Biology subjects

Margulies, D.

Publications and source records attributed to Margulies, D..

At least 19 recordsLinked to original sources

bioRxiv2025

In vivo cartography of state-dependent signal flow hierarchy in the human cerebral cortex

Understanding the principle of information flow across distributed brain networks is of paramount importance in neuroscience. Here, we introduce a novel neuroimaging framework, leveraging integrated effective connectivity (iEC) and unconstrained signal flow mapping for data-driven discovery of the human cerebral functional hierarchy. Simulation and empirical validation demonstrated the high fidelity of iEC in recovering connectome directionality and its potential relationship with histologically defined feedforward and feedback pathways. Notably, the iEC-derived hierarchy revealed a monotonically increasing level along the axis where the sensorimotor, association, and paralimbic areas are sequentially ordered - a pattern supported by the Structural Model of laminar connectivity. This hierarchy was further demonstrated to flexibly reorganize across brain states: flattening during an externally oriented condition, evidenced by a reduced slope in the hierarchy, and steepening during an internally focused condition, reflecting heightened engagement of interoceptive regions. Our study highlights the unique role of macroscale directed functional connectivity in uncovering a biologically interpretable state-dependent signal flow hierarchy.

neuroscience↗

bioRxiv2025

A pharmacological modality to sequester homomeric proteins

Molecules that can perturb protein-protein interactions have an immense impact on chemical biology and therapeutics. However, such compounds typically rely on accessory proteins to function, such as E3 ligases in the case of targeted degradation, which may restrict their target and tissue scope or lead to resistance. Here we alleviate the need for accessory proteins with a novel pharmacological modality to knock-down protein function. Our strategy exploits protein symmetry as a selective vulnerability, and is widely applicable owing to the ubiquitous nature of homomeric proteins in cellular systems. We target homomeric proteins with PINCHs (Polymerization Inducing Chimeras) - bifunctional molecules composed of two linked ligands that act as bridges between homomers and trigger their supramolecular assembly into insoluble polymers. We design PINCHs that achieve efficient polymerization of three homomeric targets. In cells, we observed that a PINCH targeting Keap1 exhibited a longer duration of action compared to its monomeric inhibitor, and a PINCH targeting BCL6 displayed selective and improved B cell toxicity compared to its monomeric parent. Our results highlight PINCHs as a novel and general strategy to modulate and knock out protein function.

biochemistry↗

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.

neuroscience↗

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.

neuroscience↗

bioRxiv2024

Canonical neurodevelopmental trajectories of structural and functional manifolds

Organisational gradients refer to a continuous low-dimensional embedding of brain regions and can quantify core organisational principles of complex systems like the human brain. Mapping how these organisational principles are altered or refined across development and phenotypes is essential to understanding the relationship between brain and behaviour. Taking a developmental approach and leveraging longitudinal and cross-sectional data from two multi-modal neuroimaging datasets, spanning the full neurotypical-neurodivergent continuum, we charted the organisational variability of structural (610 participants, N = 390 with one observation, N = 163 with two observations, and N = 57 with three) and functional (512 participants, N = 340 with one observation, N = 128 with two observations, and N = 44 with three). Across datasets, despite differing phenotypes, we observe highly similar structural and functional gradients. These gradients, or organisational principles, are highly stable across development, with the exact same ordering across early childhood into mid-adolescence. However, there is substantial developmental change in the strength of embedding within those gradients: by modelling developmental trajectories as non-linear splines, we show that structural and functional gradients exhibit sensitive periods and are refined across development. Specifically, structural gradients gradually contract in low-dimensional space as networks become more integrated, whilst the functional manifold expands, indexing functional specialisation. The coupling of these structural and functional gradients follows a unimodal-association axis and varies across individuals, with developmental effects concentrated in the more plastic higher-order networks. Importantly, these developmental effects on coupling, in these higher-order networks, are attenuated in the neurodivergent sample. Finally, we mapped structure-function coupling onto dimensions of psychopathology and cognition and demonstrate that dimensions of cognition, such as working memory, are robust predictors of coupling. In summary, across clinical and community samples, we demonstrate consistent principles of structural and functional brain organisation, with progressive structural integration and functional segregation. These gradients are established early in life, refined through development, and their coupling is predicted by working memory.

neuroscience↗

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.

