Biology subjects

Meyer-Lindenberg, A.

Publications and source records attributed to Meyer-Lindenberg, A..

13 recordsLinked to original sources

bioRxiv2026

Neurostructural correlates of real-life social drinking risk in alcohol use disorder

The social context of alcohol consumption is increasingly recognized as an important factor in the development of alcohol use disorder (AUD). However, individuals with AUD may differ in how strongly alcohol use by people around them is associated with their own drinking, and the neurostructural basis of this variation remains unclear. Here we studied 83 individuals with AUD (53 men, 30 women; mean [SD] age, 37.20 [12.42] years; median DSM-5 AUD criteria, 4) using six weeks of ecological momentary assessment and structural magnetic resonance imaging (n = 80). Across 5,221 non-solitary observations, greater exposure to surrounding drinkers was associated with increased odds of momentary drinking (odds ratio, 4.23; 95% CI, 3.60-4.97), with significant between-person variation that we quantified as social drinking risk (SDR). Higher SDR was associated with lower gray matter volume in the pregenual anterior cingulate cortex (T = 5.40; P < .001) and weaker pregenual anterior cingulate cortex-ventral striatum structural covariance (T = 3.15; P = .032). These findings support SDR as an ecologically grounded phenotype linking daily-life social-context sensitivity to cingulostriatal structure, with potential relevance for mechanistic and interventional research in AUD.

neuroscience↗

bioRxiv2023

Reactivation strength during cued recall is modulated by graph distance within cognitive maps

Declarative memory retrieval is thought to involve reinstatement of neuronal activity patterns elicited and encoded during a prior learning episode. Furthermore, it is suggested that two mechanisms operate during reinstatement, dependent on task demands: individual memory items can be reactivated simultaneously as a clustered occurrence or, alternatively, replayed sequentially as temporally separate instances. In the current study, participants learned associations between images that were embedded in a directed graph network and retained this information over a brief 8-minute consolidation period. During a subsequent cued recall session, participants retrieved the learned information while undergoing magnetoencephalographic (MEG) recording. Using a trained stimulus decoder, we found evidence for clustered reactivation of learned material. Reactivation strength of individual items during clustered reactivation decreased as a function of increasing graph distance, an ordering present solely for successful retrieval but not for retrieval failure. In line with previous research, we found evidence that sequential replay was dependent on retrieval performance and was most evident in low performers. The results provide evidence for distinct performance-dependent retrieval mechanisms with graded clustered reactivation emerging as a plausible mechanism to search within abstract cognitive maps.

neuroscience↗

bioRxiv2022

Species-conserved mechanisms of cognitive flexibility in complex environments

Rapid learning in complex and changing environments is a hallmark of intelligent behavior. Humans achieve this in part through abstract concepts applicable to multiple, related situations. It is unclear, however, whether some of the underlying computational mechanisms also exist in other species. We combined behavioral, computational and electrophysiological analyses of a multidimensional rule-learning paradigm in rats and humans. We report that both species infer task rules by sequentially testing different hypotheses, rather than learning the correct action for all possible combinations of task-related cues. Neural substrates of hypothetical rules were detected in prefrontal network activity of both species. This species-conserved mechanism reduces task dimensionality and explains key experimental observations: sudden behavioral transitions and facilitated learning after prior experience. Our findings open the black box of hypothesis testing in rodents and provide a foundation for the translational investigation of impaired cognitive flexibility.

neuroscience↗

bioRxiv2021

Real-time individual benefit from social interactions before and during the lockdown: The crucial role of personality, neurobiology and genes.

BackgroundSocial integration is a major resilience factor for staying healthy. However, the COVID-19-pandemic led to unprecedented restrictions in social life. The consequences of these social lockdowns on momentary well-being are yet not fully understood. MethodWe investigated the individual affective benefit from social interactions in a longitudinal birth cohort study. We used two real-time, real-life ecological momentary assessments once before and once during the initial lockdown of the pandemic (N~6800 total observations) to determine the protective role of social interactions on well-being. Moreover, we used a multimethod approach combining the ecological assessment data with individual risk and resilience factors to analyze the moderating mechanisms of personality, neurobiology and genes. ResultsSocial contacts were linked to higher positive affect both during normal times and during the COVID-19 pandemic, highlighting the beneficial role of social embedding. Moreover, this relationship was moderated by amygdala volume, neuroticism and polygenic risk for schizophrenia. In detail, participants with a larger left amygdala volume and higher trait neuroticism exhibited an affective benefit from more social interactions prior to the pandemic. This pattern changed during the pandemic with participants with smaller amygdala volumes and lower neurotic traits showing a social affective gain during the pandemic. Moreover, participants with low genetic risk for schizophrenia showed an affective benefit from social interactions irrespective of the time point. ConclusionOur results highlight the protective role of social integration on momentary well-being. Thereby, we offer new insights into how this relationship is differently affected by a persons, neurobiology, personality, and genes under adverse circumstances.

neuroscience↗

bioRxiv2021

Hierarchical cross-scale analysis identifies parallel ventral striatal networks coding for dynamic and stabilized olfactory reward predictions

