Biology subjects

Korponay, C.

Publications and source records attributed to Korponay, C..

10 recordsLinked to original sources

bioRxiv2026

Human striatal population state dynamics

Animal models reveal that striatal projection neurons (SPNs) fluctuate between discrete electrophysiological states with distinct levels of cortical interaction. These dynamics and their behavioral relevance remain uncharacterized in humans. Leveraging neurobiologically informed modeling of over 3 billion voxel-frame-wise striatal coactivation profiles with cortex in functional magnetic resonance imaging (fMRI), we identified population-level striatal states in humans resembling canonical SPN states that reorganized systematically with task demands, arousal and behavior. A background of low- and moderate-coactivation "down-like" and "up-like" striatal rest states with high transition reciprocity modulated task reaction times and reward reactivity. Meanwhile, sparse, disproportionately high-magnitude bursts of striatal coactivation with cortex, which emerged preferentially from the up-like rest state and whose cortical input composition varied with task context, tracked task engagement and arousal level. Findings bring a critical feature of corticostriatal neurobiology into systems-level view in humans and reveal a subthreshold state architecture whose balance encodes behaviorally relevant information.

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bioRxiv2025

Physiological Arousal as a Predominant Source of Individual Differences in Functional Brain Networks

Individual differences in brain network function and organization are promising targets for fMRI-based biomarkers in precision psychiatry, yet the sources of individual variability remain poorly understood. We show that arousal, assessed by systemic low-frequency oscillation (sLFO) amplitude in the fMRI signal, accounts for a substantial portion of variance in brain network properties (e.g.: R= 0.70 for default mode network (DMN)-dorsal attention connectivity; R= -0.63 for DMN dynamics). These relationships replicated across sessions, across independent samples, and when assessed with traditional arousal indices. Critically, associations persisted after sLFO denoising, indicating a genuine brain-physiology relationship rather than hemodynamic artifact. Pharmacological manipulation showed that drug-induced sLFO-assessed arousal changes were accompanied by corresponding shifts in network connectivity and dynamics. This work identifies arousal as a prominent determinant of variability in functional brain networks, providing a new perspective on brain-based individual differences while offering an approach to measure arousal directly from fMRI data.

neuroscience↗

bioRxiv2025

QuNex Recipes: Executable, Human-Readable Workflows for Reproducible Neuroimaging Research

Preprocessing and analysis of neuroimaging data are technically demanding, often requiring a combination of multiple software tools, modality-specific pipelines, and extensive parameter tuning to match dataset characteristics. These complexities make it difficult to document workflows in sufficient detail to ensure complete transparency and reproducibility. To address these challenges, we introduce QuNex recipes, a framework for defining and executing complete neuroimaging workflows - encompassing data onboarding, preprocessing, and analysis - in a transparent, machine- and human-readable format. Recipes are implemented as an integrated feature of the Quantitative Neuroimaging Environment & Toolbox (QuNex), a containerized, open-source platform for end-to-end multimodal and multi-species neuroimaging processing. The recipes framework enables seamless integration of QuNex commands with custom scripts and external tools, capturing every processing step and parameter setting. A fully reproducible study can thus be shared and replicated by providing only (a) the QuNex version used, (b) the recipe file, and (c) the data. This approach standardizes workflow specification, enhances transparency, and enables one-command replication of complex neuroimaging analyses. By providing a standardized way to describe and share workflows, recipes facilitate open exchange of best practices and reproducible methods within the neuroimaging community.

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bioRxiv2025

Cognition-centric brain activity across diverse imaging tasks constrains the representation of mental health in task-evoked brain function

Large-scale neuroimaging studies best powered to investigate mental health biomarkers continue to administer a set of in-scanner tasks that, to date, yield weak brain-mental health associations. Triangulating the source of these weak associations is critical to directing the focus of future work. Using these tasks strong brain-cognition associations as a positive control, we analyzed potential sources of weak brain-mental health associations across five popular fMRI tasks and dozens of task-evoked brain networks. Across tasks and networks, latent mental health factors showed substantially weaker brain associations than cognition despite comparable measurement reliability and greater interindividual variability. Moreover, increasing brain-feature dimensionality improved cognitive but not mental health signal, and task-evoked network profiles were 1.8-2.3 times more homogeneous and 3.5 times lower-dimensional than mental health profiles. Findings implicate a signal evocation bottleneck: common fMRI tasks elicit little interindividual variation in mental health-related brain activity relative to the diversity of mental health itself. Overall, these findings motivate a shift in focus to the development and use of tasks in large-scale studies more explicitly designed to evoke mental health-relevant brain activity. Significance StatementIdentification of robust individual-specific mental health-related brain signals from fMRI remains elusive, limiting the clinical utility of brain imaging. To investigate why, we systematically evaluated brain signals evoked by tasks used by the Human Connectome Project-Young Adult study, which are now commonly included in many large-scale neuroimaging studies. Our findings suggest that, more so than analytical or measurement constraints on detecting these signals, a primary limitation is a failure of these prevalent fMRI tasks to evoke mental health-relevant brain signals in the first place. These findings suggest that progress in psychiatric neuroimaging may require tasks more explicitly designed to evoke mental health-relevant brain activity.

