Biology subjects

Horacek, J.

Publications and source records attributed to Horacek, J..

9 recordsLinked to original sources

bioRxiv2026

EEG microstate dynamics during psilocybin intoxication relate to acute experience and persisting psychological changes

Psilocybin and other serotonergic psychedelics show therapeutic promise for psychiatric disorders, yet objective neural correlates linking the acute psychedelic state to persisting psychological outcomes remain limited. Electroencephalography (EEG) microstate analysis characterizes the rapid spatiotemporal organization of large-scale brain activity, offering a millisecond-resolution window into neural dynamics. Here, we examined resting-state EEG microstates in 15 healthy volunteers who participated in a double-blind, randomized, placebo-controlled crossover study of psilocybin, using both data-driven (three-microstate) and canonical (four-microstate) analysis solutions. EEG was recorded at five time points spanning pre-drug baseline, peak intoxication, and recovery. Psilocybin significantly increased the number of global field power (GFP) peaks and reduced microstate lifespan while increasing frequency of occurrence during peak intoxication (50-100 min post-administration), consistent with accelerated transitions between brain states. Notably, microstate coverage was largely preserved, with only a transient difference at peak intoxication in the 2-20 Hz band-width, suggesting that access to the repertoire of canonical brain states is broadly maintained despite altered temporal dynamics. Critically, individual differences in microstate dynamics during peak intoxication correlated with both acute subjective experience intensity and self-reported psychological changes measured 28 days post-administration, providing exploratory evidence for a link between acute neural dynamics and longer-term experiential outcomes in healthy volunteers. These findings suggest that psilocybin is associated with altered temporal organization of large-scale brain dynamics with largely preserved microstate coverage, and identify EEG microstates as candidate neural markers for psychedelic-induced alterations in consciousness with potential relevance to therapeutic research.

neuroscience↗

bioRxiv2026

Replication Challenges in Linking Personality to Resting-State Functional Connectomics

An increasing number of studies are currently focusing on personality neuroscience, a term denoting the research aimed at neuroimaging correlates of inter-individual temperament and character variability. Among other methods, a graph theoretical analysis of the functional connectivity in resting-state functional magnetic resonance imaging data was applied in a study by Gao et al. (2013), reporting novel functional connectivity correlates of personality traits. The current paper presents a conceptual replication of the results of this study and discusses the related challenges, including an extension of the original statistical methods in order to illustrate the effect of the multiple comparison problem. Five personality dimensions were obtained using the revised Big Five Personality Inventory, including scores of Extraversion and Neuroticism covered in the original paper. Using a larger sample (84 subjects) with adequate statistical power (ranging from 0.75 to 0.95 across analyses), we failed to replicate any of the nine specific neuroimaging correlates of personality presented by Gao et al. While acknowledging differences in the experimental procedures, we discuss that the lack of replication might be caused by the relatively liberal control of false positives in the original study. Indeed, the original testing scheme leads to an expected count of about 10 false positive observations among all tests; applying this scheme to our data we observed a similar number of positive tests, albeit for different relations. No significant correlations were found in our data when standard family-wise error control was applied. These results illustrate the importance of combining exploration with independent validation, use of large datasets, as well as appropriate control of multiple comparison problem in order to prevent false alarms in research into neural substrates of personality differences. Importantly, our findings do not disprove the existence of a link between personality and the brains intrinsic functional architecture; but rather suggest that such a link might be even more subtle and elusive than previously reported.

neuroscience↗

bioRxiv2025

Impact of Connectivity Granularity: A Comparison of ROI and Network-Level Approaches for Early Schizophrenia Classification

While schizophrenia diagnosis relies on clinical interviews, there is growing interest in neuroimaging-based computational tools to aid classification. In particular, resting-state fMRI-derived functional connectivity has been explored as a potential biomarker, with applications not only in supporting clinical assessment but also in research contexts such as patient stratification and probing disease mechanisms. Here, we compare two common approaches to computing functional connectivity - region of interest (ROI)-level and brain network-level - and evaluate their predictive power for classifying first-episode schizophrenia patients, in contrast to most prior work focusing on chronic patients. We show that ROI-level features consistently outperform network-level features. Despite the simplicity of our classification models, we achieved accuracies up to 83.15% using the AAL90 atlas. We also found that non-lagged functional connectivity generally outperforms lagged variants, suggesting that added temporal complexity may introduce noise rather than improve predictive power. Overall, our findings highlight region-based connectivity from a medium-resolution atlas as a promising representation for early-stage schizophrenia classification, while emphasising the need for validation on independent datasets to confirm generalisability.

