Causes and consequences of stress generation: Longitudinal associations of negative events, aggressive behaviors, rumination, and depressive symptoms.

The present study examined the causes and consequences of stress generation in university students in Japan. A two-wave longitudinal study with an 8- or 9-week interval was conducted in the fall of 2020. Undergraduate and graduate students at four universities in Japan (N = 201) completed self-report measures assessing experiences of negative interpersonal dependent events, negative non-interpersonal events, and negative independent events at two times. At the same time, they also responded to measures of aggressive behaviors, trait rumination, and depressive symptoms. Path analyses revealed that baseline aggressive behaviors were positively associated with an increase in subsequent negative interpersonal dependent events, even after controlling for the influences of negative interpersonal dependent events, rumination, and depressive symptoms at baseline. However, aggressive behaviors were not significantly associated with subsequent negative non-interpersonal dependent events or negative independent events. These findings suggest that aggressive behaviors may have been a factor leading to interpersonal stress generation. Furthermore, all categories of negative event experiences predicted an increase in subsequent depressive symptoms, but not subsequent rumination, and rumination was not significantly associated with subsequent depressive symptoms. This research extends previous studies on the causes and consequences of stress generation conducted in the US by using specific measures of aggressive behaviors and including a non-restricted sample of university students in Japan. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12144-022-02859-9.

Validation of brain-derived signals in near-infrared spectroscopy through multivoxel analysis of concurrent functional magnetic resonance imaging.

Near-infrared spectroscopy (NIRS) is a convenient and safe brain-mapping tool. However, its inevitable confounding with hemodynamic responses outside the brain, especially in the frontotemporal head, has questioned its validity. Some researchers attempted to validate NIRS signals through concurrent measurements with functional magnetic resonance imaging (fMRI), but, counterintuitively, NIRS signals rarely correlate with local fMRI signals in NIRS channels, although both mapping techniques should measure the same hemoglobin concentration. Here, we tested a novel hypothesis that different voxels within the scalp and the brain tissues might have substantially different hemoglobin absorption rates of near-infrared light, which might differentially contribute to NIRS signals across channels. Therefore, we newly applied a multivariate approach, a partial least squares regression, to explain NIRS signals with multivoxel information from fMRI within the brain and soft tissues in the head. We concurrently obtained fMRI and NIRS signals in 9 healthy human subjects engaging in an n-back task. The multivariate fMRI model was quite successfully able to predict the NIRS signals by cross-validation (interclass correlation coefficient = ∼0.85). This result confirmed that fMRI and NIRS surely measure the same hemoglobin concentration. Additional application of Monte-Carlo permutation tests confirmed that the model surely reflects temporal and spatial hemodynamic information, not random noise. After this thorough validation, we calculated the ratios of the contributions of the brain and soft-tissue hemodynamics to the NIRS signals, and found that the contribution ratios were quite different across different NIRS channels in reality, presumably because of the structural complexity of the frontotemporal regions. Hum Brain Mapp 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc.

Behavioral activation for late adolescents with subthreshold depression: a randomized controlled trial.

The main behavioral characteristic of subthreshold depression that is observed in adolescents is the low frequency of exposure to environmental rewards. Therefore, it was considered that a simple intervention conducted in short sessions, focusing on increasing access to positively reinforcing activities, would be efficacious in increasing the availability of rewards. We conduct a randomized controlled trial to examine the efficacy of such a behavioral activation program that was conducted weekly for 5 weeks in 60-min sessions. Late adolescent university students aged 18-19 years with subthreshold depression were randomly allocated to a treatment (n = 62) or a control group (n = 56). The primary outcome of the study was the Beck Depression Inventory-II score. Results indicated that late adolescent students in the treatment group showed significant improvements in their depressive symptoms (effect size -0.90, 95 % CI -1.28 to -0.51) compared to the control group. Students in the treatment group also showed significant improvements in self-reported rating of quality of life and in behavioral characteristics. It is concluded that this intervention had a large and significant effect despite being short and simple and that this low-intensity cognitive behavioral therapy program could be conducted in many different types of institutions. It is suggested that the long-term effects of the treatment program should be targeted for investigation in future studies.

