Testing the Effects of a Virtual Reality Game for Aggressive Impulse Management (VR-GAIME): Study Protocol

Background: Prior laboratory findings indicate that training avoidance movements to angry faces may lower anger and aggression among healthy participants, especially those high in trait anger. To enrich this training and make it more suitable for clinical applications, it has been developed into a Virtual Reality Game for Aggressive Impulse Management (VR-GAIME).Methods: The proposed study will examine the effects of this training in a randomized controlled trial among forensic psychiatric outpatients with aggression regulation problems (N = 60). In addition to the aggression replacement training, participants will play either the VR-GAIME or a control game. Anger will be assessed using self-report. Aggressive impulses will be measured via self-report, a validated laboratory paradigm, and rated by clinicians.Discussion: The authors hypothesize that the combination of the VR-GAIME and regular aggression treatment will be more successful in reducing aggressive behavior. One of the strengths of the proposed study is that it is the first to examine the effects of a motivational intervention in a clinical sample characterized by problems in regulating anger and aggression. Another strength of the proposed study is that the VR-GAIME will be implemented as a multi-session intervention. Additionally, the VR-GAIME applies, for the first time, serious gaming and virtual reality on an avoidance motivation intervention. If positive results are found, the VR-GAIME may be systematically deployed in forensic psychiatric settings.Trial registration: The trial is registered with The Netherlands National Trial Register, number: NTR6986

Getting a grip on your feelings: Effects of action orientation and external demands on intuitive affect regulation

The authors propose that volitional action is supported by intuitive affect regulation, defined as flexible, efficient, and nonrepressive control of own affective states. Intuitive affect regulation should be most apparent among action-oriented individuals under demanding conditions. Consistent with this, a demanding context led action-oriented individuals to down-regulate negative affect in self-reports (Study 1), in an affective Simon task (Study 2), and in a face discrimination task (Study 3). In line with the idea that intuitive affect regulation is guided by top-down self-regulation processes, intuitive affect regulation in a face discrimination task was mediated by increases in self-accessibility (Study 3). No parallel effects emerged among action-oriented participants in a nondemanding context or among state-oriented participants

How Virtual Agents Can Learn to Synchronize: an Adaptive Joint Decision-Making Model of Psychotherapy

Joint decision-making can be seen as the synchronization of actions and emotions, usually via nonverbal interaction between people while they show empathy. The aim of the current paper was (1) to develop an adaptive computational model for the type of synchrony that can occur in joint decision-making for two persons modeled as agents, and (2) to visualize the two persons by avatars as virtual agents during their decision-making. How to model joint decision-making computationally while taking into account adaptivity is rarely addressed, although such models based on psychological literature have a lot of future applications like online coaching and therapeutics. We used an adaptive network-oriented modelling approach to build an adaptive joint decision-making model in an agent-based manner and simulated multiple scenarios of such joint decision-making processes using a dedicated software environment that was implemented in MATLAB. Programming in the Unity 3D engine was done to virtualize this process as nonverbal interaction between virtual agents, their internal and external states, and the scenario. Although our adaptive joint decision model has general application areas, we have selected a therapeutic session as example scenario to visualize and interpret the example simulations

The path of ambivalence: tracing the pull of opposing evaluations using mouse trajectories

Ambivalence refers to a psychological conflict between opposing evaluations, often experienced as being torn between alternatives. This dynamic aspect of ambivalence is hard to capture with outcome-focused measures, such as response times or self-report. To gain more insight into ambivalence as it unfolds, the current work uses an embodied measure of pull, drawing on research in dynamic systems. In three studies, using different materials, we tracked people’s mouse movements as they chose between negative and positive evaluations of attitude objects. When participants evaluated ambivalent attitude objects, their mouse trajectories showed more pull of the non-chosen evaluative option than when they evaluated univalent attitude objects, revealing that participants were literally torn between the two opposing evaluations. We address the relationship of this dynamic measure to response time and self-reports of ambivalence and discuss implications and avenues for future research

The role of oxytocin in familiarization-habituation responses to social novelty

Stress or arousal responses to novel social contexts ease off when individuals get familiar with the social context. In the present study we investigated whether oxytocin is involved in this process of familiarization-habituation as oxytocin is known to increase trust and decrease anxiety. Fifty-nine healthy female subjects took part in the same experimental procedure in two sessions separated by 4 weeks. In the first (novelty) session state trust scores were significantly positively correlated with salivary oxytocin levels while in the second (familiarity) session state trust scores were significantly negatively correlated with salivary oxytocin levels. In a path model oxytocin was associated with increased trust in the novelty session and trust was associated with decreased oxytocin levels in the familiarity session. The results are consistent with the idea that oxytocin decreases stress-to-novelty responses by promoting familiarization to novel social contexts

