Biology subjects

Kaufmann, T.

Publications and source records attributed to Kaufmann, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Conserved tyrosine Y16 acts as a phosphorylation switch controlling Ena/VASP recruitment to sites of actin assembly

Ena/VASP proteins are powerful actin polymerases that accumulate at sites of active actin assembly, including lamellipodial and microspike tips, focal adhesions and pathogen surfaces, where they drive processive filament elongation. However, the mechanisms controlling their recruitment remain elusive. Here, we used cells lacking all Ena/VASP-family members to systematically test phosphomimetic and nonphosphorylatable substitutions at conserved tyrosine and serine residues implicated in subcellular targeting. Combining cell-based reconstitution with biochemical assays, we identify phosphorylation of Y16 in vertebrate Ena/VASP proteins as the decisive inhibitory modification controlling subcellular Ena/VASP recruitment, in contrast to previously proposed roles for Y39 and S157. Corresponding phosphomimetic substitutions in the C. elegans orthologue UNC-34 phenocopied uncoordinated locomotion of UNC-34 null worms, supporting the evolutionary conservation of this regulatory mechanism. Thus, our findings identify a conserved phosphorylation-sensitive switch at the EVH1-FP4 ligand interface that links EVH1-dependent targeting to dynamic control of actin assembly in adhesion, migration and pathogenesis.

cell biology↗

bioRxiv2026

Chromosomal instability shapes spatial and temporal phenotypic diversity in a malignant peripheral nerve sheath tumour

Understanding the spatial and temporal dynamics of tumour evolution is crucial for determining the drivers of cancer progression. Linking genotype to phenotype across a tumour remains challenging, however. Here, we use single-cell and spatial multi-omics to comprehensively profile a primary malignant peripheral nerve sheath tumour (MPNST) and its multifocal recurrence. Combining the native barcoding system from extensive heterogeneity in copy number alterations with mutation data, we resolve the evolutionary tree of this tumour, revealing a branching structure suggestive of ongoing chromosomal instability. We show that gene dosage effects contribute to phenotypic diversity and scale predominantly linearly with copy number. Using spatial genomics assisted by laser capture microdissection and spatial transcriptomics, we performed in situ lineage tracing in this human tumour, elucidating the relationship between local expansions and interactions between tumour cells and the microenvironment. These findings demonstrate the potential of combined bulk, single-cell and spatial techniques to dissect cancer evolution in time and space and link genotype to phenotype in detail.

genomics↗

bioRxiv2026

Whole-brain drug distribution profiles of psychedelic drugs provide insights into rapid antidepressant action

Recent studies pioneered the use of classic hallucinogens as rapid-acting antidepressants (RAAD). To further understand the link between their neuromodulatory and antidepressant effects, we combine pharmacodynamic profiles of four classic hallucinogens and the anaesthetic Ketamine with receptor density distributions from both Positron Emission Tomography (PET) and layer-resoluted autoradiography studies to develop anatomical distribution profiles of drug action strengths giving a comparative measure how strong a drug would act in a region of interest. PET-based, we find high action strengths in association cortices for classic hallucinogens, which we contextualise anatomically using functional and cytoarchitectural measures. Autoradiography-based, we observe high action strengths in the supragranular layer and multimodal temporal areas. Finally, we show how Ketamines affinity to high-affinity subtypes of 5-HT2a and D2 receptors produce classic hallucinogen-like neuroanatomical trends. Through highlighting high RAAD action strengths in regions with emotion processing functionality, our results contribute to a mechanistic understanding of rapid antidepressant action.

neuroscience↗

bioRxiv2026

Brain anatomy in major hormonal transition phases: Longitudinal and cross-sectional volume associations with menarche and menopause

