Affective Spectrum Research Articles

Serotonin 4 receptor brain binding and oxytocin-promoted affective and social cognition in healthy women – A randomized controlled trial

BackgroundOxytocin is a neuropeptide known for its prosocial properties and role in social bonding, and intervention with intranasal oxytocin is posited to modulate affective and social cognition (i.e., hot cognition). Serotonin (5-HT) neurotransmission is also involved in emotional and social behaviors and appear to work in concert with oxytocin. However, this interaction so far remains elusive in humans. Therefore, we here investigate the relation between brain 5-HT 4 receptor (5-HT4R) levels and oxytocin-modulated hot cognition. MethodsUsing a double blind, placebo-controlled, randomized crossover design, 35 healthy women received a dose of 24 IU intranasal oxytocin or placebo one month apart. The women were naturally cycling and to control for hormonal fluctuations across the menstrual cycle, intervention days were placed during the early follicular phase. Following intervention cognitive domains including affective memory, affective bias in emotion processing, moral emotions and social information preference were assessed. In a subgroup (n = 25), Positron Emission Tomography (PET) was used to image 5-HT4R brain binding at baseline with the [11C]SB207145 radiotracer. ResultsNo effect of oxytocin intervention relative to placebo was observed for any of the cognitive outcomes. Likewise, regional brain 5-HT4R binding at baseline was not associated with cognitive responses to oxytocin intervention. ConclusionOur data suggest that intervention with intranasal oxytocin does not have an overall effect on hot cognition in healthy women and further that 5-HT4R brain architecture does not mediate cognitive effects of oxytocin in the healthy state.

Empathic accuracy of romantic partner negative affect is influenced by borderline personality symptoms.

The present study sought to examine the relation between borderline personality disorder (BPD) symptoms and empathic accuracy while improving on prior methodologies by using daily affect assessment in romantic partners. BPD symptoms were assessed in both members of 81 community couples who also reported on their own and their partner's negative and positive affect daily for 3 weeks. Data were analyzed using the Truth and Bias Model of Judgment, which allows the source of empathic accuracy to be parsed into partner affect (truth) and own affect (bias). Results provided evidence that individuals with higher BPD symptoms exhibited increased empathic accuracy for a partner's negative affect, particularly when partners also had higher BPD symptoms. The source of this accuracy stemmed more from bias forces than truth forces, indicating that participants' own affective states lead to more accurate judgments of partner affective state. The results suggest that this bias reduced the general tendency among participants to underestimate partner negative affect, thus leading to higher empathic accuracy. Overall, our results extend and provide support for previous research indicating that BPD symptoms are associated with heightened, not diminished, empathic accuracy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Development of a Qualitative Assessment Instrument for Cognitive Processes in Gaming Decision

Indonesia ranks 6th with the highest number of online gamers in Asia and 12th in the world gaming market. When online gamers become addicted, they lose the ability to halt or control their gaming behavior, leading to problematic behavior. Decision-making processes at the cognitive level are considered relevant in various addictive behaviors, including inappropriate gaming behavior. Exploratory research can be conducted using a qualitative technique, with data collected through in-depth interviews, to acquire an in-depth understanding of the comparison of the interaction process of each cognitive component in decision-making to play online games. This research was conducted in Bandung from December 2021 to December 2022. Steps are needed to develop guidelines that explore the functioning of affective and cognitive responses (coping, cognitive and affective bias, and craving and urge) and executive and inhibitory control. The guideline used a cognitive theoretical framework in addictive behavior, namely the I-PACE model, with a multidimensional theoretical basis. Through theoretical deepening, it was derived as a guideline divided into three main aspects, four sub-aspects, 32 main questions, and 36 probing questions.

The COVID‐19 pandemic disrupted the healthy fading of emotions in autobiographical memory mediated via in‐person social disclosures

AbstractWe explore the impact of the COVID‐19 pandemic in the United Kingdom upon the fading affect bias in autobiographical memory, which describes the greater fading of negative emotional intensity over time compared to positive. Across two studies we show that the magnitude of the FAB is smaller for pandemic‐related events compared to pandemic‐unrelated events. The FAB is thought to represent the result of healthy coping processes operating on autobiographical memory and our results indicate that these processes were disrupted, to a certain extent, by the pandemic. These effects were mediated by frequent in‐person social disclosures of pleasant pandemic‐unrelated events, which was, in turn, associated with less fading of positive affect. Further, the FAB for both pandemic‐related and unrelated events was mediated by disclosures via social media. Together, these results highlight the potential effectiveness of using various modes of communication to facilitate emotional regulation processes in autobiographical memory.

