Ventromedial prefrontal value signals and functional connectivity during decision-making in suicidal behavior and impulsivity

Ventromedial prefrontal cortex activation and neurofeedback modulation during episodic future thinking for individuals with suicidal thoughts and behaviors

Individuals experiencing suicidal thoughts and behaviors (STBs) show less specificity and positivity during episodic future thinking (EFT). Here, we present findings from two studies aiming to (1) further our understanding of how STBs may relate to neural responsivity during EFT and (2) examine the feasibility of modulating EFT-related activation using real-time fMRI neurofeedback (rtfMRI-nf). Study 1 involved 30 individuals with major depressive disorder (MDD; half with STBs) who performed an EFT task during fMRI, for which they imagined personally-relevant future positive, negative, or neutral events. Positive EFT elicited greater ventromedial prefrontal cortex (vmPFC) activation compared to negative EFT. Importantly, the MDD + STB group exhibited reduced vmPFC activation across all EFT conditions compared to MDD-STB; although EFT fluency and subjective experience remained consistent across groups. Study 2 included rtfMRI-nf focused on vmPFC modulation during positive EFT for six participants with MDD + STBs. Results support the feasibility and acceptability of the rtfMRI-nf protocol and quantitative and qualitative observations are provided to help inform future, larger studies aiming to examine similar neurofeedback protocols. Results implicate vmPFC blunting as a promising treatment target for MDD + STBs and suggest rtfMRI-nf as one potential technique to explore for enhancing vmPFC engagement.

Imagine before you leap: Episodic future thinking combined with transcranial direct current stimulation training for impulsive choice in repetitive negative thinking

Background

Immediate reward preference in repetitive negative thinking (RNT) has a high clinical correlation with a variety of maladaptive behaviors, whereas episodic future thinking (EFT) may be conducive to dealing with non-adaptive thinking and decision-making.

Objectives

This study aimed to evaluate the efficacy of EFT training combined with transcranial direct current stimulation (tDCS) stimulation over the ventromedial PFC (vmPFC) in inhibiting impulsive choice of RNT individuals.

Method

Study 1 explored the effects of EFT on immediate reward preference of participants with high and low RNT (N = 48). Study 2 conducted a randomized controlled trial (RCT) to examine the treatment effect of the EFT-neural training on impulsive choice of high RNT individuals (N = 103).

Results

In study 1, individuals with high RNT were more likely to choose smaller and sooner (SS) rewards, however, there were no significant differences between the high-RNT group and the low-RNT group under the positive EFT condition. In study 2, a significant decrease was shown in the proportion of choosing SS rewards under the 8-week EFT-neural training, and the effect was maintained at 1 month follow-up.

Conclusion

RNT is a vulnerability factor for short-sighted behaviors, and EFT-neural training could be suitable for reducing RNT and improving immediate reward preference.

Functional Abnormality of the Reward System in Depressed Adolescents and Young Adults with and without Suicidal Behavior

OBJECTIVE

To identify local and functional connectivity abnormalities in the brain's reward network in depressed adolescents and young adults with and without suicidal behavior.

METHODS

Magnetic resonance imaging data were obtained from 41 major depressive disorder (MDD) patients with suicidal behavior (sMDD, males/females: 12/29), 44 MDD patients without suicidal behavior (nMDD, males/females: 13/32), and 52 healthy controls (HCs, males/females: 17/35). The Young Mania Scale, Hamilton Depression Scale, Columbia Suicide Scale, and Scale for Suicide Ideation were used to evaluate emotional state and suicidal ideation and behaviors. The amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo) and functional connectivity of 11 regions of interest (ROIs) in the reward network were determined.

RESULTS

ALFF values in the vmPFC of the nMDD group were significantly lower than those in the HC group (p = 0.031). The ReHo values of the nMDD group were lower in the lVS but higher in the vmPFC than those of the HC group (P = 0.018 and 0.025, respectively). Functional connectivity of the AC with the vmPFC, lVS, rVS, and vmPFC was increased in the sMDD group compared with that in the nMDD group (P = 0.038, 0.034, 0.006, respectively).

CONCLUSION

Local and functional connectivity abnormalities in the reward network were found in the MDD groups. However, increased functional connectivity was found in only the sMDD group.

