Biology subjects

Oestreich, L. K. L.

Publications and source records attributed to Oestreich, L. K. L..

7 recordsLinked to original sources

bioRxiv2026

Neurite Complexity and Plasticity Markers Track Synaptic Vesicle Density in the Living Human Brain: A Multimodal PET-MRI-EEG Study

Neuroplasticity, the brain's capacity to reorganise its structure and function, is a transdiagnostic feature across psychiatric and neurodegenerative diseases and a putative mechanism of action for pharmacological interventions. [11C]-UCBJ positron emission tomography (PET), which quantifies synaptic vesicle glycoprotein 2A (SV2A) density, offers the most direct in vivo measure of human synaptic density, but its relationship to complementary, more scalable neuroimaging measures of structural and functional plasticity remains uncharacterised. We combined [11C]-UCBJ PET, diffusion weighted imaging (DWI/NODDI), resting-state functional magnetic resonance imaging (rs-fMRI), and electroencephalography (EEG)-based sensory tasks (roving mismatch negativity, MMN; visual long-term potentiation, vLTP) in 18 healthy volunteers to test the relationship between synaptic terminal SV2A density and complementary structural and functional neuroplasticity measures, and whether these relationships were reproducible following pharmacological challenge with ketamine (n = 11) or N,N-dimethyltryptamine (DMT; n = 7). There were no statistically significant differences in PET-derived SV2A binding potential (BPND), DWI-derived neurite orientation dispersion (ODI) and structural weighted degree (SWD), EEG-derived MMN repetition suppression, and late-phase vLTP P2 potentiation, 1 to 8 days following DMT and ketamine exposure compared to baseline. BPND was coupled with ODI across cortical regions before and after pharmacological challenge, and this relationship was tighter within visual, attentional, and frontoparietal control brain networks. SWD showed a weaker, more spatially restricted association with BPND, primarily in regions belonging to the limbic and visual brain networks, but was not replicated post-drug. No consistent association was found between BPND and functional weighted degree (FWD), derived from rs-fMRI, at baseline or after pharmacological challenge. Frontotemporal BPND was positively associated with MMN repetition suppression (r = 0.61), and occipital BPND with late-phase vLTP P2 potentiation (r = 0.54), with the MMN-BPND association replicating after pharmacological challenge (r = 0.49). These findings link synaptic terminal SV2A density in the living human brain to neurite architecture and the capacity for short-term and Hebbian-like long-term synaptic plasticity, while dissociating these relationships from generic functional connectivity and magnitude of sensory-evoked responses. These data provide cross-modal validation for DWI- and EEG-derived measures as biological indices and surrogate measures of human synaptic plasticity.

neuroscience↗

bioRxiv2026

An updated roadmap for brain-mental health associations in the UK Biobank

The UK Biobank offers an unprecedented opportunity to examine associations between brain imaging and mental health at scale, but their magnitude and replicability remain unclear. We correlated 17,580 imaging-derived phenotypes across seven MRI modalities with 309 mental health phenotypes in 8,415 participants, split into discovery and validation subsets. Associations were generally small (median |r| = 0.018; top 1% of 0.108), and they replicated poorly: only 9.0% of significant discovery associations were significant in validation. Eating disorders showed the largest effects of any mental disorders but replicated in only 6.0% of cases, whereas substance use showed the highest replication (14.5%). Susceptibility-weighted imaging produced the most replicable imaging associations. Longitudinal changes in brain and mental health measures were weakly related. We provide an interactive dashboard that returns the effect-size and replicability benchmarks for any combination of mental health category and imaging modality, supporting variable selection and study design in UK Biobank research.

neuroscience↗

bioRxiv2025

MRI-Derived Markers of Acute and Chronic Inflammatory Processes in the VTA Associated with Depression