Do Individuals with Alcohol Dependence Show Higher Unfairness Sensitivity? The Relationship Between Impulsivity and Unfairness Sensitivity in Alcohol-Dependent Adults.

BACKGROUND: Alcohol-dependent patients are known to be generally more unfairness sensitive. The ultimatum game (UG) is an experimental task designed to provoke feelings of perceived unfairness. A previous study using the UG has reported more unfairness sensitivity in patients with alcohol dependence than in a nondependent control group; it has been speculated that this increased sensitivity might be due to a difficulty in impulse control. However, the mechanism of this relationship has not been clarified. Therefore, the relationship between unfairness sensitivity in interpersonal relationships and impulsivity was investigated using UG and delay discounting (DD) paradigms. METHODS: Subjects were 32 individuals with alcohol dependency and 36 healthy control individuals; both groups performed UG and DD tasks. RESULTS: Participants with alcohol dependence rejected monetary offers deemed unfair at a significantly higher rate than did control participants. Moreover, the proportion of accepting unfairness was negatively correlated with impulsivity in patients with alcohol dependence. CONCLUSIONS: Perceived unfairness is related to impulsivity in patients with alcohol dependence. These results provide insights concerning the psychopathology of alcohol dependence.

[Brain mechanisms of depression--preliminary evidence from fMRI studies].

Although brain monoamines serotonin, noradrenaline, and dopamine have been repeatedly shown to be linked to depression, it remains unclear how monoamine dysfunction is mechanistically related to symptoms of depression. We hypothesized that imbalances in the networks of regions innervated by monoamines disrupt patients' learning and decision-making abilities, and this disruption could, in turn, lead to symptoms of depression. We have conducted functional magnetic resonance imaging (fMRI) studies on learning and decision-making, mainly focusing on the role of serotonin. Our results suggest that parallel organization for reward prediction at different time scales in the striatum is under differential modulation by serotonin, and that depression is associated with a diminished recruitment of the dorsal striatum, involved in long-term reward prediction. Based on these findings, the brain mechanisms of depression are discussed.

Preliminary assessment of the behavioral activation model in Japanese undergraduate students.

Many studies have reported that behavioral activation is an effective intervention for depression. The behavioral activation model is based on several formulations. For example, depressive mood leads to avoidant behaviors, avoidance negatively affects social contacts, decreased socialization lessens opportunities for positive reinforcement, and a decrease in positive reinforcement results in more depressive mood. The purpose of this study was to examine relationships among avoidant behavior, social contact, frequency of positive reinforcement, and depressive mood by using structural equation modeling to assess support for aspects of this behavioral activation model. Participants were 630 Japanese undergraduate students and vocational school students. Results provided preliminary support for the model. Treating both avoidance and activating behavior might contribute to decreased impairment.

Dismantling cognitive-behavioural therapy components for attention-deficit hyperactivity disorder in adolescents and adults: protocol for a network meta-analysis.

INTRODUCTION: Cognitive-behavioural therapy (CBT) consists of multiple treatment techniques for each treatment model and is tailored to the patient's characteristics. Randomised controlled trials (RCTs) have reported that CBT is effective for attention-deficit/hyperactivity disorder (ADHD); however, which CBT components are effective is unknown. In order to provide the best treatment technique, it is important to know which therapeutic component or combination thereof is more effective and what the specific effect size is. METHODS AND ANALYSIS: We will perform component network meta-analysis (cNMA). The search will include studies published from database inception up to 31 March 2022, in English. The electronic databases of MEDLINE (via PubMed), EMBASE, PsycINFO, ClinicalTrials.gov and Cochrane Library will be searched. We will systematically identify all RCTs in the treatment of ADHD between the ages of 10 and 60 years, comparing interventions composed of various CBT components with controlled interventions. We will perform pairwise and network meta-analysis with random effects to estimate summary ORs and standardised mean differences. We will assess the risk of bias in selected studies using the Cochrane risk of bias tool. ETHICS AND DISSEMINATION: Since we will review published papers, ethical approval is not required. The results from this cNMA will provide a panorama of the CBT-based ADHD studies. The results of this study will be published in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42022323898.