Suicidal thoughts and behaviours among military veterans: protocol for a prospective, observational, neuroimaging study

INTRODUCTION

This study's overarching goal is to examine the relationship between brain circuits and suicidal thoughts and behaviours (STBs) in a transdiagnostic sample of US military veterans. Because STBs have been linked with maladaptive decision-making and disorders linked to impulsivity, this investigation focuses on valence and inhibitory control circuits.

METHODS AND ANALYSIS

In this prospective, observational study, we will collect functional MRI (fMRI), cognitive and clinical data from 136 veterans (target sample size) recruited from the Providence VA Health System (PVAHS): 68 with STBs and 68 matched controls. Behavioural data will be collected using standardised measures of STBs, psychiatric symptoms, cognition, functioning and medical history. Neuroimaging data will include structural, task and resting fMRI. We will conduct follow-up interviews and assessments at 6, 12 and 24 months post-enrolment. Primary analyses will compare data from veterans with and without STBs and will also evaluate whether activation and connectivity within circuits of valence and inhibition covary with historical and prospective patterns of suicidal ideation and behaviour.

ETHICS AND DISSEMINATION

The PVAHS Institutional Review Board approved this study (2018-051). Written informed consent will be obtained from all participants. Findings from this study will be published in peer-reviewed journals and presented at local, regional, national and international conferences.Nauder Namaky, Ph.D.* nauder_namaky@brown.edu.

Suicide prevention and ketamine: insights from computational modeling

Suicide is a pressing public health issue, with over 700,000 individuals dying each year. Ketamine has emerged as a promising treatment for suicidal thoughts and behaviors (STBs), yet the complex mechanisms underlying ketamine's anti-suicidal effect are not fully understood. Computational psychiatry provides a promising framework for exploring the dynamic interactions underlying suicidality and ketamine's therapeutic action, offering insight into potential biomarkers, treatment targets, and the underlying mechanisms of both. This paper provides an overview of current computational theories of suicidality and ketamine's mechanism of action, and discusses various computational modeling approaches that attempt to explain ketamine's anti-suicidal effect. More specifically, the therapeutic potential of ketamine is explored in the context of the mismatch negativity and the predictive coding framework, by considering neurocircuits involved in learning and decision-making, and investigating altered connectivity strengths and receptor densities targeted by ketamine. Theory-driven computational models offer a promising approach to integrate existing knowledge of suicidality and ketamine, and for the extraction of model-derived mechanistic parameters that can be used to identify patient subgroups and personalized treatment approaches. Future computational studies on ketamine's mechanism of action should optimize task design and modeling approaches to ensure parameter reliability, and external factors such as set and setting, as well as psychedelic-assisted therapy should be evaluated for their additional therapeutic value.

Dissociated deficits of anticipated and experienced regret in at-risk suicidal individuals

Backgrounds

Decision-making deficits have been reported as trans-diagnostic characteristics of vulnerability to suicidal behaviors, independent of co-existing psychiatric disorders. Individuals with suicidal behaviors often regret their decision to attempt suicide and may have impairments in future-oriented processing. However, it is not clear how people with suicidal dispositions use future-oriented cognition and past experience of regret to guide decision-making. Here, we examined the processes of regret anticipation and experience in subclinical youth with and without suicidal ideation during value-based decision-making.

Methods

In total, 80 young adults with suicidal ideation and 79 healthy controls completed a computational counterfactual thinking task and self-reported measures of suicidal behaviors, depression, anxiety, impulsivity, rumination, hopelessness, and childhood maltreatment.

Results

Individuals with suicidal ideation showed a reduced ability to anticipate regret compared to healthy controls. Specifically, suicidal ideators’ experience of regret/relief was significantly different from that of healthy controls upon obtained outcomes, while their disappointment/pleasure experience was not significantly different from healthy controls.

Conclusion

These findings suggest that young adults with suicidal ideation have difficulty predicting the consequences or the future value of their behavior. Individuals with suicidal ideation showed impairments in value comparison and flat affect to retrospective rewards, whereas individuals with high suicidality showed blunted affect to immediate rewards. Identifying the counterfactual decision-making characteristics of at-risk suicidal individuals may help to elucidate measurable markers of suicidal vulnerability and identify future intervention targets.

