scholarly journals Deeply Felt Affect: The Emergence of Valence in Deep Active Inference

2019 ◽  
Author(s):  
Casper Hesp ◽  
Ryan Smith ◽  
Thomas Parr ◽  
Micah Allen ◽  
Karl Friston ◽  
...  
Keyword(s):  
Affective State ◽  
Emotional Valence ◽  
Adaptive Behaviour ◽  
Active Inference ◽  
Affective States ◽  
Mental Action ◽  
Sensory Data ◽  
Context Learning ◽  
Domain Generality ◽  
Internal Action

The positive-negative axis of emotional valence has long been recognised as fundamental to adaptive behaviour, but its domain-generality has largely eluded formal theories and modelling. Using deep active inference – a hierarchical inference scheme that rests on inverting a model of how sensory data are generated – we develop a principled Bayesian account of emotional valence. This formulation associates valence with subjective fitness and exploits the domain-generality of second-order beliefs (i.e., beliefs about beliefs). We construct an affective agent that infers its valence state from the expected precision of its phenotype-congruent action model (i.e., subjective fitness) in any given environment. The ensuing affective states then optimise that confidence pre-emptively. The evidence for inferred (i.e., ‘felt’) valenced states depends upon the (Bayes-optimal) updating term for subjective fitness, which we label affective charge (AC). We simulate affective inference in a T-maze paradigm requiring context learning, followed by context reversal. The result is a deep (biologically plausible) agent that infers its affective state and reduces its uncertainty through internal action (i.e., optimises prior beliefs that underwrite confidence). Thus, we demonstrate the potential of active inference in providing a formal and computationally tractable account of the link between affect, (mental) action, and implicit meta-cognition.

scholarly journals Deeply Felt Affect: The Emergence of Valence in Deep Active Inference

2020 ◽  
pp. 1-49
Author(s):  
Casper Hesp ◽  
Ryan Smith ◽  
Thomas Parr ◽  
Micah Allen ◽  
Karl J. Friston ◽  
...  
Keyword(s):  
Affective State ◽  
Emotional Valence ◽  
Face Validity ◽  
Active Inference ◽  
Mental Action ◽  
Sensory Data ◽  
Context Learning ◽  
Domain Generality ◽  
Internal Action ◽  
Action Model

The positive-negative axis of emotional valence has long been recognized as fundamental to adaptive behavior, but its origin and underlying function have largely eluded formal theorizing and computational modeling. Using deep active inference, a hierarchical inference scheme that rests on inverting a model of how sensory data are generated, we develop a principled Bayesian model of emotional valence. This formulation asserts that agents infer their valence state based on the expected precision of their action model—an internal estimate of overall model fitness (“subjective fitness”). This index of subjective fitness can be estimated within any environment and exploits the domain generality of second-order beliefs (beliefs about beliefs). We show how maintaining internal valence representations allows the ensuing affective agent to optimize confidence in action selection preemptively. Valence representations can in turn be optimized by leveraging the (Bayes-optimal) updating term for subjective fitness, which we label affective charge (AC). AC tracks changes in fitness estimates and lends a sign to otherwise unsigned divergences between predictions and outcomes. We simulate the resulting affective inference by subjecting an in silico affective agent to a T-maze paradigm requiring context learning, followed by context reversal. This formulation of affective inference offers a principled account of the link between affect, (mental) action, and implicit metacognition. It characterizes how a deep biological system can infer its affective state and reduce uncertainty about such inferences through internal action (i.e., top-down modulation of priors that underwrite confidence). Thus, we demonstrate the potential of active inference to provide a formal and computationally tractable account of affect. Our demonstration of the face validity and potential utility of this formulation represents the first step within a larger research program. Next, this model can be leveraged to test the hypothesized role of valence by fitting the model to behavioral and neuronal responses.

scholarly journals Mood dynamics are associated with learning and not choice

2019 ◽  
Author(s):  
Bastien Blain ◽  
Robb Rutledge
Keyword(s):  
Affective State ◽  
Computational Modelling ◽  
Risky Choice ◽  
Adaptive Behaviour ◽  
Prediction Errors ◽  
Affective States ◽  
Environmental Statistics ◽  
Probability Prediction ◽  
The Difference ◽  
Choice Tasks

Updating predictions about which stimuli are associated with reward is an important aspect of adaptive behaviour believed to relate to prediction errors, the difference between experienced and predicted outcomes. Behavioural sensitivity to prediction errors flexibly adapts to environmental statistics. Prediction errors also influence affective states during risky choice tasks that do not require learning, but the relationship between emotions and adaptive behaviour is unknown. Here, using computational modelling we found that mood dynamics, like behaviour, are sensitive to learning-relevant model variables (i.e., probability prediction error). Unlike behaviour, mood dynamics are not sensitive to model variables that influence choice (i.e., expected value), and increasing volatility does not reduce how many trials influence affective state. Finally, depressive symptoms reduce overall mood more in volatile than stable environments. Our findings suggest that mood dynamics are selective for variables relevant to adaptive behaviour and suggest a greater role for mood in learning than choice.