The unbiased identification of brain circuits responsible for behavior and their local cellular computations is a challenge for neuroscience. We establish here a hierarchical cross-scale approach from behavioral modeling and fMRI in task-performing mice to cellular network dynamics to identify how reward predictions are represented in the forebrain upon olfactory conditioning. fMRI identified functional segregation in reward prediction and error computations among olfactory cortices and subcortical circuits. Among them, the olfactory tubercle contributed both to dynamic reward predictions and prediction error. In this region, cellular recordings revealed two parallel neuronal populations for prediction coding. One population produced stabilized predictions as distributed stimulus-bound transient network activity; the other evolved during anticipatory waiting and fully reflected predicted value in single-units, dynamically integrating the recent cue-specific history of uncertain outcomes. Thus, the cross-scale approach revealed regional functional differentiation among the distributed forebrain circuits with a limbic hotspot for multiple non-redundant reward prediction coding.

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

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↗

bioRxiv2019

Brain state stability during working memory is explained by network control theory, modulated by dopamine D1/D2 receptor function, and diminished in schizophrenia

Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. Here, we show that working memory entails brain-wide switching between activity states. The stability of states relates to dopamine D1 receptor gene expression while state transitions are influenced by D2 receptor expression and pharmacological modulation. Schizophrenia patients show altered network control properties, including a more diverse energy landscape and decreased stability of working memory representations.

neuroscience↗

bioRxiv2019

Longitudinal transcriptome-wide gene expression analysis of sleep deprivation treatment showsinvolvement of circadian genes and immune pathways

BackgroundTherapeutic sleep deprivation (SD) rapidly induces robust, transient antidepressant effects in a large proportion of major mood disorder patients suffering from a depressive episode, but underlying biological factors remain poorly understood. Research suggests that these patients may have altered circadian molecular genetic clocks and that SD functions through resetting dysregulated genes; additional factors may be involved, warranting further investigation. Leveraging advances in microarray technology enabling the transcriptome-wide assessment of gene expression, this study aimed to examine gene expression changes accompanying SD and recovery sleep in patients suffering from an episode of depression. MethodsPatients (N=78) and controls (N=15) underwent SD, with blood taken at the same time of day before, after one night of SD and after recovery sleep. A transcriptome-wide gene-by-gene approach was used, with a targeted look also taken at circadian genes. Furthermore, gene set enrichment, and longitudinal gene set analyses including the time point after recovery sleep, were conducted. ResultsCircadian genes were significantly affected by SD, with patterns suggesting that molecular clocks of responders and non-responders, as well as patients and controls respond differently to chronobiologic stimuli. Notably, gene set analyses revealed a strong widespread effect of SD on pathways involved in immune function and inflammatory response, such as those involved in cytokine and especially in interleukin signalling. Longitudinal gene set analyses showed that in responders these pathways were upregulated after SD; in non-responders, little response was observed. ConclusionsOur findings emphasize the close relationship between circadian, immune and sleep systems and their link to etiology of depression at the transcriptomic level.

epidemiology↗

bioRxiv2019

Generative network models identify biological mechanisms of altered structural brain connectivity in schizophrenia

BackgroundAlterations in the structural connectome of schizophrenia patients have been widely characterized, but the mechanisms leading to those alterations remain largely unknown. Generative network models have recently been introduced as a tool to test the biological underpinnings of the formation of altered structural brain networks.\n\nMethodsWe evaluated different generative network models to investigate the formation of structural brain networks in healthy controls (n=152), schizophrenia patients (n=66) and their unaffected first-degree relatives (n=32), and we identified spatial and topological factors contributing to network formation. We further investigated the association of these factors to cognition and to polygenic risk for schizophrenia.\n\nResultsStructural brain networks can be best accounted for by a two-factor model combining spatial constraints and topological neighborhood structure. The same wiring model explained brain network formation for all groups analyzed. However, relatives and schizophrenia patients exhibited significantly lower spatial constraints and lower topological facilitation compared to healthy controls. The model parameter for spatial constraint was correlated with the polygenic risk for schizophrenia and predicted reduced cognitive performance.\n\nConclusionsOur results identify spatial constraints and local topological structure as two interrelated mechanisms contributing to normal brain development as well as altered connectomes in schizophrenia. Spatial constraints were linked to the genetic risk for schizophrenia and general cognitive functioning, thereby providing insights into their biological basis and behavioral relevance.

neuroscience↗

bioRxiv2019

Neural network-based alterations during repeated heat pain stimulation in major depression

The current study aimed to identify alterations in brain activation and connectivity related to nociceptive processing and pain sensitization in major depressive disorder (MDD), using repeated heat pain stimulation during functional magnetic resonance imaging (fMRI) in 37 MDD patients and 33 healthy controls. Regional activation did not differ between groups, but functional connectivity was significantly decreased in MDD in a neural network connecting frontal, temporal and occipital areas (family-wise error (FWE)-corrected pFWE = 0.045). Supplemental analyses suggested a significant association between network connectivity and trait neuroticism (p = 0.007) but not with the clinical state or familiar risk of MDD (all p values > 0.13). Our data relate a network-based phenotype for altered pain processing and antinociceptive control to MDD and encourage future studies on the shared intermediate neural psychological risk architecture of MDD and chronic pain.

neuroscience↗

bioRxiv2018

The dark side of the mean: brain structural heterogeneity in schizophrenia and its polygenic risk.

