Electrophysiological Measurement of Emotion and Somatic State Affecting Ambiguity Decision: Evidences From SCRs, ERPs, and HR

Normatively irrelevant disgust interferes with decision under uncertainty: Insights from the Iowa gambling task

This study investigates whether a not informative, irrelevant emotional reaction of disgust interferes with decision-making under uncertainty. We manipulate the Iowa Gambling Task (IGT) by associating a disgust-eliciting image with selections from Disadvantageous/Bad decks (Congruent condition) or Advantageous/Good decks (Incongruent condition). A Control condition without manipulations is also included. Results indicate an increased probability of selecting from a Good deck as the task unfolds in all conditions. However, this effect is modulated by the experimental manipulation. Specifically, we detect a detrimental effect (i.e., a significant decrease in the intercept) of the disgust-eliciting image in Incongruent condition (vs. Control), but this effect is limited to the early stages of the task (i.e., first twenty trials). No differences in performance trends are detected between Congruent and Control conditions. Anticipatory Skin Conductance Response, heart rate, and pupil dilation are also assessed as indexes of anticipatory autonomic activation following the Somatic Marker Hypothesis, but no effects are shown for the first two indexes in any of the conditions. Only a decreasing trend is detected for pupil dilation as the task unfolds in Control and Incongruent conditions. Results are discussed in line with the "risk as feelings" framework, the Somatic Marker Hypothesis, and IGT literature.

Investigating the relationship between self-reported interoceptive experience and risk propensity

Risky behaviour may be associated with visceral experiences, such as increased heart rate. Previous studies examining the relationship between perception of such signals (interoception) and risk-taking typically used behavioural tasks with potential for monetary reward. This approach may be less informative for understanding general risk propensity. In addition, such research does not usually consider the varied ways individuals engage with interoceptive signals. However, examining these different forms of engagement may help us understand how subjective experience of interoception influences risk-taking. As such, we performed two surveys (n = 471, primarily young adults) to examine the relationship between self-reported engagement with interoceptive signals (measured using the Multidimensional Assessment of Interoceptive Awareness) and a generalised measure of risk propensity (the General Risk Propensity Scale). Results indicated that different ways of interpreting or engaging with interoceptive signals were differentially associated with risk propensity. In particular, they provide preliminary evidence that those with the ability to ignore or not worry about visceral signals when they are uncomfortable display greater risk propensity (and these effects may possibly be gender-specific).

Can cognition help predict suicide risk in patients with major depressive disorder? A machine learning study

BACKGROUND

Previous studies suggest that deficits in cognition may increase the risk of suicide. Our study aims to develop a machine learning (ML) algorithm-based suicide risk prediction model using cognition in patients with major depressive disorder (MDD).

METHODS

Participants comprised 52 depressed suicide attempters (DSA) and 61 depressed non-suicide attempters (DNS), and 98 healthy controls (HC). All participants were required to complete a series of questionnaires, the Suicide Stroop Task (SST) and the Iowa Gambling Task (IGT). The performance in IGT was analyzed using repeated measures ANOVA. ML with extreme gradient boosting (XGBoost) classification algorithm and locally explanatory techniques assessed performance and relative importance of characteristics for predicting suicide attempts. Prediction performances were compared with the area under the curve (AUC), decision curve analysis (DCA), and net reclassification improvement (NRI).

RESULTS

DSA and DNS preferred to select the card from disadvantageous decks (decks "A" + "B") under risky situation (p = 0.023) and showed a significantly poorer learning effect during the IGT (F = 2.331, p = 0.019) compared with HC. Performance of XGBoost model based on demographic and clinical characteristics was compared with that of the model created after adding cognition data (AUC, 0.779 vs. 0.819, p > 0.05). The net benefit of model was improved and cognition resulted in continuous reclassification improvement with NRI of 5.3%. Several clinical dimensions were significant predictors in the XGBoost classification algorithm.

LIMITATIONS

A limited sample size and failure to include sufficient suicide risk factors in the predictive model.

CONCLUSION

This study demonstrate that cognitive deficits may serve as an important risk factor to predict suicide attempts in patients with MDD. Combined with other demographic characteristics and attributes drawn from clinical questionnaires, cognitive function can improve the predictive effectiveness of the ML model. Additionally, explanatory ML models can help clinicians detect specific risk factors for each suicide attempter within MDD patients. These findings may be helpful for clinicians to detect those at high risk of suicide attempts quickly and accurately, and help them make proactive treatment decisions.

Attentional and Behavioral Disengagement as Coping Responses to Technostress and Financial Stress: An Experiment Based on Psychophysiological, Perceptual, and Behavioral Data

Discontinuance of information systems (IS) is a common phenomenon. It is thus critical to understand the decision process and psychophysiological mechanisms that underlie the intention and corresponding behaviors to discontinue IS use, particularly within the digital financial technology usage context, where continuance rates remain low despite increased adoption. Discontinuance has been identified as one coping behavior to avoid stressful situations. However, research has not yet explored this phenomenon toward digital financial technologies. This manuscript builds upon a pilot study that investigated the combined influence of technostress and financial stress on users’ responses toward digital financial decision-making tasks and aims to disentangle the specific impacts of unexpected technology behaviors and perceived financial loss on attentional and behavioral disengagement as coping responses, which may lead to discontinuance from digital financial technology usage. A two-factor within-subject design was developed, where perceived techno-unreliability as variable system response time delays under time pressure and perceived financial loss as negative financial outcomes were manipulated in a 3 × 2 design. Psychophysiological, perceptual, and behavioral data were collected from N = 15 participants while performing an adapted version of the Iowa Gambling Task. The results indicate that unexpected technology behaviors have a far greater impact than perceived financial loss on (1) physiological arousal and emotional valence, demonstrated by decreased skin conductance levels and curvilinear emotional valence responses, (2) feedback processing and decision-making, corroborated by curvilinear negative heart rate (BPM) and positive heart rate variability (HRV) responses, decreased skin conductance level (SCL), increased perceptions of system unresponsiveness and techno-unreliability, and mental workload, (3) attentional disengagement supported by curvilinear HRV and decreased SCL, and (4) behavioral disengagement as coping response, represented by curvilinear decision time and increasingly poor financial decision quality. Overall, these results suggest a feedforward and feedback loop of cognitive and affective mechanisms toward attentional and behavioral disengagement, which may lead to a decision of disengagement-discontinuance as a coping outcome in stressful human-computer interaction situations.

Influence Factors for Decision-Making Performance of Suicide Attempters and Suicide Ideators: The Roles of Somatic Markers and Explicit Knowledge

Impaired decision-making has been observed in suicide attempters during the Iowa Gambling Task (IGT). Decision-making performance is influenced by somatic markers and explicit knowledge, but it is still unclear of the influencing role on decision-making performance in suicidal individuals. We aimed to investigate whether there is a decision-making deficit in suicide attempters, suicide ideators, as well as the distinct roles of somatic markers and explicit knowledge wherein. Thirteen suicide attempters, 23 suicide ideators, and 19 healthy controls performed the IGT. Both somatic markers (by the skin conductance responses, SCRs) and explicit knowledge (by the subjective experience rating and a list of questions) were recorded. No significant differences were found among the three groups on IGT performance, explicit knowledge, and anticipatory SCRs. IGT Performance of suicide attempters was positively correlated with explicit knowledge index while behavior performance was positively associated with the SCRs in healthy controls. These results indicate that the suicide attempters seem to apply a compensatory strategy by mostly utilizing explicit knowledge to perform normally as healthy controls in the IGT.