Biology subjects

Shafiei, G.

Publications and source records attributed to Shafiei, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Insula functional connectivity development follows a canonical antero-posterior axis of organization

The insula is a heterogeneous region associated with a range of functional domains including sensory, cognitive, and emotional processing. Cytoarchitectural and functional studies have described an antero-posterior axis of insula organization. However, the insula's functional development remains sparsely described. We delineated the development of insula resting-state functional connectivity across 562 individuals (6-22 years) using generalized additive models and population value decomposition. We show insulo-cortical functional connectivity development differs across the insula: anterior subregions have predominantly decreasing connectivity across the age range examined, whereas posterior subregions have variable connectivity that aligns with the sensorimotor-association axis. Vertex-level analysis revealed that age-related trajectories followed an antero-posterior axis that aligned with estimates of insula microstructure. Our results emphasize that the development of insula connectivity is spatially heterogeneous and aligns with known cytoarchitecture. The normative insula development described here provides a foundation for investigating how emerging psychopathology may be linked to variation in insula development.

neuroscience↗

bioRxiv2026

Quantifying Uncertainty in Brain Age Predictions via Conformal Prediction

Youth can exhibit signs of delayed or accelerated neurodevelopment, measurable via brain magnetic resonance imaging (MRI). Brain age prediction seeks to estimate brain age at an individual level using machine learning models fitted on healthy individuals. The brain age gap (BAG): the difference between brain age and chronological age, has been studied as a potential biomarker. However, BAG suffers from known limitations, including dependence on chronological age, regression to the mean, and challenges in interpretability. As an alternative framework, we introduce brain age intervals (BAIs) as a normative interval on an individual's chronological age, based on MRI measures. BAIs can be derived using a recent statistical framework called conformal prediction that yields prediction intervals with guaranteed coverage. We train several brain age prediction models on structural and functional MRI scans from the Reproducible Brain Charts dataset (aged 6-22) and estimated BAIs. The BAIs demonstrated stable empirical coverage close to the nominal 90% level (median coverage=91%, width=7.36 years, root mean square error (RMSE)=2.20 years across 100 repeated train-test splits). Associations between interval coverage and clinical measures (p-factor, parental education) were weak, with only a modest directional signal for parental education. Together, these findings demonstrate the feasibility of uncertainty-aware brain age modeling in youth populations while highlighting the need for larger and more diverse samples to detect meaningful clinical and environmental associations.

neuroscience↗

bioRxiv2026

Linking human brain functional connectivity to underlying neurotransmission

The human brain is organized into interacting functional systems. Their underlying neurobiological mechanisms remain difficult to study in vivo. Here, we adopt a topological framework to quantify the association between neurobiology and brain functional connectivity derived from both resting-state fMRI and MEG. Across six healthy adult cohorts (n = 19-112), regional variation in fMRI connectivity robustly aligns with the distribution of neurotransmitter receptors and transporters. These patterns are present in every single subject, replicate across all cohorts, and are mirrored in MEG. Most prominently, noradrenergic modulation of connectivity in a sensorimotor-insular network is consistently detected across individuals and linked to autonomic arousal. In pharmacological and clinical samples, associations are sensitive to neurotransmitter system manipulation and are altered in early psychosis, aligning with clinical symptomatology. These findings provide biological insight into typical and atypical functional organization of the human brain using a framework linking underlying neurobiology to the functional connectome (NEOFC).

neuroscience↗

bioRxiv2026

Highly replicable multisite patterns of adolescent white matter maturation

The Adolescent Brain Cognitive Development (ABCD) Study is the largest U.S.-based neuroimaging initiative of adolescent brain maturation. Diffusion MRI (dMRI) provides unique insights into white matter organization, yet applying advanced processing pipelines and managing technical variability across scanning environments remains challenging at scale. To address these issues, we present ABCD-BIDS Community Collection (ABCC) release 3.1.0, including a curated resource of more than 24,000 fully processed ABCD dMRI datasets. ABCC provides fully processed images, nuanced image quality metrics, advanced microstructural measures, and person-specific bundle tractography. Evaluating these rich data revealed that measures of diffusion restriction and non-Gaussianity--in particular the intracellular volume fraction from NODDI and return-to-origin probability from MAP-MRI--were highly sensitive to neurodevelopment and robust to variation in image quality. Additionally, harmonization of microstructural features markedly improved the cross-vendor generalizability of developmental effects. Together, ABCC accelerates reproducible, rigorous research on adolescent white matter development.