Tuning down the emotional brain: an fMRI study of the effects of cognitive load on the processing of affective images

The present research examines whether cognitive load can modulate the processing of negative emotional stimuli, even after negative stimuli have already activated emotional centers of the brain. In a functional magnetic resonance imaging (fMRI) study, participants viewed neutral and negative stimuli that were followed by an attention-demanding arithmetic task. As expected, exposure to negative stimuli led to increased activation in emotional regions (the amygdalae and the right insula). Subsequently induced task load led to increased activation in cognitive regions (right dorsolateral frontal cortex, right superior parietal cortex). Importantly, task load down-regulated the brain's response to negative stimuli in emotional regions. Task load also reduced subjectively experienced negative emotion in response to negative stimuli. Finally, coactivation analyses suggest that during task performance, activity in right dorsolateral frontal cortex was related to activity in the amygdalae and the right insula. Together, these findings indicate that cognitive load is capable of tuning down the emotional brain. © 2009 Elsevier Inc. All rights reserved

A Multisite Preregistered Paradigmatic Test of the Ego-Depletion Effect

We conducted a preregistered multilaboratory project (k = 36; N = 3,531) to assess the size and robustness of ego-depletion effects using a novel replication method, termed the paradigmatic replication approach. Each laboratory implemented one of two procedures that was intended to manipulate self-control and tested performance on a subsequent measure of self-control. Confirmatory tests found a nonsignificant result (d = 0.06). Confirmatory Bayesian meta-analyses using an informed-prior hypothesis (δ = 0.30, SD = 0.15) found that the data were 4 times more likely under the null than the alternative hypothesis. Hence, preregistered analyses did not find evidence for a depletion effect. Exploratory analyses on the full sample (i.e., ignoring exclusion criteria) found a statistically significant effect (d = 0.08); Bayesian analyses showed that the data were about equally likely under the null and informed-prior hypotheses. Exploratory moderator tests suggested that the depletion effect was larger for participants who reported more fatigue but was not moderated by trait self-control, willpower beliefs, or action orientation.</p

In quest of a systematic framework for unifying and defining nanoscience

This article proposes a systematic framework for unifying and defining nanoscience based on historic first principles and step logic that led to a “central paradigm” (i.e., unifying framework) for traditional elemental/small-molecule chemistry. As such, a Nanomaterials classification roadmap is proposed, which divides all nanomatter into Category I: discrete, well-defined and Category II: statistical, undefined nanoparticles. We consider only Category I, well-defined nanoparticles which are >90% monodisperse as a function of Critical Nanoscale Design Parameters (CNDPs) defined according to: (a) size, (b) shape, (c) surface chemistry, (d) flexibility, and (e) elemental composition. Classified as either hard (H) (i.e., inorganic-based) or soft (S) (i.e., organic-based) categories, these nanoparticles were found to manifest pervasive atom mimicry features that included: (1) a dominance of zero-dimensional (0D) core–shell nanoarchitectures, (2) the ability to self-assemble or chemically bond as discrete, quantized nanounits, and (3) exhibited well-defined nanoscale valencies and stoichiometries reminiscent of atom-based elements. These discrete nanoparticle categories are referred to as hard or soft particle nanoelements. Many examples describing chemical bonding/assembly of these nanoelements have been reported in the literature. We refer to these hard:hard (H-n:H-n), soft:soft (S-n:S-n), or hard:soft (H-n:S-n) nanoelement combinations as nanocompounds. Due to their quantized features, many nanoelement and nanocompound categories are reported to exhibit well-defined nanoperiodic property patterns. These periodic property patterns are dependent on their quantized nanofeatures (CNDPs) and dramatically influence intrinsic physicochemical properties (i.e., melting points, reactivity/self-assembly, sterics, and nanoencapsulation), as well as important functional/performance properties (i.e., magnetic, photonic, electronic, and toxicologic properties). We propose this perspective as a modest first step toward more clearly defining synthetic nanochemistry as well as providing a systematic framework for unifying nanoscience. With further progress, one should anticipate the evolution of future nanoperiodic table(s) suitable for predicting important risk/benefit boundaries in the field of nanoscience