Biology subjects

Dugre, J. R.

Publications and source records attributed to Dugre, J. R..

6 recordsLinked to original sources

bioRxiv2026

Epigenetic and brain age across development: Performance and associations in the MIND consortium

Understanding how biological age measures perform across development lays the groundwork for investigations into lifespan trajectories of healthy aging. We provide the most comprehensive assessment of epigenetic and brain age models across development (birth to 24 years; [≤]20,917 observations across 15 cohorts), evaluating how these models associate with chronological age and with each other, and how these associations change across development. Chronological age-prediction accuracy of epigenetic and brain age models was modest and varied substantially. Accuracy improved with age and stabilized by middle childhood. Few brain and fewer epigenetic clocks performed stably and well across all developmental stages. Performance was better when age range and tissue corresponded between training and testing data. Associations between epigenetic-brain age residuals were small, and changed little across development, tissues or clock generation. Given this developmentally dynamic system of epigenetic-brain age performances and associations, we give key recommendations to improve developmental research in this field.

neuroscience↗

bioRxiv2026

Brain Age in Conduct Disorder: A Mega-Analysis of the ENIGMA Antisocial Behavior Working Group

Conduct disorder (CD) is the leading global cause of mental health burden in children and adolescents and has recently been hypothesized to be a neurodevelopmental disorder. Although prior research has identified neuroanatomical differences associated with CD, it remains unclear whether these differences reflect atypical brain development. Here, we investigated the difference between an individuals brain age and chronological age as a proxy for variations in brain maturation. Using a pretrained model, we estimated brain age from structural neuroimaging data obtained from 1,119 youth with CD and 1,183 typically developing controls across 14 international cohorts participating in the ENIGMA-Antisocial Behavior Working Group. Youth with CD exhibited a statistically robust but small acceleration in brain age compared to typically developing youth (around 0.50 years), which was restricted to the adolescence-onset subtype of the disorder. Our large-scale, coordinated analysis provides the first evidence of accelerated neurodevelopment as a potential mechanism underlying CD.

neuroscience↗

bioRxiv2025

The neural orchestra of aggression: neurogenetic network mapping of human aggressiveness

Over the last century, researchers have successfully mapped the core neural circuitry underlying aggression in non-human animals. In contrast, advances in human neuroimaging have been hindered by persistent challenges with reproducibility. Here, we adopted a recently developed network-based framework to test the hypothesis that seemingly heterogeneous findings in aggression research converge on a common brain network. We conducted network mapping to integrate functional and structural imaging findings of human aggression across 39 and 31 samples, respectively, revealing substantial overlap across both functional (up to 84%) and structural (up to 74%) imaging modalities. Strikingly, we found that these networks were largely explained by the expression of genes implicated in genome-wide association studies of aggression and related phenotypes. By integrating network-based approaches of neuroimaging data with gene expression, our work provides a reliable and comprehensive account of the neurogenetic architecture underlying aggressive behavior, resolving longstanding discrepancies in its neurobiology.

neuroscience↗

bioRxiv2025

Mapping the Structural Brain Network of Psychopathy: Convergent Evidence from Humans and Chimpanzees

Psychopathy, a condition characterized by profound emotional and interpersonal deficits, has long been hypothesized to stem, in part, from structural brain abnormalities. Yet neuroimaging findings remain inconsistent. To address these discrepancies, we applied a novel structural network mapping approach combined with cross-species analyses. Traditional meta-analysis revealed weak spatial convergence across 20 samples. Nevertheless, we found that heterogeneous peak locations coalesced into a distributed set of regions encompassing the insular, and prefrontal cortices. This network overlapped strikingly (r = .93) with a lesion-derived network causally linked to antisocial behaviour, and variation within it predicted volumetric risk scores in both humans (n = 107, R{superscript 2} = .16) and chimpanzees (n = 148, R{superscript 2} = .21). These findings suggest that psychopathy reflects abnormalities across a collection of distributed regions rather than isolated areas, providing a unifying explanation for decades of inconsistent results and advancing our understanding of its clinical, biological, and evolutionary bases.

neuroscience↗

bioRxiv2025

Propagation Mapping: A Precision Framework for Reconstructing the Neural Circuitry of Brain Maps

Human brain mapping has traditionally relied on univariate approaches to characterize regional activity, whereas more recent work focuses on interactions between regions to capture network-level organization. Despite their parallel development, growing evidence suggests that integrating both approaches is critical for a comprehensive understanding of task-evoked brain activity. The present study introduces propagation mapping, an extension of activity flow mapping that models task-evoked brain activity as the propagation of regional signal amplitudes along whole-brain topological routes. This study aims to evaluate propagation maps as reliable neurobiological features for neuroimaging research. Using functional connectomes and structural covariance network derived from a large normative sample (n=1,000), propagation patterns of task-evoked activity were accurately captured (average R2 = 0.947, MAE=0.155, and RMSE=0.229) across 94 participants. Mapping performance remained stable across different task contrasts, parcellation atlases, and signal intensity and spatial distance between regions. Similar performance was observed at both the subject and group levels in an independent sample using the amplitude of low-frequency oscillations during resting-state (n=189). Importantly, despite its reliance on normative connectomes which could homogenize subject-specific variance, propagation mapping instead redistributed individual variance along propagation routes (Cohens d = 0.10, p=0.17). As a biologically comprehensive representation of brain organization, propagation mapping offers a powerful and user-friendly alternative to traditional regional analyses and provides new avenues for discovery in neurological and psychiatric neuroimaging research.

neuroscience↗

bioRxiv2023

Towards a Neurobiologically-driven Ontology of Mental Functions:A Data-driven Summary of the Twenty Years of Neuroimaging Meta-Analyses

A persistent effort in neuroscience has been to pinpoint the neurobiological substrates that support mental processes. The Research Domain Criteria (RDoC) aims to develop a new framework based on fundamental neurobiological dimensions. However, results from several meta-analysis of task-based fMRI showed substantial spatial overlap between several mental processes including emotion and anticipatory processes, irrespectively of the valence. Consequently, there is a crucial need to better characterize the core neurobiological processes using a data-driven techniques, given that these analytic approaches can capture the core neurobiological processes across neuroimaging literature that may not be identifiable through expert-driven categories. Therefore, we sought to examine the main data-driven co-activation networks across the past 20 years of published meta-analyses on task-based fMRI studies. We manually extracted 19,822 coordinates from 1,347 identified meta-analytic experiments. A Correlation-Matrix-Based Hierarchical Clustering was conducted on spatial similarity between these meta-analytic experiments, to identify the main co-activation networks. Activation likelihood estimation was then used to identify spatially convergent brain regions across experiments in each network. Across 1,347 meta-analyses, we found 13 co-activation networks which were further characterized by various psychological terms and distinct association with receptor density maps and intrinsic functional connectivity networks. At a fMRI activation resolution, neurobiological processes seem more similar than different across various mental functions. We discussed the potential limitation of linking brain activation to psychological labels and investigated potential avenues to tackle this long-lasting research question.

neuroscience↗