Biology subjects

Tillmann, J.

Publications and source records attributed to Tillmann, J..

10 recordsLinked to original sources

bioRxiv2026

Millisecond-scale detection of mouse ultrasonic vocalizations enables closed-loop experiments

Mouse ultrasonic vocalizations (USVs) provide a rapidly evolving readout of social interaction but are typically analysed only after acquisition. Here we introduce DeepFisFis, a waveform-based neural network that detects USVs while they are being produced. DeepFisFis classifies consecutive 5 ms audio segments directly from the waveform with high accuracy, processing each segment in approximately 2.5 ms and therefore faster than the incoming audio stream. This enables ongoing vocalizations to guide experimental interventions in real time. In a deployed closed-loop system, detections triggered an external stimulus, demonstrating online control of ongoing vocal behaviour. DeepFisFis also enables event-triggered data acquisition: gating storage around detected calls preserved more than 99% of vocalization time while retaining only approximately 22% of the continuous recording. DeepFisFis thus transforms USVs from a retrospective behavioural readout into a real-time experimental signal for selective acquisition and closed-loop causal interrogation of vocal communication and its underlying neural circuits.

neuroscience↗

bioRxiv2025

Nanoscale dendritic shaft constrictions shape synaptic integration in fine caliber principal neuron dendrites

Traditionally, theoretical studies typically described dendritic morphology as optimized for efficient synaptic voltage transfer from spines to the soma, implemented as a tubular design respecting Ralls 3/2 rule for impedance matching at branch points. Here, we reveal that this view is an oversimplification. Using three high-resolution imaging techniques, we demonstrate that dendrites in cortical and hippocampal neurons contain nanoscale constrictions, comparable in diameter to spine necks. We provide theoretical and experimental evidence that these constrictions partition the dendrite into distinct electrical compartments, significantly shaping dendritic integration of synaptic potentials.

neuroscience↗

bioRxiv2022

Fine-grained topographic organization within somatosensory cortex during resting-state and emotional face-matching task and its association with ASD traits

BACKGROUNDSensory atypicalities are particularly common in autism spectrum disorders (ASD). Nevertheless, our knowledge about the divergence of the underlying somatosensory region and its association with ASD phenotype features is limited. METHODSWe applied a data-driven approach to map the fine-grained variations in functional connectivity of the primary somatosensory cortex (S1) to the rest of the brain in 240 autistic and 164 neurotypical individuals from the EU-AIMS LEAP dataset, aged between 7 and 30. We estimated the S1 connection topography ( connectopy) during rest and during the emotional face-matching (Hariri) task, an established measure of emotion reactivity, and accessed its association with a set of clinical and behavioral variables. RESULTSWe demonstrated that the S1 connectopy is organized along a dorsoventral axis, mapping onto the somatotopic organization of S1. We found that its spatial characteristics were linked to the individuals adaptive functioning skills, as measured by the Vineland Adaptive Behavior Scales, across the whole sample. Higher functional differentiation characterized the S1 connectopies of individuals with higher daily life adaptive skills. Notably, we detected significant differences between rest and the Hariri task in the S1 connectopies, as well as their projection maps onto the rest of the brain suggesting a task-modulating effect on S1 due to emotion processing. CONCLUSIONSVariation of daily life adaptive skills appears to be reflected in the brains mesoscale neural circuitry, as shown by the S1 connectivity profile, which is also differentially modulated during rest and emotional processing.

neuroscience↗

bioRxiv2021

Excitatory/inhibitory imbalance in autism: the role of glutamate and GABA gene-sets in symptoms and cortical brain structure

BackgroundThe excitatory/inhibitory (E/I) imbalance hypothesis posits that an imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) mechanisms underlies the behavioral characteristics of autism spectrum disorder (autism). However, how E/I imbalance arises and how it may differ across autism symptomatology and brain regions is not well understood. MethodsWe used innovative analysis methods - combining competitive gene-set analysis and gene-expression profiles in relation to cortical thickness (CT)- to investigate the relationship between genetic variance, brain structure and autism symptomatology of participants from the EU-AIMS LEAP cohort (autism=360, male/female=259/101; neurotypical control participants=279, male/female=178/101) aged 6 to 30 years. Competitive gene-set analysis investigated associations between glutamatergic and GABAergic signaling pathway gene-sets and clinical measures, and CT. Additionally, we investigated expression profiles of the genes within those sets throughout the brain and how those profiles relate to differences in CT between autistic and neurotypical control participants in the same regions. ResultsThe glutamate gene-set was associated with all autism symptom severity scores on the Autism Diagnostic Observation Schedule-2 (ADOS-2) and the Autism Diagnostic Interview-Revised (ADI-R) within the autistic group, while the GABA set was associated with sensory processing measures (using the SSP subscales) across all participants. Brain regions with greater gene expression of both glutamate and GABA genes showed greater differences in CT between autistic and neurotypical control participants. ConclusionsOur results suggest crucial roles for glutamate and GABA genes in autism symptomatology as well as CT, where GABA is more strongly associated with sensory processing and glutamate more with autism symptom severity.

