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One of the main limitations of pharmacological fMRI is its inability to provide a molecular insight into the main effect of compounds, leaving an open question about the relationship between drug effects and haemodynamic response. The aim of this study is to investigate the acute effects of 3,4-methylenedioxymethamphetamine (MDMA) on functional connectivity (FC) using a novel multimodal method (Receptor-Enriched Analysis of functional Connectivity by Targets - REACT). This approach enriches the resting state (rs-)fMRI analysis with the molecular information about the distribution density of serotonin receptors in the brain, given the serotonergic action of MDMA. Twenty healthy subjects participated in this double-blind, placebo-controlled, crossover study. A high-resolution in vivo atlas of four serotonin receptors (5-HT1A, 5-HT1B, 5-HT2A, and 5-HT4) and its transporter (5-HTT) was used as a template in a two-step multivariate regression analysis to estimate the spatial maps reflecting the whole-brain connectivity behaviour related to each target under placebo and MDMA. Results showed that the networks exhibiting significant changes after MDMA administration are the ones informed by the 5-HTT and 5-HT1A distribution density maps, which are the main targets of this compound. Changes in the 5-HT1A-enriched functional maps were also associated with the pharmacokinetic levels of MDMA and MDMA-induced FC changes in the 5-HT2A-enriched maps correlated with the spiritual experience subscale of the Altered States of Consciousness Questionnaire. By enriching the rs-fMRI analysis with molecular data of voxel-wise distribution of the serotonin receptors across the brain, we showed that MDMA effects on FC can be understood through the distribution of its main targets. This result supports the ability of this method to characterise the specificity of the functional response of the brain to MDMA binding to serotonergic receptors, paving the way to the definition of a new fingerprint in the characterization of new compounds and potentially to a further understanding to the response to treatment. [Display omitted] •MDMA connectivity effects understood through the distribution of 5-HT1A and 5-HTT.•Direct link between PK levels of MDMA and 5-HT1A-enriched functional connectivity maps.•Ability to link receptor targets to functional mechanisms underlying behaviour.•Mapping pharmacodynamic effects onto the drug's molecular targets.

Psychoactive drugs can transiently perturb brain physiology while preserving brain structure. The role of physiological state in shaping neural function can therefore be investigated through neuroimaging of pharmacologically induced effects. Previously, using pharmacological neuroimaging, we found that neural and experiential effects of lysergic acid diethylamide (LSD) are attributable to agonism of the serotonin-2A receptor (Preller et al., 2018). Here, we integrate brain-wide transcriptomics with biophysically based circuit modeling to simulate acute neuromodulatory effects of LSD on human cortical large-scale spatiotemporal dynamics. Our model captures the inter-areal topography of LSD-induced changes in cortical blood oxygen level-dependent (BOLD) functional connectivity. These findings suggest that serotonin-2A-mediated modulation of pyramidal-neuronal gain is a circuit mechanism through which LSD alters cortical functional topography. Individual-subject model fitting captures patterns of individual neural differences in pharmacological response related to altered states of consciousness. This work establishes a framework for linking molecular-level manipulations to systems-level functional alterations, with implications for precision medicine.

Mounting evidence suggests that function and connectivity of the striatum is disrupted in schizophrenia 1 – 5 . We have developed a new hypothesis-driven neuroimaging biomarker for schizophrenia identification, prognosis and subtyping based on functional striatal abnormalities (FSA). FSA scores provide a personalized index of striatal dysfunction, ranging from normal to highly pathological. Using inter-site cross-validation on functional magnetic resonance images acquired from seven independent scanners ( n  = 1,100), FSA distinguished individuals with schizophrenia from healthy controls with an accuracy exceeding 80% (sensitivity, 79.3%; specificity, 81.5%). In two longitudinal cohorts, inter-individual variation in baseline FSA scores was significantly associated with antipsychotic treatment response. FSA revealed a spectrum of severity in striatal dysfunction across neuropsychiatric disorders, where dysfunction was most severe in schizophrenia, milder in bipolar disorder, and indistinguishable from healthy individuals in depression, obsessive-compulsive disorder and attention-deficit hyperactivity disorder. Loci of striatal hyperactivity recapitulated the spatial distribution of dopaminergic function and the expression profiles of polygenic risk for schizophrenia. In conclusion, we have developed a new biomarker to index striatal dysfunction and established its utility in predicting antipsychotic treatment response, clinical stratification and elucidating striatal dysfunction in neuropsychiatric disorders. A new cross-validated neuroimaging biomarker that reflects striatal dysfunctioning can be used to distinguish patients with schizophrenia from healthy controls, and is associated with treatment response to antipsychotics.

