Alcohol-related violence is a serious and common social problem. Moreover, violent behaviour is much more common in alcohol-dependent individuals. Animal experiments and human studies have provided ...insights into the acute effect of alcohol on aggressive behaviour and into common factors underlying acute and chronic alcohol intake and aggression. These studies have shown that environmental factors, such as early-life stress, interact with genetic variations in serotonin-related genes that affect serotonergic and GABAergic neurotransmission. This leads to increased amygdala activity and impaired prefrontal function that, together, predispose to both increased alcohol intake and impulsive aggression. In addition, acute and chronic alcohol intake can further impair executive control and thereby facilitate aggressive behaviour.
Dysfunctional decision-making has been implicated in the positive and negative symptoms of schizophrenia. Decision-making can be conceptualized within the framework of hierarchical predictive coding ...as the result of a Bayesian inference process that uses prior beliefs to infer states of the world. According to this idea, prior beliefs encoded at higher levels in the brain are fed back as predictive signals to lower levels. Whenever these predictions are violated by the incoming sensory data, a prediction error is generated and fed forward to update beliefs encoded at higher levels. Well-documented impairments in cognitive decision-making support the view that these neural inference mechanisms are altered in schizophrenia. There is also extensive evidence relating the symptoms of schizophrenia to aberrant signaling of prediction errors, especially in the domain of reward and value-based decision-making. Moreover, the idea of altered predictive coding is supported by evidence for impaired low-level sensory mechanisms and motor processes. We review behavioral and neural findings from these research areas and provide an integrated view suggesting that schizophrenia may be related to a pervasive alteration in predictive coding at multiple hierarchical levels, including cognitive and value-based decision-making processes as well as sensory and motor systems. We relate these findings to decision-making processes and propose that varying degrees of impairment in the implicated brain areas contribute to the variety of psychotic experiences.
•Altered predictive coding may account for impaired decision-making in schizophrenia.•Decision-making can be conceptualized within the predictive-coding framework.•Empirical data suggest impairments in all brain circuits relevant for decision-making.•Heterogeneity of psychosis may be due to varying impairments in predictive coding.
The brain is an inherently dynamic system, and executive cognition requires dynamically reconfiguring, highly evolving networks of brain regions that interact in complex and transient communication ...patterns. However, a precise characterization of these reconfiguration processes during cognitive function in humans remains elusive. Here, we use a series of techniques developed in the field of “dynamic network neuroscience” to investigate the dynamics of functional brain networks in 344 healthy subjects during a working-memory challenge (the “n-back” task). In contrast to a control condition, in which dynamic changes in cortical networks were spread evenly across systems, the effortful working-memory condition was characterized by a reconfiguration of frontoparietal and frontotemporal networks. This reconfiguration, which characterizes “network flexibility,” employs transient and heterogeneous connectivity between frontal systems, which we refer to as “integration.” Frontal integration predicted neuropsychological measures requiring working memory and executive cognition, suggesting that dynamic network reconfiguration between frontal systems supports those functions. Our results characterize dynamic reconfiguration of large-scale distributed neural circuits during executive cognition in humans and have implications for understanding impaired cognitive function in disorders affecting connectivity, such as schizophrenia or dementia.
Abstract
Social isolation and discrimination are growing public health concerns associated with poor physical and mental health. They are risk factors for increased morbidity and mortality and ...reduced quality of life. Despite their detrimental effects on health, there is a lack of knowledge regarding translation across the domains of experimental research, clinical studies, and real-life applications. Here, we review and synthesize evidence from basic research in animals and humans to clinical translation and interventions. Animal models indicate that social separation stress, particularly in early life, activates the hypothalamic-pituitary-adrenal axis and interacts with monoaminergic, glutamatergic, and GABAergic neurotransmitter systems, inducing long-lasting reductions in serotonin turnover and alterations in dopamine receptor sensitivity. These findings are of particular importance for human social isolation stress, as effects of social isolation stress on the same neurotransmitter systems have been implicated in addictive, psychotic, and affective disorders. Children may be particularly vulnerable due to lasting effects of social isolation and discrimination stress on the developing brain. The effects of social isolation and loneliness are pronounced in the context of social exclusion due to discrimination and racism, during widespread infectious disease related containment strategies such as quarantine, and in older persons due to sociodemographic changes. This highlights the importance of new strategies for social inclusion and outreach, including gender, culture, and socially sensitive telemedicine and digital interventions for mental health care.