Depression and approach-avoidance decisions to emotional displays: The role of anhedonia

Depression is linked to dysfunctional appetitive and aversive motivational systems and effort-based decision-making, yet whether such deficits extend to social decisions remains unclear. Participants (23 non-depressed, 48 depressed - 24 with a past history of suicide attempt) completed a social decision-making task consisting in freely choosing whether to approach or avoid individuals displaying happy or angry expressions. Occasionally, participants had to make a further effort (change button press) to obtain the desired outcome. All participants preferentially avoided anger on their first choice. Yet, depressed patients less often chose to approach happy individuals, as a function of anhedonia severity. Depressed patients were also less inclined than controls to change their response when the anticipated outcome of their first choice was undesirable (approach angry and avoid happy). Again, such effect correlated with anhedonia severity. Our results support that both altered valuation and willingness to exert effort impact approach-avoidance decisions in social contexts in depression. On this basis, we propose a new integrating framework for reconciling different hypotheses on the effect of depression and anhedonia on motivational responses to emotional stimuli.

Neuroimaging alterations of the suicidal brain and its relevance to practice: an updated review of MRI studies

Suicide is a leading cause of death in the United States. Historically, scientific inquiry has focused on psychological theory. However, more recent studies have started to shed light on complex biosignatures using MRI techniques, including task-based and resting-state functional MRI, brain morphometry, and diffusion tensor imaging. Here, we review recent research across these modalities, with a focus on participants with depression and Suicidal Thoughts and Behavior (STB). A PubMed search identified 149 articles specific to our population of study, and this was further refined to rule out more diffuse pathologies such as psychotic disorders and organic brain injury and illness. This left 69 articles which are reviewed in the current study. The collated articles reviewed point to a complex impairment showing atypical functional activation in areas associated with perception of reward, social/affective stimuli, top-down control, and reward-based learning. This is broadly supported by the atypical morphometric and diffusion-weighted alterations and, most significantly, in the network-based resting-state functional connectivity data that extrapolates network functions from well validated psychological paradigms using functional MRI analysis. We see an emerging picture of cognitive dysfunction evident in task-based and resting state fMRI and network neuroscience studies, likely preceded by structural changes best demonstrated in morphometric and diffusion-weighted studies. We propose a clinically-oriented chronology of the diathesis-stress model of suicide and link other areas of research that may be useful to the practicing clinician, while helping to advance the translational study of the neurobiology of suicide.

An fMRI examination of the neural basis of suicide attempts: The role of mentalizing in the context of mood

OBJECTIVES

Facial emotion recognition (FER) deficits in depressed mood disorder patients contribute to suicidality. Prior research shows that intrinsic brain activity patterns are altered by attempting suicide. Therefore, we investigated in depressed patients whether differences in FER contribute to their clinical symptoms of suicide.

METHODS

Neural activity in response to an FER task was compared across three groups: healthy controls (HCs, N = 66), suicide non-attempter (SNA, N = 50), suicide attempter (SA, N = 25). Modulation of brain networks by the task and functional connectivity (FC) within (using spatial map, spectral power) and between (using functional network connectivity; FNC) were examined. The contribution of these differences to suicidal symptoms in each group was also examined.

RESULTS

Patient groups displayed impaired FC both within and between networks but differed in nature and networks involved. They also showed differential modulation of networks by task, such that compared with both HC and SNA, SA displayed impaired FC within the default-mode network (DMN) and also its task modulation. In the SA group, FC within the DMN and FNC between two lateral prefrontal networks, and its interaction with the basal ganglia network contributed significantly to the clinical symptoms of suicide.

CONCLUSIONS

This study affirms differences between SA and SNA brain activity patterns and suggests that suicidal activity probably emanates via different mechanisms in these patient groups. Perhaps, over-attribution of emotion impairs one's self-referential thought processes and coupled with diminished emotional control this makes depressed individuals vulnerable to suicide.

