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Despite the growing deployment of network representation to comprehend psychological phenomena, the question of whether and how networks can effectively describe the effects of psychological interventions remains elusive. Network control theory, the engineering study of networked interventions, has recently emerged as a viable methodology to characterize and guide interventions. However, there is a scarcity of empirical studies testing the extent to which it can be useful within a psychological context. In this paper, we investigate a representative psychological intervention experiment, use network control theory to model the intervention and predict its effect. Using this data, we showed that: (1) the observed psychological effect, in terms of sensitivity and specificity, relates to the regional network control theoretic metrics (average and modal controllability), (2) the size of change following intervention negatively correlates with a whole-network topology that quantifies the "ease" of change as described by control theory (control energy), and (3) responses after intervention can be predicted based on formal results from control theory. These insights assert that network control theory has significant potential as a tool for investigating psychological interventions. Drawing on this specific example and the overarching framework of network control theory, we further elaborate on the conceptualization of psychological interventions, methodological considerations, and future directions in this burgeoning field. [ABSTRACT FROM AUTHOR]

Despite the growing deployment of network representation to comprehend psychological phenomena, the question of whether and how networks can effectively describe the effects of psychological interventions remains elusive. Network control theory, the engineering study of networked interventions, has recently emerged as a viable methodology to characterize and guide interventions. However, there is a scarcity of empirical studies testing the extent to which it can be useful within a psychological context. In this paper, we investigate a representative psychological intervention experiment, use network control theory to model the intervention and predict its effect. Using this data, we showed that: (1) the observed psychological effect, in terms of sensitivity and specificity, relates to the regional network control theoretic metrics (average and modal controllability), (2) the size of change following intervention negatively correlates with a whole-network topology that quantifies the "ease" of change as described by control theory (control energy), and (3) responses after intervention can be predicted based on formal results from control theory. These insights assert that network control theory has significant potential as a tool for investigating psychological interventions. Drawing on this specific example and the overarching framework of network control theory, we further elaborate on the conceptualization of psychological interventions, methodological considerations, and future directions in this burgeoning field. [ABSTRACT FROM AUTHOR]

Background: Motivational dysregulation represents a core vulnerability factor for bipolar disorder. Whether this also comprises aberrant learning of stimulus-reinforcer contingencies is less clear.Methods: To answer this question, we compared healthy first-degree relatives of individuals with bipolar disorder (n = 42) known to convey an increased risk of developing a bipolar spectrum disorder and healthy individuals (n = 97). Further, we investigated the effects of the behavioral activation system (BAS) on reinforcement learning across the entire sample. All participants were assessed with a probabilistic learning task that distinguishes learning from positive and negative feedback. Main outcome measures included choice frequencies and learning rate parameters generated by computational reinforcement learning algorithms.Results: First-degree relatives choose more rewarding stimuli more consistently and showed marginally reduced learning rates from unexpected negative feedback. Further, first-degree relatives had lower BAS scores than controls, which were negatively associated with learning rates from unexpected negative feedback.Limitations: However as probands also reported other mental disorders such as Attention-Deficit/Hyperactivity Disorder and substance abuse among their first-degree relatives, we cannot know, whether these findings are specific to the risk for bipolar disorder.Conclusion: The behavior of first-degree relatives of individuals with bipolar disorder, who also display increased BAS sensitivity, is less influenced by unexpected negative feedback. This reduced learning from unexpected negative feedback biases subsequent choices towards stimuli with higher probabilities for a reward. In sum, our results confirm the role of aberrant reinforcement learning in the pathophysiology of bipolar disorder. [ABSTRACT FROM AUTHOR]