neuroscience↗

bioRxiv2020

Attenuated Anticipation of Social and Monetary Rewards in Autism Spectrum Disorders

BackgroundReward processing has been proposed to underpin atypical social behavior, a core feature of autism spectrum disorder (ASD). However, previous neuroimaging studies have yielded inconsistent results regarding the specificity of atypicalities for social rewards in ASD. Utilizing a large sample, we aimed to assess altered reward processing in response to reward type (social, monetary) and reward phase (anticipation, delivery) in ASD. MethodsFunctional magnetic resonance imaging during social and monetary reward anticipation and delivery was performed in 212 individuals with ASD (7.6-30.5 years) and 181 typically developing (TD) participants (7.6-30.8 years). ResultsAcross social and monetary reward anticipation, whole-brain analyses (p<0.05, family-wise error-corrected) showed hypoactivation of the right ventral striatum (VS) in ASD. Further, region of interest (ROI) analysis across both reward types yielded hypoactivation in ASD in both the left and right VS. Across delivery of social and monetary reward, hyperactivation of the VS in individuals with ASD did not survive correction for multiple comparisons. Reward type by diagnostic group interactions, and a dimensional analysis of autism trait scores were not significant during anticipation or delivery. Levels of attention-deficit/hyperactivity disorder (ADHD) symptoms did not affect reward processing in ASD. ConclusionsOur results do not support current theories linking atypical social interaction in ASD to specific alterations in processing of social rewards. Instead, they point towards a generalized hypoactivity of VS in ASD during anticipation of both social and monetary rewards. We suggest that this indicates attenuated subjective reward value in ASD independent of social content and ADHD symptoms.

neuroscience↗

bioRxiv2020

Gray matter covariations and core symptoms of autism. The EU-AIMS Longitudinal European Autism Project

BackgroundVoxel-based Morphometry (VBM) studies in Autism Spectrum Disorder (autism) have yielded diverging results. This might partly be attributed to structural alterations being associating with the combined influence of several regions rather than with a single region. Further, these structural covariation differences may relate to continuous measures of autism rather than with categorical case-control contrasts. The current study aimed to identify structural covariation alterations in autism, and assessed canonical correlations between brain covariation patterns and core autism symptoms. MethodsWe studied 347 individuals with autism and 252 typically developing individuals, aged between 6 and 30 years, who have been deeply phenotyped in the Longitudinal European Autism Project (LEAP). All participants VBM maps were decomposed into spatially independent components using Independent Component Analysis. A Generalized Linear Model (GLM) was used to examine case-control differences. Next, Canonical Correlation Analysis (CCA) was performed to separately explore the integrated effects between all the brain sources of gray matter variation and two sets of core autism symptoms. ResultsGLM analyses showed significant case-control differences for two independent components. The first component was primarily associated with decreased density of bilateral insula, inferior frontal gyrus, orbitofrontal cortex, and increased density of caudate nucleus in the autism group relative to typically developing individuals. The second component was related to decreased densities of the bilateral amygdala, hippocampus, and parahippocampal gyrus in the autism group relative to typically developing individuals. The CCA results showed significant correlations between components that involved variation of thalamus, putamen, precentral gyrus, frontal, parietal, and occipital lobes, and the cerebellum, and repetitive, rigid and stereotyped behaviors and abnormal sensory behaviors in autism individuals. LimitationsOnly 55.9% of the participants with autism had complete questionnaire data on continuous parent-reported symptom measures. ConclusionsCovaried areas associated with autism diagnosis and/or symptoms are scattered across the whole brain and include the limbic system, basal ganglia, thalamus, cerebellum, precentral gyrus, and parts of the frontal, parietal, and occipital lobes. Some of these areas potentially subserve social-communicative behavior whereas others may underpin sensory processing and integration, and motor behavior.

neuroscience↗

bioRxiv2020

Towards robust and replicable sex differences in the intrinsic brain function of autism