Be Here Now: Dispositional Mindfulness Enhances Fading Affect Bias

ObjectivesThe current study examined the relationship between dispositional mindfulness and fading affect bias, where the affect associated with negative events fades more quickly and fully than affect associated with positive events. Although much of the previous work has focused on conditions that hinder fading affect bias (e.g., depression, anxiety), few studies have examined individual difference variables that could enhance the asymmetric fading of positive and negative affect associated with autobiographical events.MethodsParticipants (n = 241) recalled and described positive and negative life events and rated the initial and current emotional intensity of those events. Events were also rated on importance, memorability, and how often they had been thought about. Participants also completed the Five Facet Mindfulness Questionnaire (FFMQ) to assess dispositional mindfulness.ResultsFading affect bias emerged in the study and the strength of the effect was predicted by dispositional mindfulness. The relationship was driven by the observing and describing subscales of the FFMQ. The data fit a model where increased thinking about positive events, but not negative events, mediated the relationship between the observing subscale and fading affect bias.ConclusionsThe findings suggest that an ability to be centred in the present moment—as measured by dispositional mindfulness—enhances one’s capacity to move on from past events. Specifically, the ability to both observe and describe internal states and the external world enhances the beneficial asymmetric fade of affect associated with negative and positive life events.PreregistrationThis study is not preregistered.

Coronaphobia flips the emotional world upside down: Unhealthy variables positively predict the fading affect bias at high physical symptoms of coronavirus anxiety

AbstractThe fading affect bias (FAB) refers to the faster fading of unpleasant affect than pleasant affect. The present study investigated various healthy and unhealthy variables as predictors of the FAB across physical symptoms of coronavirus anxiety (PSCA) as well as across events involving and not involving COVID‐19. The data were collected in the heart of the pandemic from April 18, 2020 to January 23, 2021. As expected, social distancing, grit, positive positive and negative affect schedule (PANAS), and rehearsals positively predicted the FAB, whereas negative PANAS, depression, generalized anxiety, and stress negatively predicted the FAB. These results supported the mobilization‐minimization hypothesis, self‐enhancement theories, and the broaden and build theory. Interestingly, PSCA moderated the relations of several variables, such that grit, hypochondria, neuroticism, average daily hours thinking and talking about COVID‐19, negative PANAS, and anxiety predicted the FAB in the expected ways at low PSCA, but all the variables, except negative PANAS and anxiety, positively predicted the FAB at high PSCA. The negative relations between FAB and both negative PANAS and anxiety diminished from low to medium PSCA, and those negative relations remained small at high PSCA. Rehearsal ratings did not mediate the 3‐way interactions. These results emphasize the dramatic effect on emotion regulation, as measured by the FAB, produced by the COVID‐19 pandemic.

Change in Negative Affective Bias following a Single Ketamine Treatment for Treatment-Resistant Depression

Ketamine has recently emerged as a highly effective new treatment for people with treatment-resistant depression with rapid antidepressant effects. However, these effects are often short lasting, and the potential cognitive mechanisms underlying the therapeutic effects, such as effects on emotional processing bias, remain poorly understood. In the present study, we explored potential changes in emotional and cognitive processing following a single treatment of subcutaneous ketamine in a randomised double-blind controlled study with an active control. Participants with treatment-resistant major depressive disorder (MDD) were recruited from a single site from the Ketamine for Adult Depression Study (KADS Trial) and were randomly assigned to receive racemic ketamine hydrochloride ( n = 10 ) or midazolam hydrochloride ( n = 11 ) in a 1 : 1 ratio. A healthy control sample ( n = 23 ) was recruited to attend a single experimental session without any treatment. All MDD participants completed mood ratings and cognitive assessments prior to and one day after a single randomised treatment. The results showed no significant differences in performance changes after treatment across the majority of emotion-related (i.e., Emotional Stroop Task, Affective Go/No-Go Task) and cognitive (Ruff 2 and 7 Selective Attention Test, Controlled Word Association Test) outcome measures. Participants who received ketamine showed a significant improvement in a negative processing bias test (i.e., The Scrambled Sentence Task; Cohen’s d = .67 , p = .016 ), which was not significantly associated with improvement in psychological symptoms ( r = − .662 , p = .074 ). The results from this exploratory study suggest that a single ketamine treatment may modulate negative affective bias. Limitations to this study included the small sample size and lack of follow-up. Future larger trials are required to confirm this finding.