A major tenet in theoretical neuroscience is that cognitive and behavioral processes are ultimately implemented in terms of the neural system dynamics. Accordingly, a major aim for the analysis of neurophysiological measurements should lie in the identification of the computational dynamics underlying task processing. Here we advance a state space model (SSM) based on generative piecewise-linear recurrent neural networks (PLRNN) to assess dynamics from neuroimaging data. In contrast to many other nonlinear time series models which have been proposed for reconstructing latent dynamics, our model is easily interpretable in neural terms, amenable to systematic dynamical systems analysis of the resulting set of equations, and can straightforwardly be transformed into an equivalent continuous-time dynamical system. The major contributions of this paper are the introduction of a new observation model suitable for functional magnetic resonance imaging (fMRI) coupled to the latent PLRNN, an efficient stepwise training procedure that forces the latent model to capture the ‘true’ underlying dynamics rather than just fitting (or predicting) the observations, and of an empirical measure based on the Kullback-Leibler divergence to evaluate from empirical time series how well this goal of approximating the underlying dynamics has been achieved. We validate and illustrate the power of our approach on simulated ‘ground-truth’ dynamical systems as well as on experimental fMRI time series, and demonstrate that the learnt dynamics harbors task-related nonlinear structure that a linear dynamical model fails to capture. Given that fMRI is one of the most common techniques for measuring brain activity non-invasively in human subjects, this approach may provide a novel step toward analyzing aberrant (nonlinear) dynamics for clinical assessment or neuroscientific research. [ABSTRACT FROM AUTHOR]

Behavioral experiments are usually designed to tap into a specific cognitive function, but animals may solve a given task through a variety of different and individual behavioral strategies, some of them not foreseen by the experimenter. Animal learning may therefore be seen more as the process of selecting among, and adapting, potential behavioral policies, rather than mere strengthening of associative links. Calcium influx through high-voltage-gated Ca2+ channels is central to synaptic plasticity, and altered expression of Cav1.2 channels and the CACNA1C gene have been associated with severe learning deficits and psychiatric disorders. Given this, we were interested in how specifically a selective functional ablation of the Cacna1c gene would modulate the learning process. Using a detailed, individual-level analysis of learning on an operant cue discrimination task in terms of behavioral strategies, combined with Bayesian selection among computational models estimated from the empirical data, we show that a Cacna1c knockout does not impair learning in general but has a much more specific effect: the majority of Cacna1c knockout mice still managed to increase reward feedback across trials but did so by adapting an outcome-based strategy, while the majority of matched controls adopted the experimentally intended cue-association rule. Our results thus point to a quite specific role of a single gene in learning and highlight that much more mechanistic insight could be gained by examining response patterns in terms of a larger repertoire of potential behavioral strategies. The results may also have clinical implications for treating psychiatric disorders. [ABSTRACT FROM AUTHOR]

Background: Dysfunctional fear responses play a central role in many mental disorders. New insights in learning and memory suggest that pharmacological and behavioural interventions during the reconsolidation of reactivated fear memories may increase the efficacy of therapeutic interventions. It has been proposed that interventions applied during reconsolidation may modify the original fear memory, and thus prevent the spontaneous recovery and reinstatement of the fear response. Methods: We investigated whether pharmacological (propranolol) and behavioural (reappraisal, multisensory stimulation) interventions reduce fear memory, and prevent reinstatement of fear in comparison to a placebo control group. Eighty healthy female subjects underwent a differential fear conditioning procedure with three stimuli (CS). Two of these (CS+) were paired with an electric shock on day 1. On day 2, 20 subjects were pseudo-randomly assigned to either the propranolol or placebo condition, or underwent one of the two behavioural interventions after one of the two CS+ was reactivated. On day 3, all subjects underwent an extinction phase, followed by a reinstatement test. Dependent variables were US expectancy ratings, fear-potentiated startle, and skin conductance response. Results: Differential fear responses to the reactivated and non-reactivated CS+ were observed only in the propranolol condition. Here, the non-reactivated CS+ evoked stronger fear-potentiated startle-responses compared to the placebo group. None of the interventions prevented the return of the extinguished fear response after re-exposure to the unconditioned stimulus. Conclusions: Our data are in line with an increasing body of research stating that the occurrence of reconsolidation may be constrained by boundary conditions such as subtle differences in experimental manipulations and instructions. In conclusion, our findings do not support a beneficial effect in using reconsolidation processes to enhance effects of psychotherapeutic interventions. This implies that more research is required before therapeutic interventions may benefit from a combination with reconsolidation processes. [ABSTRACT FROM AUTHOR]