neuroscience↗

bioRxiv2025

Unsupervised Approach for Electric Signal Separation in Gnathonemus petersii: Linking Behavior and Electrocommunication

The transfer of information between individuals is fundamental to living systems. Therefore, communication should be studied in various species. Weakly electric fish, Gnathonemus petersii, provides a unique model organism for such investigations due to its advanced electrocommunication capabilities, using electric organ discharges (EODs). Separating EODs from multiple individuals is crucial yet challenging. To remediate it, we developed an unsupervised algorithm for EOD separation in two free-swimming individuals. Using continuous wavelet transform, t-distributed Stochastic Neighbor Embedding, and hierarchical clustering, we achieved accurate discrimination of EODs without the necessity of any training data. This approach overcomes the supervised algorithms based on previously published methods in accuracy and computational efficiency, simplifies experimental procedures, and supports animal well-being by reducing the number of required measurements. Additionally, we introduced a novel technique to map electric signals onto auditory representations, facilitating intuitive analysis of EOD sequences. These advancements lay the groundwork for future studies of EOD-based communication, highlighting the potential of Gnathonemus petersii in neuroethological, psychopharmacological, and translational research.

animal behavior and cognition↗

bioRxiv2024

Resting-state hyper- and hypo-connectivity in early schizophrenia: which tip of the iceberg should we focus on?

In this study, we explore the intricate landscape of brain connectivity in the early stages of schizophrenia, focusing on the patterns of hyper- and hypoconnectivity. Despite existing literatures support for altered functional connectivity (FC) in schizophrenia, inconsistencies and controversies persist regarding specific dysconnections. Leveraging a large sample of 100 first-episode schizophrenia patients (42 females/58 males) and 90 healthy controls (50 females/40 males), we compare the functional connectivity across 90 brain regions of the Automated Anatomical Labeling atlas. We inspected the effects of medication and examined the association between FC changes and duration of untreated psychosis, duration of antipsychotic treatment, as well as symptom severity of the disorder. Our approach also includes a comparative analysis of three denoising strategies for functional magnetic resonance imaging data. In patients, 15 region pairs exhibited increased FC, whereas 150 pairs showed reduced FC relative to controls. Despite this numerical asymmetry, the overall distribution of FC changes was relatively balanced: the median FC was not systematically shifted, indicating no global tendency toward either hyper- or hypoconnectivity. Notably, seveFC alterations were significantly associated with variability in symptom severity and antipsychotic medication across patients. Taken together, these results suggest a pattern of localized dysconnections embedded within an otherwise globally balanced change in connectivity profile in early schizophrenia. Importantly, this balance was substantially disrupted towards dominant observation of hypoconnectivity when less stringent denoising strategies were applied, with results increasingly dominated by hypoconnectivity, pointing to data preprocessing as a critical source of variability across studies.

neuroscience↗

bioRxiv2024

Behavioral pharmacology of mescaline - the role of serotonin 5-HT2A, 5-HT2B, 5-HT2C and 5-HT1A receptors

RationaleMescaline is a classical psychedelic compound with a phenylethylamine structure that primarily acts on serotonin 5-HT2A/C receptors, but also binds to 5-HT1A and 5-HT2B receptors. Despite being the first psychedelic ever isolated and synthesized, the precise role of different serotonin receptor subtypes in its behavioral pharmacology is not fully understood. ObjectivesIn this study, we aimed to investigate how selective antagonists of 5-HT2A, 5-HT2B, 5-HT2C, and 5-HT1A receptors affect the behavioral changes induced by subcutaneous administration of mescaline (at doses of 10, 20, and 100 mg/kg) in rats. MethodsWe used adult male Wistar rats in all our experiments. We evaluated locomotor activity using the open field test, and assessed sensorimotor gating deficits by measuring prepulse inhibition (PPI) of acoustic startle reaction (ASR). ResultsWhile the highest dose of mescaline induced hyperlocomotion, which almost all the other antagonists reversed, the PPI deficits were selectively normalized by the 5-HT2A antagonist. The 5-HT2C antagonist partially reversed the small decrease in locomotor activity induced by lower doses of mescaline. ConclusionOur findings suggest that mescaline-induced changes in behavior are primarily mediated by the 5-HT2A receptor subtype, with less pronounced contributions from the 5-HT2C receptor. The other antagonists had limited effects.