neuroscience↗

bioRxiv2026

Mapping developmental patterns of intrinsic timescale

Intrinsic timescale is a commonly used measure of spontaneous neural dynamics that quantifies the temporal window of processing of neuronal populations. Intrinsic timescale displays a hierarchical cortical organization across multiple species and imaging modalities, with shorter timescales in sensorimotor cortex compared to association cortex. However, less is known about how intrinsic timescale evolves during human brain development and whether its cortical maturation patterns generalize to independent developmental samples. Here we estimate the intrinsic timescale in two independent cross-sectional datasets of youth (HCPD: n=565; HBN: n=729; age range 8-22 years) and investigate its neurodevelopmental patterns. We find that developmental patterns in the intrinsic timescale follow a hierarchical pattern that recapitulates an axis spanning sensorimotor to association cortices (S-A axis). Our analysis of an independent healthy young adult dataset (HCPYA: n=973, age range 22-37 years) underscores the specificity of these developmental findings, suggesting that the intrinsic timescale develops along the S-A axis in youth and stabilizes in adulthood. Together, these results reveal convergence between major axes of cortical organization and development, highlighting intrinsic timescale as a principled marker of hierarchical brain maturation in youth.

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bioRxiv2026

White Matter Myelin Shapes Macroscale Functional Connectivity Through Integrative Communication

White matter structural connectivity constrains large-scale brain communication, yet most network models do not account for biologically meaningful differences between connections. Although axonal diameter and myelination influence neural signaling at the microscale, how these features shape systems-level functional connectivity remains unclear. Here, we test whether structural connectomes weighted by white matter microstructure give rise to distinct communication regimes that differentially predict multimodal functional connectivity. Combining quantitative MRI and advanced diffusion modeling, we constructed whole-brain networks weighted by tract caliber and multiple myelin-sensitive measures. To these, we applied routing- and diffusion-based communication models and used the resulting communication metrics to predict haemodynamic and frequency-resolved electromagnetic connectivity. Myelin-weighted networks preferentially enhanced long-range communication efficiency and redistributed spectral energy toward globally integrative topological eigenmodes. In contrast, caliber-weighted networks emphasized mesoscale organization and short-range communication. Across nested regression models controlling for geometric embedding and network topology, myelin-sensitive communication explained unique variance in functional connectivity with effects varying systematically across cortical systems and frequency bands. The strongest coupling was observed for alpha-band connectivity in association and attentional networks, consistent with a role for myelin-dependent communication delays in supporting long-range alpha synchrony. These findings demonstrate how distinct white matter microstructural features give rise to heterogeneous large-scale communication regimes: tract caliber and myelin bias communication toward locally specialized and globally integrative architectures, respectively. By integrating biologically informed connectomics with communication modeling and multimodal functional data, this work advances a mechanistic account of how white matter microstructure shapes macroscale brain dynamics.

