Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

Background: Cognitive Behavior Therapy (CBT) is a gold standard approach for treating major depressive disorder (MDD) among adolescents. However, nearly half of adolescents receiving CBT do not improve. In order to personalize treatment, it is essential to identify objective markers that predict treatment responsiveness. Toward addressing this aim, this study investigated neurophysiological processes related to self-referential processing that predicted CBT response among depressed, female adolescents.

Methods: At baseline, female adolescents ages 13-18-years-old (N=80) completed a comprehensive clinical assessment, and a self-referential encoding task was administered while electroencephalogram (EEG) data were recorded. Baseline EEG data were utilized to identify oscillatory differences between healthy (HC, n=38) and depressed (MDD, n=42) adolescents. Following the baseline assessment, depressed youth received up to 12-weeks of CBT. Baseline differences in EEG oscillations between healthy and depressed youth were used to guide CBT prediction analysis. Cluster-based event-related spectral perturbation analysis (ERSP) probed theta and alpha event-related synchronization/desynchronization (ERS/ERD) response to negative and positive words.

Results: Baseline analyses showed that, relative to the healthy adolescents, depressed youth exhibited higher levels of frontal theta ERS and a greater posterior alpha ERD. Multilevel modeling identified primary neural pre-treatment predictors of treatment response: greater theta ERS in the right prefrontal cortex (PFC) after the onset of negative words and lower alpha ERD in both the right PFC and posterior cingulate cortex (PCC). ERS and ERD associations with treatment response remained significant, with baseline depressive and anxiety symptoms included as covariates in all analyses.

Conclusions: Consistent with prior research, results highlighted that relative to healthy youth, depressed adolescents are characterized by prominent theta synchronization and alpha desynchronization over PFC and PCC, respectively. Cluster-based ERSP analysis also identified key mechanisms underlying depression-related self-referential processing that predicted improved symptoms during the CBT course. Ultimately, a better characterization of the neural underpinnings of adolescent depression and its treatment may lead to more personalized interventions.

Background: Maternal Immune Activation (MIA) has been hypothesized to have an adverse effect on child neurodevelopment, but only a few neuroimaging studies have been performed to date, mostly in neonates. In this population-based cohort study, we investigated the association between MIA and multiple neuroimaging modalities depicting brain development from childhood to adolescence.

Methods: We used data of mother-child pairs from the Generation R Study. To define our exposure, we measured IL-1β, IL-6, IL-17a, IL-23 and IFN-γ, and CRP at two time points during pregnancy. Given that levels of these 5 cytokines were highly correlated, we were able to compute a Cytokine index. We used multiple brain imaging modalities as outcomes, encompassing global and regional measures of brain morphology (structural MRI, volume, n=3,295), white matter microstructure (diffusion MRI, FA and MD, n=3,267), and functional connectivity (functional MRI, graph theory measures and network-level connectivity, n=2,914) at child mean ages 10 and 14 years. We performed mixed-effects models using the child's age as continuous time variable.

Results: We found no significant association or time interaction between MIA and any neuroimaging outcomes in children over time. These associations were similar for the Cytokine index, CRP, and individual cytokines. We observed no evidence for differential effects of timing of prenatal MIA or child sex after multiple testing correction.

Conclusions: This longitudinal population-based study reports no evidence for an association between MIA and child brain development in the general population. Our findings differ from prior research in neonates showing structural and functional brain abnormalities after MIA.

One of the primary challenges in metabolic psychiatry is that the disrupted brain functions that underlie psychiatric conditions arise from a complex set of downstream and feedback processes spanning across multiple spatiotemporal scales. Importantly, the same circuit can have multiple points of failure, each of which results in a different type of dysregulation, and thus elicits distinct cascades downstream that produce divergent signs and symptoms. Here, we illustrate this challenge by examining how subtle differences in circuit perturbations can lead to divergent clinical outcomes. We also discuss how computational models can perform the spatially heterogenous integration and bridge in vitro and in vivo paradigms. By leveraging recent methodological advances and tools, computational models can integrate relevant processes across scales (e.g., TCA-cycle, ion channel, neural microassembly, whole-brain macro-circuit) and across physiological systems (e.g., neural, endocrine, immune, vascular), providing a framework that can unite these mechanistic processes in a manner that goes beyond the conceptual and descriptive, to the quantitative and generative. These hold the potential to sharpen our intuitions towards circuit-based models for personalized diagnostics and treatment.

