Is interesting knowledge a reward? An integrative model of emotion, reward and appraisal frameworks of epistemic curiosity. DOI Open Access
Asli Erdemli, Catherine Audrin, David Sander

et al.

Published: April 16, 2024

Is interesting knowledge a reward? To tackle this question, we review drive, optimal arousal, intrinsic motivation, information-gap, emotion, reward, and computational accounts of epistemic curiosity. fMRI, EEG, physiological behavioral evidence in favor the curiosity-as-a-reward-anticipation hypothesis is discussed: curiosity activates dopaminergic brain reward circuit, enhances attention, memory, academic learning. We propose an appraisal model which integrates active inference According to model, emotion triggered by perceived relevance, uncertainty coping potential knowledge-gaps. Curiosity confers value its object, triggers anticipation process motivates exploitative knowledge-seeking behavior (i.e., wanting knowledge). Once satisfied, future expectations are updated according affective prediction errors (i.e. liking learning). If appraised as low, knowledge-gap creates anxiety leads information-avoidance. also discuss what roles play frustration, enjoyment, boredom surprise dynamics knowledge-acquisition.

Language: Английский

The Human Affectome DOI Creative Commons
Daniela Schiller, Alessandra Nicoletta Cruz Yu, Nelly Alia‐Klein

et al.

Neuroscience & Biobehavioral Reviews, Journal Year: 2023, Volume and Issue: 158, P. 105450 - 105450

Published: Nov. 3, 2023

Over the last decades, interdisciplinary field of affective sciences has seen proliferation rather than integration theoretical perspectives. This is due to differences in metaphysical and mechanistic assumptions about human phenomena (what they are how work) which, shaped by academic motivations values, have determined constructs operationalizations. An assumption on purpose can be used as a teleological principle guide construction common set assumptions—a framework for research. In this capstone paper special issue "Towards an Integrated Understanding Human Affectome", we gather tiered synthesize that account collectively. teleologically-grounded offers principled agenda launchpad both organizing existing perspectives generating new ones. Ultimately, hope Affectome brings us step closer not only integrated understanding phenomena, but

Language: Английский

Citations

29
Emotion prediction as computation over a generative theory of mind DOI Creative Commons
Sean Dae Houlihan,

Max Kleiman‐Weiner,

Luke Hewitt

et al.

Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Journal Year: 2023, Volume and Issue: 381(2251)

Published: June 4, 2023

From sparse descriptions of events, observers can make systematic and nuanced predictions what emotions the people involved will experience. We propose a formal model emotion prediction in context public high-stakes social dilemma. This uses inverse planning to infer person's beliefs preferences, including preferences for equity maintaining good reputation. The then combines these inferred mental contents with event compute 'appraisals': whether situation conformed expectations fulfilled preferences. learn functions mapping computed appraisals labels, allowing match human observers' quantitative 20 emotions, joy, relief, guilt envy. Model comparison indicates that monetary are not sufficient explain predictions; factored into nearly every emotion. Human both use minimal individualizing information adjust how different respond same event. Thus, our framework integrates planning, concepts single computational reverse-engineer people's intuitive theory emotions. article is part discussion meeting issue 'Cognitive artificial intelligence'.

Language: Английский

Citations

22
A levels-of-analysis framework for studying social emotions DOI
Hongbo Yu, Xiaoxue Gao, Bo Shen

et al.

Nature Reviews Psychology, Journal Year: 2024, Volume and Issue: 3(3), P. 198 - 213

Published: Feb. 21, 2024

Language: Английский

Citations

5
A cognitive-computational account of mood swings in adolescence DOI Creative Commons

Klára Gregorová,

Eran Eldar, Lorenz Deserno

et al.

Trends in Cognitive Sciences, Journal Year: 2024, Volume and Issue: 28(4), P. 290 - 303

Published: March 18, 2024

Teenagers have a reputation for being fickle, in both their choices and moods. This variability may help adolescents as they begin to independently navigate novel environments. Recently, however, adolescent moodiness has also been linked psychopathology. Here, we consider adolescents' mood swings from computational perspective, grounded reinforcement learning (RL). model proposes that is determined by surprises about outcomes the environment, how much learn these surprises. It additionally suggests biases choice bidirectional manner. Integrating independent lines of research, sketch cognitive-computational account mood, learning, dynamics influence each other, with implications normative psychopathological development.

