balance between plasticity and stability varies across the brain is an important open question. Within a processing hierarchy, it is thought that plasticity is increased at higher levels of cortical processing, but direct quantitative comparisons between low- and high-level plasticity have not been made so far. Here, we addressed this issue for the human cortical visual system. By quantifying plasticity as the complement of the heritability of functional connectivity, we demonstrate a non-monotonic relationship between plasticity and hierarchical level, such that plasticity decreases from early to mid-level cortex, and then increases further of the visual hierarchy. This non-monotonic relationship argues against recent theory that the balance between plasticity and stability is governed by the costs of the \"coding-catastrophe\", and can be explained by a concurrent decline of short-term adaptation and rise of long-term plasticity up the visual processing hierarchy.

neuroscience↗

bioRxiv2018

The functional organisation of the hippocampus along its long axis is gradual and predicts recollection

Understanding the functional organisation of the hippocampus is crucial for understanding its role in cognition and disorders in which it is implicated. Different views have been proposed of how function is distributed along its long axis: one view suggests segregation, whereas the alternative view postulates a more gradual organisation. Here, we applied a novel connectopic mapping data-analysis approach to the resting-state fMRI data of participants of the Human Connectome Project, and demonstrate that the functional organisation of the hippocampal longitudinal axis is gradual rather than segregated into parcels. In addition, we show that inter-individual variations in this gradual organisation predicts variations in recollection memory better than a characterisation based on parcellation. These results present an important step forward in understanding the functional organisation of the human hippocampus and have important implications for translating between rodent and human research.

neuroscience↗

bioRxiv2017

Functional corticostriatal connection topographies predict goal directed behaviour in humans

Anatomical tracing studies in non-human primates have suggested that corticostriatal connectivity is topographically organized: nearby locations in striatum are connected with nearby locations in cortex. The topographic organization of corticostriatal connectivity is thought to underpin many goal-directed behaviours, but these topographies have not been completely characterised in humans and their relationship to uniquely human behaviours remains to be fully determined. Instead, the dominant approach employs parcellations that cannot model the continuous nature of the topography, nor accommodate overlapping cortical projections in the striatum. Here, we employ a different approach to studying human corticostriatal circuitry: we estimate smoothly-varying and spatially overlapping connection topographies from resting state fMRI. These correspond exceptionally well with and extend the topographies predicted from primate tracing studies. We show that striatal topography is preserved in regions not previously known to have topographic connections with the striatum and that many goal-directed behaviours can be mapped precisely onto individual variations in the spatial layout of striatal connectivity.

neuroscience↗