Cognitive Network Science Reveals Bias in GPT-3, GPT-3.5 Turbo, and GPT-4 Mirroring Math Anxiety in High-School Students

Large Language Models (LLMs) are becoming increasingly integrated into our lives. Hence, it is important to understand the biases present in their outputs in order to avoid perpetuating harmful stereotypes, which originate in our own flawed ways of thinking. This challenge requires developing new benchmarks and methods for quantifying affective and semantic bias, keeping in mind that LLMs act as psycho-social mirrors that reflect the views and tendencies that are prevalent in society. One such tendency that has harmful negative effects is the global phenomenon of anxiety toward math and STEM subjects. In this study, we introduce a novel application of network science and cognitive psychology to understand biases towards math and STEM fields in LLMs from ChatGPT, such as GPT-3, GPT-3.5, and GPT-4. Specifically, we use behavioral forma mentis networks (BFMNs) to understand how these LLMs frame math and STEM disciplines in relation to other concepts. We use data obtained by probing the three LLMs in a language generation task that has previously been applied to humans. Our findings indicate that LLMs have negative perceptions of math and STEM fields, associating math with negative concepts in 6 cases out of 10. We observe significant differences across OpenAI’s models: newer versions (i.e., GPT-4) produce 5× semantically richer, more emotionally polarized perceptions with fewer negative associations compared to older versions and N=159 high-school students. These findings suggest that advances in the architecture of LLMs may lead to increasingly less biased models that could even perhaps someday aid in reducing harmful stereotypes in society rather than perpetuating them.

"Rear bias" in spatial auditory perception: Attentional and affective vigilance to sounds occurring outside the visual field.

Presented studies explored the rear bias phenomenon, that is, the attentional and affective bias to sounds occurring behind the listener. Physiological and psychological reactions (i.e., fEMG, EDA/SCR, Simple Reaction Task-SRT, and self-assessments of affect-related states) were measured in response to tones of different frequencies (Study 1) and emotional vocalizations (Study 2) presented in rear and front spatial locations. Results showed that emotional vocalizations, when located in the back, facilitate reactions related to attention orientation (i.e., auricularis muscle response and simple reaction times) and evoke higher arousal-both physiological (as measured by SCR) and psychological (self-assessment scale). Importantly, observed asymmetries were larger for negative and threat-related signals (e.g., anger) than positive/nonthreatening ones (e.g., achievement). By contrast, there were only small differences for the relatively higher frequency tones. The observed relationships are discussed in terms of one of the postulated auditory system's functions, which is monitoring of the environment in order to quickly detect potential threats that occur outside of the visual field (e.g., behind one's back).

Intracranial stimulation and EEG feature analysis reveal affective salience network specialization.

Emotion is represented in limbic and prefrontal brain areas, herein termed the affective salience network (ASN). Within the ASN, there are substantial unknowns about how valence and emotional intensity are processed-specifically, which nodes are associated with affective bias (a phenomenon in which participants interpret emotions in a manner consistent with their own mood). A recently developed feature detection approach ('specparam') was used to select dominant spectral features from human intracranial electrophysiological data, revealing affective specialization within specific nodes of the ASN. Spectral analysis of dominant features at the channel level suggests that dorsal anterior cingulate (dACC), anterior insula and ventral-medial prefrontal cortex (vmPFC) are sensitive to valence and intensity, while the amygdala is primarily sensitive to intensity. Akaike information criterion model comparisons corroborated the spectral analysis findings, suggesting all four nodes are more sensitive to intensity compared to valence. The data also revealed that activity in dACC and vmPFC were predictive of the extent of affective bias in the ratings of facial expressions-a proxy measure of instantaneous mood. To examine causality of the dACC in affective experience, 130 Hz continuous stimulation was applied to dACC while patients viewed and rated emotional faces. Faces were rated significantly happier during stimulation, even after accounting for differences in baseline ratings. Together the data suggest a causal role for dACC during the processing of external affective stimuli.

