Biology subjects

Forkel, S. J.

Publications and source records attributed to Forkel, S. J..

9 recordsLinked to original sources

bioRxiv2026

Neuroscience in Conversation: Tracking Scientific Change Through an Open Seminar Archive

Scientific talks capture how researchers frame questions, debate ideas, and communicate emerging methods, providing a complementary record of scientific change to the published literature. We investigated whether an open neuroscience seminar archive could reveal shifting scientific attention and contain predictive information about subsequent discourse. We analysed 470 English-language transcripts from the Clinical Neuroanatomy Seminars YouTube channel, spanning 2010-2026 and approximately 2.6 million words, using longitudinal vocabulary analysis, unsupervised topic clustering, conceptual comparisons, and rolling temporal forecasting. The archive captured sustained discussion of language, white matter anatomy, connectivity, clinical neuroscience, and neurobiological mechanisms, alongside changes in their relative prominence. Network-related terminology became more prominent than localisation-related terminology, references to individual variability and computational approaches increased, and open science practices became more visible in scientific discussion. Beyond retrospective description, a regression model predicted keyword frequencies one and two years ahead with approximately 12% and 17% lower mean absolute error, respectively, than a persistence baseline. This modest gain is better explained by smoothing of year-to-year fluctuations than by genuine prediction: terms showing the strongest recent growth tended to fall back rather than continue rising. These findings suggest that spoken scientific discourse shows clear longitudinal change but offers limited evidence of information about subsequent shifts in attention. Interpretation remains grounded in the archive curated scope and changing content composition. By making nearly two decades of freely accessible neuroimaging education amenable to systematic analysis, this study connects open educational practice with the study of science itself. Open seminar archives can serve as reusable research resources, preserving the conversations through which scientific communities develop and revise their ideas.

neuroscience↗

bioRxiv2026

Neurotransmitter circuits of the human language network and their disruption in post-stroke aphasia

Language depends on distributed brain networks whose neurochemical organisation remains largely unknown. Here, we combine large-scale functional MRI, positron-emission tomography-derived receptor and transporter maps, and structural connectomics to characterise the neurotransmitter architecture of the human language network and its disruption in post-stroke aphasia. We show that language circuits are organised by connection class: cortico-cortical pathways are dominated by serotonergic and glutamatergic signalling, thalamo-cortical projections are predominantly cholinergic, and anterior temporal connections show GABAergic circuit enrichment. In 239 stroke patients, aphasia was associated with distinct neurochemical disruption profiles, with lobar lesions showing postsynaptic serotonergic injury and subcortical aphasia showing preferential presynaptic cholinergic or serotonergic disruption. These findings map the neurochemical architecture of the language network and establish a neurotransmitter circuit-level framework for post-stroke aphasia. The post-hoc analysis of four pharmacological trials revealed an association between treatment-to-neurotransmitter matching and aphasia improvement, suggesting that personalised pharmacological strategies may enhance behavioural intervention responsiveness.

neuroscience↗

bioRxiv2025

Lifespan Trajectories of Asymmetry in White Matter Tracts

Asymmetry in white matter is believed to give rise to the brains capacity for specialized processing and is involved in the lateralization of various cognitive processes, such as language and visuo-spatial reasoning. Although studies of white matter asymmetry have been previously documented, they have often been constrained by limited age ranges, sample sizes, or the scope of the tracts and structural features examined. While normative lifespan charts for brain structures are emerging, comprehensive charts detailing white matter asymmetries across numerous pathways and diverse structural measures have been notably absent. This study addresses this gap by leveraging a large-scale dataset of 35,120 typically developing and aging individuals, ranging from 0 to 100 years of age, from 50 primary neuroimaging studies. We generated comprehensive lifespan trajectories for 30 lateralized association and projection white matter tracts, examining 6 distinct microstructural and macrostructural features of these pathways. Our findings reveal that: (1) asymmetries are widespread across the brains white matter and are present in all 30 pathways; (2) for a given pathway, the degree and direction of asymmetry differ between features of tissue microstructure and pathway macrostructure; (3) asymmetries vary across and within pathway types (association and projection tracts); and (4) these asymmetries are not static, following unique trajectories across the lifespan, with distinct changes during development, and a general trend of becoming more asymmetric with increasing age (particularly in later adulthood) across pathways. This study represents the most extensive characterization of white matter asymmetry across the lifespan to date, charting how lateralization patterns emerge, mature, and change throughout life. It provides a foundational resource for understanding the principles of white matter organization from early to late life, its relation to functional specialization and inter-individual variability, and offers a key reference for interpreting deviations during healthy development and aging as well as those associated with clinical populations.

neuroscience↗

bioRxiv2024

The relationship between white matter architecture and language lateralisation in the healthy brain

Interhemispheric anatomical asymmetries have long been thought to be related to language lateralisation. Previous studies have explored whether asymmetries in the diffusion characteristics of white matter language tracts are consistent with language lateralisation. These studies, typically with smaller cohorts, yielded mixed results. This study investigated whether connectomic analysis of quantitative anisotropy (QA) and shape features of white matter tracts across the whole brain are associated with language lateralisation. We analysed 1040 healthy individuals from the Human Connectome Project database. Hemispheric language dominance for each participant was quantified using a laterality quotient (LQ) derived from fMRI activation in regions of interest (ROIs) associated with a language comprehension task compared against a math task. A linear regression model was used to examine the relationship between structural asymmetry and functional lateralisation. Connectometry revealed that LQs were significantly negatively correlated with QA of corpus callosum tracts, including forceps minor, body, tapetum, and forceps major, indicating that reduced language dominance (more bilateral language representation) is associated with increased QA in these regions. The QA of the left arcuate fasciculus, cingulum, and right cerebellar tracts was positively associated with LQ, suggesting that stronger structural asymmetry in these tracts may identify left language dominance. Language lateralisation was not significantly associated with the shape metrics (including length, span, curl, elongation, diameter, volume, and surface area) of all white matter tracts. These results suggest that diffusion measures of microstructural architecture, and not the geometric features of reconstructed white matter tracts, are associated with lateralisation of language comprehension functions. People with increased dependence on both cerebral hemispheres for language processing may have more developed commissural fibres, which may support more efficient interhemispheric communication.