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bioRxiv2026

Integrating Functional Transdiagnostic Dimensions of Psychopathology with Cortical Organization

Childhood and adolescence represent a critical period in which neurodevelopmental psychiatric conditions emerge; traditional case-control approaches often underestimate the complexity and co-occurrence of psychiatric conditions, calling for a transdiagnostic approach as a complementary measure. Open-access data sharing initiatives provide an opportunity to decipher structural- and functional-based organisational constraints on the relationship between brain connectivity and psychopathology. Using a highly heterogenous and comorbid neurodevelopmental sample of children and adolescents aged between 6 and 17 years old at-risk of neurodevelopmental conditions (N = 174, 114 males, mean age 10.72 {+/-} 2.21 years), and age-matched neurotypical controls (N = 27, 12 males, mean age 10.65 {+/-} 2.07 years), we identified a multivariate association, or latent variable, between resting-state functional connectivity and psychopathology. We extensively benchmarked this latent construct to develop a more parsimonious account of childhood psychopathology though an analytical framework spanning biological maps, brain connectivity, and behaviour. Participant-level expression of this latent brain-behaviour association differed by diagnostic burden and symptomatology, and pre-empted longitudinal psychopathology. Whilst diagnostic status was useful for interpretation, the latent construct transcended traditional diagnostic borders, revealing a neurotypical-neurodivergent continuum. The relationship between functional connectivity and neurodevelopmental psychopathology was circumscribed by functional connectivity networks (visual, fronto-parietal, and dorsal attention) and cytoarchitectonic class (primary/secondary sensory and primary sensory cortices). The latent variable aligned with magnetoencephalography-defined electrophysiological alpha (), high-gamma ({gamma}), and theta ({theta}) frequency bands, and was enriched across cortical distributions of astrocytes and excitatory neurones. The connectivity signature was significantly aligned with the archetypal sensorimotor-to-association axis and validated in an independent sample of pre-adolescents (N = 3504), with the strongest alignment with the principal component of gene expression and myelination and were relatively less enriched in cortical regions related to language, indicating a protective effect, and more positively enriched in regions related to executive functioning, conferring greater risk of psychopathology. Together, our findings suggest that the predictive link between functional connectivity and common symptoms of neurodevelopmental psychopathology are circumscribed by underlying macroscale anatomical, functional, and cognitive-related hierarchies.

neuroscience↗

bioRxiv2025

Corticolimbic structure-function coupling is sensitive to childhood adversity and buffers adversity-related symptoms during development

Childhood adversity is a potent predictor of mental health problems across the lifespan, and a rich cross-species literature implicates stress-sensitive corticolimbic circuits in adversity-related psychopathology. Structure-function coupling (SFC) is a promising multimodal marker that is sensitive to developmental plasticity. While emerging evidence suggests cortical SFC is sensitive to adversity exposure during early childhood, it is unknown how SFC in stress-sensitive corticolimbic circuits links adversity exposure with mental health across development. We examined associations between adversity exposure, transdiagnostic symptomatology, and both amygdala-cortical and hippocampal-cortical SFC across development in a large sample of youth (N = 607, 39% F). Results revealed that adversity exposure moderated age-related change in amygdala-vmPFC SFC (p = .007), such that youth exposed to higher, but not lower, levels of adversity showed an age-related increase in amygdala-vmPFC SFC. Further, amygdala-vmPFC SFC buffered the effect of adversity on internalizing symptoms (p = .012), such that those youth with higher adversity exposure who had stronger amygdala-vmPFC SFC also displayed lower internalizing symptoms. Separately, higher adversity exposure was associated with lower hippocampal-limbic network SFC (p = .037), which moderated the effect of adversity on internalizing symptoms (p = .010). These findings highlight that structural and functional neurodevelopment of amygdala-vmPFC and hippocampal-limbic network connections may adapt in distinct ways to support mental health following adversity, with implications for risk and resilience against internalizing psychopathology. Significance StatementDelineating how childhood adversity alters neurodevelopment is critical to understanding the origins of adversity-related risk for mental health disorders. Here, we leverage a multimodal marker of the correspondence between brain structure and function to test how corticolimbic circuits are jointly shaped by adversity exposure. Results reveal that the structure-function coupling of amygdala-vmPFC and hippocampal-limbic networks is associated with adversity exposure and differentially moderate risk for internalizing psychopathology. These findings suggest key roles for neural stress regulation and memory circuits in adapting to support optimal functioning following adversity exposure, and highlight the concordance of neural structure and function as an important indicator of individual-level risk and resilience.

