Biology subjects

Hauke, D. J.

Publications and source records attributed to Hauke, D. J..

4 recordsLinked to original sources

bioRxiv2026

Fronto-Temporal Dysconnectivity and Cortical Excitability in High Schizotypy: Associations with Symptom Dimensions

BackgroundPsychosis has been conceptualised as a continuum extending from healthy individuals with psychotic-like experiences to clinical populations with schizophrenia. It is unclear which biological mechanisms found in chronic schizophrenia extend across the psychosis continuum to healthy individuals with high positive schizotypy (HS). In this study, we used computational modeling to test whether changes in effective connectivity and excitation/inhibition (E/I) balance reported in schizophrenia are also found in HS. MethodsA total of 2425 individuals from the general population were screened for HS. A subset (N=141) was invited for in-depth phenotyping. Resting-state functional magnetic resonance imaging (rsfMRI) and proton magnetic resonance spectroscopy (1H-MRS) were recorded in n=69 HS individuals and n=72 group-matched controls with low schizotypy (LS). We used dynamic causal modeling to estimate effective connectivity between bilateral primary auditory cortex (A1), superior temporal gyrus (STG), and inferior frontal gyrus (IFG). ResultsBilateral backward connectivity from IFG to STG was significantly reduced in HS compared to LS. Widespread cortical disinhibition in the auditory cortex-IFG network correlated with more severe positive schizotypy scores and impulsive nonconformity. Reduced excitability in the same network was correlated with stronger cognitive disorganisation. ConclusionsOur results favour a psychosis-continuum hypothesis, suggesting that reduced top-down drive from frontal cortex and compensatory allostatic upregulation of cortical excitability, as observed in chronic schizophrenia, also extend to groups with sub-clinical psychotic symptoms. Frontal cortex dysfunction may serve as a biologically interpretable biomarker of psychosis risk and a target for preventative interventions.

neuroscience↗

bioRxiv2025

Ketamine and Psilocybin Differentially Impact Sensory Learning During the Mismatch Negativity

Ketamine and psilocybin show potential as therapies for various mental illnesses, including major depressive disorder. However, further investigation into their neural mechanisms is required to understand their effects on the brain. By combining computational modelling with electroencephalography (EEG), we examine the effects of ketamine and psilocybin on hierarchical sensory pwPE learning in the context of the auditory mismatch negativity, an event-related potential consistently shown to be reduced under psychotomimetic interventions. We employed a Bayesian framework and re-analyzed a previously acquired EEG dataset (Schmidt et al., 2012) by modelling single-trial EEG data using the Hierarchical Gaussian Filter. Using a placebo-controlled within-subject crossover design, healthy subjects were administered either S-ketamine or psilocybin during an auditory roving paradigm of pure sinusoidal tones. Our findings elucidate distinct neural impacts of ketamine and psilocybin on sensory learning: ketamine led to a larger reduction in the effect of sensory precision compared to placebo from 207 to 316 ms peaking at 277 ms in the frontal central channels, while psilocybin showed no significant effect. Both drugs reduced the expression of belief precision between 160 to 184 ms, peaking at 172 ms. For higher-level volatility pwPEs, ketamine reduced the expression at 312 ms while psilocybin had a null effect. For perception of elementary imagery, ketamine had a greater effect than psilocybin on sensory and volatility precision, while psilocybin had a greater effect on volatility pwPEs. Our findings suggest hallucinogens have distinct effects on sensory learning that could inform tailored therapies for major depression.

neuroscience↗

bioRxiv2025

A Canonical Microcircuit for Estimating Excitation/Inhibition (E/I) Balance

Excitation/inhibition (E/I) balance is crucial for maintaining healthy brain function and can be disrupted in various neurological and psychiatric disorders. Despite its importance, there are few tools to study E/I balance non-invasively in humans. Here, we propose a canonical microcircuit model to estimate E/I balance from non-invasive magneto- and electroencephalography (M/EEG) recordings by parameterising global pyramidal and inhibitory cell excitability. We first establish that E/I parameters are identifiable and recoverable. We then explore the effects of these new parameters and their interaction with other parameters in a series of simulations. To highlight the clinical relevance of this new model, we simulate changes in E/I balance and their impact on event-related potentials (ERPs) derived from paired-click, passive and active oddball paradigms, which are among the most robust clinical biomarkers of schizophrenia. Our simulations show that a loss of pyramidal cell excitability can explain reduced ERP amplitudes across all three paradigms, mirroring empirical findings in schizophrenia. This method may serve as a computational assay for estimating synaptopathy and E/I balance from non-invasive M/EEG recordings across various clinical conditions thereby advancing efforts to develop personalised interventions to restore E/I balance.

neuroscience↗

bioRxiv2022

The effect of lysergic acid diethylamide (LSD) on whole-brain functional and effective connectivity

Psychedelics have emerged as promising candidate treatments for various psychiatric conditions, and given their clinical potential, there is a need to identify biomarkers that underlie their effects. Here, we investigate the neural mechanisms of lysergic acid diethylamide (LSD) using regression dynamic causal modelling (rDCM), a novel technique that assesses whole-brain effective connectivity (EC) during resting-state functional magnetic resonance imaging (fMRI). We modelled data from two randomized, placebo-controlled, double-blind, cross-over trials, in which 45 participants were administered 100g LSD and placebo in two resting-state fMRI sessions. We compared EC against whole-brain functional connectivity (FC) using classical statistics and machine learning methods. Multivariate analyses of EC parameters revealed widespread increases in interregional connectivity and reduced self-inhibition under LSD compared to placebo, with the notable exception of primarily decreased interregional connectivity and increased self-inhibition in occipital brain regions. This finding suggests that LSD perturbs the Excitation/Inhibition balance of the brain. Moreover, random forests classified LSD vs. placebo states based on FC and EC with comparably high accuracy (FC: 85.56%, EC: 91.11%) suggesting that both EC and FC are promising candidates for clinically-relevant biomarkers of LSD effects.

neuroscience↗