A pilot study investigating affective forecasting biases with a novel virtual reality-based paradigm

A body of research indicates that people are prone to overestimate the affective impact of future events. Here, we developed a novel experimental paradigm to study these affective forecasting biases under laboratory conditions using subjective (arousal and valence) and autonomic measures (skin conductance responses, SCRs, and heart rate). Thirty participants predicted their emotional responses to 15 unpleasant, 15 neutral, and 15 pleasant scenarios (affective forecasting phase) to which they were then exposed in virtual reality (emotional experience phase). Results showed that participants anticipated more extreme arousal and valence scores than they actually experienced for unpleasant and pleasant scenarios. The emotional experience phase was characterized by classic autonomic patterns, i.e., higher SCRs for emotionally arousing scenarios and greater peak cardiac acceleration for pleasant scenarios. During the affective forecasting phase, we found only a moderate association between arousal scores and SCRs and no valence-dependent modulation of cardiac activity. This paradigm opens up new perspectives for investigating affective forecasting abilities under lab-controlled conditions, notably in psychiatric disorders with anxious anticipations.

The computational psychopathology of emotion.

Mood and anxiety disorders involve recurring, maladaptive patterns of distinct emotions and moods. Here, we argue that understanding these maladaptive patterns first requires understanding how emotions and moods guide adaptive behavior. We thus review recent progress in computational accounts of emotion that aims to explain the adaptive role of distinct emotions and mood. We then highlight how this emerging approach could be used to explain maladaptive emotions in various psychopathologies. In particular, we identify three computational factors that may be responsible for excessive emotions and moods of different types: self-intensifying affective biases, misestimations of predictability, and misestimations of controllability. Finally, we outline how the psychopathological roles of these factors can be tested, and how they may be used to improve psychotherapeutic and psychopharmacological interventions.

The challenge of cognitive science for medical diagnosis

The historical tendency to view medicine as both an art and a science may have contributed to a disinclination among clinicians towards cognitive science. In particular, this has had an impact on the approach towards the diagnostic process which is a barometer of clinical decision-making behaviour and is increasingly seen as a yardstick of clinician calibration and performance. The process itself is more complicated and complex than was previously imagined, with multiple variables that are difficult to predict, are interactive, and show nonlinearity. They appear to characterise a complex adaptive system. Many aspects of the diagnostic process, including the psychophysics of signal detection and discrimination, ergonomics, probability theory, decision analysis, factor analysis, causal analysis and more recent developments in judgement and decision-making (JDM), especially including the domain of heuristics and cognitive and affective biases, appear fundamental to a good understanding of it. A preliminary analysis of factors such as manifestness of illness and others that may impede clinicians’ awareness and understanding of these issues is proposed here. It seems essential that medical trainees be explicitly and systematically exposed to specific areas of cognitive science during the undergraduate curriculum, and learn to incorporate them into clinical reasoning and decision-making. Importantly, this understanding is needed for the development of cognitive bias mitigation and improved calibration of JDM in clinical practice.

Consumer Visual and Affective Bias for Soothing Dolls.