neuroscience↗

bioRxiv2025

Anatomical White Matter Tracts Span the Cortical Hierarchy to Support Cognitive Diversity

Long-range white matter (WM) tracts support cognition by enabling communication between distant cortical regions, which are organized along a hierarchy defined by the sensorimotor-to-association (S-A) axis. However, it remains unknown how WM tracts are positioned within the cortical hierarchy to support cognition. Here, we show that WM tracts are differentially positioned in the cortical hierarchy to support specific cognitive functions, and that tracts spanning the hierarchy connect regions with greater cognitive diversity. Moreover, tracts situated within the same hierarchical level connect biologically similar regions, while those crossing the hierarchy bridge distinct biological milieux to support diverse cognitive functions. The placement of tracts in the cortical hierarchy also reflects developmental variation in tract microstructure and individual differences in cognition. Together, these findings provide a framework that moves beyond conventional categories of association or projection tracts and links WM tract anatomy to cortical organization, cognitive function, cortical neurobiology, and neurodevelopment. We anticipate that this cortex-anchored framework for describing WM tracts may aid the interpretation of individual differences in WM structure related to development and behavior.

neuroscience↗

bioRxiv2025

An Open, Fully-processed, Longitudinal Data Resource to Study Brain Development and Transdiagnostic Executive Function

Executive function (EF) develops rapidly during adolescence. However, deficits in EF also emerge in adolescence, representing a transdiagnostic symptom associated with many forms of psychopathology. To promote transdiagnostic research on EF during development, we introduce a new data resource - the Penn Longitudinal Executive functioning in Adolescent Development study (Penn LEAD) - that combines longitudinal multimodal imaging data with rich clinical and cognitive phenotyping. These data include 225 imaging sessions from 132 individuals (8-16 years old at the time of enrollment) who are typically developing (27.3%), or meet criteria for attention-deficit hyperactivity disorder (20.5%) or the psychosis-spectrum (52.3%). In addition to phenotypic data from multiple cognitive tasks focused on EF, the study includes data from structural MRI, diffusion MRI, n-back task fMRI, resting-state fMRI, and arterial spin-labeled MRI. Notably, all raw data, fully-processed derived data, and detailed quality control recommendations are publicly shared on OpenNeuro. We anticipate that such analysis-ready data will accelerate research on EF development in psychiatry.

neuroscience↗

bioRxiv2025

netneurotools: a trainee-oriented approach to network neuroscience

Brain imaging is an increasingly inter-disciplinary field, encompassing multiple data types and multiple analytic traditions. Projects typically involve many moving parts, such as building customized preprocessing pipelines, transforming between data formats, preparing datasets for analysis, and ultimately displaying results. The field is conventionally built on highly specialized software packages that solve these individual challenges well, but are not necessarily designed to be interoperable. Trainees new to the field are therefore often left to come up with isolated heuristics and workarounds to complete a project. Here we present a way to navigate the increasingly complex informatics ecosystem of brain imaging. netneurotools is our labs internal Python toolkit that has been continuously developed and maintained by the labs trainees. The philosophy of the toolkit is that it should be the Swiss army knife of the lab: functions and routines that we often use but that are not part of any established pipeline or package. Since its inception, the toolkit has been open and welcomes contribution from neuroscientists across the globe. netneurotools presents a necessary counterweight to out-of-the-box software packages and highlights the importance of smaller, ad hoc functions for implementing projects. By opening a window into the inner workings of a lab, netneurotools also presents an opportunity to begin a new type of discourse among groups and establish tangible links within the community.

