Biological psychiatry. Cognitive neuroscience and neuroimaging最新文献

Background: Auditory steady-state response (ASSR) abnormalities in the 40-Hz (gamma band) frequency have been observed in schizophrenia and rodent studies of N-methyl D-aspartate glutamate receptor (NMDAR) hypofunction. However, the extent to which 40-Hz ASSR abnormalities in schizophrenia resemble deficits in 40-Hz ASSR induced by acute administration of ketamine, an NMDAR antagonist, is not yet known.

Methods: To address this knowledge gap, we conducted parallel EEG studies: a crossover, placebo-controlled ketamine drug challenge study in healthy subjects (Study 1) and a comparison of patients with schizophrenia and healthy controls subjects (Study 2). Time-frequency analysis of the ASSR was used to calculate baseline, broadband gamma power, evoked power, total power, phase-locking factor, and phase-locking angle.

Results: Relative to healthy controls, schizophrenia patients exhibited increases in pre-stimulus broadband gamma power and reductions in 40-Hz ASSR evoked power, total power, and phase-locking factor, replicating prior studies. However, we failed to replicate previous findings of 40-Hz ASSR phase delay in schizophrenia. Relative to placebo, ketamine: increased pre-stimulus broadband gamma power, reduced 40-Hz ASSR evoked power, total power, and phase-locking factor, and advanced the phase of the 40-Hz ASSR.

Conclusion: Normalized by their respective control groups/conditions, direct comparison of these measures between schizophrenia and ketamine data only revealed significant differences in phase, supporting the role of NMDAR hypofunction in mediating gamma oscillation abnormalities in schizophrenia.

Background: Autism Spectrum Disorder (ASD) and alexithymia are both linked to difficulties in facial affect recognition (FAR) alongside differences in social brain activity. According to the Alexithymia Hypothesis, difficulties in emotion processing in ASD can be attributed to increased levels of co-occurring alexithymia. Despite substantial evidence supporting the hypothesis at the behavioral level, the effects of co-occurring alexithymia on brain function during FAR remain unexplored.

Methods: Data from 120 participants (60 ASD, 60 controls) who completed an FAR task were analyzed using functional magnetic resonance imaging and behavioral measures. The task included both explicit and implicit measures of FAR. Autistic participants were further categorized based on their alexithymia status. Group differences in FAR performance and associated brain activation were investigated.

Results: Autistic participants showed lower FAR performance compared to controls, regardless of alexithymia status. Imaging revealed three cortical clusters with reduced activation in alexithymic compared to non-alexithymic ASD participants during explicit FAR, including the left inferior parietal gyrus, cuneus, and middle temporal gyrus. During implicit FAR, alexithymic ASD participants showed three cortical clusters of increased activation, including the left precentral gyrus, right precuneus, and temporoparietal junction.

Discussion: Our study shows an unexpected dissociation between behavior and brain response: While ASD affects FAR performance, only co-occurring alexithymia modulates corresponding social brain activations. Though not supporting the Alexithymia Hypothesis on the behavioral level, the study highlights the complex relationship between ASD and co-occurring alexithymia, emphasizing the significance of co-occurring conditions in understanding emotion processing in ASD.

Background: Although combat-deployed soldiers are at a high risk for developing trauma-related psychopathology, most will remain resilient for the duration and aftermath of their deployment tour. The neural basis of this type of resilience is largely unknown, and few longitudinal studies exist on neural adaptation to combat in resilient individuals for whom a pre-exposure measurement was collected. Here, we delineate changes in the architecture of functional brain networks from pre- to post-combat in psychopathology-free, resilient participants.

Methods: Tier 1 infantry recruits (n=50) participated in this longitudinal functional MRI (fMRI) study, along with a comparison group of university students (n=50). Changes in within- and between-network functional connectivity as a function of exposure group were analyzed.

Results: Significant group-by-time interactions manifested in the default mode, cognitive control, and ventral attention networks: significant increases from baseline, in both within- and between-network connectivity, were noted post-deployment in soldiers only.

Conclusions: These results indicate global changes in brain functional architecture in resilient combat-deployed participants relative to age-matched students, suggesting that neural adaptation may support resilience to combat exposure.

Clinicaltrials: gov Identifier: NCT04651192; https://clinicaltrials.gov/study/NCT04651192.

Background: Self-regulation often is disrupted in depression and is characterized by negative affect and inflexible parasympathetic responses. Yet, our understanding of brain mechanisms of self-regulatory processes largely has been limited to laboratory contexts. Measuring individual differences in self-regulatory processes in everyday life - and their neural correlates - could inform our understanding of depression phenotypes and reveal novel intervention targets that impact everyday functioning.