BackgroundMarked sex differences in autism prevalence accentuate the need to understand the role of biological sex-related factors in autism. Efforts to unravel sex differences in the brain organization of autism have, however, been challenged by the limited availability of female data. MethodsWe addressed this gap by using a large sample of males and females with autism and neurotypical (NT) control individuals (ABIDE; Autism: 362 males, 82 females; NT: 409 males, 166 females; 7-18 years). Discovery analyses examined main effects of diagnosis, sex and their interaction across five resting-state fMRI (R-fMRI) metrics (voxel-level Z > 3.1, cluster-level P < 0.01, gaussian random field corrected). Secondary analyses assessed the robustness of the results to different pre-processing approaches and their replicability in two independent samples: the EU-AIMS Longitudinal European Autism Project (LEAP) and the Gender Explorations of Neurogenetics and Development to Advance Autism Research (GENDAAR). ResultsDiscovery analyses in ABIDE revealed significant main effects across the intrinsic functional connectivity (iFC) of the posterior cingulate cortex, regional homogeneity and voxel-mirrored homotopic connectivity (VMHC) in several cortical regions, largely converging in the default network midline. Sex-by-diagnosis interactions were confined to the dorsolateral occipital cortex, with reduced VMHC in females with autism. All findings were robust to different pre-processing steps. Replicability in independent samples varied by R-fMRI measures and effects with the targeted sex-by-diagnosis interaction being replicated in the larger of the two replication samples - EU-AIMS LEAP. LimitationsGiven the lack of a priori harmonization among the discovery and replication datasets available to date, sample-related variation remained and may have affected replicability. ConclusionsAtypical cross-hemispheric interactions are neurobiologically relevant to autism. They likely result from the combination of sex-dependent and sex-independent factors with a differential effect across functional cortical networks. Systematic assessments of the factors contributing to replicability are needed and necessitate coordinated large-scale data collection across studies.

neuroscience↗

bioRxiv2020

Differential functional neural circuitry behind autism subtypes with marked imbalance between social-communicative and restricted repetitive behavior symptom domains

Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here we developed a phenotypic stratification model that makes highly accurate (97-99%) out-of-sample SC=RRB, SC>RRB, and RRB>SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n=509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC>RRB and visual association circuitry in SC=RRB. The SC=RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.

neuroscience↗

bioRxiv2020

Atypical brain asymmetry in autism - a candidate for clinically meaningful stratification

BackgroundAutism Spectrum Disorder (henceforth autism) is a highly heterogeneous neurodevelopmental condition with few effective treatments for core and associated features. To make progress we need to both identify and validate neural markers that help to parse heterogeneity to tailor therapies to specific neurobiological profiles. Atypical hemispheric lateralization is a stable feature across studies in autism, however its potential of lateralization as a neural stratification marker has not been widely examined. MethodsIn order to dissect heterogeneity in lateralization in autism, we used the large EU-AIMS Longitudinal European Autism Project dataset comprising 352 individuals with autism and 233 neurotypical (NT) controls as well as a replication dataset from ABIDE (513 autism, 691 NT) using a promising approach that moves beyond mean-group comparisons. We derived grey matter voxelwise laterality values for each subject and modelled individual deviations from the normative pattern of brain laterality across age using normative modeling. ResultsResults showed that individuals with autism had highly individualized patterns of both extreme right- and leftward deviations, particularly in language-, motor- and visuospatial regions, associated with symptom severity. Language delay (LD) explained most variance in extreme rightward patterns, whereas core autism symptom severity explained most variance in extreme leftward patterns. Follow-up analyses showed that a stepwise pattern emerged with individuals with autism with LD showing more pronounced rightward deviations than autism individuals without LD. ConclusionOur analyses corroborate the need for novel (dimensional) approaches to delineate the heterogeneous neuroanatomy in autism, and indicate atypical lateralization may constitute a neurophenotype for clinically meaningful stratification in autism.

neuroscience↗

bioRxiv2018

Reproducible functional connectivity alterations are associated with autism spectrum disorder

Despite the high clinical burden little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here we address these questions in the most comprehensive, large-scale effort to date comprising evaluation of four large ASD cohorts. We followed a strict exploration and replication procedure to identify core rs-fMRI functional connectivity (degree centrality) alterations associated with ASD as compared to typically developing (TD) controls (ASD: N=841, TD: N=984). We then tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status and clinical symptom severity. We find reproducible patterns of ASD-associated functional hyper- and hypo-connectivity with hypo-connectivity being primarily restricted to sensory-motor regions and hyper-connectivity hubs being predominately located in prefrontal and parietal cortices. We establish shifts in between-network connectivity from outside to within the identified regions as a key driver of these abnormalities. The magnitude of these alterations is linked to core ASD symptoms related to communication and social interaction and is not affected by age, sex or medication status. The identified brain functional alterations provide a reproducible pathophysiological phenotype underlying the diagnosis of ASD reconciling previous divergent findings. The large effect sizes in standardized cohorts and the link to clinical symptoms emphasize the importance of the identified imaging alterations as potential treatment and stratification biomarkers for ASD.

neuroscience↗