scholarly journals Evaluation of miRNA as Biomarkers of Emotional Valence in Pigs

Animals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 2054
Author(s):  
Laura Marsh ◽  
Mark R. Hutchinson ◽  
Clive McLaughlan ◽  
Stefan T. Musolino ◽  
Michelle L. Hebart ◽  
...  
Keyword(s):  
Positive Emotions ◽  
Affective State ◽  
Emotional Valence ◽  
Emotional States ◽  
Affective States ◽  
Production Environment ◽  
Large White ◽  
Judgment Bias ◽  
Positive Affective State ◽  
The Brain

The ability to assess the welfare of animals is dependent on our ability to accurately determine their emotional (affective) state, with particular emphasis being placed on the identification of positive emotions. The challenge remains that current physiological and behavioral indices are either unable to distinguish between positive and negative emotional states, or they are simply not suitable for a production environment. Therefore, the development of novel measures of animal emotion is a necessity. Here we investigated the efficacy of microRNA (miRNA) in the brain and blood as biomarkers of emotional state in the pig. Female Large White × Landrace pigs (n = 24) were selected at weaning and trained to perform a judgment bias test (JBT), before being exposed for 5 weeks to either enriched (n = 12) or barren housing (n = 12) conditions. Pigs were tested on the JBT once prior to treatment, and immediately following treatment. MiRNA and neurotransmitters were analyzed in blood and brain tissue after euthanasia. Treatment had no effect on the outcomes of the JBT. There was also no effect of treatment on miRNA expression in blood or the brain (FDR p > 0.05). However, pigs exposed to enriched housing had elevated dopamine within the striatum compared to pigs in barren housing (p = 0.02). The results imply that either (a) miRNAs are not likely to be valid biomarkers of a positive affective state, at least under the type of conditions employed in this study, or (b) that the study design used to modify affective state was not able to create differential affective states, and therefore establish the validity of miRNA as biomarkers.

scholarly journals Multimodal Affective State Assessment Using fNIRS + EEG and Spontaneous Facial Expression

2020 ◽  
Vol 10 (2) ◽  
pp. 85 ◽  
Author(s):  
Yanjia Sun ◽  
Hasan Ayaz ◽  
Ali N. Akansu
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Brain Activity ◽  
Affective State ◽  
Emotional Valence ◽  
Video Content ◽  
Affective States ◽  
Eeg Signals ◽  
Image Content ◽  
Affective Expressions

Human facial expressions are regarded as a vital indicator of one’s emotion and intention, and even reveal the state of health and wellbeing. Emotional states have been associated with information processing within and between subcortical and cortical areas of the brain, including the amygdala and prefrontal cortex. In this study, we evaluated the relationship between spontaneous human facial affective expressions and multi-modal brain activity measured via non-invasive and wearable sensors: functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) signals. The affective states of twelve male participants detected via fNIRS, EEG, and spontaneous facial expressions were investigated in response to both image-content stimuli and video-content stimuli. We propose a method to jointly evaluate fNIRS and EEG signals for affective state detection (emotional valence as positive or negative). Experimental results reveal a strong correlation between spontaneous facial affective expressions and the perceived emotional valence. Moreover, the affective states were estimated by the fNIRS, EEG, and fNIRS + EEG brain activity measurements. We show that the proposed EEG + fNIRS hybrid method outperforms fNIRS-only and EEG-only approaches. Our findings indicate that the dynamic (video-content based) stimuli triggers a larger affective response than the static (image-content based) stimuli. These findings also suggest joint utilization of facial expression and wearable neuroimaging, fNIRS, and EEG, for improved emotional analysis and affective brain–computer interface applications.

scholarly journals Towards estimating affective states in Virtual Reality based on behavioral data

2021 ◽  
Author(s):  
Valentin Holzwarth ◽  
Johannes Schneider ◽  
Joshua Handali ◽  
Joy Gisler ◽  
Christian Hirt ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Adaptive Systems ◽  
User Study ◽  
Affective State ◽  
Head Movements ◽  
Affective States ◽  
Physical Demand ◽  
Perceived Performance ◽  
Sequential Administration ◽  
Better Than