Methods: In individuals with remitted major depressive disorder (rMDD) and healthy comparison participants (N=74), we measured two dimensions of regulation success in everyday life - perceived success with regulating affect, and physiological success (parasympathetic augmentation following regulation attempts) - and their neural correlates using an fMRI emotion regulation task.

Results: Perceptions of success were weakly associated with physiological success and had partially distinct neural correlates. Perceived success and physiological success in everyday life predicted reduced activity in brain regions involved in emotional salience while reacting to aversive stimuli in the scanner. During reappraisal in the scanner, greater perceived success in everyday life was dimensionally associated with more reappraisal-related activity in regions involved in cognitive control (including dorsolateral and dorsomedial prefrontal cortex); in contrast, physiological success predicted enhanced downregulation of salience network activity (amygdala, insula).

Conclusions: Results suggest linking psychophysiology with behavior in everyday life can provide a window into dissociable dimensions of self-regulatory functioning. Integrating ambulatory and brain-based metrics may elucidate self-regulatory phenotypes with distinct neurophysiological mechanisms and targets for intervention to impact functioning in daily life.

Background: Decision-making in uncertain environments can lead to varied outcomes, and how we process those outcomes may depend on our emotional state. Understanding how individuals interpret the sources of uncertainty is crucial for understanding adaptive behavior and mental well-being. Uncertainty can be broadly categorized into two components: volatility and stochasticity. Volatility describes how quickly conditions change. Stochasticity, on the other hand, refers to outcome randomness. We investigated how anxiety and apathy influenced people's perceptions of uncertainty, and how uncertainty perception shaped explore-exploit decisions.

Methods: Participants (N = 1001, non-clinical sample) completed a restless three-armed bandit task that was analyzed using both latent state and process models.

Results: Anxious individuals perceived uncertainty as resulting more from volatility, leading to increased exploration and learning rates, especially after reward omission. Conversely, apathetic individuals viewed uncertainty as more stochastic, resulting in decreased exploration and learning rates. The perceived volatility-to-stochasticity ratio mediated the anxiety-exploration relationship post-adverse outcomes. Dimensionality reduction showed exploration and uncertainty estimation to be distinct but related latent factors shaping a manifold of adaptive behavior that is modulated by anxiety and apathy.

Conclusions: These findings reveal distinct computational mechanisms for how anxiety and apathy influence decision-making, providing a framework for understanding cognitive and affective processes in neuropsychiatric disorders.

Objective: Acute experimental models of antidepressant placebo effects suggest that expectancies, encoded within the salience network (SN), are reinforced by sensory evidence and mood fluctuations. However, whether these dynamics extend to longer timescales remains unknown. To answer this question, we investigated how SN and default mode network (DMN) functional connectivity during the processing of antidepressant expectancies facilitates the shift from salience attribution to contextual cues in the SN to belief-induced mood responses in the DMN, both acutely and long-term.

Methods: Sixty psychotropic-free patients with major depressive disorder (MDD) completed an acute antidepressant placebo fMRI experiment manipulating placebo-associated expectancies and their reinforcement while assessing trial-by-trial mood improvement, before entering an 8-week double-blind, randomized, placebo-controlled trial (RCT) of a selective serotonin reuptake inhibitor (SSRI) or placebo.

Results: Learned antidepressant expectancies predicted by a reinforcement learning model modulated SN-DMN connectivity. Acutely, greater modulation predicted higher effects of expectancy and reinforcement manipulations on reported expectancies and mood. Over 8 weeks, no significant drug effects on mood improvement were observed. However, participants who believed they were receiving an antidepressant exhibited significantly greater mood improvement, irrespective of the actual treatment received. Moreover, increased SN-DMN connectivity predicted mood improvement, especially in placebo-treated participants who believed they received an SSRI.

Conclusion: SN-DMN interactions may play a critical role in the evolution of antidepressant response expectancies, drug-assignment beliefs, and their effects on mood.

Objective: Conduct disorder (CD) is associated with deficits in the use of punishment for reinforcement learning (RL) and subsequent decision-making, contributing to reckless, antisocial, and aggressive behaviors. Here, we used functional magnetic resonance imaging (fMRI) to examine whether differences in behavioral learning rates derived from computational modeling, particularly for punishment, are reflected in aberrant neural responses in youths with CD compared to typically-developing controls (TDCs).

Methods: 75 youths with CD and 99 TDCs (9-18 years, 47% girls) performed a probabilistic RL task with punishment, reward, and neutral contingencies. Using fMRI data in conjunction with computational modeling indices (learning rate α), we investigated group differences for the three learning conditions in whole-brain and regions-of-interest (ROI) analyses, including the ventral striatum and insula.

Results: Whole-brain analysis revealed typical neural responses for RL in both groups. However, linear regression models for the ROI analyses revealed that only the response pattern of the (anterior) insula during punishment learning was different in CD compared to TDCs.