Mindfulness meditation has numerous purported benefits to psychological wellbeing, however, problems such as adherence to mindfulness tasks, quality of mindfulness sessions, or dosage of mindfulness interventions may hinder individuals from accessing the purported benefits of mindfulness. Methodologies including closed-loop systems and real-time neurofeedback may provide tools to help bolster success in mindfulness task performance, titrate the exposure to mindfulness interventions, or improve engagement with mindfulness sessions. This review explores the use of closed-loop systems and real-time neurofeedback to influence, augment, or promote mindfulness interventions. Various closed-loop neurofeedback signals from functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) have been used to provide subjective correlates to mindfulness states including: fMRI region-of-interest based signals (e.g., posterior cingulate cortex), fMRI network-based signals (e.g., default mode network, central executive network, salience network), and EEG spectral-based signals (e.g., alpha, theta, and gamma bands). Past research has focused on how successful interventions has aligned with the subjective mindfulness meditation experience. Future research may pivot towards using appropriate control conditions (e.g., mindfulness-only or sham-neurofeedback) to quantify the effects of closed-loop systems and neurofeedback-guided mindfulness meditation in improving cognition and wellbeing.

Background: While individuals with autism often face challenges in everyday social interactions, they may demonstrate proficiency in structured Theory of Mind (ToM) tasks that assess their ability to infer others' mental states. Using functional MRI and pupillometry, we investigated whether these discrepancies stem from diminished spontaneous mentalizing or broader difficulties in unstructured contexts.

Methods: Fifty-two adults diagnosed with autism and 52 neurotypical controls viewed 'Partly Cloudy', a nonverbal animated film with a dynamic social narrative known to engage the ToM brain network during specific scenes. Analysis focused on comparing brain and pupil responses to these ToM events. Additionally, dynamic intersubject correlations explored the variability of these responses throughout the film.

Results: Both groups showed similar brain and pupil responses to ToM events and provided comparable descriptions of the characters' mental states. However, participants with autism exhibited significantly stronger correlations in their responses across the film's social narrative, indicating reduced inter-individual variability. This distinct pattern emerged well before any ToM events and involved brain regions beyond the ToM network.

Conclusions: Our findings provide functional evidence of spontaneous mentalizing in autism, demonstrating this capacity in a context affording but not requiring mentalizing. Rather than responses to ToM events, a novel neurocognitive signature - inter-individual variability in brain and pupil responses to evolving social narratives - differentiated neurotypical individuals from those with autism. These results suggest that idiosyncratic narrative processing in unstructured settings, a common element of everyday social interactions, may offer a more sensitive scenario for understanding the autistic mind.

Background: Early substance use initiation (SUI) places youth at substantially higher risk for later substance use disorders. Furthermore, adolescence is a critical period for the maturation of brain networks, the pace and magnitude of which are susceptible to environmental influences and may shape risk for SUI.

Methods: We examined whether patterns of functional brain connectivity during rest (rsFC), measured longitudinally in pre-and-early adolescence, can predict future SUI. Next, in an independent sub-sample, we tested whether these patterns are associated with earlier environmental exposures, specifically neighborhood pollution and socioeconomic dimensions. We utilized data from the Adolescent Brain Cognitive Development (ABCD) Study®. SUI was defined as first-time use of at least one full dose of alcohol, nicotine, cannabis, or other drugs. We created a control group (N = 228) of participants without SUI who were matched with the SUI group (N = 233) on age, sex, race/ethnicity, and parental income and education.

Results: Multivariate analysis showed that whole-brain rsFC from 9-10 to 11-12 years of age (prior to SUI) prospectively differentiated the SUI and control groups. The SUI-related rsFC pattern was also related to aging in both groups, suggesting a pattern of accelerated maturation in the years prior to SUI. This same pattern of rsFC was predicted by higher pollution, but not neighborhood disadvantage (adjusted for family socioeconomic factors) in an independent sub-sample (N = 2,854).