Neural and personality correlates of individual differences related to the effects of acute tryptophan depletion on future reward evaluation.

BACKGROUND/AIMS: In general, humans tend to discount the value of delayed reward. An increase in the rate of discounting leads to an inability to select a delayed reward over a smaller immediate reward (reward-delay impulsivity). Although deficits in the serotonergic system are implicated in this reward-delay impulsivity, there is individual variation in response to serotonin depletion. The aim of the present study was to investigate whether the effects of serotonin depletion on the ability to evaluate future reward are affected by individual personality traits or brain activation. METHODS: Personality traits were assessed using the NEO-Five Factor Inventory and Temperament and Character Inventory. The central serotonergic levels of 16 healthy volunteers were manipulated by dietary tryptophan depletion. Subjects performed a delayed reward choice task that required the continuous estimation of reward value during functional magnetic resonance imaging scanning. RESULTS: Discounting rates were increased in 9 participants, but were unchanged or decreased in 7 participants in response to tryptophan depletion. Participants whose discounting rate was increased by tryptophan depletion had significantly higher neuroticism and lower self-directedness. Furthermore, tryptophan depletion differentially affected the groups in terms of hemodynamic responses to the value of predicted future reward in the right insula. CONCLUSIONS: These results suggest that individuals who have high neuroticism and low self-directedness as personality traits are particularly vulnerable to the effect of low serotonin on future reward evaluation accompanied by altered brain activation patterns.

Sex differences in neural activation to ambiguous facial expression in happy and sad context.

Functional magnetic resonance imaging (fMRI) was used to investigate brain activation associated with a facial expression identification task (stimuli were full emotional, half emotional, or ambiguous in both happy and sad context) in 10 men and 10 women, fMRI assessment revealed significant interaction of sex x context in the right putamen for the ambiguous faces. Women showed a greater BOLD response to ambiguous facial expression in the sad context than in the happy context, while men showed a greater response in the happy context. Further, women showed a greater BOLD response than did men to ambiguous facial expression in the sad context, while men showed a greater response than women in the happy context. These results suggest that sad and happy context differentially modulate right putamen activation related to processing of ambiguous facial expression in men and women.

Metacognitive Ability and the Precision of Confidence.

In prior research, signal detection theory (SDT) has been widely utilized to assess metacognitive ability. However, the SDT metacognitive model requires the use of a two-alternative forced-choice task, while confidence must also be measured discretely. In our model, participants' cognitive ability and their confidence in the cognitive task were used to estimate their metacognitive abilities. Therefore, in this study, a metacognitive model that can be applied to various cognitive tasks was developed. This model implements the item response theory (IRT) and Q-learning models to estimate cognitive ability; participants' metacognitive ability is defined as the discrepancy between their confidence in their cognitive ability and their actual cognitive ability. The entire procedure was divided into two experiments. In experiment 1, two different cognitive tasks were used to estimate metacognitive ability and to examine overall discriminative and convergent validity. Notably, the parameters representing metacognitive ability did not correlate with cognitive ability but were positively correlated between the two tasks. In experiment 2, we performed a similar analysis using a different task to test the replicability of experiment 1. The results for experiment 2 were replicated for discriminative and convergent validity, albeit with weak results. Our metacognitive model exhibited high interpretability and versatility.

Preliminary validation of the self-report measure assessing experiences of negative independent and dependent event frequency in Japanese university students.