BackgroundHormonal transition phases represent windows of increased neuroplasticity across the female lifespan. In this study, we aim to investigate the brain anatomical architecture of hormonal transition phases by directly comparing menarche, as a period of rising levels of steroid hormones, and menopause, as a time of declining levels. MethodsWe fit linear models on cross-sectional and linear mixed-effect models on longitudinal magnetic resonance imaging (MRI) datasets, to explore the effects of menarche onset (ABCD study data, Ncross-sectional=1274, Nlongitudinal=611) and transition into menopause (UK Biobank data, Ncross-sectional=1614, Nlongitudinal=212) on 66 cortical and 135 subcortical brain volumes, and to identify brain structures with opposing but regional overlapping effects in both periods. Models were adjusted for age and corrected for multiple comparison (P <.05; FDR-corrected). ResultsCross-sectionally, using a between-subject design, 83 brain volumes showed effects of menarche-onset and 17 volumes showed effects of menopause-transition. Of these, seven brain volumes were significantly affected by both transitional periods, showing opposing directional volume changes. Longitudinally, using a within-subject design, 56 brain volumes exhibited menarche effects, of which 46 replicated cross-sectionally. No menopause effect survived correction for multiple comparison, likely due to limited longitudinal sample size. ConclusionOur findings confirm regionally overlapping brain structural alteration between the two hormonal phases - menarche and menopause - showing the hypothesized opposite effect directions. Additionally, our results show the robustness of menarche effects, which converged across cross-sectional and longitudinal study designs. Taken together, our results contribute to a better understanding of hormone related neuroplasticity, emphasizing the importance of not only understanding individual phases, but understanding the overarching patterns across the female reproductive lifespan.

neuroscience↗

bioRxiv2026

Decomposing response inhibition: a POMDP model

Inhibitory control is a core cognitive function whose competence varies across the population, with impairments often observed in psychiatric conditions such as attention deficit hyperactivity disorder (ADHD). The Stop Signal Task (SST) is a widely used paradigm for assessing this ability. However, conventional formalizations of SST performance, such as the independent race model, rely on assumptions that are frequently violated in modern experimental designs. Furthermore, they typically fit only mean reaction times, overlooking crucial trial-by-trial dynamics. To address these limitations, we formalize the SST as a partially observable Markov decision process (POMDP). This framework characterizes inhibitory control with two components: noisy perceptual inference regarding stimuli and optimal control balanced against potential costs. To fit this model to the Adolescent Brain Cognitive Development (ABCD) study baseline cohort (N = 3,567), we introduce Transformer-encoded Simulation-Based Inference (TeSBI). This end-to-end architecture learns compact, sequence-aware embeddings from raw behavioral data. It enables efficient, amortized inference of individual-level posteriors. Extensive validation confirms it extracts reliable and identifiable parameters. We identify distinct latent computational attributes associated with scores on ADHD questionnaires. Controlling for sex, IQ, and medication status, children with higher ADHD scores exhibit subtle but robust shifts in computational attributes. They show a reduction in go cue directional precision, alongside a blunted sensitivity to stop error, go error and time costs. The learned embedding space reveals a continuous manifold in which children with higher ADHD scores are heterogeneously distributed, rather than forming distinct disorder clusters. This indicates that similar clinical characteristics can emerge from diverse combinations of computational mechanisms, supporting a dimensional perspective on neurodiversity. Our end-to-end framework can be extended to a broader range of cognitive tasks. It offers a scalable, theory-driven solution for analyzing large-scale behavioral data.