Objective: There is a general agreement that physical pain serves as an alarm signal for the prevention of and reaction to physical harm. It has recently been hypothesized that “social pain,” as induced by social rejection or abandonment, may rely on comparable, phylogenetically old brain structures. As plausible as this theory may sound, scientific evidence for this idea is sparse. This study therefore attempts to link both types of pain directly. We studied patients with borderline personality disorder (BPD) because BPD is characterized by opposing alterations in physical and social pain; hyposensitivity to physical pain is associated with hypersensitivity to social pain, as indicated by an enhanced rejection sensitivity. Method: Twenty unmedicated female BPD patients and 20 healthy participants (HC, matched for age and education) played a virtual ball-tossing game (cyberball), with the conditions for exclusion, inclusion, and a control condition with predefined game rules. Each cyberball block was followed by a temperature stimulus (with a subjective pain intensity of 60% in half the cases). The cerebral responses were measured by functional magnetic resonance imaging. The Adult Rejection Sensitivity Questionnaire was used to assess rejection sensitivity. Results: Higher temperature heat stimuli had to be applied to BPD patients relative to HCs to reach a comparable subjective experience of painfulness in both groups, which suggested a general hyposensitivity to pain in BPD patients. Social exclusion led to a subjectively reported hypersensitivity to physical pain in both groups that was accompanied by an enhanced activation in the anterior insula and the thalamus. In BPD, physical pain processing after exclusion was additionally linked to enhanced posterior insula activation. After inclusion, BPD patients showed reduced amygdala activation during pain in comparison with HC. In BPD patients, higher rejection sensitivity was associated with lower activation differences during pain processing following social exclusion and inclusion in the insula and in the amygdala. Discussion: Despite the similar behavioral effects in both groups, BPD patients differed from HC in their neural processing of physical pain depending on the preceding social situation. Rejection sensitivity further modulated the impact of social exclusion on neural pain processing in BPD, but not in healthy controls. [ABSTRACT FROM AUTHOR]

Within cognitive neuroscience, in nearly every experimental setting, subjects are presented with stimuli that appear at either constant or variable points in time, referred to as interstimulus intervals (ISIs). These temporal patterns differ in the degree to which an exact stimulus onset may be predicted. We investigated whether this experimental feature affects brain and behavior, and whether the impact is modulated by the cognitive demands of a task. Subjects (N = 26) were assessed via fMRI while solving three different tasks under either temporally predictable (constant ISI) or unpredictable (variable ISI) conditions. The tasks differed with regard to demands on working memory and response uncertainty. Compared to constant ISIs, variable (i.e., less predictable) ISIs led to a general increase in reaction time and in right amygdala activation. Depending on the cognitive demands required by the specific task, the left amygdala, the parietal cortex, the supplementary motor area, and the dorsolateral prefrontal cortex were engaged as well. The results indicate that the temporal structure in a stimulus sequence affects both overt and covert behaviors. Implicit temporal uncertainty increases activation in several brain regions depending on cognitive demands. Thus, an often-overlooked basic design feature, the application of constant or variable ISIs, may contribute to heterogeneity in cognitive neuroscience findings. [ABSTRACT FROM AUTHOR]

An intense fear of abandonment or rejection is a central feature of social relationships for individuals with borderline personality disorder (BPD). A total of 20 unmedicated BPD patients and 20 healthy participants (HC, matched for age and education) played a virtual ball-tossing game including the three conditions: exclusion, inclusion and a control condition with predefined game rules, whereas cerebral activity was assessed using functional magnetic resonance imaging. Subjective experiences of exclusion were assessed after each blocked condition. Both groups felt similarly excluded during the exclusion condition; however, BPD subjects felt more excluded than HC during the inclusion and control conditions. In all three conditions, BPD patients showed a stronger engagement of the dorsal anterior cingulate and medial prefrontal cortex. For HC, activation in several cerebral regions such as the insula and the precuneus differed depending on the interaction situation, whereas for BPD subjects activation in these regions was not modulated by experimental conditions. Subjects with BPD differed from HC in both their subjective reactions to and their neural processing of social interaction situations. Our data suggest that individuals with BPD have difficulty in discriminating between social situations, and tend to hypermentalize during social encounters that are not determined by the intentions of others. [ABSTRACT FROM AUTHOR]