Single-cell (SC) analysis provides unique insight into individual cell dynamics and cell-to-cell heterogeneity. Here, we utilize trapped ion mobility separation coupled with dual-polarity ionization mass spectrometry imaging (MSI) to enable high-throughput in situ profiling of the SC lipidome. Multimodal SC imaging, in which dual-polarity-mode MSI is used to perform serial data acquisition runs on individual cells, significantly enhanced SC lipidome coverage. High-spatial resolution SC-MSI identifies both inter- and intracellular lipid heterogeneity; this heterogeneity is further explicated by Uniform Manifold Approximation and Projection and machine learning-driven classifications. We characterize SC lipidome alteration in response to stearoyl-CoA desaturase 1 inhibition and, additionally, identify cell-layer specific lipid distribution patterns in mouse cerebellar cortex. This integrated multimodal SC-MSI technology enables high-resolution spatial mapping of intercellular and cell-to-cell lipidome heterogeneity, SC lipidome remodeling induced by pharmacological intervention, and region-specific lipid diversity within tissue. Single-cell analysis provides unique insight into individual cell dynamics and cell-to-cell heterogeneity. Here, the authors utilize trapped ion mobility separation coupled with dual-polarity ionization mass spectrometry imaging to enable high-throughput in situ profiling of single-cell lipidome.

There is a paucity of empirical research on the use of non-pharmacological interventions to both treat and curb the spread of Alzheimer’s disease (AD) across the globe. This paper examines the biochemical and clinical outlook and the social implications of the condition in relation to psychological aspects that may indicate a direction for further interventions. There is a scarcity of research on the effectiveness of using various psychological aspects of AD, a disease characterized by a process of transition from health and independence to a dependent state with a progressive loss of memory and functional skills. The paper investigates the biochemical and psychological aspects of AD and their significance for improving quality of life for patients with this disease. Psychological interventions based on, among other factors, biochemical studies, are conducted to improve the emotional wellbeing of AD patients and may assist in slowing down the progression of the disease. To date, however, no effective methods of AD treatment have been established.

Imaging transcriptomics has become a power tool for linking imaging-derived phenotypes (IDPs) to genomic mechanisms. Yet, its potential for guiding CNS drug discovery remains underexplored. Here, utilizing spatially-dense representations of the human brain transcriptome, we present an analytical framework for the transcriptomic decoding of high-resolution surface-based neuroimaging patterns, and for linking IDPs to the transcriptomic landscape of complex neurotransmission systems in vivo. Leveraging publicly available Positron Emission Tomography (PET) data, we initially validated our approach against molecular targets with a high correspondence between gene expression and protein binding. Subsequently, we used the cortical gene expression profiles of candidate genes to dissect two discrete classes of GABA A -receptor subunits, each characterized by a distinct cortical expression pattern, and to link these to specific behavioural symptoms and traits. Our approach thus represents a future avenue for in vivo pharmacotranscriptomics that may guide the development of targeted pharmacotherapies and personalized interventions. This study presents an analytic framework to link imaging-derived brain phenotypes to gene expression. In the future, this approach may facilitate in vivo pharmacotranscriptomics and the development of personalized (pharmacological) interventions.