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bioRxiv2024

Concurrent large-scale brain dynamics during the emotional face matching task and their relation to behavior and mental health

Prior investigations of emotion processings neural underpinnings rely on a priori models of brain response, obscuring detection of task-relevant neurobiological processes with complex temporal dynamics. To overcome this limitation, we applied unsupervised machine learning to functional magnetic resonance imaging data acquired during the emotional face matching task (EFMT) in healthy young adults from the Human Connectome Project (n=413; n=416 replication). Tensorial independent component analysis showed that the EFMT engages 10 large-scale brain networks - each recruiting visual association cortex in distinct temporal fashions and in tandem with diverse non-visual regions - that collectively recruit 74% of cortex, posterior cerebellum, and amygdala. Despite prominent use of the EFMT to probe negative affect and related psychopathology, EFMT-recruited networks strongly reflected individual differences in cognition but not internalizing/negative affect. Overall, we characterize a richer-than-expected tapestry of concurrent EFMT-recruited brain processes, their diverse activation dynamics, and their relations to task performance and latent mental health phenotypes.

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bioRxiv2023

Brain-wide functional connectivity artifactually inflates throughout fMRI scans: a problem and solution

The fMRI blood oxygen level-dependent (BOLD) signal is a mainstay of neuroimaging assessment of neuronal activity and functional connectivity in vivo. Thus, a chief priority is maximizing this signals reliability and validity. To this end, the fMRI community has invested considerable effort into optimizing both experimental designs and physiological denoising procedures to improve the accuracy, across-scan reproducibility, and subject discriminability of BOLD-derived metrics like functional connectivity. Despite these advances, we discover that a substantial and ubiquitous defect remains in fMRI datasets: functional connectivity throughout the brain artifactually inflates during the course of fMRI scans - by an average of more than 70% in 15 minutes of scan time - at spatially heterogeneous rates, producing both spatial and temporal distortion of brain connectivity maps. We provide evidence that this inflation is driven by a previously unrecognized time-dependent increase of non-neuronal, systemic low-frequency oscillation (sLFO) blood flow signal during fMRI scanning. This signal is not removed by standard denoising procedures such as independent component analysis (ICA). However, we demonstrate that a specialized sLFO denoising procedure - Regressor Interpolation at Progressive Time Delays (RIPTiDe) - can be added to standard denoising pipelines to significantly attenuate functional connectivity inflation. We confirm the presence of sLFO-driven functional connectivity inflation in multiple independent fMRI datasets - including the Human Connectome Project - as well as across resting-state, task, and sleep-state conditions, and demonstrate its potential to produce false positive findings. Collectively, we present evidence for a previously unknown physiological phenomenon that spatiotemporally distorts estimates of brain connectivity in human fMRI datasets, and present a solution for mitigating this artifact.

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bioRxiv2022

The temporal organization of corticostriatal communications

The cortex and striatum are linked by hundreds of thousands of structural connections, and the transmission of temporally aligned communications across many of these connections at once is an electrophysiological prerequisite for striatal activation. Despite the importance of communication timing in corticostriatal circuitry, there is little understanding of its system-level organization and properties. To investigate this, we leveraged emerging methods to "temporally unwrap" fMRI data and measure patterns of cortex-striatum node-pair coactivation at frame-wise (i.e., <1 sec) resolution in low head-motion subjects from the Human Connectome Project. First, we identify communities of cortex-striatum node-pairs with preferentially synchronized coactivation patterns. Surprisingly, we find that the map of striatal areas with temporally aligned cortical coactivation patterns does not simply reflect the map of striatal areas with similar cortical connectivity profiles. As a result of the distinct spatial organization of these gradients, striatal nodes connected to similar areas of cortex may nonetheless interact with these cortical areas at different times, and striatal nodes connected to different areas of cortex may nonetheless interact with these areas at similar times. We provide evidence for a possible mechanism driving this divergence: striatal nodes with similar cortical connectivity profiles may have differently timed interactions with cortex if they have different modulatory input profiles (i.e., from the midbrain and thalamus) that differentially gate their responsivity to cortical input. Overall, this blended organization may serve to both increase the repertoire of striatal responses to frontal input and facilitate coordination across functional domains in the temporal dimension. Findings provide a framework to investigate the role of corticostriatal temporal coordination in behavior and disease. SIGNIFICANCE STATEMENTWe provide the first systems-level account of temporal communication patterns between cortex-striatum node-pairs, mapping communities of node-pairs with synchronized communication patterns using an emerging fMRI temporal-unwrapping technique and providing evidence for the mechanism that dictates the organization of these communities. Findings have broad implications for our understanding of the functional architecture of corticostriatal circuits.