neuroscience↗

bioRxiv2026

Sex-stratified insights into the genetics of brain volumes in late adulthood

BackgroundThe prevalence, timing and disease course of mental and neurological disorders vary according to sex, yet the neurogenetic mechanisms underlying sex differences in these disorders remain poorly understood. Methods. Here, we explored the genetic architecture of the anatomical volumes of 257 regions of interest across the brain using multivariate genome-wide analyses in 15,740 male and 15,740 female participants from the UK Biobank, matched on age and scan site. ResultsOur findings revealed that the genetics of brain volume is highly similar between females and males in late adulthood. Yet, we found evidence of possible autosomal sex heterogeneity, particularly in the number of brain-volume associated genes, which was higher in females than in males. Variability in the number of identified genes were marked in limbic regions such as the insula, the cingulate cortex, the hippocampus and the amygdala. Conclusion.Overall, our findings contribute to a better understanding of the genetic determinants of brain volumes in males and females. Because neurogenetics may also influence the risk for sex-prevalent brain disorders, the current findings have the potential to facilitate precision medicine approaches in improving prevention strategies and targeted treatments. Plain English summaryMental and neurobiological disorders often differ between females and males. Some disorders are more common in one sex than the other, and symptoms can present or evolve differently. Variation in brain biology, partly shaped by genetic factors, may contribute to these observed patterns. In this study, we investigated genetic factors linked to brain structure in females and males separately. We focused on the volumes of 257 brain regions and analyzed genetic data from more than 30,000 adults from the UK Biobank. Overall, we found that the patterns of association between genetics and brain volumes are largely similar between females and males in late adulthood. At the same time, we observed evidence of sex-dependent patterns, particularly in the number of genes associated with brain volume, which tended to be higher in females than in males. These differences were marked in brain regions involved in the limbic system. Together, our findings improve our understanding of how genetics contribute to brain structure in females and males. HighlightsGenetic influences on brain volumes are largely shared between females and males in late adulthood. Gene-level variability was observed, with a higher number of brain volumes associated genes identified in females than in male, in both multivariate and univariate analyses. This gene-level variability was most pronounced in limbic regions, such as the insular and cingulate cortices.

genetics↗

bioRxiv2025

Inter- and intra-individual differences in brain sex map to neuroendocrine profiles

Sex hormone fluctuations modulate structural and functional brain dynamics, yet little is known how sex steroid levels map onto the expression of sex differences in the brain. Here, we trained machine learning models for brain sex classification based on anatomical structures in cross-sectional data of N = 1090 individuals (50% females, age matched). Applied to dense sampled data of one male and two females in different hormonal states (naturally cycling, oral contraceptive user, pregnancy), we linked inter- and intra-individual fluctuations in brain sex to neuroendocrine modulation. We found lower variation in brain sex across time in the male compared to the female subjects. Oral contraceptive use was associated with a more female-like brain, while (inverted) U-shaped brain sex trajectories emerged across menstrual cycle phases and pregnancy trimesters. Overall, our findings suggest that changes in brain sex capture hormone-related plasticity over time in dense sampled individuals.

neuroscience↗

bioRxiv2025

Traces of parenthood but not pregnancy loss in UK Biobank structural brain MRI data

Pregnancy induces neuroanatomical changes in the human brain. Earlier studies detected traces of motherhood decades after childbirth. It is unclear whether these reflect persisting traces of pregnancy or effects of parenthood. We investigated effects of past birth and of pregnancy loss in women, and effects of fatherhood in men, using univariate and machine learning analyses on 205 regional brain volumes. A group of mothers and an age-matched sample of nulliparous women (N=4357 per group, mean age 63 years) from the UK Biobank, with no past pregnancy losses, showed significant volumetric group differences in 14 regions at Bonferroni-adjusted =.05. Likewise, we identified 18 significant group differences between age-matched samples of fathers and non-fathers of the same size (mean age 63.4), with 9 regions overlapping between sexes. Brain-wide association statistics for past live birth in mothers and those for fatherhood correlated (r = 0.55). XGBoost machine learning models trained to classify parenthood status separately in both datasets showed performance that was low, but significantly above chance (10-fold cross validation: AUC=0.56, p<1e-5 Motherhood classifier, AUC=0.54, p<1e-5, Fatherhood classifier, 10k permutations). We tested the motherhood classification model on an independent test sample comprising of four age-matched groups: 1. women who have never been pregnant, 2. women with past pregnancy loss but no live births, 3. women with live births but no pregnancy loss, and 4. women who experienced both. Class probability was significantly associated with live births, but not past loss. These findings may suggest that neuroanatomical patterns of past childbirth partly also reflect traces of parenthood and not solely persisting traces of past pregnancy, although a more detailed characterization of pregnancy loss data would be needed for full confirmation of this interpretation. Therefore, further research is needed to quantify the extent and understand the nature of these changes, particularly considering the known vulnerability for mental disorders associated with reproductive events.