Soothing dolls are becoming increasingly popular in a society with a lot of physical and mental stress. Many products are also combined with soothing dolls to stimulate consumers' desire for impulse buying. However, there is no research on the relationship between consumers' purchasing behavior, consumers' preference for soothing dolls, and visual preference. The purpose of this study was to examine the possible factors that affect the emotional and visual preferences of soothing dolls. Two local stores' sales lists were used to extract three different types of dolls. The 2D and 3D versions of these three dolls were used. Subjective emotional preferences were examined by the self-assessment manikin (SAM) scale, with 5-point Likert scales for valence and arousal factors. An eye tracker was used to examine visual preferences, both before and after positive/negative emotion stimulation by the International Affective Picture System (IAPS). There were 37 subjects involved, with an age range of 20-28 years. The experimental results show that the average valence/arousal scores for 2D/3D dolls were (3.80, 3.74) and (2.65, 2.68), respectively. There was no statistical difference, but both 2D and 3D pictures had high valence scores. Eye tracker analysis revealed no gaze difference in visual preference between 2D and 3D dolls. After negative emotional picture stimulation, the observation time of the left-side doll decreased from 2.307 (std 0.905) to 1.947 (std 1.038) seconds, p < 0.001; and that of the right-side picture increased from 1.898 (std 0.907) to 2.252 (std 1.046) seconds, p < 0.001. The average observation time ratio of the eye on the 3D doll was 40.6%, higher than that on the 2D doll (34.3%, p = 0.02). Soothing dolls may be beneficial for emotion relaxation. Soothing dolls always have high valence features according to the SAM evaluation's measurement. Moreover, this study proposes a novel research model using an eye-tracker and the SAM for the SOR framework.

Future application of an attention bias test to assess affective states in sheep

The affective states of animals comprise a key aspect of welfare that can be difficult to assess. An attention-bias test was developed for sheep, which assessed allocation of attention between a predator threat and a food reward, as a potential measure of affective state. The method was pharmacologically validated as a measure of anxiety-like states, finding that ‘anxious’ sheep were more vigilant, less likely to feed and spent more time looking towards the previous location of a dog than did ‘calm’ sheep. Across six further validation studies, the method was modified and explored as a measure of other types of affective states. This perspective article aims to provide guidance on what the method can tell us about affective state and make recommendations for further research by using this approach. Evidence was strongest across the studies for the test as a measure of anxiety-like states, but it is clear that there are other factors affecting animal behaviour during testing that need to be further investigated. One study showed potential for a modified method to assess depression-like states in sheep, while the impact of chronic stress on affect and attention bias remains unclear. It is likely that the test cannot be used to measure positive affect in sheep without further modification, due to the fear-eliciting nature of the test. Versions of the method using food as a positive stimulus allow for a clearer interpretation of attention than do versions using a conspecific photograph, and are recommended for use in future studies where appetite is not expected to be a confounding factor. In this context, vigilance behaviour may indicate trait anxiety or fearfulness, while other measures of attention may be more sensitive to transient changes in affect. Modifications to the method are suggested to allow for a clearer characterisation of attention in livestock species and to improve the practical application of the test. Overall, the attention-bias test shows promise as a measure of negative affective states, but the method is still very new and further research is needed to better determine its potential use as a welfare-assessment tool.

Be optimistic or be cautious? Affective forecasting bias in allocation decisions and its effect.

People's forecasts of their future emotions play an essential role in their behavior and experience of well-being. However, their emotional reactions may fall short of what they expect, which has implications for subsequent decision making. The current paper investigated the accuracy of affective forecasting about resource allocations and how this (in)accuracy predicts future allocation decisions. Two experimental studies were conducted. Study 1 (N = 84) examined the extent to which people can accurately predict how allocation decisions will feel using an ultimatum game on the part of the allocator. Study 2 tested whether the affective forecasting bias affects future allocation decisions, with 192 participants playing a two-round ultimatum game on the part of allocators. Study 1 found an affective forecasting bias, and people anticipated more powerful emotional reactions to both positive and negative allocation events than they actually experienced when the events occurred. Study 2 found that increased affective forecasting bias resulted in less generous decisions in positive event conditions and more generous decisions in negative event conditions. These results extend previous findings concerning affective forecasting bias and the feelings-as-information model in resource allocation interactions and show that the difference between anticipated and experienced emotion is also informative in allocation decisions. The results suggest that being more cautious when forecasting positive outcomes and more optimistic when forecasting negative outcomes can be beneficial to one's well-being.