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bioRxiv2022

Dissociable misconfigurations of striatal functional connectivity profiles in smokers

Corticostriatal circuits are central to reward processing and reinforcement learning functions that often become dysregulated in substance use disorder (SUD) and drive compulsive drug use. Human neuroimaging research seeking to identify how corticostriatal circuits become altered in SUD has primarily focused on evaluating connectivity between cortex-striatum node-pairs. Yet, striatal nodes receive appreciable input from many cortical nodes, and the morphological and electrophysiological properties of striatal nodes dictate that combinational features of their multivariate "connectivity profiles" shape their activity more so than any individual cortical node. Here, we introduce an approach for quantifying and statistically evaluating different types of multivariate connectivity profile configuration differences (i.e., aggregate divergence, rank order arrangement, and entropy shift) that may reflect different forms of circuit plasticity, and apply it to nicotine dependent smokers (n=46) as an exemplar SUD. Foremost, we find evidence of significant connectivity profile misconfiguration throughout much of the striatum, suggesting that prior findings of abnormal connections between individual striatal-cortical node-pairs may only represent the "tip of the iceberg" of corticostriatal circuit alteration in nicotine dependence. Moreover, we find that dorsolateral and ventromedial striatum display distinct types of connectivity profile misconfiguration. Whereas dorsolateral striatum almost exclusively displays abnormal rank order arrangement that is present in both the nicotine sated and acutely abstinent states - indicative of a "trait" misconfiguration - ventromedial striatum almost exclusively displays abnormal aggregate divergence that only manifests during acute abstinence - indicative of a "state" misconfiguration. Further, we identify a unique striatal site in the right caudal ventral putamen that displays multiple forms of connectivity profile misconfiguration, where connections with cognitive processing cortical areas overtake those with motor/premotor control cortical areas as the strongest in the connectivity profile, and acute abstinence significantly strengthens this abnormal arrangement. Moreover, the interactive magnitude of these misconfigurations during acute abstinence is significantly linked to dependence severity. Collectively, the present findings underscore the need for increased examination of connectivity profile misconfigurations as a mechanism of SUD etiology and as a potential guide for identifying therapeutic intervention targets.

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bioRxiv2021

Connectivity profile laterality in corticostriatal functional circuitry: a fingerprinting approach

An abnormal magnitude of hemispheric difference (i.e. laterality) in corticostriatal circuits is a shared feature of numerous neurodevelopmental and psychiatric disorders. Detailed quantitation and regional localization of corticostriatal laterality in normative samples stands to further the understanding of hemispheric differences in healthy and disease states. Here, we used a fingerprinting approach to quantify "functional connectivity profile laterality" - the overall magnitude by which a voxels profile of connectivity with homotopic regions of the ipsilateral and contralateral cortex differs - in the striatum. Laterality magnitude heatmaps revealed "laterality hotspots" - constituting outliers in the voxel-wise distribution -in the right ventrolateral putamen and left central caudate. Findings were replicated in an independent sample, with significant (p<0.05) spatial overlap observed between the location of the laterality hotspots across samples, as measured via Dice coefficients. At both hotspots, a primary driver of overall laterality was the difference in striatal connectivity strength with the right and left pars opercularis of the inferior frontal gyrus. Right and left striatum laterality magnitude maps were found to significantly differ (p<0.05) at the hotspot locations. Moreover, using subjects left, but not right, striatum laterality magnitude maps, a support vector machine trained on a discovery sample (n=77) and tested on a replication sample (n=77) significantly predicted (r=0.25, p=0.028) subject performance on a language task, known for its lateralized nature. Laterality magnitude maps remained consistent across different cortical atlas parcellations and did not differ significantly between right-handed and left-handed individuals. In sum, meaningful variation in functional connectivity profile laterality - both spatially within the striatum and across subjects - is evident in corticostriatal circuits. Findings provide a basis to examine corticostriatal connectivity profile laterality in psychiatric illness.

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bioRxiv2020

Corticostriatal Projections of Macaque Area 44

Ventrolateral frontal area 44 is implicated in inhibitory motor functions and facilitating prefrontal control over vocalization. Yet, the corticostriatal circuitry that may contribute to area 44 functions is not clear, as prior investigation of area 44 corticostriatal projections is limited. Here, we used anterograde and retrograde tracing in macaques to map the innervation zone of area 44 corticostriatal projections, quantify their strengths, and evaluate their convergence with corticostriatal projections from non-motor and motor-related frontal regions. First, terminal fields from a rostral area 44 injection site were found primarily in the central caudate nucleus, whereas those from a caudal area 44 injection site were found primarily in the ventrolateral putamen. Second, amongst sampled striatal retrograde injection sites, area 44 input as a percentage of total frontal cortical input was highest in the ventral putamen at the level of the anterior commissure. Third, area 44 projections converged with both orofacial premotor area 6VR and other motor related projections (in the putamen), and with non-motor prefrontal projections (in the caudate nucleus). These findings support the role of area 44 as an interface between motor and non-motor functional domains, possibly facilitated by rostral and caudal area 44 subregions with distinct corticostriatal connectivity profiles.

neuroscience↗