Language: Английский

Citations

5
The affective gradient hypothesis: an affect-centered account of motivated behavior DOI
Amitai Shenhav

Trends in Cognitive Sciences, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 1, 2024

Language: Английский

Citations

5
Towards a Generative Model for Emotion Dynamics DOI Open Access
Oisín Ryan, Fabian Dablander, Jonas M B Haslbeck

et al.

Published: March 17, 2023

Most theories of emotion suggest that emotions are reactions to situations we encounter in daily life. Process further specify a feedback loop between our environment, attention, emotions, and action clarifies the adaptive nature emotions. In principle, such process describe how develop life, consequently, measures collected from individuals many times day studies using Experience Sampling Methodology (ESM) should be highly useful advancing these theories. However, current predominantly verbal therefore do not make clear predictions about data. this paper, take first step towards generative model dynamics by formalizing link which provides us with basic We show incomplete already reproduces nine empirical phenomena time series related (temporal) statistical associations their distributional form. then discuss can draw on existing (process) extend into complete dynamics. Finally, models facilitate theory development advance measurement, study design, analysis.

Language: Английский

Citations

11
Wanting to matter and learning to care: A neurodevelopmental window of opportunity for (Pro) social learning? DOI Creative Commons
Ronald E. Dahl, Emma Armstrong‐Carter, Wouter van den Bos

et al.

Developmental Cognitive Neuroscience, Journal Year: 2024, Volume and Issue: 69, P. 101430 - 101430

Published: Aug. 14, 2024

Wanting to matter-to feel socially recognized, appreciated, and capable of actions that benefit others-represents a fundamental motivation in human development. The motivational salience mattering appears increase adolescence. Evidence suggests this is related pubertal increases the incentive for gaining social value personal agency. This can provide useful heuristic understanding proclivities (i.e. wanting matter) influence action-outcome learning as young adolescents are exploring how navigate increasingly complex relational environments. Adolescence also brings new capacities, motives, opportunities care about contribute others. Together, these create window opportunity: sensitive period gain salient feelings through caring prosocial valued societal contributions. Successfully discovering ways by doing things matter others may formative socio-emotional self/other. Advances processes their neurodevelopmental underpinnings inform strategies improve developmental trajectories competence wellbeing among growing up rapidly changing techno-centric world.

Language: Английский

Citations

4
Frequency-specific changes in prefrontal activity associated with maladaptive belief updating in volatile environments in euthymic bipolar disorder DOI Creative Commons
Marina Ivanova, Ksenia Germanova, D. S. Petelin

et al.

Translational Psychiatry, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 17, 2025

Language: Английский

Citations

0
Negative affect-driven impulsivity as hierarchical model-based overgeneralization DOI
A. Okan, Michael N. Hallquist

Trends in Cognitive Sciences, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

Citations

0
Emotions and individual differences shape human foraging under threat DOI Creative Commons
Hailey A. Trier, Jill X. O’Reilly, Lisa Spiering

et al.

Nature Mental Health, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Abstract A common behavior in natural environments is foraging for rewards. However, this often the presence of predators. Therefore, one most fundamental decisions humans, as other animals, how to apportion time between reward-motivated pursuit and threat-motivated checking behavior. To understand what affects people strike balance, we developed an ecologically inspired task looked at both within-participant dynamics (moods) between-participant individual differences (questionnaires about real-life behaviors) two large internet samples ( n = 374 702) a cross-sectional design. For dynamics, found that regulate task-evoked stress homeostatically by changing (increasing hiding). Individual differences, even superficially related traits (apathy–anhedonia anxiety–compulsive checking) reliably mapped onto unique behaviors. Worse performance, due maladaptive checking, was linked gender (women checked excessively) specific anxiety-related traits: somatic anxiety (reduced self-reported worry) compulsivity (self-reported disorganized checking). While anhedonia decreased engagement, apathy, strikingly, improved overall performance reducing excessive checking. In summary, provide multifaceted paradigm assessment threat naturalistic sensitive moods they change throughout clinical dimensions. Thus, it could serve objective measurement tool future studies interested threat, vigilance or behavior–emotion interactions contexts requiring reward seeking avoidance.

Language: Английский

Citations

0