•Many patients with chronic pain show distorted body images.•Improvements in body images go along with symptom improvement in chronic pain.•Multisensory feedback interventions are promising to treat ...distorted body images.•Virtual reality feedback training can modify links between innocuous input and pain.•Virtual reality interventions could improve distorted body images in chronic pain.
Individuals with chronic pain often show a distorted body image. Various studies demonstrated that improvements in body image go along with symptom improvement in chronic pain. This renders distorted body images a promising target for feedback intervention programs. We propose that interventions that comprise of virtual reality (VR) multisensory feedback training provide a promising new avenue for the treatment of chronic pain. Thus far, VR-based interventions have been primarily applied to distract patients from pain. Recently, first attempts have been made to apply VR-based interventions as active sensory feedback training. VR-based feedback training allows the dynamic modification of virtual limbs that are perceived as one’s own. This offers unique opportunities to target long-term associations between sensory input and pain in patients with chronic pain. We predict that multisensory VR feedback interventions could be effective in reducing fear-avoidance behavior and improving distorted body images. We review current developments and provide an outlook on future directions in the promising field of VR feedback interventions for the multisensory treatment of chronic pain.
Increased striatal dopamine synthesis capacity has consistently been reported in patients with schizophrenia. However, the mechanism translating this into behavior and symptoms remains unclear. It ...has been proposed that heightened striatal dopamine may blunt dopaminergic reward prediction error signaling during reinforcement learning. In this study, we investigated striatal dopamine synthesis capacity, reward prediction errors, and their association in unmedicated schizophrenia patients (n = 19) and healthy controls (n = 23). They took part in FDOPA-PET and underwent functional magnetic resonance imaging (fMRI) scanning, where they performed a reversal-learning paradigm. The groups were compared regarding dopamine synthesis capacity (Kicer), fMRI neural prediction error signals, and the correlation of both. Patients did not differ from controls with respect to striatal Kicer. Taking into account, comorbid alcohol abuse revealed that patients without such abuse showed elevated Kicer in the associative striatum, while those with abuse did not differ from controls. Comparing all patients to controls, patients performed worse during reversal learning and displayed reduced prediction error signaling in the ventral striatum. In controls, Kicer in the limbic striatum correlated with higher reward prediction error signaling, while there was no significant association in patients. Kicer in the associative striatum correlated with higher positive symptoms and blunted reward prediction error signaling was associated with negative symptoms. Our results suggest a dissociation between striatal subregions and symptom domains, with elevated dopamine synthesis capacity in the associative striatum contributing to positive symptoms while blunted prediction error signaling in the ventral striatum related to negative symptoms.
The COVID-19 pandemic and its associated lockdown measures impacted mental health worldwide. However, the temporal dynamics of causal factors that modulate mental health during lockdown are not well ...understood.
We aimed to understand how a COVID-19 lockdown changes the temporal dynamics of loneliness and other factors affecting mental health. This is the first study that compares network characteristics between lockdown stages to prioritize mental health intervention targets.
We combined ecological momentary assessments with wrist-worn motion tracking to investigate the mechanism and changes in network centrality of symptoms and behaviors before and during lockdown. A total of 258 participants who reported at least mild loneliness and distress were assessed 8 times a day for 7 consecutive days over a 213-day period from August 8, 2020, through March 9, 2021, in Germany, covering a "no-lockdown" and a "lockdown" stage. COVID-19-related worry, information-seeking, perceived restriction, and loneliness were assessed by digital visual analog scales ranging from 0 to 100. Social activity was assessed on a 7-point Likert scale, while physical activity was recorded from wrist-worn actigraphy devices.
We built a multilevel vector autoregressive model to estimate dynamic networks. To compare network characteristics between a no-lockdown stage and a lockdown stage, we performed permutation tests. During lockdown, loneliness had the highest impact within the network, as indicated by its centrality index (ie, an index to identify variables that have a strong influence on the other variables). Moreover, during lockdown, the centrality of loneliness significantly increased. Physical activity contributed to a decrease in loneliness amid the lockdown stage.
The COVID-19 lockdown increased the central role of loneliness in triggering stress-related behaviors and cognition. Our study indicates that loneliness should be prioritized in mental health interventions during lockdown. Moreover, physical activity can serve as a buffer for loneliness amid social restrictions.