ImportanceBetween-subject variability in brain structure is determined by gene-environment interactions, possibly reflecting differential sensitivity to environmental and genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner cortices and smaller subcortical volumes in patients. However, such group-level comparisons may mask considerable within-group heterogeneity, which has largely remained unnoticed in the literature\n\nObjectiveTo compare brain structural variability between individuals with SZ and healthy controls (HC) and to test if respective variability reflects the polygenic risk for SZ (PRS) in HC.\n\nDesign, Setting, and ParticipantsWe compared MRI derived cortical thickness and subcortical volumes between 2,010 healthy controls and 1,151 patients with SZ across 16 cohorts. Secondly, we tested for associations between PRS and MRI features in 12,490 participants from UK Biobank.\n\nMain Outcomes and MeasuresWe modeled mean and dispersion effects of SZ and PRS using double generalized linear models. We performed vertex-wise analyses for thickness, and region-of-interest analysis for cortical, subcortical and hippocampal subfield volumes. Follow-up analyses included within-sample analysis, controlling for intracranial volume and population covariates, test of robustness of PRS threshold, and outlier removal.\n\nResultsCompared to controls, patients with SZ showed higher heterogeneity in cortical thickness, cortical and ventricle volumes, and hippocampal subfields. Higher PRS was associated with thinner frontal and temporal cortices, as well as smaller left CA2/3, but was not significantly associated with dispersion.\n\nConclusion and relevanceSZ is associated with substantial brain structural heterogeneity beyond the mean differences. These findings possibly reflect higher differential sensitivity to environmental and genetic perturbations in patients, supporting the heterogeneous nature of SZ. Higher PRS for SZ was associated with thinner fronto-temporal cortices and smaller subcortical volumes, but there were no significant associations with the heterogeneity in these measures, i.e. the variability among individuals with high PRS were comparable to the variability among individuals with low PRS. This suggests that brain variability in SZ results from interactions between environmental and genetic factors that are not captured by the PGR. Factors contributing to heterogeneity in fronto-temporal cortices and hippocampus are thus key to further our understanding of how genetic and environmental factors shape brain biology in SZ.\n\nKey PointsQuestion: Is schizophrenia and its polygenic risk associated with brain structural heterogeneity in addition to mean changes?\n\nFindings: In a sample of 1151 patients and 2010 controls, schizophrenia was associated with increased heterogeneity in fronto-temporal thickness, cortical, ventricle, and hippocampal volumes, besides robust reductions in mean estimates. In an independent sample of 12,490 controls, polygenic risk for schizophrenia was associated with thinner fronto-temporal cortices and smaller CA2/3 of the left hippocampus, but not with heterogeneity.\n\nMeaning: Schizophrenia is associated with increased inter-individual differences in brainstructure, possibly reflecting clinical heterogeneity, gene-environment interactions, or secondary disease factors.

neuroscience↗

bioRxiv2018

In vitro evaluation of the decontamination effect of cold argon plasma on selected bacteria frequently encountered in small animal bite injuries

ObjectiveThe beneficial effects of cold argon plasma (CAP) on wound healing and its capacity for bacterial decontamination has recently been documented. However, despite favourable reports from experimental trials and human applications, the first in vivo studies in small animals did not prove any decontamination effect in canine bite wounds.\n\nThe present study therefore aimed to evaluate the decontamination effect of CAP in different bacteria frequently encountered in canine bite wounds in vitro.\n\nMethodsStandard strains of Escherichia (E.) coli, Staphylococcus (S.) pseudintermedius, S. aureus, Streptococcus (Sc.) canis, Pseudomonas (P.) aeruginosa and Pasteurella multocida were investigated. To evaluate the influence of the bacterial growth phase, each bacterium was incubated in nutrient broth for 3 and 8 hours, respectively, before argon plasma treatment. Three different bacterial concentrations were created per bacterium and growth phase, and each was exposed to cold plasma at a gas flow rate of 5 standard litres/minute of argon for 30 seconds, 1 minute and 2 minutes.\n\nResultsArgon treatment resulted in acceptable decontamination rates (range 98.9-99.9%) in all bacteria species in vitro; however, differences in susceptibility were detected in the different tested bacteria. Treatment time significantly (P<0.05) correlated with the decontamination rate in E. coli, Sc. canis and S. aureus, with an exposure time of 2 minutes being most effective. The initial bacterial concentration significantly (P<0.05) influenced decontamination in Pasteurella multocida and P. aeruginosa, in which treatment time was not as important. The growth phase only influenced decontamination in S. pseudintermedius.\n\nConclusionCAP exerts effective antibacterial activity against the tested bacteria strains in vitro, with species specific effects of treatment time, growth phase and concentration.

microbiology↗