neuroscience↗

bioRxiv2024

Mapping patterns of thought onto brain activity during movie-watching

Movie-watching is a central aspect of our lives and an important paradigm for understanding the brain mechanisms behind cognition as it occurs in daily life. Contemporary views of ongoing thought argue that the ability to make sense of events in the here and now depend on the neural processing of incoming sensory information by auditory and visual cortex, which are kept in check by systems in association cortex. However, we currently lack an understanding of how patterns of ongoing thoughts map onto the different brain systems when we watch a film, partly because methods of sampling experience disrupt the dynamics of brain activity and the experience of movie-watching. Our study established a novel method for mapping thought patterns onto the brain activity that occurs at different moments of a film, which does not disrupt the time course of brain activity or the movie-watching experience. We found moments when experience sampling highlighted engagement with multi-sensory features of the film or highlighted thoughts with episodic features, regions of sensory cortex were more active and subsequent memory for events in the movie was better--on the other hand, periods of intrusive distraction emerged when activity in regions of association cortex within the frontoparietal system was reduced. These results highlight the critical role sensory systems play in the multi- modal experience of movie-watching and provide evidence for the role of association cortex in reducing distraction when we watch films. Significance statementStates like movie-watching provide a window into the brain mechanisms behind cognition in daily life. However, we know relatively little about the mapping between brain activity during movies and associated thought patterns because of difficulties in measuring cognition without disrupting how brain activity naturally unfolds. We establish a novel method to link different experiential states to brain activity during movie-watching with minimal interruptions to viewers or disruptions to brain dynamics. We found states of sensory engagement occur in moments of films when activity in visual and auditory cortex are high. In contrast, states of distraction are reduced when activity in frontoparietal regions is high. Our study, therefore, establishes both sensory and association cortex as core features of the movie-watching experience.

neuroscience↗

bioRxiv2023

Exploring the embodied mind: functional connectome fingerprinting of meditation expertise

BACKGROUNDShort mindfulness-based interventions have gained traction in research due to their positive impact on well-being, cognition, and clinical symptoms across various settings. However, these short-term trainings are viewed as preliminary steps within a more extensive transformative path, presumably leading to long-lasting trait changes. Despite this, little is still known about the brain correlates of these meditation traits. METHODTo address this gap, we investigated the neural correlates of meditation expertise in long-term Buddhist practitioners, comparing the large-scale brain functional connectivity of 28 expert meditators with 47 matched novices. Our hypothesis posited that meditation expertise would be associated with specific and enduring patterns of functional connectivity present during both meditative (open monitoring/open presence and loving-kindness compassion meditations) and non-meditative resting states, as measured by connectivity gradients. RESULTSApplying a support vector classifier to states not included in training, we successfully decoded expertise as a trait, demonstrating its non-state-dependent nature. The signature of expertise was further characterized by an increased integration of large-scale brain networks, including the dorsal and ventral attention, limbic, frontoparietal and somatomotor networks. The latter correlated with a higher ability to create psychological distance from thoughts and emotions. CONCLUSIONSuch heightened integration of bodily maps with affective and attentional networks in meditation experts could point toward a signature of the embodied cognition cultivated in these contemplative practices.

neuroscience↗

bioRxiv2023

Experience sampling reveals the role that covert goal states play in task-relevant behavior.

Cognitive neuroscience has gained insight into covert states using experience sampling. Traditionally, this approach has focused on off-task states, however, task-relevant states are also maintained via covert processes. Our study examined whether experience sampling can also provide insights into covert goal-relevant states that support task performance. To address this question, we developed a neural state-space, using dimensions of brain function variation, that allows neural correlates of overt and covert states to be examined in a common analytic space. We use this to describe brain activity during task performance, its relation to covert states identified via experience sampling, and links between individual variation in overt and covert states and task performance. Our study established activity patterns within association cortex emphasizing the fronto-parietal network both during target detection and a covert state of deliberate task focus which was associated with better task performance. In contrast, periods of vigilance and a covert off-task state were both linked to activity patterns emphasizing the default mode network. Our study shows experience sampling can not only describe covert states that are unrelated to the task at hand, but can also be used to highlight the role fronto-parietal regions play in the maintenance of covert task-relevant states.

neuroscience↗

bioRxiv2023

The Cellular Underpinnings of the Human Cortical Connectome

The functional properties of the human brain arise, in part, from the vast assortment of cell types that pattern the cortex. The cortical sheet can be broadly divided into distinct networks, which are further embedded into processing streams, or gradients, that extend from unimodal systems through higher-order association territories. Here, using transcriptional data from the Allen Human Brain Atlas, we demonstrate that imputed cell type distributions are spatially coupled to the functional organization of cortex, as estimated through fMRI. Cortical cellular profiles follow the macro-scale organization of the functional gradients as well as the associated large-scale networks. Distinct cellular fingerprints were evident across networks, and a classifier trained on post-mortem cell-type distributions was able to predict the functional network allegiance of cortical tissue samples. These data indicate that the in vivo organization of the cortical sheet is reflected in the spatial variability of its cellular composition.