Self-injurious thoughts and behaviors and alterations in positive valence systems: A systematic review of the literature

Self-injurious thoughts and behaviors (SITBs), which include suicidal ideation (SI), suicide attempts (SA), and nonsuicidal self-injury (NSSI), are prevalent and associated with impairments in functioning and elevated risk of suicide deaths. Preventing suicide is a complex problem, with numerous systems likely contributing to the onset and maintenance of SITBs, and there is a critical need to identify more precise predictors of risk. Positive valence systems (PVS) are an understudied domain with promise for improving understanding of risk processes underlying SITBs. In this systematic review, we evaluate the evidence for the potential role of altered PVS function in SI, SA, and/or NSSI, including alterations in reward responsiveness, learning, and valuation assessed through behavioral, physiological and circuit measures. Results provide preliminary support for associations between distinct aspects of PVS function and alterations in SITBs. Specifically, SI appears to be characterized by low reward responsiveness, whereas little research has examined reward responsiveness in SA, and NSSI has been characterized by hyper-responsiveness to rewards. Alterations in reward learning and valuation are commonly examined in SA, with some evidence that they may be more strongly associated with attempts than SI or NSSI. At the same time, the literature is limited in that some constructs are commonly examined in one form of SITBs but not others. Further, research is predominantly cross-sectional and focused on adults, raising questions about the role of PVS function in developmental pathways to SITBs. We conclude by integrating the research to date and highlighting promising directions for future research.

Momentary interpersonal processes of suicidal surges in borderline personality disorder

BACKGROUND

Suicide rates are high in borderline personality disorder (BPD) where interpersonal problems trigger intense affective dysregulation and impulses to act on suicidal thoughts. To date, however, no study has examined how interpersonal stressors contribute to momentary within-person links among affect and impulsivity with suicidal ideation (SI), and how those links vary over time in people's daily lives.

METHODS

A total of 153 individuals diagnosed with BPD and 52 healthy controls completed a 21-day ecological momentary assessment protocol. Of these 153 individuals with BPD, 105 had a history of suicide attempts. Multilevel structural equation modeling was used to examine dynamic links among interpersonal perceptions, affect, state impulsivity, and suicidal intent.

RESULTS

Aggregated across interactions, lower perceived warmth in others was associated with SI. This direct relationship, however, did not extend to momentary within-person associations. Instead, interpersonal conflicts were linked to SI indirectly via greater negative affect and lower positive affect. While a robust within-person link between interpersonal perceptions and impulsivity emerged, impulsivity did not account for the relationship between interpersonal perceptions and SI.

CONCLUSION

This intensive longitudinal study illustrates momentary interpersonal signatures of an emerging suicidal crisis. Among people with BPD at high risk for suicide, interpersonal triggers initiate a cascade of affective dysregulation, which in turn gives rise to SI.

Exploring neurometabolic alterations in bipolar disorder with suicidal ideation based on proton magnetic resonance spectroscopy and machine learning technology

Bipolar disorder (BD) is associated with a high risk of suicide. We used proton magnetic resonance spectroscopy (1H-MRS) to detect biochemical metabolite ratios in the bilateral prefrontal white matter (PWM) and hippocampus in 32 BD patients with suicidal ideation (SI) and 18 BD patients without SI, identified potential brain biochemical differences and used abnormal metabolite ratios to predict the severity of suicide risk based on the support vector machine (SVM) algorithm. Furthermore, we analyzed the correlations between biochemical metabolites and clinical variables in BD patients with SI. There were three main findings: (1) the highest classification accuracy of 88% and an area under the curve of 0.9 were achieved in distinguishing BD patients with and without SI, with N-acetyl aspartate (NAA)/creatine (Cr), myo-inositol (mI)/Cr values in the bilateral PWM, NAA/Cr and choline (Cho)/Cr values in the left hippocampus, and Cho/Cr values in the right hippocampus being the features contributing the most; (2) the above seven features could be used to predict Self-rating Idea of Suicide Scale scores (r = 0.4261, p = 0.0302); and (3) the level of neuronal function in the left hippocampus may be related to the duration of illness, the level of membrane phospholipid catabolism in the left hippocampus may be related to the severity of depression, and the level of inositol metabolism in the left PWM may be related to the age of onset in BD patients with SI. Our results showed that the combination of multiple brain biochemical metabolites could better predict the risk and severity of suicide in patients with BD and that there was a significant correlation between biochemical metabolic values and clinical variables in BD patients with SI.