neuroscience↗

bioRxiv2025

Predicting Developmental Norms from Baseline Cortical Thickness in Longitudinal Studies

BackgroundNormative models have gained popularity in computational psychiatry for studying individual-level differences relative to population norms in biological data such as brain imaging, where measures like cortical thickness are typically predicted from variables such as age and sex. Nearly all published models to date are based on cross-sectional data, limiting their ability to predict longitudinal change. MethodsHere, we used longitudinal brain data from the Adolescent Brain Cognitive Development (ABCD) study, comprising cortical thickness measures from 180 regions per hemisphere in youths at baseline (N=6179; 47% females), 2-year (N=6179; 47% females), and 4-year (N=805; 45% females) follow-up. A training set was established from baseline and 2-year follow-up data (N=5374; 47% females), while data from individuals with all three time points available served as an independent test set (N=805; 45% females). We developed sex-specific Baseline-Conditioned Norms (B-Norms) that predict brain region thickness at follow-up based on baseline thickness, baseline age, and follow-up age, and compared them to sex-specific Cross-Sectional Norms (C-Norms) based on age alone. ResultsOut-of-sample testing in 2-year and 4-year follow-up data showed that B-Norms consistently provided better fits than C-Norms for nearly all cortical regions. Explained variance was higher in B-Norms than in C-Norms. No significant differences between time points (p = 0.45) were detected. Repeated measures ANOVA revealed differences in higher-order moments (e.g., skewness and kurtosis) for both models; for example, skewness varied by model, sex, time point, and their interactions. ConclusionWhile improved fit alone does not necessarily indicate a superior normative model, since normative models aim to capture population variance rather than simply optimize fit, we demonstrated that four regions were associated with pubertal changes in B-Norms but not in C-Norms, suggesting enhanced sensitivity of B-Norms to developmental processes. Together, our findings highlight the potential of B-Norms for capturing normative variation in longitudinal structural brain change. HighlightsO_LIBaseline-Conditioned (B-Norm) models consistently outperform Cross-Sectional (C-Norm) models across all cortical regions. C_LIO_LIB-Norm deviation scores show stronger associations with pubertal progression in females than C-Norm deviations, indicating higher developmental sensitivity. C_LIO_LIThis contrasts with brain-age models, where improved fit typically reduces the association between residuals and downstream clinical or developmental variation. C_LI SummaryNormative modeling has been applied to study how brain measures, such as gray matter thickness or volume, change across development. These models help identify how an individuals brain may differ from what is typical for their age or sex, which could eventually support more personalized treatments. However, most existing models use only one-time (cross-sectional) data, meaning they cannot capture how the brain changes over time. Longitudinal data, tracking the same individuals across multiple time points, is more informative but harder and more expensive to collect. We analyzed brain scans from over 6000 young people in the Adolescent Brain Cognitive Development (ABCD) study, about half of whom were girls. Each participant had brain scans at the start of the study, two and four years later. We showed that Baseline-Conditioned Norms (B-Norms), used each persons first scan and their ages at baseline and follow-up timepoint to predict later brain changes. We compared this to Cross-Sectional Norms (C-Norm), which only used age. B-Norms predicted brain thickness more accurately and importantly were better at detecting brain differences linked to puberty, especially in girls. Although better fit alone does not prove superiority, our findings suggest that using our proposed B-Norms, we potentially also capture more developmental variance suggesting that our B-Norms are possibly more sensitive to sex-specific brain development over time.

neuroscience↗

bioRxiv2025

Optimizing automated sleep stage scoring of 5-second mini-epochs: a transfer learning study