Background: The popularization of social media has led to the coalescing of user groups around mental health conditions; in particular, depression. Social media offers a rich environment for contextualizing and predicting users' self-reported burden of depression. Modern artificial intelligence (AI) methods are commonly employed in analyzing user-generated sentiment on social media. In the forthcoming systematic review, we will examine the content validity of these computer-based health surveillance models with respect to standard diagnostic frameworks. Drawing from a clinical perspective, we will attempt to establish a normative judgment about the strengths of these modern AI applications in the detection of depression. Methods: We will perform a systematic review of English and German language publications from 2010 to 2020 in PubMed, APA PsychInfo, Science Direct, EMBASE Psych, Google Scholar, and Web of Science. The inclusion criteria span cohort, case-control, cross-sectional studies, randomized controlled studies, in addition to reports on conference proceedings. The systematic review will exclude some gray source materials, specifically editorials, newspaper articles, and blog posts. Our primary outcome is self-reported depression, as expressed on social media. Secondary outcomes will be the types of AI methods used for social media depression screen, and the clinical validation procedures accompanying these methods. In a second step, we will utilize the evidence-strengthening Population, Intervention, Comparison, Outcomes, Study type (PICOS) tool to refine our inclusion and exclusion criteria. Following the independent assessment of the evidence sources by two authors for the risk of bias, the data extraction process will culminate in a thematic synthesis of reviewed studies. Discussion: We present the protocol for a systematic review which will consider all existing literature from peer reviewed publication sources relevant to the primary and secondary outcomes. The completed review will discuss depression as a self-reported health outcome in social media material. We will examine the computational methods, including AI and machine learning techniques which are commonly used for online depression surveillance. Furthermore, we will focus on standard clinical assessments, as indicating content validity, in the design of the algorithms. The methodological quality of the clinical construct of the algorithms will be evaluated with the COnsensus-based Standards for the selection of health status Measurement Instruments (COSMIN) framework. We conclude the study with a normative judgment about the current application of AI to screen for depression on social media. Systematic review registration: International Prospective Register of Systematic Reviews PROSPERO (registration number CRD42020187874). [ABSTRACT FROM AUTHOR]

Background: Fear responses are particularly intense and persistent in post-traumatic stress disorder (PTSD), and can be evoked by unspecific cues that resemble the original traumatic event. Overgeneralisation of fear might be one of the underlying mechanisms. We investigated the generalisation and discrimination of fear in individuals with and without PTSD related to prolonged childhood maltreatment. Methods: Sixty trauma-exposed women with (N = 30) and without (N = 30) PTSD and 30 healthy control participants (HC) underwent a fear conditioning and generalisation paradigm. In a contingency learning procedure, one of two circles of different sizes was associated with an electrical shock (danger cue), while the other circle represented a safety cue. During generalisation testing, online risk ratings, reaction times and fear-potentiated startle were measured in response to safety and danger cues as well as to eight generalisation stimuli, i.e. circles of parametrically varying size creating a continuum of similarity between the danger and safety cue. Results: The increase in reaction times from the safety cue across the different generalisation classes to the danger cue was less pronounced in PTSD compared with HC. Moreover, PTSD participants expected higher risk of an aversive event independent of stimulus types and task. Conclusions: Alterations in generalisation constitute one part of fear memory alterations in PTSD. Neither the accuracy of a risk judgement nor the strength of the induced fear was affected. Instead, processing times as an index of uncertainty during risk judgements suggested a reduced differentiation between safety and threat in PTSD. [ABSTRACT FROM AUTHOR]