Conclusions: Youths with CD have atypical neural responses to learning from punishment (but not from reward), specifically in the insula. This suggests a selective dysfunction of RL mechanisms in CD thereby contributing to 'punishment insensitivity/hyposensitivity' as a hallmark of the disorder. As the (anterior) insula is involved in avoidance behaviors related to negative affect or arousal, insula dysfunction in CD may contribute to inappropriate behavioral decision-making, which increases the risk for reckless, antisocial, and aggressive behaviors in affected youth.

Background: Effective connectivity (EC) analysis provides valuable insights into the directionality of neural interactions, crucial for understanding the mechanisms underlying cognitive and emotional regulation in depressive and anxiety disorders. This study examined EC within key neural networks during working memory (WM) and emotional regulation (ER) tasks in young adults, both healthy and seeking help from mental health professionals for emotional distress.

Methods: Dynamic Causal Modeling (DCM) was employed to analyze EC in two independent samples (n=97 and n=94). Participants performed an emotional n-back task to assess EC across the Central Executive Network (CEN), Default Mode Network (DMN), Salience Network (SN), and Face Processing Network. Group-level Parametric Empirical Bayes (PEB) analyses were conducted to examine EC patterns, with sub-analyses comparing individuals with and without depression and anxiety.

Results: Consistent patterns of positive (posterior probability > 0.95) DMN→CEN and DMN→SN EC were observed in both samples, predominantly in Low and High WM conditions without ER. However, individuals without depressive or anxiety disorders exhibited a significantly greater number of preserved connections that were replicated across both samples.

Conclusions: This study highlights the different patterns of DMN→CEN EC in conditions with High and Low WM loads with/without ER, suggesting that in higher WM loads with ER, the integration of the DMN with the CEN is reduced to facilitate successful cognitive task performance. The findings also suggest that DMN→CEN and DMN→SN EC are significantly reduced in depressive and anxiety disorders, highlighting this pattern of reduced EC as a potential neural marker of these disorders.

The default mode network (DMN) is intricately linked with processes such as self-referential thinking, episodic memory recall, goal-directed cognition, self-projection, and theory of mind. Over recent years, there has been a surge in examining its functional connectivity, particularly its relationship with frontoparietal networks (FPN) involved in top-down attention, executive function, and cognitive control. The fluidity in switching between these internal and external modes of processing-highlighted by anti-correlated functional connectivity-has been proposed as an indicator of cognitive health. Due to the ease of estimation of functional connectivity-based measures through resting state fMRI paradigms, there is now a wealth of large-scale datasets, paving the way for standardized connectivity benchmarks. This review delves into the promising role of DMN connectivity metrics as potential biomarkers of cognitive state across attention, internal mentation, mind wandering and meditation states, and investigating deviations in trait-level measures across aging and in clinical conditions such as Alzheimer's disease, Parkinson's, depression, ADHD, and others. Additionally, we tackle the issue of reliability of network estimation and functional connectivity and share recommendations for using functional connectivity measures as a biomarker of cognitive health.

Background: Chronic cortisol overexposure plays a significant role in the development of neuropathological changes associated with neuropsychiatric and neurodegenerative disorders. The hippocampus, the primary target of cortisol, may exhibit characteristic regional responses due to its internal heterogeneity. This study explores structural and functional alterations of hippocampal subfields in Cushing's disease (CD), an endogenous model of chronic cortisol overexposure.

Methods: Utilizing structural and resting-state functional magnetic resonance imaging data from 169 participants (86 CD patients and 83 healthy controls) recruited from a single center, we investigated specific structural changes in hippocampal subfields and explored the functional connectivity alterations driven by these structural abnormalities. We also analyzed potential associative mechanisms between these changes and biological attributes, neuropsychiatric representations, cognitive function, and gene expression profiles.

Results: Compared to healthy controls, CD patients exhibited significant bilateral volume reductions in multiple hippocampal subfields. Notably, volumetric decreases in the left hippocampal body and tail subfields were significantly correlated with cortisol levels, Montreal Cognitive Assessment scores, and quality of life measures. Disrupted connectivity between the structurally abnormal hippocampal subfields and ventromedial prefrontal cortex may impair reward-based decision making and emotional regulation, with this dysconnectivity linked to structural changes in right hippocampal subfields. Additionally, another region exhibiting dysconnectivity was located in the left pallidum and putamen. Gene expression patterns associated with synaptic components may underlie these macrostructural alterations.

Conclusions: Our findings elucidate the subfield-specific effects of chronic cortisol overexposure on the hippocampus, enhancing understanding of shared neuropathological traits linked to cortisol dysregulation in neuropsychiatric and neurodegenerative disorders.