BackgroundDepression is a leading cause of disability worldwide, with inflammation increasingly recognized as a contributing factor. Inflammatory processes can disrupt the brains reward circuitry, particularly the ventral tegmental area (VTA), which is central to dopamine-mediated motivation and reward. This study investigates whether MRI-derived markers sensitive to neuroinflammation and microstructure in the VTA are associated with depression diagnosis and symptom severity. MethodsWe analyzed diffusion weighted imaging and quantitative susceptibility mapping data from 32,495 UK Biobank participants, including 3,807 individuals with ICD-10 diagnosed depression. Metrics sensitive to neuroinflammation (free water [FW], isotropic volume fraction [ISOVF], magnetic susceptibility) and microstructure (intracellular volume fraction [ICVF], orientation dispersion index [ODI] volume) were extracted from the VTA. Group differences between the major depression group and BMI, sex, and age-matched healthy controls were assessed using ANOVAs and linear regression was used to predict acute symptom severity based on Recent Depressive Symptoms scores. ResultsParticipants with depression diagnosis had significantly higher FW (p < 0.001) and ISOVF (p = 0.001) compared to HCs, indicating increased extracellular processes such as inflammation in the VTA. Lower ISOVF ({beta} = -0.46, p = 0.017) and higher ICVF ({beta} = 0.34, p = 0.007) and ODI ({beta} = 0.49, p = 0.004) were associated with higher depression severity, independent of depressive diagnosis history. ConclusionsOur findings reveal distinct patterns of VTA microstructural changes associated with depression history versus acute depressive symptom severity, suggesting different underlying pathophysiological mechanisms. Distinct patterns of neuroinflammation may differentiate acute from chronic depression, informing targeted interventions.

neuroscience↗

bioRxiv2023

White matter microstructure is associated with the precision of visual working memory

Visual working memory is critical for goal-directed behaviour as it maintains continuity between previous and current visual input. Functional neuroimaging studies have shown that visual working memory relies on communication between distributed brain regions, which implies an important role for long-range white matter connections in visual working memory performance. Here, we characterised the relationship between the microstructure of white matter association tracts and the precision of visual working memory representations. To that purpose, we devised a delayed estimation task which required participants to reproduce visual features along a continuous scale. A sample of 80 healthy adults performed the task and underwent diffusion-weighted MRI. We applied mixture distribution modelling to quantify the precision of working memory representations and guess rates, both of which contribute to observed responses. Latent components of tract-specific microstructural indices were identified by principal component analysis. Higher working memory precision was associated with lower bulk diffusion across ten tracts of interest and higher directionality of diffusion in a group of frontoparietal-occipital tracts. Importantly, there was no association between guess rates and any of the structural components. Our findings suggest that microstructural properties of white matter tracts connecting posterior and frontal brain regions mediate, in a functionally specific manner, the precision of visual working memory.

neuroscience↗

bioRxiv2018

White matter connectivity disruptions in the pre-clinical continuum of psychosis: A connectome study

BackgroundWidespread white matter disruptions in schizophrenia have been commonly reported, but it remains unanswered whether these abnormalities are associated with schizophrenia specifically or whether they range along a psychotic continuum into the healthy population. Investigating the extent of white matter connectivity disruptions specific to psychotic-like experiences in healthy individuals is insofar important as it is a necessary first step towards the development of prodromal psychosis biomarkers.\n\nMethodsHigh resolution, multi-shell diffusion-weighted magnetic resonance images were acquired from 89 healthy individuals. Whole-brain white matter fiber tracking was performed to quantify the strength of white matter connections. Network-based statistics were applied to white matter connections in a regression model in order to test for a linear relationship between streamline count and psychotic-like experiences.\n\nResultsA significant subnetwork was identified whereby streamline count declined with increasing quantity of psychotic-like experiences. This network of significant connectivity reductions affected all cortical lobes, subcortical structures and the cerebellum.\n\nConclusionA widespread network of linearly declining connectivity strength with increasing number of psychotic-like experiences was identified in healthy individuals. This finding is in line with white matter connectivity reductions reported from early to chronic stages of schizophrenia. We suggest that these white matter changes might be a potential biomarker for the identification of individuals at high risk for transitioning to psychosis.