Background: Novel approaches in mobile mental health (mHealth) apps that make use of Artificial Intelligence (AI), Ecological Momentary Assessments, and Ecological Momentary Interventions have the potential to support young people in the achievement of mental health and wellbeing goals. However, little is known on the perspectives of young people and mental health experts on this rapidly advancing technology. This study aims to investigate the subjective needs, attitudes, and preferences of key stakeholders towards an AI–informed mHealth app, including young people and experts on mHealth promotion and prevention in youth. Methods: We used a convergent parallel mixed–method study design. Two semi–structured online focus groups (n = 8) and expert interviews (n = 5) to explore users and stakeholders perspectives were conducted. Furthermore a representative online survey was completed by young people (n = 666) to investigate attitudes, current use and preferences towards apps for mental health promotion and prevention. Results: Survey results show that more than two-thirds of young people have experience with mHealth apps, and 60% make regular use of 1–2 apps. A minority (17%) reported to feel negative about the application of AI in general, and 19% were negative about the embedding of AI in mHealth apps. This is in line with qualitative findings, where young people displayed rather positive attitudes towards AI and its integration into mHealth apps. Participants reported pragmatic attitudes towards data sharing and safety practices, implying openness to share data if it adds value for users and if the data request is not too intimate, however demanded transparency of data usage and control over personalization. Experts perceived AI-informed mHealth apps as a complementary solution to on–site delivered interventions in future health promotion among young people. Experts emphasized opportunities in regard with low-threshold access through the use of smartphones, and the chance to reach young people in risk situations. Conclusions: The findings of this exploratory study highlight the importance of further participatory development of training components prior to implementation of a digital mHealth training in routine practice of mental health promotion and prevention. Our results may help to guide developments based on stakeholders' first recommendations for an AI-informed mHealth app. [ABSTRACT FROM AUTHOR]

Emerging studies corroborate the importance of neuroimaging biomarkers and machine learning to improve diagnostic classification of amyotrophic lateral sclerosis (ALS). While most studies focus on structural data, recent studies assessing functional connectivity between brain regions by linear methods highlight the role of brain function. These studies have yet to be combined with brain structure and nonlinear functional features. We investigate the role of linear and nonlinear functional brain features, and the benefit of combining brain structure and function for ALS classification. ALS patients (N = 97) and healthy controls (N = 59) underwent structural and functional resting state magnetic resonance imaging. Based on key hubs of resting state networks, we defined three feature sets comprising brain volume, resting state functional connectivity (rsFC), as well as (nonlinear) resting state dynamics assessed via recurrent neural networks. Unimodal and multimodal random forest classifiers were built to classify ALS. Out‐of‐sample prediction errors were assessed via five‐fold cross‐validation. Unimodal classifiers achieved a classification accuracy of 56.35–61.66%. Multimodal classifiers outperformed unimodal classifiers achieving accuracies of 62.85–66.82%. Evaluating the ranking of individual features' importance scores across all classifiers revealed that rsFC features were most dominant in classification. While univariate analyses revealed reduced rsFC in ALS patients, functional features more generally indicated deficits in information integration across resting state brain networks in ALS. The present work undermines that combining brain structure and function provides an additional benefit to diagnostic classification, as indicated by multimodal classifiers, while emphasizing the importance of capturing both linear and nonlinear functional brain properties to identify discriminative biomarkers of ALS. [ABSTRACT FROM AUTHOR]

Abstract: Different domains of executive function such as working memory and response inhibition were investigated together with elementary cognitive processes in borderline personality disorder (BPD). Patients with BPD (N=28) were compared to nonpatient controls (NP, N=28) on eight tasks (e.g. n-back, Go/NoGo, CPT-AX). In order to separate impairments in different cognitive domains and to assess the influence of more elementary cognitive processes on executive functioning, tasks were embedded in a reaction-time-decomposition approach. BPD patients solved tasks with accuracies comparable to those of nonpatients. The only exception was the n-back task, for which working memory is required: here, error rates were higher and increased more prominently in BPD patients depending on working memory load. In most tasks, movement times were shorter for BPD patients than for nonpatients, while the quality of task-solving was comparable. The faster processing in the BPD group was observable starting with the simplest task, i.e. a simple reaction-time task. These findings suggest that domains of executive functioning are differentially affected in BPD. In contrast to load-dependent deficits in working memory, response inhibition processes were unimpaired. Faster action-related processes could be observed in BPD patients in a variety of tasks; however, these did not influence executive functioning. [Copyright &y& Elsevier]