A Computational Model of Hopelessness and Active-Escape Bias in Suicidality

Currently, psychiatric practice lacks reliable predictive tools and a sufficiently detailed mechanistic understanding of suicidal thoughts and behaviors (STB) to provide timely and personalized interventions. Developing computational models of STB that integrate across behavioral, cognitive and neural levels of analysis could help better understand STB vulnerabilities and guide personalized interventions. To that end, we present a computational model based on the active inference framework. With this model, we show that several STB risk markers - hopelessness, Pavlovian bias and active-escape bias - are interrelated via the drive to maximize one's model evidence. We propose four ways in which these effects can arise: (1) increased learning from aversive outcomes, (2) reduced belief decay in response to unexpected outcomes, (3) increased stress sensitivity and (4) reduced sense of stressor controllability. These proposals stem from considering the neurocircuits implicated in STB: how the locus coeruleus - norepinephrine (LC-NE) system together with the amygdala (Amy), the dorsal prefrontal cortex (dPFC) and the anterior cingulate cortex (ACC) mediate learning in response to acute stress and volatility as well as how the dorsal raphe nucleus - serotonin (DRN-5-HT) system together with the ventromedial prefrontal cortex (vmPFC) mediate stress reactivity based on perceived stressor controllability. We validate the model by simulating performance in an Avoid/Escape Go/No-Go task replicating recent behavioral findings. This serves as a proof of concept and provides a computational hypothesis space that can be tested empirically and be used to distinguish planful versus impulsive STB subtypes. We discuss the relevance of the proposed model for treatment response prediction, including pharmacotherapy and psychotherapy, as well as sex differences as it relates to stress reactivity and suicide risk.

Filling the gaps: Cognitive control as a critical lens for understanding mechanisms of value-based decision-making

While often seeming to investigate rather different problems, research into value-based decision making and cognitive control have historically offered parallel insights into how people select thoughts and actions. While the former studies how people weigh costs and benefits to make a decision, the latter studies how they adjust information processing to achieve their goals. Recent work has highlighted ways in which decision-making research can inform our understanding of cognitive control. Here, we provide the complementary perspective: how cognitive control research has informed understanding of decision-making. We highlight three particular areas of research where this critical interchange has occurred: (1) how different types of goals shape the evaluation of choice options, (2) how people use control to adjust the ways they make their decisions, and (3) how people monitor decisions to inform adjustments to control at multiple levels and timescales. We show how adopting this alternate viewpoint offers new insight into the determinants of both decisions and control; provides alternative interpretations for common neuroeconomic findings; and generates fruitful directions for future research.

Delay discounting in suicidal behavior: Myopic preference or inconsistent valuation?

Prior studies sought to explain the predisposition to suicidal behavior in terms of myopic preference for immediate versus delayed reward, generating mixed evidence. Data from gambling and bandit tasks, however, suggest that suboptimal decisions in suicidal individuals are explained by inconsistent valuation rather than myopic preferences. We tested these two alternative hypotheses using a delay discounting task in 622 adults (suicide attempters with depression, suicide ideators with depression, nonsuicidal participants with depression, and healthy controls) recruited across three sites through inpatient psychiatric units, mood disorders clinics, primary care, and advertisements. Multilevel models revealed group differences in valuation consistencies in all three samples, with high-lethality suicide attempters exhibiting less consistent valuation than all other groups in Samples 1 and 3 and less consistent valuation than the healthy controls or participants with depression in Sample 2. In contrast, group differences in preference for immediate versus delayed reward were observed only in Sample 1 and were due to the high-lethality suicide attempters displaying a weaker preference for immediate reward than low-lethality suicide attempters. The findings were robust to confounds such as cognitive functioning and comorbidities. Seemingly impulsive choices in suicidal behavior are explained by inconsistent reward valuation rather than a true preference for immediate reward. In a suicidal crisis, this inconsistency may result in a misestimation of the value of suicide relative to constructive alternatives and deterrents. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Detecting Suicide Ideation in the Era of Social Media: The Population Neuroscience Perspective