animal behavior and cognition↗

bioRxiv2024

Deviation from typical brain activity during naturalistic stimulation predicts personality traits

The relationship between personality and brain activity has been an increasingly popular topic of neuroscientific research. Naturalistic viewing has been shown to enhance individual differences and might, therefore, be particularly useful for exploring this relationship. Here, we thus examine neural signatures of personality using naturalistic fMRI of 82 healthy subjects. We implemented a simple dimensionality reduction method to characterize brain activity by its typicality, assessed a range of personality traits using widely-used personality inventories, and tested the relationship between the two. We found that there is, indeed, a relationship between personality and the typicality of brain activity, which appears to be most consistently manifested by lower typicality in subjects with higher Neuroticism/Harm Avoidance. Our results highlight the usefulness of naturalistic viewing data for exploring the relationship between individual differences in personality and brain activity.

neuroscience↗

bioRxiv2019

Estimating Sparse Neuronal Signal from Hemodynamic Response: the Mixture Components Inference Approach

The approximate knowledge of the hemodynamic response to neuronal activity is widely used in statistical testing of effects of external stimulation, but has also been applied to estimate the neuronal activity directly from functional magnetic resonance data without knowing the stimulus timing. To this end, sparse linear regression methods have been previously used, including the well-known LASSO and the Dantzig selector. These methods generate a parametric family of solutions with different sparsity, among which a choice is finally based using some information criteria. As an alternative we propose a novel approach that instead utilizes the whole family of sparse regression solutions. Their ensemble provides a first approximation of probability of activation at each timepoint, and together with the conditional neuronal activity distributions estimated with the theory of mixtures with varying concentrations, they serve as the inputs to a Bayes classifier ultimately deciding between the true and false activations. As we show in extensive numerical simulations, the new method performs favourably in comparison with standard approaches in a range of realistic scenarios. This is mainly due to the avoidance of overfitting and underfitting that commonly plague the solutions based on sparse regression combined with model selection methods, including the corrected Akaike Information Criterion. This advantage is finally documented on fMRI task dataset.

neuroscience↗

bioRxiv2017

Toxoplasmosis, but not borreliosis, is associated with psychiatric disorders: A cross-sectional survey on 46 thousand of subjects

Infection by the parasite Toxoplasma, which affects about 33% of world population, is associated with increased risk of several mental health disorders, the most strongly with schizophrenia. It is unknown whether toxoplasmosis really plays a substantial role in the etiopathogenesis of these disorders and whether schizophrenia is associated with this infection the most strongly, or whether this association has just been the most intensively studied for historical reasons. We used the data from 3,440 and 7,800 subjects tested for toxoplasmosis and borreliosis, respectively, who took part in an internet survey, for searching in the associations of these infections with 22 mental health disorders and other indices of impaired mental health. The typical symptom associated with toxoplasmosis was anxiety, and the typical toxoplasmosis-associated disorders were autism (OR=4.86), schizophrenia (OR=3.34), attention deficit hyperactivity disorder (OR=3.02), Asperger syndrome (OR=2.49), antisocial personality disorder (OR=1.81), OCD (OR=1.69), and anxiety disorder (OR=1.57). Borreliosis was associated only with symptoms of depression and with major depression (OR=1.65). The negative effects of borreliosis were detectable only in the Toxoplasma-infected subjects. Toxoplasmosis could play a substantial role in the etiopathogenesis of mental health disorders and its association with schizophrenia is the second strongest association, after autism.

neuroscience↗