Background: Gene by environment (G×E) interaction between genetic variation in the promoter region of the serotonin transporter gene (serotonin transporter-linked polymorphic region [5-HTTLPR]) and stressful life events (SLEs) has been extensively studied in the context of depression. Recent findings suggest increased neural and endocrine stress sensitivity as a possible mechanism conveying elevated vulnerability to psychopathology. Furthermore, these G×E mediated alterations very likely reflect interrelated biological processes. Methods: In the present functional magnetic resonance imaging study, amygdala reactivity to fearful stimuli was assessed in healthy male adults (n = 44), who were previously found to differ with regard to endocrine stress reactivity as a function of 5-HTTLPR × SLEs. Furthermore, functional connectivity between the amygdala and the hypothalamus was measured as a potential mechanism linking elevated neural and endocrine responses during stressful/threatening situations. The study sample was carefully preselected regarding 5-HTTLPR genotype and SLEs. Results: We report significant G×E interaction on neural response patterns and functional amygdala-hypothalamus connectivity. Specifically, homozygous carriers of the 5-HTTLPR S'' allele with a history of SLEs (S''S''/high SLEs group) displayed elevated bilateral amygdala activation in response to fearful faces. Within the same sample, a comparable G×E interaction effect has previously been demonstrated regarding increased cortisol reactivity, indicating a cross-validation of heightened biological stress sensitivity. Furthermore, S''S''/high SLEs subjects were characterized by an increased functional coupling between the right amygdala and the hypothalamus, thus indicating a potential link between neural and endocrine hyperreactivity. Conclusions: The present findings contribute to the ongoing debate on 5-HTTLPR × SLEs interaction and are discussed with respect to clinical implications. [Copyright &y& Elsevier]

Background. Public health measures to curb SARS-CoV-2 transmission rates may have negative psychosocial consequences in youth. Digital interventions may help to mitigate these effects. We investigated the associations between social isolation, COVID-19-related cognitive preoccupation, worries, and anxiety, objective social risk indicators, and psychological distress, as well as use of, and attitude toward, mobile health (mHealth) interventions in youth. Methods. Data were collected as part of the "Mental Health And Innovation During COVID-19 Survey"--a cross-sectional panel study including a representative sample of individuals aged 16-25 years (N = 666; Mage = 21.3; assessment period: May 5, 2020 to May 16, 2020). Results. Overall, 38% of youth met criteria for moderate or severe psychological distress. Social isolation worries and anxiety, and objective risk indicators were associated with psychological distress, with evidence of dose-response relationships for some of these associations. For instance, psychological distress was progressively more likely to occur as levels of social isolation increased (reporting "never" as reference group: "occasionally": adjusted odds ratio [aOR] 9.1, 95% confidence interval [CI] 4.3-19.1, p < 0.001; "often": aOR 22.2, CI 9.8-50.2, p < 0.001; "very often": aOR 42.3, CI 14.1-126.8, p < 0.001). There was evidence that psychological distress, worries, and anxiety were associated with a positive attitude toward using mHealth interventions, whereas psychological distress, worries, and anxiety were associated with actual use. Conclusions. Public healthmeasures during pandemicsmay be associated with poor mental health outcomes in youth. Evidence-based digital interventions may help mitigate the negative psychosocial impact without risk of viral infection given there is an objective need and subjective demand. [ABSTRACT FROM AUTHOR]

Deleterious effects of adverse childhood experiences (ACE) on human brain volume are widely reported. First evidence points to differential effects of ACE on brain volume in terms of timing of ACE. Upcoming studies additionally point towards the impact of different types (i.e., neglect and abuse) of ACE in terms of timing. The current study aimed to investigate the correlation between retrospectively reported severity of type (i.e., the extent to which subjects were exposed to abuse and/or neglect, respectively) and timing of ACE on female brain volume in a sample of prolonged traumatized subjects. A female sample with ACE (N = 68) underwent structural magnetic resonance imaging and a structured interview exploring the severity of ACE from age 3 up to 17 using the "Maltreatment and Abuse Chronology of Exposure" (MACE). Random forest regression with conditional interference trees was applied to assess the impact of ACE severity as well as the severity of ACE type, (i.e. to what extent individuals were exposed to neglect and/or abuse) at certain ages on pre-defined regions of interest such as the amygdala, hippocampus, and anterior cingulate (ACC) volume. Analyses revealed differential type and timing-specific effects of ACE on stress sensitive brain structures: Amygdala and hippocampal volume were affected by ACE severity during a period covering preadolescence and early adolescence. Crucially, this effect was driven by the severity of neglect. [ABSTRACT FROM AUTHOR]