AbstractInferring users’ perceptions of Virtual Environments (VEs) is essential for Virtual Reality (VR) research. Traditionally, this is achieved through assessing users’ affective states before and after being exposed to a VE, based on standardized, self-assessment questionnaires. The main disadvantage of questionnaires is their sequential administration, i.e., a user’s affective state is measured asynchronously to its generation within the VE. A synchronous measurement of users’ affective states would be highly favorable, e.g., in the context of adaptive systems. Drawing from nonverbal behavior research, we argue that behavioral measures could be a powerful approach to assess users’ affective states in VR. In this paper, we contribute by providing methods and measures evaluated in a user study involving 42 participants to assess a users’ affective states by measuring head movements during VR exposure. We show that head yaw significantly correlates with presence, mental and physical demand, perceived performance, and system usability. We also exploit the identified relationships for two practical tasks that are based on head yaw: (1) predicting a user’s affective state, and (2) detecting manipulated questionnaire answers, i.e., answers that are possibly non-truthful. We found that affective states can be predicted significantly better than a naive estimate for mental demand, physical demand, perceived performance, and usability. Further, manipulated or non-truthful answers can also be estimated significantly better than by a naive approach. These findings mark an initial step in the development of novel methods to assess user perception of VEs.

scholarly journals The Interpretation of E-Motions in Faces and Bodies Derived from Static Artworks by Individuals with High Functioning Autistic Spectrum

Vision ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 17
Author(s):  
Maria Elisa Della-Torre ◽  
Daniele Zavagno ◽  
Rossana Actis-Grosso
Keyword(s):  
Positive Emotions ◽  
Emotional Experience ◽  
Affective State ◽  
Likert Scale ◽  
Autism Spectrum ◽  
Emotional Expressions ◽  
Affective States ◽  
Dynamic Component ◽  
Specific Emotion ◽  
Similar Range

E-motions are defined as those affective states the expressions of which—conveyed either by static faces or body posture—embody a dynamic component and, consequently, convey a higher sense of dynamicity than other emotional expressions. An experiment is presented, aimed at testing whether e-motions are perceived as such also by individuals with autism spectrum disorders (ASDs), which have been associated with impairments in emotion recognition and in motion perception. To this aim we replicate with ASD individuals a study, originally conducted with typically developed individuals (TDs), in which we showed to both ASD and TD participants 14 bodiless heads and 14 headless bodies taken from eleven static artworks and four drawings. The Experiment was divided into two sessions. In Session 1 participants were asked to freely associate each stimulus to an emotion or an affective state (Task 1, option A); if they were unable to find a specific emotion, the experimenter showed them a list of eight possible emotions (words) and asked them to choose one from such list, that best described the affective state portrayed in the image (Task 1, option B). After their choice, they were asked to rate the intensity of the perceived emotion on a seven point Likert scale (Task 2). In Session 2 participants were requested to evaluate the degree of dynamicity conveyed by each stimulus on a 7 point Likert scale. Results showed that ASDs and TDs shared a similar range of verbal expressions defining emotions; however, ASDs (i) showed an impairment in the ability to spontaneously assign an emotion to a headless body, and (ii) they more frequently used terms denoting negative emotions (for both faces and bodies) as compared to neutral emotions, which in turn were more frequently used by TDs. No difference emerged between the two groups for positive emotions, with happiness being the emotion better recognized in both faces and in bodies. Although overall there are no significant differences between the two groups with respect to the emotions assigned to the images and the degree of perceived dynamicity, the interaction Artwork x Group showed that for some images ASDs assigned a different value than TDs to perceived dynamicity. Moreover, two images were interpreted by ASDs as conveying completely different emotions than those perceived by TDs. Results are discussed in light of the ability of ASDs to resolve ambiguity, and of possible different cognitive styles characterizing the aesthetical/emotional experience.

scholarly journals Effects of Classroom Activities on Affective State—A Comparison of Third and Fifth Graders

2016 ◽  
Vol 6 (2) ◽  
pp. 1 ◽  
Author(s):  
Michael Fartoukh ◽  
Lucile Chanquoy
Keyword(s):  
Academic Performance ◽  
Educational Psychology ◽  
Grade Level ◽  
Fifth Graders ◽  
Affective State ◽  
Third Graders ◽  
Cognitive Resources ◽  
Affective States ◽  
Classroom Activities ◽  
School Day

<p>We analysed the influence of classroom activities on children’s affective states. Children perform many different activities in the course of an ordinary school day, some of which may trigger changes in their affective state and thus in the availability of their cognitive resources and their degree of motivation. To observe the effects of two such activities (listening to a text and performing a dictation) on affective state, according to grade, we asked 39 third graders and 40 fifth graders to specify their affective state at several points in the day. Results showed that this state varied from one activity to another, and was also dependent on grade level. Third graders differed from fifth graders in the feelings elicited by the activities. The possible implications of these findings for the field of educational psychology and children’s academic performance are discussed.</p>

scholarly journals Intelligent Monitoring of Affective Factors Underlying Sport Performance by Means of Wearable and Mobile Technology