Post‐traumatic stress disorder (PTSD) is a psychiatric disorder of high prevalence and major socioeconomic impact. Patients suffering from PTSD typically present intrusion and avoidance symptoms and ...alterations in arousal, mood and cognition that last for more than 1 month. Animal models are an indispensable tool to investigate underlying pathophysiological pathways and, in particular, the complex interplay of neuroendocrine, genetic and environmental factors that may be responsible for PTSD induction. Since the 1960s, numerous stress paradigms in rodents have been developed, based largely on Seligman's seminal formulation of ‘learned helplessness’ in canines. Rodent stress models make use of physiological or psychological stressors such as foot shock, underwater trauma, social defeat, early life stress or predator‐based stress. Apart from the brief exposure to an acute stressor, chronic stress models combining a succession of different stressors for a period of several weeks have also been developed. Chronic stress models in rats and mice may elicit characteristic PTSD‐like symptoms alongside, more broadly, depressive‐like behaviours. In this review, the major existing rodent models of PTSD are reviewed in terms of validity, advantages and limitations; moreover, significant results and implications for future research—such as the role of FKBP5, a mediator of the glucocorticoid stress response and promising target for therapeutic interventions—are discussed.
Rationale
A dimensional approach in psychiatry aims to identify core mechanisms of mental disorders across nosological boundaries.
Objectives
We compared anticipation of reward between major ...psychiatric disorders, and investigated whether reward anticipation is impaired in several mental disorders and whether there is a common psychopathological correlate (negative mood) of such an impairment.
Methods
We used functional magnetic resonance imaging (fMRI) and a monetary incentive delay (MID) task to study the functional correlates of reward anticipation across major psychiatric disorders in 184 subjects, with the diagnoses of alcohol dependence (
n
= 26), schizophrenia (
n
= 44), major depressive disorder (MDD,
n
= 24), bipolar disorder (acute manic episode,
n
= 13), attention deficit/hyperactivity disorder (ADHD,
n
= 23), and healthy controls (
n
= 54). Subjects’ individual Beck Depression Inventory-and State-Trait Anxiety Inventory-scores were correlated with clusters showing significant activation during reward anticipation.
Results
During reward anticipation, we observed significant group differences in ventral striatal (VS) activation: patients with schizophrenia, alcohol dependence, and major depression showed significantly less ventral striatal activation compared to healthy controls. Depressive symptoms correlated with dysfunction in reward anticipation regardless of diagnostic entity. There was no significant correlation between anxiety symptoms and VS functional activation.
Conclusion
Our findings demonstrate a neurobiological dysfunction related to reward prediction that transcended disorder categories and was related to measures of depressed mood. The findings underline the potential of a dimensional approach in psychiatry and strengthen the hypothesis that neurobiological research in psychiatric disorders can be targeted at core mechanisms that are likely to be implicated in a range of clinical entities.
Characterizing the brain connectome using neuroimaging data and measures derived from graph theory emerged as a new approach that has been applied to brain maturation, cognitive function and ...neuropsychiatric disorders. For a broad application of this method especially for clinical populations and longitudinal studies, the reliability of this approach and its robustness to confounding factors need to be explored. Here we investigated test–retest reliability of graph metrics of functional networks derived from functional magnetic resonance imaging (fMRI) recorded in 33 healthy subjects during rest. We constructed undirected networks based on the Anatomic-Automatic-Labeling (AAL) atlas template and calculated several commonly used measures from the field of graph theory, focusing on the influence of different strategies for confound correction. For each subject, method and session we computed the following graph metrics: clustering coefficient, characteristic path length, local and global efficiency, assortativity, modularity, hierarchy and the small-worldness scalar. Reliability of each graph metric was assessed using the intraclass correlation coefficient (ICC).
Overall ICCs ranged from low to high (0 to 0.763) depending on the method and metric. Methodologically, the use of a broader frequency band (0.008–0.15Hz) yielded highest reliability indices (mean ICC=0.484), followed by the use of global regression (mean ICC=0.399). In general, the second order metrics (small-worldness, hierarchy, assortativity) studied here, tended to be more robust than first order metrics.
In conclusion, our study provides methodological recommendations which allow the computation of sufficiently robust markers of network organization using graph metrics derived from fMRI data at rest.
► Test–retest reliability of graph metrics derived from resting-state fMRI. ► Different preprocessing and confound correction methods are examined. ► Moderate overall reliability, but differed between methods. ► Using a broad filter frequency range (0.008–0.15Hz) yielded best results.
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