Social media platforms are increasingly used across many population groups not only to communicate and consume information, but also to express symptoms of psychological distress and suicidal thoughts. The detection of suicidal ideation (SI) can contribute to suicide prevention. Twitter data suggesting SI have been associated with negative emotions (e.g., shame, sadness) and a number of geographical and ecological variables (e.g., geographic location, environmental stress). Other important research contributions on SI come from studies in neuroscience. To date, very few research studies have been conducted that combine different disciplines (epidemiology, health geography, neurosciences, psychology, and social media big data science), to build innovative research directions on this topic. This article aims to offer a new interdisciplinary perspective, that is, a Population Neuroscience perspective on SI in order to highlight new ways in which multiple scientific fields interact to successfully investigate emotions and stress in social media to detect SI in the population. We argue that a Population Neuroscience perspective may help to better understand the mechanisms underpinning SI and to promote more effective strategies to prevent suicide timely and at scale.

Social Disconnection in Late Life Suicide: An NIMH Workshop on State of the Research in Identifying Mechanisms, Treatment Targets, and Interventions

Both social disconnection and suicide are significant public health concerns among older adults, and social disconnection is associated with greater risk for suicide-related thoughts and behaviors in late life. We present a synthesis of research discussed during a workshop hosted by the National Institute of Mental Health on social disconnection and late-life suicide. Social disconnection is related to suicide risk in late life via a variety of mechanisms, including biological, behavioral, and psychological correlates. Researchers in several scientific fields have begun to establish these connections and identify targets for interventions to reduce risk in late life. While research has demonstrated that social connection is amenable to change, there is little research to date on the most evidence-based interventions to mitigate social disconnection or the related risks. However, there are several promising biological, behavioral, and psychological interventions that may target various mechanisms, as well as social disconnection itself. With a relative paucity of research in this area, these lines of study are ripe for innovative investigation. In order to most effectively advance the field, we must establish more consistent definitions of social connection and disconnection; more accurately measure and assess older adults' social needs; examine the most effective approaches and modalities for assessment and intervention; take into account important contextual factors; and apply a translational, convergent scientific approach.

New Methods for Assessing Rapid Changes in Suicide Risk

Rapid-acting interventions for the suicide crisis have the potential to transform treatment. In addition, recent innovations in suicide research methods may similarly expand our understanding of the psychological and neurobiological correlates of suicidal thoughts and behaviors. This review discusses the limitations and challenges associated with current methods of suicide risk assessment and presents new techniques currently being developed to measure rapid changes in suicidal thoughts and behavior. These novel assessment strategies include ecological momentary assessment, digital phenotyping, cognitive and implicit bias metrics, and neuroimaging paradigms and analysis methodologies to identify neural circuits associated with suicide risk. This review is intended to both describe the current state of our ability to assess rapid changes in suicide risk as well as to explore future directions for clinical, neurobiological, and computational markers research in suicide-focused clinical trials.

Machine Learning-Based Identification of Suicidal Risk in Patients With Schizophrenia Using Multi-Level Resting-State fMRI Features

BACKGROUND

Some studies suggest that as much as 40% of all causes of death in a group of patients with schizophrenia can be attributed to suicides and compared with the general population, patients with schizophrenia have an 8.5-fold greater suicide risk (SR). There is a vital need for accurate and reliable methods to predict the SR among patients with schizophrenia based on biological measures. However, it is unknown whether the suicidal risk in schizophrenia can be related to alterations in spontaneous brain activity, or if the resting-state functional magnetic resonance imaging (rsfMRI) measures can be used alongside machine learning (ML) algorithms in order to identify patients with SR.

METHODS

Fifty-nine participants including patients with schizophrenia with and without SR as well as age and gender-matched healthy underwent 13 min resting-state functional magnetic resonance imaging. Both static and dynamic indexes of the amplitude of low-frequency fluctuation (ALFF), the fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity as well as functional connectivity (FC) were calculated and used as an input for five machine learning algorithms: Gradient boosting (GB), LASSO, Logistic Regression (LR), Random Forest and Support Vector Machine.

RESULTS

All groups revealed different intra-network functional connectivity in ventral DMN and anterior SN. The best performance was reached for the LASSO applied to FC with an accuracy of 70% and AUROC of 0.76 (p < 0.05). Significant classification ability was also reached for GB and LR using fALFF and ALFF measures.