Conclusion: Brain functional connectivity patterns in early adolescence that are linked to accelerated maturation can predict SUI in youth and are associated with exposure to pollution.

The use of antipsychotic drugs is associated with adverse metabolic effects. Disruptions in glucose metabolism such as hyperglycemia and insulin resistance have been shown to occur with antipsychotic use, independent of changes in body weight or adiposity. The regulation of whole-body glucose metabolism is partly mediated by the central nervous system (CNS). In particular, the hypothalamus and brainstem are responsive to peripheral energy signals and subsequently mediate feedback mechanisms to maintain peripheral glucose homeostasis. In this scoping review of preclinical in vivo studies, we aimed to explore central mechanisms through which antipsychotics dysregulate glucose metabolism. A systematic search for animal studies identified 29 studies that met our eligibility criteria for qualitative synthesis. The studies suggest that antipsychotic-induced changes in autonomic nervous system activity, certain neurotransmitter systems, expression of neuropeptides, and central insulin action mediate impairments in glucose metabolism. These findings provide insight into potential targets for the mitigation of the adverse effects of antipsychotics on glucose metabolism.

Background: Trauma is a risk factor for developing maladaptive alcohol use. Preclinical research has shown that stress alters the processing of midbrain and striatal reward and incentive signals. However, little research has been conducted on alterations in reward-related neurocircuitry post-trauma in humans. Neuroimaging markers may be particularly useful as they can provide insight into the mechanisms that may make an individual vulnerable to developing trauma-related psychopathologies. This study aimed to identify reward-related neural correlates associated with changes in alcohol use after trauma exposure.

Methods: Participants were recruited from U.S. emergency departments for the AURORA study (N=286, 178 female). Trauma-related change in alcohol use at 8 weeks post-trauma relative to pre-trauma was quantified as a change in 30-day total drinking per the PhenX Toolkit Alcohol 30-Day Quantity and Frequency Measure. Reward-related neurocircuitry activation and functional connectivity (FC) were assessed 2 weeks post-trauma using fMRI during a monetary reward task using region of interest and whole-brain voxelwise analyses.

Results: Greater increase in alcohol use from pre-trauma to 8 weeks post-trauma was predicted by (1) greater ventral tegmental area (VTA) and (2) greater cerebellum activation during Gain>Loss trials measured 2 weeks post-trauma and (3) greater seed-based FC between the VTA and lateral occipital cortex and precuneus.

Conclusions: Altered VTA activation and FC early post-trauma may be associated with reward-seeking and processing, contributing to greater alcohol use post-trauma. These data provide novel evidence of neural correlates that underlie increased alcohol use early post-trauma that may be targeted via early interventions to prevent the development of maladaptive alcohol use.

Background: Despite the diverse nature of clinical trajectories after a first-episode of psychosis, few baseline characteristics have been predictive of clinical improvement, and the neurobiological underpinnings of this heterogeneity remain largely unknown. Elevated extracellular free water (FW) in the brain is a diffusion imaging measure that has been consistently reported in different phases of psychosis that may indicate a neuroinflammatory state. Its predictive capacity in terms of clinical outcomes, however, is unknown.

Methods: We used diffusion imaging to determine FW and tissue-specific fractional anisotropy (FA-t) in first-episode psychosis. Forty-seven participants were categorized as clinical "Improvers" (n=26) if they achieved a 20% decrease in total Brief Psychiatric Rating Scale (BPRS) score at 12 months. To determine the predictive capacity of FW and FA-t, these measures were introduced in a stepwise logistic regression model to predict clinical improvement. For those measures surviving the model, regional between-group differences were also investigated in cortical surface or white matter tracts as applicable.

Results: Higher gray matter (GM) FW (OR-CI 1.134 - 2.543) and FA-t (OR-CI: 0.905 - 2.038) both predicted Improver status. FW in GM also linearly correlated with BPRS total score at 12 months follow-up. Examining regional specificity, Improvers showed greater FW predominantly in temporal regions and higher FA-t values in several white matter tracts, including bilateral longitudinal superior fasciculus.

Conclusions: Our results show that elevated FW in GM and FA-t predict further clinical improvement during the initial phases of psychosis. The potential roles of brain inflammatory processes in predicting clinical improvement are discussed.