Study objectiveConventional sleep staging relies on 30-second epochs, potentially concealing transient sleep stage intrusion and reducing precision. Building on our previous study of mini-epochs, we investigated whether U-Sleep, an existing automatic deep learning-based sleep staging model with high performance in epochs, could be optimized to similar performance level in 5-second mini-epoch scoring, thereby enabling more detailed sleep characterization. MethodsWe created a dataset of 48,000 human-scored 5-second mini-epochs from 100 PSGs. We compared mini-epochs to human-scored epochs before U-Sleep was optimized using transfer learning and evaluated on a test set. Model performance was assessed using F1-scores, confusion matrices, stage distributions and transition rates comparing scorings of the original U-Sleep before, and the optimized U-Sleep after transfer learning to human-scored mini-epochs. ResultsCompared to human-scored epochs, human-scored mini-epochs captured significantly more transitions (1.70/minute vs. 0.21/minute, p<0.001), and significantly more wake (8.4% versus 5.4%), N1 (7.2% versus 5.4%), and N2 (51.8% versus 40.9%), less N3 (15.4% versus 25.2%) and REM sleep (16.7% versus 23.0%) (all p<0.001). Optimizing U-Sleep improved its performance significantly from F1=0.74 to F1=0.81 (p<0.05) and gave increased transition rates in the test set (original U-Sleep: 1.06/minute, optimized U-Sleep: 1.34/minute, human-scored miniepochs: 1.70/minute). Stage distributions did not differ between optimized U-Sleeps scorings and human-scored mini-epochs. ConclusionsAfter optimization, U-Sleep performance in mini-epochs matched the high performance levels previously reported in both human and automated 30-second epoch scoring. This demonstrates the feasibility of precise, automated high resolution sleep staging. Future work should include external validation and application to full-night recordings. Statement of significanceConventional 30-second epochs limit temporal resolution in sleep staging and may conceal transient intrusions of wake or sleep stages. However, no validated methods are available for highresolution scoring. In this study, we trained and validated the state-of-the-art deep learning model U-Sleep for accurate automatic 5-second mini-epoch scoring using a large dataset of humanscored mini-epochs. The optimized model achieved a high performance, matching levels from previously reported automatic and human epoch scoring. Compared to epoch scoring, miniepochs captured significantly more stage transitions, supporting their ability to uncover sleep dynamics that are otherwise lost. Our findings show the potential of high-resolution sleep staging for more detailed characterization of sleep architecture and demonstrate the feasibility of precise, automatic mini-epoch scoring.

bioengineering↗

bioRxiv2025

Single-cell chromatin landscape and DNA methylation patterns reveal shared molecular programs in human tumor and non-tumor tissue CCR8+ Treg cells

Regulatory T (Treg) cells, a subset of CD4+ T cells, play a crucial role in immunoregulation. Notably, CCR8-expressing Treg cells in tissues also contribute to organ homeostasis and repair. To determine whether these tissue-regenerative programs are active in the tumor microenvironment, we employed single-cell chromatin accessibility and genome-wide DNA methylation analyses to investigate CCR8+ tissue Treg cells isolated from human tumor and adjacent tumor-free tissues. Our findings indicate that CCR8+ tissue Treg cells from tumor and corresponding tumor-free tissues exhibit a high degree of similarity, suggesting that the tumor microenvironment may harbor highly activated tissue Treg cells. This observation was consistent across various tumor types and origins, including primary tumors and metastases. Using quantitative proteomics, we identified several candidate factors associated with the regenerative and suppressive programs of Treg cells, which may serve as potential reservoir of druggable targets for future therapeutic interventions.

immunology↗

bioRxiv2025

Thalamic Nuclei Volumes Across Psychiatric and Neurological Disorders: A Multi-Site Magnetic Resonance Imaging Study