Proceedings ◽  
2018 ◽  
Vol 2 (19) ◽  
pp. 1202 ◽  
Author(s):  
Carlos Bailon ◽  
Miguel Damas ◽  
Hector Pomares ◽  
Daniel Sanabria ◽  
Pandelis Perakakis ◽  
...  
Keyword(s):  
Wearable Sensors ◽  
Affective State ◽  
Sport Performance ◽  
Affective States ◽  
Complete Evaluation ◽  
Affective Factors ◽  
Physiological Variables ◽  
Sport Events ◽  
The Impact ◽  
The Relationship

The fluctuation of affective states is a contributing factor to sport performance variability. The context surrounding athletes during their daily life and the evolution of their physiological variables beyond sport events are relevant factors, as they modulate the affective state of the subject over time. However, traditional procedures to assess the affective state are limited to self-reported questionnaires within controlled settings, thus removing the impact of the context. This work proposes a multimodal, context-aware platform that combines the data acquired through smartphones and wearable sensors to assess the affective state of the athlete. The platform is aimed at ubiquitously monitoring the fluctuations of affective states during longitudinal studies within naturalistic environments, overcoming the limitations of previous studies and allowing for the complete evaluation of the factors that could modulate the affective state. This system will also facilitate and expedite the analysis of the relationship between affective states and sport performance.

scholarly journals Losing stinks! The effect of competition outcome on body odour quality

2020 ◽  
Vol 375 (1800) ◽  
pp. 20190267 ◽  
Author(s):  
Jitka Fialová ◽  
Vít Třebický ◽  
Radim Kuba ◽  
David Stella ◽  
Jakub Binter ◽  
...  
Keyword(s):  
Human Body ◽  
Dominance Hierarchy ◽  
Affective State ◽  
Real Life ◽  
Olfactory Communication ◽  
Affective States ◽  
Formal Level ◽  
Body Odour ◽  
Axillary Odour

Dominance hierarchy is often established via repeated agonistic encounters where consistent winners are considered dominant. Human body odour contains cues to psychological dominance and competition, but it is not known whether competition outcome (a marker of a change in dominance hierarchy) affects the hedonic quality of human axillary odour. Therefore, we investigated the effect of winning and losing on odour quality. We collected odour samples from Mixed Martial Arts fighters approximately 1 h before and immediately after a match. Raters then assessed samples for pleasantness, attractiveness, masculinity and intensity. We also obtained data on donors' affective state and cortisol and testosterone levels, since these are known to be associated with competition and body odour quality. Perceived body odour pleasantness, attractiveness and intensity significantly decreased while masculinity increased after a match irrespective of the outcome. Nonetheless, losing a match affected the pleasantness of body odour more profoundly, though bordering formal level of significance. Moreover, a path analysis revealed that match loss led to a decrease in odour attractiveness, which was mediated by participants’ negative affective states. Our study suggests that physical competition and to some extent also its outcome affect the perceived quality of human body odour in specific real-life settings, thus providing cues to dominance-related characteristics. This article is part of the Theo Murphy meeting issue ‘Olfactory communication in humans’.

THE INTERACTION OF INTUITION AND RATIONALITY DURING ESCALATED NPD DECISIONS: AN INVESTIGATION OF DECISION-MAKERS’ AFFECTIVE STATES

2019 ◽  
Vol 24 (04) ◽  
pp. 2050033
Author(s):  
TOBIAS ROETH ◽  
PATRICK SPIETH ◽  
VERENA JOACHIM
Keyword(s):  
Decision Making ◽  
New Product Development ◽  
Affective State ◽  
Decision Makers ◽  
Affective States ◽  
Escalating Commitment ◽  
Decision Making Styles ◽  
Intuitive Decision Making ◽  
Affect Infusion Model ◽  
Commitment Escalation

Decision-makers often struggle to terminate unsuccessful new product development (NPD) projects, so that escalating commitment occurs. Although research shows that rational and intuitive decision-making styles (DMS) as well as a decision-maker’s affective state determines the performance of NPD decisions, little is known about their influences on escalating commitment. By applying the affect infusion model in an experimental study, we investigate how a decision-maker’s affective state influence their escalating commitment by focusing on their use of a rational and an intuitive DMS. Our findings, based on 366 respondents, show that a rational DMS is unable to reduce commitment escalation. Surprisingly, an intuitive DMS is able to reduce a decision-maker’s commitment in the case of a positive affect, whereas a rational DMS increases their commitment in the case of a negative affect. Thus, our interdisciplinary research on affect and decision-making extends and contributes to research into decision-making during the NPD process as well as into escalating commitment.

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