Background: In the past, different stress generation studies have used self-report measures comprising different items to assess each category of negative events. Moreover, the validity of these scales has not been adequately investigated. Therefore, we developed a self-report measure dedicated to assessing experiences of negative interpersonal dependent events, negative non-interpersonal dependent events, and negative independent events in university students, which was named the Negative Independent/Dependent Events Scale. Methods: Japanese undergraduate students (N = 247; mean age = 19.18 years, SD = 3.08) responded to the Negative Independent/Dependent Events Scale, which had items selected for adequate content validity. They also responded to self-report measures of depressive symptoms, reassurance-seeking behaviors, inattention, and lack of perseverance. Results: All the negative events subscales had moderate positive correlations with depressive symptoms. In addition, the negative interpersonal dependent events subscale showed a moderate positive correlation with reassurance-seeking behaviors, and the negative non-interpersonal dependent events subscale showed a strong positive correlation with inattention. Furthermore, the negative non-interpersonal dependent events subscale was more strongly correlated with inattention than the other two negative events subscales. In contrast, the negative interpersonal dependent events subscale was more strongly correlated with reassurance-seeking behaviors than with the negative independent events subscale but not more strongly than with the negative non-interpersonal dependent events subscale. Conclusions: These findings indicated the acceptable construct validity of the Negative Independent/Dependent Events Scale. However, further research is necessary to establish the discriminant validity of the negative interpersonal dependent events subscale and the negative non-interpersonal dependent events subscale.

In COVID-19 Health Messaging, Loss Framing Increases Anxiety with Little-to-No Concomitant Benefits: Experimental Evidence from 84 Countries.

The COVID-19 pandemic (and its aftermath) highlights a critical need to communicate health information effectively to the global public. Given that subtle differences in information framing can have meaningful effects on behavior, behavioral science research highlights a pressing question: Is it more effective to frame COVID-19 health messages in terms of potential losses (e.g., "If you do not practice these steps, you can endanger yourself and others") or potential gains (e.g., "If you practice these steps, you can protect yourself and others")? Collecting data in 48 languages from 15,929 participants in 84 countries, we experimentally tested the effects of message framing on COVID-19-related judgments, intentions, and feelings. Loss- (vs. gain-) framed messages increased self-reported anxiety among participants cross-nationally with little-to-no impact on policy attitudes, behavioral intentions, or information seeking relevant to pandemic risks. These results were consistent across 84 countries, three variations of the message framing wording, and 560 data processing and analytic choices. Thus, results provide an empirical answer to a global communication question and highlight the emotional toll of loss-framed messages. Critically, this work demonstrates the importance of considering unintended affective consequences when evaluating nudge-style interventions.

Inter-individual discount factor differences in reward prediction are topographically associated with caudate activation.

In general, humans tend to devalue a delayed reward. Such delay discounting is a theoretical and computational concept in which the discount factor influences the time scale of the trade-off between delay of reward and amount of reward. The discount factor relies on the individual's ability to evaluate the future reward. Using functional magnetic resonance imaging, we investigated brain mechanisms for reward valuation at different individual discount factors in a delayed reward choice task. In the task, participants were required to select small/immediate or large/delayed rewards to maximize the total reward over time. The discount factor for each participant individually was calculated from the behavioral data based on an exponential discounting model. The estimated value of a future reward increases as the expected delivery approaches, so the time course of these estimated values was computed based on each individual's discount factor; each was entered into the regression analysis as an explanatory (independent) variable. After the region of interest was narrowed anatomically to the caudate, a peak coordinate was detected in each individual. A correlation analysis revealed that the location of the peak along the dorsal-ventral axis in the right caudate was positively correlated with the discount factor. This implies that individuals who showed a larger discount factor had peak activations in a more dorsal part of the right caudate associated with future reward prediction. This evidence also suggests that a higher ability to delay reward prediction might be related to activation of the more dorsal caudate.

Classifying patients with depressive and anxiety disorders according to symptom network structures: A Gaussian graphical mixture model-based clustering.