Psychedelic drugs, including the serotonin 2a (5-HT2A) receptor partial agonist psilocybin, are receiving renewed attention for their possible efficacy in treating a variety of neuropsychiatric disorders. Psilocybin induces widespread dysregulation of cortical activity, but circuit-level mechanisms underlying this effect are unclear. The claustrum is a subcortical nucleus that highly expresses 5-HT2A receptors and provides glutamatergic inputs to arguably all areas of the cerebral cortex. We therefore tested the hypothesis that psilocybin modulates claustrum function in humans. Fifteen healthy participants (10M, 5F) completed this within-subjects study in which whole-brain resting-state blood-oxygenation level-dependent (BOLD) signal was measured 100 ​min after blinded oral administration of placebo and 10 mg/70 ​kg psilocybin. Left and right claustrum signal was isolated using small region confound correction. Psilocybin significantly decreased both the amplitude of low frequency fluctuations as well as the variance of BOLD signal in the left and right claustrum. Psilocybin also significantly decreased functional connectivity of the right claustrum with auditory and default mode networks (DMN), increased right claustrum connectivity with the fronto-parietal task control network (FPTC), and decreased left claustrum connectivity with the FPTC. DMN integrity was associated with right-claustrum connectivity with the DMN, while FPTC integrity and modularity were associated with right claustrum and left claustrum connectivity with the FPTC, respectively. Subjective effects of psilocybin predicted changes in the amplitude of low frequency fluctuations and the variance of BOLD signal in the left and right claustrum. Observed effects were specific to claustrum, compared to flanking regions of interest (the left and right insula and putamen). This study used a pharmacological intervention to provide the first empirical evidence in any species for a significant role of 5-HT2A receptor signaling in claustrum functioning, and supports a possible role of the claustrum in the subjective and therapeutic effects of psilocybin.

Purpose of Review This review summarizes recent advances in research on the neurobiology of borderline personality disorder (BPD) according to structural brain imaging investigations and resting-state and task-based functional brain activation studies. Recent Findings Extending established findings on differences in regional brain volumes and cortical thickness between BPD and healthy controls, recent research illuminates shared and distinct brain structural characteristics compared to other psychiatric diagnoses, and uncovers relations of these brain structures with transdiagnostic symptoms and clinical features. Resting-state functional brain imaging studies reveal disruptions among adolescents and adults with BPD in frontolimbic and default-mode networks, which primarily underlie affect regulation and self-referential processes, respectively. Recent task-based functional brain imaging research builds on existing neurobiological understanding of emotion and cognition in BPD by revealing novel intersections with interpersonal- and stress-related processes. Studies of psychological and pharmacological interventions suggest possible effects on neural regions underlying emotion processing and behavioral control. Summary Recent advances in neurobiological research on BPD underscore the pathophysiology of affective, behavioral and self-interpersonal symptoms, with growing interest in adolescents with BPD and the impacts of psychological and biological interventions. Corresponding with the increased prominence of alternative dimensional models of personality disorder in recent years, there is a gradual rise in studies examining the relationships of brain structures and functional brain activation with BPD-relevant symptom dimensions, including within transdiagnostic samples.

Involvement of dopamine in regulating exploration during decision-making has long been hypothesized, but direct causal evidence in humans is still lacking. Here, we use a combination of computational modeling, pharmacological intervention and functional magnetic resonance imaging to address this issue. Thirty-one healthy male participants performed a restless four-armed bandit task in a within-subjects design under three drug conditions: 150 mg of the dopamine precursor L-dopa, 2 mg of the D2 receptor antagonist haloperidol, and placebo. Choices were best explained by an extension of an established Bayesian learning model accounting for perseveration, directed exploration and random exploration. Modeling revealed attenuated directed exploration under L-dopa, while neural signatures of exploration, exploitation and prediction error were unaffected. Instead, L-dopa attenuated neural representations of overall uncertainty in insula and dorsal anterior cingulate cortex. Our results highlight the computational role of these regions in exploration and suggest that dopamine modulates how this circuit tracks accumulating uncertainty during decision-making.

Identifying biomarkers in schizophrenia during the first episode without the confounding effects of treatment has been challenging. Leveraging these biomarkers to establish diagnosis and make individualized predictions of future treatment responses to antipsychotics would be of great value, but there has been limited progress. In this study, by using machine learning algorithms and the functional connections of the superior temporal cortex, we successfully identified the first-episode drug-naive (FEDN) schizophrenia patients (accuracy 78.6%) and predict their responses to antipsychotic treatment (accuracy 82.5%) at an individual level. The functional connections (FC) were derived using the mutual information and the correlations, between the blood-oxygen-level dependent signals of the superior temporal cortex and other cortical regions acquired with the resting-state functional magnetic resonance imaging. We also found that the mutual information and correlation FC was informative in identifying individual FEDN schizophrenia and prediction of treatment response, respectively. The methods and findings in this paper could provide a critical step toward individualized identification and treatment response prediction in first-episode drug-naive schizophrenia, which could complement other biomarkers in the development of precision medicine approaches for this severe mental disorder.