The human thalamus is an integrative hub for multiple cortical and subcortical circuits involved in sensory processing and higher cognitive functions. Thalamic volume differences have been reported across multiple psychiatric and neurological disorders, but previous studies have typically relied on small samples, focused on one or a limited number of disorders, or investigated the thalamus as a whole without considering its functional subdivisions. In this multi-site study, we compared thalamic nuclei volumes across mild cognitive impairment (MCI), dementia (DEM), major depressive disorder, schizophrenia spectrum disorder (SCZ), clinical high risk for schizophrenia, bipolar spectrum disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder, Parkinsons disease, multiple sclerosis (MS), and healthy controls (N > 8 000). Using structural MRI, we segmented 25 bilateral thalamic nuclei, corresponding to six anatomical groups. Linear models revealed that anterior, medial and lateral regions of the thalamus were significantly smaller in several conditions, with largest effects observed for MCI, DEM, SCZ and MS. In contrast, the ventral and intralaminar groups were relatively normal. This pattern of effects largely corresponds to the canonical functional subdivision of the thalamus into higher-order and sensory regions. At the level of individual nuclei, the clinical conditions were associated with distinct patterns of alterations, while left and right lateral geniculate nuclei were implicated in six of the disorders, suggesting a possible relation with circadian and sleep disturbances. Together, the results highlight a role for the higher-order thalamus in common brain disorders and a differential involvement at the nuclei level, refining our understanding of thalamic pathology across common brain disorders.

neuroscience↗

bioRxiv2024

Large transient assemblies of Apaf1 constitute the apoptosome in cells

Upon cell death signals, the apoptotic protease-activating factor Apaf1 and cytochrome c interact to form the apoptosome complex. The apoptosome is crucial for mitochondrial apoptosis, as it activates caspases that dismantle the cell. However, the assembly mechanism and appearance of the apoptosome in vivo remain unclear. We show that upon onset of apoptosis, Apaf1 molecules accumulate into multiple foci per cell. Disassembly of the foci is linked to survival of the cell. Structurally, Apaf1 foci resemble organelle-sized, cloud-like assemblies. Foci form upon specific molecular interactions with cytochrome c and depending on procaspase-9. We propose that Apaf1 foci correspond to the apoptosome in cells. Transientness and ultrastructure of Apaf1 foci suggest that the dynamic spatiotemporal organisation of apoptosome components regulates progression of apoptosis.

cell biology↗

bioRxiv2024

Leveraging Crosslinker Diffusion to Template Stiffness Gradients in Alginate Hydrogels

Mechanobiology drives many important cell biological behaviors such as stem cell differentiation, cancer drug resistance and cell migration up stiffness gradients, a process called durotaxis. The development of 3D hydrogel systems with tunable 2D mechanical gradient patterns affords the ability to study these mechanosensitive cell behaviors to understand cancer invasion or enhance wound healing through directed migration. In this paper, we developed an approach to spatially imprint within alginate hydrogels, gradients in mechanical properties that can be used to probe mechanobiology. Stencils were easily designed and fabricated using a common craft cutter to control the presentation of a calcium crosslinking solution to alginate gels. Different stencil shapes result in different gradients in opacity that can be imprinted into both thick and thin alginate gels of arbitrary 2D shape. The steepness of the opacity gradient as well as the maximum opacity can be controlled based on reproducible crosslinking kinetics regulated through calcium concentration and gradient developing time. Calcium crosslinking results in both opacity changes as well as increases in elastic modulus in the bulk hydrogel. Opacity correlates with elastic modulus, allowing it to be used as a proxy for local elastic modulus. Functionalized alginate gels with collagen and imprinting stiffness gradients within them resulted in cell invasion that was spatially dependent, where stiffer regions facilitated deeper invasion of breast cancer cells. Consequently, this stenciling approach represents a facile way to control stiffness gradients in alginate gels in order to study mechanosensitive cellular behavior. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=45 SRC="FIGDIR/small/599742v2_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@1182404org.highwire.dtl.DTLVardef@1e4bfb1org.highwire.dtl.DTLVardef@e52778org.highwire.dtl.DTLVardef@8237bd_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2022

Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study

Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion MRI). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N=34,029) and ABCD Study (N=8,607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=192 SRC="FIGDIR/small/521181v3_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@1e7eadcorg.highwire.dtl.DTLVardef@ec127eorg.highwire.dtl.DTLVardef@b21f14org.highwire.dtl.DTLVardef@1690c5_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2022

Homunculus Interruptus: A motor association area in the depth of the central sulcus

Cells in the precentral gyrus of the human brain directly send signals to the periphery to generate movement and are topologically organized as a map of the body. We find that movement induced electrophysiological changes from implanted depth electrodes extend this map 3-dimensionally throughout the volume of the gyrus. Unexpectedly, this organization is interrupted by a motor association area in the depths of the central sulcus at its mid-lateral aspect that is active during many different types of movements from both sides of the body.

neuroscience↗

bioRxiv2022

SMITH: Spatially Constrained Stochastic Model for Simulation of Intra-Tumour Heterogeneity

MotivationSimulations of cancer evolution and cellular growth have proven highly useful to study, in detail, the various aspects of intra-tumour heterogeneity, including the effect of selection, mutation rates, and spatial constraints. However, most methods are computationally expensive lattice-embedded models which cannot simulate tumours with a realistic number of cells and rely on various simplifications. Alternatively, well-mixed stochastic models, while efficient and scalable, do not typically include spatial constraints and cannot reproduce the rich clonal dynamics observed in real-world tumours. ResultsWe present SMITH, a simple, efficient, and explainable model of cancer evolution that combines the advantages of well-mixed stochastic models with a new confinement mechanism which limits the growth of clones based on the overall tumour size. We demonstrate that this confinement mechanism is sufficient to induce the rich clonal dynamics observed in spatial models, while allowing for a clear geometric interpretation and efficient simulation of one billion cells within a few minutes on a desktop PC. We explore the extent of stochasticity and rigorously assess the effects of cell turnover, mutation rate, fitness effects and confinement on the resulting clonal structures. Availability and ImplementationSMITH is implemented in C# and freely available at bitbucket.org/schwarzlab/smith together with binaries for all major platforms. For rich visualisations of the simulated clonal dynamics we provide an accompanying Python package PyFish at bitbucket.org/schwarzlab/pyfish. Supplementary informationAll supplementary figures are in the supplementary document.

bioinformatics↗

bioRxiv2022

Interrelated effects of age and parenthood on whole-brain controllability: protective effects of parenthood in mothers

BackgroundControllability is a measure of the brains ability to orchestrate neural activity which can be quantified in terms of properties of the brains network connectivity. Evidence from the literature suggests that aging can exert a general effect on whole-brain controllability. Mounting evidence, on the other hand, suggests that parenthood and motherhood in particular lead to long-lasting changes in brain architecture that effectively slow down brain aging. We hypothesize that parenthood might preserve brain controllability properties from aging. MethodsIn a sample of 814 healthy individuals (aged 33.9{+/-}12.7 years, 522 females), we estimate whole-brain controllability and compare the aging effects in subjects with vs. those without children. We use diffusion tensor imaging (DTI) to estimate the brain structural connectome. The level of brain control is then calculated from the connectomic properties of the brain structure. Specifically, we measure the network control over many low-energy state transitions (average controllability) and the network control over difficult-to-reach states (modal controllability). Results and conclusionIn nulliparous females, whole-brain average controllability increases, and modal controllability decreases with age, a trend that we do not observe in parous females. Statistical comparison of the controllability metrics shows that modal controllability is higher and average controllability is lower in parous females compared to nulliparous females. In men, we observed the same trend, but the difference between nulliparous and parous males do not reach statistical significance. Our results provide strong evidence that parenthood contradicts aging effects on brain controllability and the effect is stronger in mothers.

neuroscience↗