The relationship between psychiatric symptoms and affective forecasting bias

Background and objectivesAffective forecasting (AF) is the prediction of future emotional states. Negatively biased affective forecasts (i.e., overestimating negative affect) have been associated with trait anxiety, social anxiety, and depression symptoms, but few studies have tested these relationships while covarying commonly co-occurring symptoms. MethodsIn this study, participants (N = 114) completed a computer game in dyads. Participants were randomized into one of two conditions: a condition in which they were led to believe they were at-fault for losing their dyad money (n = 24 dyads) or a condition in which they were told no one was at fault (n = 34 dyads). Prior to the computer game, participants forecasted their affect for each potential game outcome. ResultsMore severe social anxiety, trait-level anxiety, and depressive symptoms were all associated with more negative AF bias in the at-fault relative to the no-fault condition, and this effect persisted when controlling for other symptoms. Cognitive and social anxiety sensitivity was also associated with more negative AF bias. LimitationsThe generalizability of our findings is innately limited by our non-clinical, undergraduate sample. Future work should replicate and extend our research in more diverse populations and clinical samples. ConclusionsOverall, our results support that AF biases are observed across a range of psychopathology symptoms and associated with transdiagnostic cognitive risk factors. Future work should continue investigating the etiological role of AF bias in psychopathology.

Is Purple Lost in Translation? The Affective Meaning of Purple, Violet, and Lilac Cognates in 16 Languages and 30 Populations.

Colour-emotion association data show a universal consistency in colour-emotion associations, apart from emotion associations withPURPLE. Possibly, its heterogeneity was due to different cognates used as basic colour terms between languages. We analysed emotion associations with PURPLE across 30 populations, 28 countries, and 16 languages (4,008 participants in total). Crucially, these languages usedthe cognates of purple, lilac, or violet to denote the basic PURPLE category. We found small but systematic affective differences between these cognates. They were ordered as purple > lilac > violet on valence, arousal, and power biases. Statistically, the cognate purple was the most strongly biased towards associations withpositiveemotions, and lilac was biased more strongly than violet. Purple was more biased towards high power emotions than violet, but cognates did not differ on arousal biases. Additionally, affective biases differed by population, suggesting high variability within each cognate. Thus, cognates partly account for inconsistencies in the meaning of PURPLE, without explaining their origins.

A repeated measures cognitive affective bias test in rats: comparison with forced swim test.

There is an urgent need to identify behaviours in animals that can provide insight into the aetiology and potential treatment of depression in humans. This study aimed to validate a repeated measures cognitive affective bias (CAB) test in a rat model of chronic stress and compare CAB with forced swim test (FST) measures. Male and female Sprague Dawley rats were trained to associate large and small rewards with scent, spatial, and tactile cues, and their response to an ambiguous tactile stimulus tested. Rats underwent weekly CAB testing for 4weeks with no intervention, or for 2weeks of chronic restraint stress (CRS), followed by 2weeks of fluoxetine, vehicle, or no treatment. CRS rats also underwent the FST at selected timepoints. In control rats, CAB was positive and remained stable over the 4-week period. In CRS-fluoxetine and CRS-vehicle groups, CAB was initially positive, became negative during chronic restraint stress, and returned to positive by 2weeks after treatment. However, in the CRS-no treatment group, CAB was variable at the outset and unstable over time. Behaviour in the FST was not affected by treatment, and there was no correlation between CAB and FST outcomes. Instability in the CRS-no treatment group precluded interpretation of the impact of fluoxetine on CAB post-CRS. Our results suggest that behaviour in the FST does not reflect or alter affective state and support the use of CAB tests as part of the behavioural testing repertoire for preclinical animal models of affective disorders.

Does CEO emotion matter? CEO affectivity and corporate social responsibility

AbstractResearch SummaryWhile prior research has generated meaningful insights into the antecedents of firms' corporate social responsibility (CSR), little attention has been devoted to examining the influence of CEO affectivity—a relatively stable tendency to experience positive or negative emotions. This study explores how CEO positive affectivity (PA) and negative affectivity (NA) may be related to firms' CSR activities. Specifically, we contend that CEO PA is positively related to CSR, whereas CEO NA is negatively related to CSR. We further investigate how CEO social capital may moderate the relationship between CEO affectivity and CSR. Our results support our hypotheses, suggesting the unique role of CEO emotions in CSR research.Managerial SummaryDoes CEO emotion affect firms' CSR activities? Our study finds that CEO PA increases a firm's engagement in CSR, while CEO NA decreases a firm's engagement in CSR. The above relationships are also subject to the influence of CEO social capital. Our findings suggest that CEOs should be aware of how their affective tendencies can influence their firm's CSR strategy and consider avenues to utilize emotional influence advantageously while avoiding potential affective bias.