neuroscience↗

bioRxiv2022

Macro-scale patterns in functional connectivity associated with ongoing thought patterns and dispositional traits

Complex macro-scale patterns of brain activity that emerge during periods of wakeful rest provide insight into the organisation of neural function, how these differentiate individuals based on their traits, and the neural basis of different types of self-generated thoughts. Although brain activity during wakeful rest is valuable for understanding important features of human cognition, its unconstrained nature makes it difficult to disentangle neural features related to personality traits from those related to the thoughts occurring at rest. Our study builds on recent perspectives from work on ongoing conscious thought that highlight the interactions between three brain networks - ventral and dorsal attention networks, as well as the default mode network. We combined measures of personality with state-of-the-art indices of ongoing thoughts at rest and brain imaging analysis and explored whether this tri-partite view can provide a framework within which to understand the contribution of states and traits to observed patterns of neural activity at rest. To capture macro-scale relationships between different brain systems, we calculated cortical gradients to describe brain organisation in a low dimensional space. Our analysis established that for more introverted individuals, regions of the ventral attention network were functionally more aligned to regions of the somatomotor system and the default mode network. At the same time, a pattern of detailed self-generated thought was associated with a decoupling of regions of dorsal attention from regions in the default mode network. Our study, therefore, establishes that interactions between attention systems and the default mode network are important influences on ongoing thought at rest and highlights the value of integrating contemporary perspectives on conscious experience when understanding patterns of brain activity at rest.

neuroscience↗

bioRxiv2022

Designed active-site library reveals thousands of functional GFP variants

Mutations in a protein active site can lead to dramatic and useful changes in protein activity. The active site, however, is extremely sensitive to mutations due to a high density of molecular interactions, drastically reducing the likelihood of obtaining functional multipoint mutants. We introduce an atomistic and machine-learning-based approach, called htFuncLib, to design a sequence space in which mutations form low-energy combinations that mitigate the risk of incompatible interactions. We applied htFuncLib to the GFP chromophore-binding pocket, and, using fluorescence readout, recovered >16,000 unique designs encoding as many as eight active-site mutations. Many designs exhibit substantial and useful diversity in functional thermostability (up to 96 {degrees}C), fluorescence lifetime, and quantum yield. By eliminating incompatible active-site mutations, htFuncLib generates a large diversity of functional sequences. We envision that htFuncLib will be useful for one-shot optimization of activity in enzymes, binders, and other proteins.

biochemistry↗

bioRxiv2021

A low-resource reliable pipeline to democratize multi-modal connectome estimation and analysis

Connectomics--the study of brain networks--provides a unique and valuable opportunity to study the brain. Research in human connectomics, leveraging functional and diffusion Magnetic Resonance Imaging (MRI), is a resource-intensive practice. Typical analysis routines require significant computational capabilities and subject matter expertise. Establishing a pipeline that is low-resource, easy to use, and off-the-shelf (can be applied across multifarious datasets without parameter tuning to reliably estimate plausible connectomes), would significantly lower the barrier to entry into connectomics, thereby democratizing the field by empowering a more diverse and inclusive community of connectomists. We therefore introduce MRI to Graphs (m2g). To illustrate its properties, we used m2g to process MRI data from 35 different studies ({approx} 6,000 scans) from 15 sites without any manual intervention or parameter tuning. Every single scan yielded an estimated connectome that adhered to established properties, such as stronger ipsilateral than contralateral connections in structural connectomes, and stronger homotopic than heterotopic correlations in functional connectomes. Moreover, the connectomes estimated by m2g are more similar within individuals than between them, suggesting that m2g preserves biological variability. m2g is portable, and can run on a single CPU with 16 GB of RAM in less than a couple hours, or be deployed on the cloud using its docker container. All code is available on https://github.com/neurodata/m2g and documentation is available on docs.neurodata.io/m2g.

bioinformatics↗

bioRxiv2021

Long-range connections mirror and link microarchitectural and cognitive hierarchies in the human brain