Patients with mental disorders often suffer from comorbidity. Transdiagnostic understandings of mental disorders are expected to provide more accurate and detailed descriptions of psychopathology and be helpful in developing efficient treatments. Although conventional clustering techniques, such as latent profile analysis, are useful for the taxonomy of psychopathology, they provide little implications for targeting specific symptoms in each cluster. To overcome these limitations, we introduced Gaussian graphical mixture model (GGMM)-based clustering, a method developed in mathematical statistics to integrate clustering and network statistical approaches. To illustrate the technical details and clinical utility of the analysis, we applied GGMM-based clustering to a Japanese sample of 1,521 patients (Mage = 42.42 years), who had diagnostic labels of major depressive disorder (MDD; n = 406), panic disorder (PD; n = 198), social anxiety disorder (SAD; n = 116), obsessive-compulsive disorder (OCD; n = 66), comorbid MDD and any anxiety disorder (n = 636), or comorbid anxiety disorders (n = 99). As a result, we identified the following four transdiagnostic clusters characterized by i) strong OCD and PD symptoms, and moderate MDD and SAD symptoms; ii) moderate MDD, PD, and SAD symptoms, and weak OCD symptoms; iii) weak symptoms of all four disorders; and iv) strong symptoms of all four disorders. Simultaneously, a covariance symptom network within each cluster was visualized. The discussion highlighted that the GGMM-based clusters help us generate clinical hypotheses for transdiagnostic clusters by enabling further investigations of each symptom network, such as the calculation of centrality indexes.

Depression, Rumination, and Impulsive Action: A Latent Variable Approach to Behavioral Impulsivity.

Previous research on the relationship between rumination and behavioral impulsivity has been limited because impulsivity was assessed by using individual tasks. This study examined the concurrent associations of a latent variable named impulsive action with rumination and depression to alleviate the task-impurity problem and the low reliability of laboratory tasks assessing impulsivity. This study also examined whether stressors mediated the association between impulsive action and rumination. University students in Japan (N = 176) conducted three laboratory tasks assessing impulsive action: the Go/No-Go Task, the Stop Signal Task, and the Conners Continuous Performance Test 3rd Edition. They also completed self-report measures of rumination, stressors, and depression. Results indicated that the latent variable named impulsive action constructed from the performance in these three tasks was positively associated with rumination. Moreover, stressors mediated this association. Also, impulsive action was positively associated with depression via the increase in stressors and rumination. These findings and those of previous studies examining associations between rumination and self-reported impulsivity suggest that impulsivity might be a determinant of rumination.

Sadness enhances the experience of pain via neural activation in the anterior cingulate cortex and amygdala: an fMRI study.

Pain is a multidimensional experience. Human pain perception can be modulated by subjective emotional responses. We examined this association within the context of a neuroimaging study, using functional MRI to examine neural responses to electrical pain-inducing stimuli in 15 healthy subjects (6 females; age range=20-30 years). Pain-inducing stimuli were presented during different emotional contexts, which were induced via the continuous presentation (5 s) of sad, happy, or neutral pictures of faces. We found that subjective pain ratings were higher in the sad emotional context than in the happy and neutral contexts, and that pain-related activation in the ACC was more pronounced in the sad context relative to the happy and neutral contexts. Psychophysiological interaction (PPI) and dynamic causal modeling (DCM) analyses demonstrated amygdala to ACC connections during the experience of pain in the sad context. These findings serve to highlight the neural mechanisms that may be relevant to understanding the broader relationship between somatic complaints and negative emotion.

Psychosocial functioning in patients with Treatment-Resistant Depression after group cognitive behavioral therapy.

BACKGROUND: Although patients with Treatment Resistant Depression (TRD) often have impaired social functioning, few studies have investigated the effectiveness of psychosocial treatment for these patients. We examined whether adding group cognitive behavioral therapy (group-CBT) to medication would improve both the depressive symptoms and the social functioning of patient with mild TRD, and whether any improvements would be maintained over one year. METHODS: Forty-three patients with TRD were treated with 12 weekly sessions of group-CBT. Patients were assessed with the Global Assessment of Functioning scale (GAF), the 36-item Short-Form Health Survey (SF-36), the Hamilton Rating Scale for Depression (HRSD), the Dysfunctional Attitudes Scale (DAS), and the Automatic Thought Questionnaire-Revised (ATQ-R) at baseline, at the termination of treatment, and at the 12-month follow-up. RESULTS: Thirty-eight patients completed treatment; five dropped out. For the patients who completed treatment, post-treatment scores on the GAF and SF-36 were significantly higher than baseline scores. Scores on the HRSD, DAS, and ATQ-R were significantly lower after the treatment. Thus patients improved on all measurements of psychosocial functioning and mood symptoms. Twenty patients participated in the 12-month follow-up. Their improvements for psychosocial functioning, depressive symptoms, and dysfunctional cognitions were sustained at 12 months following the completion of group-CBT. CONCLUSIONS: These findings suggest a positive effect that the addition of cognitive behavioural group therapy to medication on depressive symptoms and social functioning of mildly depressed patients, showing treatment resistance.