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bioRxiv2025

Brain network dynamics determine tau presence while regional vulnerability governs tau load in Alzheimer's disease

In Alzheimers disease (AD), tau pathology accumulates gradually throughout the brain, with clinical decline reflecting tau progression. A comprehensive understanding of, first, whether tau propagation is predominantly governed by connectome-based diffusion, regional vulnerability, or an interplay of both, and second, which types of brain connectivity or regional factors best explain tau propagation, remains crucial for advancing our understanding of AD progression. Here, we apply multi-scale, biologically informed disease progression simulations to human data, to disentangle the influence of local mechanisms on global tau progression patterns in AD. We find that whether tau reaches a brain region (presence) and how much tau accumulates there (load) are governed by different mechanisms. Tau presence patterns are highly consistent across the population, and can be largely explained through synaptic spread through white-matter networks and excitatory-inhibitory dynamics. Meanwhile tau load differs across people, and is driven by a combination of synaptic spread and intrinsic or extrinsic regional properties, including regional {beta}-amyloid load, MAPT gene expression and regional blood flow. Finally, while distinct tau patterns in the population could each be explained by established AD mechanisms, our models highlight a role of distinct brain networks (parietal networks in MTL-sparing AD tau subtype) and neurotransmitter systems (cholinergic system in posterior subtype). Together, this work suggests that network dynamics likely determine the sequence of regional tau progression, while individual-specific tissue-vulnerability factors influence regional tau load.

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bioRxiv2025

An engine for systematic discovery of cause-effect relationships between brain structure and function

Characterising how perturbations of brain architecture influence brain function is essential to understand the origins of brain dysfunction, and devise potential avenues of treatment. Here we introduce a computational engine for systematic causal discovery of the functional consequences of altering network architecture and local biophysics in the brain. We integrate multimodal anatomical and functional neuroimaging to implement over 2, 000 in-silico brains, and provide mechanistic insight into the functional consequences of local lesions, global wiring, and empirically-derived maps of regional cytoarchitecture and chemoarchitecture. We comprehensively assess how each manipulation of brain macrostructure reshapes spatial and temporal signal coordination, information dynamics, and functional hierarchy--as well as spontaneous co-activation of meta-analytic cognitive circuits, and > 6, 000 dimensions of local neural dynamics. Our computational model systematically identifies which features of brain architecture have overlapping or antagonistic causal influence over each dimension of brain function, and how functional properties are traded off against each other across disorders and neuromodulation. We find that regions functional vulnerability to lesions in silico recapitulates their vulnerability to neurodevelopmental and psychiatric in vivo, along a core-periphery organisation. We provide convergent evidence that the brains wiring diagram is finely tuned to favour the hierarchical integration of information. Notably, our model successfully recapitulates known empirical results that have not been modelled before, including desynchronisation and flattening of the brains functional hierarchy induced by psychedelic 5HT2A agonists. To catalyse future discoveries, we make this resource freely available to the neuroscience community through an interactive website (https://systematic-causal-mapping.up.railway.app/), where users can interrogate our systematic database of simulated cause-effect relationships. Altogether, we provide a powerful computational engine to predict the functional consequences of experimental or clinical interventions, and drive neuroscientific hypothesis-generation.

neuroscience↗

bioRxiv2025

Comprehensive profiling of anaesthetised brain dynamics across phylogeny

Intrinsic dynamics of neuronal circuits shape information processing. Combining neuroimaging with causal perturbation offers the opportunity to understand how local dynamics mediate the link between neurobiology and functional repertoire. We compile a unique dataset of multi-scale neural activity during wakefulness and anaesthetic-induced suppression of information processing encompassing human, macaque, marmoset, mouse, zebrafish and nematode. Applying massive feature extraction, we comprehensively characterise local neural dynamics across >6,000 time-series features. Using dynamics as a common space for cross-species comparison reveals a conserved dynamical profile of anaesthesia across species, characterised by shorter intrinsic timescales of neural activity and dampened interregional synchrony. This dynamical regime is experimentally reversed in vivo by deep-brain stimulation of the macaque centromedian thalamus, restoring behavioural responsiveness. Spatially, this conserved dynamical phenotype covaries with conserved transcriptional profiles of excitatory and inhibitory neurotransmission across human, macaque, marmoset and mouse cortex. Biophysical modelling provides a mechanistic link between the macroscale dynamical phenotype of anaesthesia, and microscale effects of key molecular targets on the timescales of synaptic excitation and inhibition. Altogether, comprehensive dynamical phenotyping reveals a shared neural endpoint of anaesthesia: across species and scales, anaesthetics induce spatio-temporal isolation of local neural activity.