AO_SCPLOWBSTRACTC_SCPLOWCore features of higher-order cognition are hypothesized to be implemented via distributed cortical networks that are linked via long-range connections. However, these connections are biologically expensive, and it is unknown how the computational advantages long-range connections provide overcome the associated wiring costs. Our study investigated this question by exploring the relationship between long-range functional connections and local cortical microarchitecture. Specifically, our work (i) profiled distant cortical connectivity using resting-state fMRI and cortico-cortical geodesic distance mapping, (ii) assessed how long-range connections reflect local brain microarchitecture, and (iii) studied the microarchitectural similarity of regions connected through long-range connections. Analysis of two independent datasets indicated that sensory and motor areas had more clustered short-range connectivity patterns, while transmodal association cortices, including regions of the default mode network, were characterized by distributed, long-range connections. Confirmatory meta-analysis suggested that this topographical difference mirrored a shift in cognitive function, from perception/action towards emotional and social cognitive processing. Analysis of myelin-sensitive in vivo MRI in the same participants as well as post mortem histology and gene expression established that gradients in functional connectivity distance are paralleled by those present in cortical microarchitecture. Moreover, long-range connections were found to link together spatially remote regions of association cortex with an unexpectedly similar microarchitecture. These findings provide novel insights into how the organization of distributed functional networks in transmodal association cortex contribute to cognition, because they suggest that long-range connections link together distant islands of association cortex with similar microstructural features.

neuroscience↗

bioRxiv2021

Genetic and phylogenetic uncoupling of structure and function in human transmodal cortex

Brain structure scaffolds intrinsic function, supporting cognition and ultimately behavioral flexibility. However, it remains unclear how a static, genetically controlled architecture supports flexible cognition and behavior. Here, we synthesize genetic, phylogenetic and cognitive analyses to understand how the macroscale organization of structure-function coupling across the cortex can inform its role in cognition. In humans, structure-function coupling was highest in regions of unimodal cortex and lowest in transmodal cortex, a pattern that was mirrored by a reduced alignment with heritable connectivity profiles. Structure-function uncoupling in non-human primates had a similar spatial distribution, but we observed an increased coupling between structure and function in association regions in macaques relative to humans. Meta-analysis suggested regions with the least genetic control (low heritable correspondence and different across primates) are linked to social cognition and autobiographical memory. Our findings establish the genetic and evolutionary uncoupling of structure and function in different transmodal systems may support the emergence of complex, culturally embedded forms of cognition.

neuroscience↗

bioRxiv2021

Spatiotemporal dynamics of human attention revealed byintracerebral recording

Exogenous attention, the process that makes external salient stimuli pop-out of a visual scene, is essential for survival. How attention-capturing events modulate human brain processing remains unclear. Here we show how the psychological construct of exogenous attention gradually emerges over large-scale gradients in the human cortex, by analyzing activity from 1,403 intracortical contacts implanted in 28 individuals, while they performed an exogenous attention task. The timing, location and task-relevance of attentional events defined a spatiotemporal gradient of three neural clusters, which mapped onto cortical gradients and presented a hierarchy of timescales. Visual attributes modulated neural activity at one end of the gradient, while at the other end it reflected the upcoming response timing, with attentional effects occurring at the intersection of visual and response signals. These findings challenge multi-step models of attention, and suggest that frontoparietal networks, which process sequential stimuli as separate events sharing the same location, drive exogenous attention phenomena such as inhibition of return.

neuroscience↗

bioRxiv2020

A collaborative resource platform for non-human primate neuroimaging

Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field.

neuroscience↗

bioRxiv2020

A novel approach for assessing hypoperfusion in stroke using spatial independent component analysis of resting-state fMRI data

Individualized treatment of acute stroke depends on the timely detection of ischemia and potentially salvageable tissue in the brain. Using functional MRI (fMRI), it is possible to characterize cerebral blood flow from blood-oxygen-level-dependent (BOLD) signals without the administration of exogenous contrast agents. In this study, we applied spatial independent component analysis to resting-state fMRI data of 37 stroke patients scanned within 24 hours of symptom onset, 17 of whom received follow-up scans the next day. Our analysis revealed "Hypoperfusion spatially-Independent Components" (HICs) whose spatial patterns of BOLD signal resembled regions of delayed perfusion depicted by dynamic susceptibility contrast MRI. These HICs were detected even in the presence of excessive patient motion, and disappeared following successful tissue reperfusion. The unique spatial and temporal features of HICs allowed them to be distinguished with high accuracy from other components in a user-independent manner (AUC = 0.95, accuracy = 0.96, sensitivity = 1.00, specificity = 0.96). Our study therefore presents a new, non-invasive method for assessing blood flow in acute stroke that minimizes interpretative subjectivity and is robust to severe patient motion.

neuroscience↗