neuroscience↗

bioRxiv2018

Structural connectivity facilitates functional connectivity of auditory prediction error generation within a fronto-temporal network

Auditory prediction errors, i.e. the mismatch between predicted and actual auditory input, are generated by a hierarchical functional network of cortical sources. This network is also interconnected by auditory white matter pathways. Hence it would be reasonable to assume that these structural and functional networks are quantitatively related, which is what the present study set out to investigate. Specifically, whether structural connectivity of auditory white matter pathways enables effective connectivity of auditory prediction error generation. Eighty-nine participants underwent diffusion weighted magnetic resonance imaging. Anatomically-constrained tractography was used to extract auditory white matter pathways, namely the bilateral arcuate fasciculus, the inferior occipito-frontal fasciculi (IOFF), and the auditory interhemispheric pathway, from which Apparent Fibre Density (AFD) was calculated. The same participants also underwent a stochastic oddball paradigm, which was used to elicit prediction error responses, while undergoing electroencephalographic recordings. Dynamic causal modelling (DCM) was used to investigate the effective connectivity of auditory prediction error generation in brain regions interconnected by the above mentioned auditory white matter pathways. Brain areas interconnected by all auditory white matter pathways best explained the dynamics of auditory prediction error responses. Furthermore, AFD in the right IOFF and right arcuate fasciculus significantly predicted the effective connectivity parameters underlying auditory prediction error generation. In conclusion, the generation of auditory prediction errors within an effectively connected, fronto-temporal network was found to be facilitated by the structural connectivity of auditory white matter pathways. These findings build upon the notion that structural connectivity facilitates dynamic interactions within brain regions that are effectively connected.\n\nSignificance statementThe brain continuously generates and updates hypotheses that predict forthcoming sensory input. Within the auditory domain, it has repeatedly been reported that these predictions about the auditory environment are facilitated by specific functional cortical connections. These functionally connected brain regions are also structurally connected via auditory white matter pathways. For the first time, this study provides quantitative evidence for a structural basis along which this functional network of auditory prediction error generation operates. This finding provides evidence for the notion that the functional connectivity of dynamically interacting brain areas is facilitated by structural connectivity amongst these brain areas.

neuroscience↗

bioRxiv2017

The functional anatomy of self-generated and predictable speech

Sensory attenuation refers to the cortical suppression of self-generated sensations relative to externally-generated sensations. This attenuation of cortical responsiveness is the result of internal forward models which make precise predictions about forthcoming sensations. Forward models of sensory attenuation in the auditory domain are thought to operate along auditory white matter pathways such as the arcuate fasciculus and the frontal aslant. The aim of this study was to investigate whether brain regions that are structurally connected via these white matter pathways are also effectively connected during overt speech, as well as as when listening to externally-generated speech that is temporally predictable via a visual cue. Using Electroencephalography (EEG) and Dynamic Causal Modelling (DCM) we investigated network models that link the primary auditory cortex to Wernickes and Brocas area either directly or indirectly through Geschwinds territory, which are structurally connected via the arcuate fasciculus. Connections between Brocas and supplementary motor area, which are structurally connected via the frontal aslant, were also included. Our results revealed that bilateral areas interconnected by indirect and direct pathways of the arcuate fasciculus, in addition to regions interconnected by the frontal aslant best explain the EEG responses to both self-generated speech, and speech that is externally-generated but temporally predictable. These findings indicate that structurally connected brain regions thought to be involved in auditory attenuation are also effectively connected. Critically, our findings expand on the notion of internal forward models, whereby sensory consequences of our actions are internally predicted and reflected in reduced cortical responsiveness to these sensations.\n\nHighlightsO_LIEffective connectivity of auditory attenuation to self-generated and predictable speech\nC_LIO_LIEEG and DCM were used to investigate several plausible network models\nC_LIO_LIStructurally connected brain areas of auditory attenuation are effectively connected\nC_LIO_LIInternal forward models modulate self-generated and predictable speech\nC_LI

neuroscience↗