neuroscience↗

bioRxiv2025

Two Axes of White Matter Development

Despite decades of neuroimaging research, how white matter develops along the length of major tracts in humans remains unknown. Here, we identify fundamental patterns of white matter maturation by examining developmental variation along major, long-range cortico-cortical tracts in youth ages 5-23 years using diffusion MRI from three large-scale, cross-sectional datasets (total N = 2,716). Across datasets, we delineate two replicable axes of human white matter development. First, we find a deep-to-superficial axis, in which superficial tract regions near the cortical surface exhibit greater age-related change than deep tract regions. Second, we demonstrate that the development of superficial tract regions aligns with the cortical hierarchy defined by the sensorimotor-association axis, with tract ends adjacent to sensorimotor cortices maturing earlier than those adjacent to association cortices. These results reveal developmental variation along tracts that conventional tract-average analyses have previously obscured, challenging the implicit assumption that white matter tracts mature uniformly along their length. Such developmental variation along tracts may have functional implications, including mitigating ephaptic coupling in densely packed deep tract regions and tuning neural synchrony through hierarchical development in superficial tract regions - ultimately refining neural transmission in youth.

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bioRxiv2025

Mapping energy metabolism systems in the human brain

Energy metabolism involves a network of biochemical reactions that generate ATP, utilizing substrates such as glucose and oxygen supplied via cerebral blood flow. Energy substrates are metabolized in multiple interrelated pathways that are cell- and organelle-specific. These pathways not only generate energy but are also fundamental to the production of essential biomolecules required for neuronal function and survival. How these complex biochemical processes are distributed over the cortex is integral to understanding the structure and function of the brain. Here, using curated gene sets and whole-brain transcriptomics, we generate maps of five fundamental energy metabolic pathways: glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, oxidative phosphorylation and lactate metabolism. We find consistent divergence between primarily energy-producing pathways and anabolic pathways, particularly in unimodal sensory cortices. We then explore the spatial alignment of these maps with multi-scale structural and functional attributes, including metabolic uptake, neurophysiological oscillations, cell type composition, laminar organization and macro-scale connectivity. Finally, we show that metabolic pathways exhibit unique developmental trajectories from the fetal stage to adulthood. The primary energy-producing pathways peak in late childhood, while the anabolic pentose phosphate pathway shows pronounced expression in the fetal stage and declines throughout life. Together, these results highlight the rich biochemical complexity of energy metabolism organization in the brain.

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bioRxiv2025

Reproducible Brain Charts: An open data resource for mapping brain development and its associations with mental health

Major mental disorders are increasingly understood as disorders of brain development. Large and heterogeneous samples are required to define generalizable links between brain development and psychopathology. To this end, we introduce the Reproducible Brain Charts (RBC), an open data resource that integrates data from 5 large studies of brain development in youth from three continents (N=6,346; 45% Female). Confirmatory bifactor models were used to create harmonized psychiatric phenotypes that capture major dimensions of psychopathology. Following rigorous quality assurance, neuroimaging data were carefully curated and processed using consistent pipelines in a reproducible manner with DataLad, the Configurable Pipeline for the Analysis of Connectomes (C-PAC), and FreeSurfer. Initial analyses of RBC data emphasize the benefit of careful quality assurance and data harmonization in delineating developmental effects and associations with psychopathology. Critically, all RBC data - including harmonized psychiatric phenotypes, unprocessed images, and fully processed imaging derivatives - are openly shared without a data use agreement via the International Neuroimaging Data-sharing Initiative. Together, RBC facilitates large-scale, reproducible, and generalizable research in developmental and psychiatric neuroscience.

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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.

neuroscience↗