Computational Psychiatry Research Map (CPSYMAP): A New Database for Visualizing Research Papers.

The field of computational psychiatry is growing in prominence along with recent advances in computational neuroscience, machine learning, and the cumulative scientific understanding of psychiatric disorders. Computational approaches based on cutting-edge technologies and high-dimensional data are expected to provide an understanding of psychiatric disorders with integrating the notions of psychology and neuroscience, and to contribute to clinical practices. However, the multidisciplinary nature of this field seems to limit the development of computational psychiatry studies. Computational psychiatry combines knowledge from neuroscience, psychiatry, and computation; thus, there is an emerging need for a platform to integrate and coordinate these perspectives. In this study, we developed a new database for visualizing research papers as a two-dimensional "map" called the Computational Psychiatry Research Map (CPSYMAP). This map shows the distribution of papers along neuroscientific, psychiatric, and computational dimensions to enable anyone to find niche research and deepen their understanding ofthe field.

[Simulation of Schizophrenia].

There have been so many and various researches of schizophrenia since the early days of modern psychiatry, but the pathology remains unexplained, and the treatmens not established. One of the reasons is the complexity of a brain which makes it difficult to form a bridge between biological findings and symptoms. Computational psychiatry has been recently expected to overcome this difficulty. In the field, a brain is seen as an information-processing system, and the dynamics of a brain are expressed using mathematical models. In addition, mental disorders are expressed as changes including parameters in the models. Here, we introduce some studies conducted in Japan.

Linear Ballistic Accumulator Modeling of Attentional Bias Modification Revealed Disturbed Evidence Accumulation of Negative Information by Explicit Instruction.

In recent years, several attentional bias modification (ABM) studies have been conducted. Previous studies have suggested that explicit instruction (i.e., informing participants of the contingency of stimuli) enhances the effect of ABM. However, the specific working mechanism has not been identified. This is partly because reaction time (RT) data are typically reduced to an attention bias score, which is a mere difference of RT between experimental and control conditions. This data reduction causes a loss of information, as RT reflects various cognitive processes at play while making a response or decision. To overcome this issue, the present study applied linear ballistic accumulator (LBA) modeling to the outcomes (RT measures) of explicitly guided (compared to standard) ABM. This computational modeling approach allowed us to dissociate RTs into distinct components that can be relevant for attentional bias, such as efficiency of information processing or prior knowledge of the task; this provides an understanding of the mechanism of action underlying explicitly guided ABM. The analyzed data were RT-observed in the dot-probe task, which was administered before and after 3-days of ABM training. Our main focus was on the changes in LBA components that would be induced by the training. Additionally, we analyzed in-session performances over the 3 days of training. The LBA analysis revealed a significant reduction in processing efficiency (i.e., drift rate) in the congruent condition, where the target probe is presented in the same location as a negative stimulus. This explains the reduction in the overall attentional bias score, suggesting that explicit ABM suppresses processing of negative stimuli. Moreover, the results suggest that explicitly guided ABM may influence prior knowledge of the target location in the training task and make participants prepared to respond to the task. These findings highlight the usefulness of LBA-based analysis to explore the underlying cognitive mechanisms in ABM, and indeed our analyses revealed the differences between the explicit and the standard ABM that could not be identified by traditional RT analysis or attentional bias scores.