CONCLUSION

Our findings suggest that SR in schizophrenia can be seen on the level of DMN and SN functional connectivity alterations. ML algorithms were able to significantly differentiate SR patients. Our results could be useful in developing neuromarkers of SR in schizophrenia based on non-invasive rsfMRI.

Better modulation for risk decision-making after optimized magnetic stimulation

Traditional repetitive transcranial magnetic stimulation can only produce a significant but weak effect on the cortex while theta burst stimulation (TBS), a patterned accelerated form of stimulation, can produce a stronger poststimulation effect, which may improve decision-making abilities. We designed a comparative assessment of the effect of intermittent TBS (iTBS), 20 Hz, in two risk decision-making tasks on healthy controls. Participants were randomized and assigned to the iTBS (n = 29), 20 Hz (n = 29), or sham (n = 29) groups. The effects of the different methods of left dorsolateral prefrontal cortex stimulation on risk decision-making functions were compared based on subjects' performance in the Game of Dice Task (GDT) and Risky Gains Task (RGT). The main indicators were positive and negative feedback utilization rates of GDT and RGT. Both iTBS and 20 Hz stimulation resulted in significant improvements upon negative feedback in the GDT, with increases in safe options and reductions in risky options; iTBS stimulation increased subjects' use of positive feedback in the GDT and RGT (all p < 0.05). Furthermore, the iTBS group had a stronger feedback risk reduction effect than the 20 Hz or sham group following RGT negative feedback (p < 0.05). Individuals would integrate positive and negative information more efficiently, leading to them making rational choices after excitatory transcranial magnetic stimulation. Moreover, iTBS has a stronger risk reduction effect following negative feedback than the 20Hz stimulation did. In summary, iTBS might have clinical value in decision promotion.

Impulsivity as a Risk Factor for Suicide in Bipolar Disorder

The accurate assessment of suicide risk in psychiatric, especially affective disorder diagnosed patients, remains a crucial clinical need. In this study, we applied temperament and character inventory (TCI), Barratt impulsiveness scale 11 (BIS-11), PEBL simple reaction time (SRT) test, continuous performance task (CPT), and Iowa gambling task (IGT) to seek for variables linked with attempted suicide in bipolar affective disorder group (n = 60; attempters n = 17). The main findings were: strong correlations between self-report tool scores and objective parameters in CPT; the difference between attempters and non-attempters was found in the number of correctly responded trials in IGT; only one parameter differed between attempters and non-attempters in BPI diagnosis; and no significant differences between suicide attempters and non-attempters in TCI, BIS-11, and SRT were found. These justify the conclusion that impulsivity itself is not a strong predictor, and used as a single variable might not be sufficient to indicate the high suicide risk group among bipolar patients.

Structural-functional decoupling predicts suicide attempts in bipolar disorder patients with a current major depressive episode

Bipolar disorder (BD) is associated with a high risk of suicidality, and it is challenging to predict suicide attempts in clinical practice to date. Although structural and functional connectivity alterations from neuroimaging studies have been previously reported in BD with suicide attempts, little is known about how abnormal structural and functional connectivity relates to each other. Here, we hypothesize that structure connectivity constrains functional connectivity, and structural-functional coupling is a more sensitive biomarker to detect subtle brain abnormalities than any single modality in BD patients with a current major depressive episode who had attempted suicide. By investigating structural and resting-state fMRI connectivity, as well as their coupling among 191 BD depression patients with or without a history of suicide attempts and 113 healthy controls, we found that suicide attempters in BD depression patients showed significantly decreased central-temporal structural connectivity, increased frontal-temporal functional connectivity, along with decreased structural-functional coupling compared with non-suicide attempters. Crucially, the altered structural connectivity network predicted the abnormal functional connectivity network profile, and the structural-functional coupling was significantly correlated with suicide risk but not with depression or anxiety severity. Our findings suggest that the structural connectome is the key determinant of brain dysfunction, and structural-functional coupling could serve as a valuable trait-like biomarker for BD suicidal predication over and above the intramodality network connectivity. Such a measure can have clinical implications for early identification of suicide attempters with BD depression and inform strategies for prevention.