neuroscience↗

bioRxiv2022

Stroke disconnectome decodes reading networks

Cognitive functional neuroimaging has been around for over 30 years and has shed light on the brain areas relevant for reading. However, new methodological developments enable mapping the interaction between functional imaging and the underlying white matter networks. In this study, we used such a novel method, called the disconnectome, to decode the reading circuitry in the brain. We used the resulting disconnection patterns to predict the typical lesion that would lead to reading deficits after brain damage. Our results suggest that white matter connections critical for reading include fronto-parietal U-shaped fibres and the vertical occipital fasciculus (VOF). The lesion most predictive of a reading deficit would impinge on the left temporal, occipital, and inferior parietal gyri. This novel framework can systematically be applied to bridge the gap between the neuropathology of language and cognitive neuroscience.

neuroscience↗

bioRxiv2022

Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain

Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks are linked to cognitive states and pathologies. However, the white matter connections supporting connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network. Using the Human Connectome Project, we generated an atlas of 30 resting-state networks. The method also allows highlighting the overlap between networks, which revealed that most of the brains white matter (89%) is shared between multiple networks, with 16% shared by at least 7 resting-state networks. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the correlations and the communication within resting-state networks. We provide an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage on RSNs. In a first clinical application of the software, we were able to link stroke patients and impacted resting-state networks, showing that their symptoms aligned well with the estimated functions of the networks.

neuroscience↗

bioRxiv2021

The genetic architecture of language functional connectivity

Language is a unique trait of the human species, of which the genetic architecture remains largely unknown. Through language disorders studies, many candidate genes were identified. However, such complex and multifactorial trait is unlikely to be driven by only few genes and case-control studies, suffering from a lack of power, struggle to uncover significant variants. In parallel, neuroimaging has significantly contributed to the understanding of structural and functional aspects of language in the human brain and the recent availability of large scale cohorts like UK Biobank have made possible to study language via image-derived endophenotypes in the general population. Because of its strong relationship with task-based fMRI activations and its easiness of acquisition, resting-state functional MRI have been more popularised, making it a good surrogate of functional neuronal processes. Taking advantage of such a synergistic system by aggregating effects across spatially distributed traits, we performed a multivariate genome-wide association study (mvGWAS) between genetic variations and resting-state functional connectivity (FC) of classical brain language areas in the inferior frontal (pars opercularis, triangularis and orbitalis), temporal and inferior parietal lobes (angular and supramarginal gyri), in 32,186 participants from UK Biobank. Twenty genomic loci were found associated with language FCs, out of which three were replicated in an independent replication sample. A locus in 3p11.1, regulating EPHA3 gene expression, is found associated with FCs of the semantic component of the language network, while a locus in 15q14, regulating THBS1 gene expression is found associated with FCs of the perceptualmotor language processing, bringing novel insights into the neurobiology of language.

genetics↗

bioRxiv2021

Functionnectome: a framework to analyse the contribution of brain circuits to fMRI

In recent years, the field of functional neuroimaging has moved away from a pure localisationist approach of isolated functional brain regions to a more integrated view of these regions within functional networks. However, the methods used to investigate functional networks rely on local signals in grey matter and are limited in identifying anatomical circuitries supporting the interaction between brain regions. Mapping the brain circuits mediating the functional signal between brain regions would propel our understanding of the brains functional signatures and dysfunctions. We developed a novel method to unravel the relationship between brain circuits and functions: The Functionnectome. The Functionectome combines the functional signal from fMRI with white matter circuits anatomy to unlock and chart the first maps of functional white matter. To showcase this new methods versatility, we provide the first functional white matter maps revealing the joint contribution of connected areas to motor, working memory, and language functions. The Functionnectome comes with an open-source companion software and opens new avenues into studying functional networks by applying the method to already existing dataset and beyond task fMRI.

neuroscience↗

bioRxiv2020

Mapping the principal gradient onto the corpus callosum

Gradients capture some of the variance of the resting-state functional magnetic resonance imaging (rsfMRI) signal. Amongst these, the principal gradient depicts a functional processing hierarchy that spans from sensory-motor cortices to regions of the default-mode network. While the cortex has been well characterised in terms of gradients little is known about its underlying white matter. For instance, comprehensive mapping of the principal gradient on the largest white matter tract, the corpus callosum, is still missing. We hence mapped the principal gradient onto the callosal midsection using the 7T human connectome project dataset. We further explored how quantitative measures and variability in callosal midsection connectivity relate to the principal gradient values. In so doing, we demonstrated that the extreme values of the principal gradient are located within the callosal genu and the posterior body, have lower connectivity variability but a larger spatial extent along the midsection of the corpus callosum than mid-range values. Our results shed light on the relationship between the brains functional hierarchy and the corpus callosum. We further speculate about how these results may bridge the gap between functional hierarchy, brain asymmetries, and evolution.

neuroscience↗