Computational models of subjective feelings in psychiatry

Kao, Chang-Hao; Feng, Gloria; Hur, Jihyun K.; Jarvis, Huw; Rutledge, Robb B.

doi:10.1016/j.neubiorev.2022.105008

Cited by 14 publications

(9 citation statements)

References 141 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, the acute stress (during the last month) is supposed to trigger shifts in goal-directed vs. habitual behavior pattern, which is concomitant with specific network configurations, especially frontostriatal circuits (CEN: LPFCal SN: VTA/putamen/caudate↓, lateral/medial OFC↓) ( 7 ). Stronger PEs may contribute to highly variable momentary mood fluctuations due to stronger reward feedback dynamics, whereas the influence of PEs on RL is compromised in depressed individuals ( 51 ). In summary, these studies highlight a promising target for RL-based NF interventions for anhedonic depression to produce flexible mood changes.…”

Section: Discussionmentioning

confidence: 99%

A feasibility study of goal-directed network-based real-time fMRI neurofeedback for anhedonic depression

Wang,

Zhou,

et al. 2023

Front. Psychiatry

View full text Add to dashboard Cite

Anhedonia is a hallmark symptom of depression that often lacks adequate interventions. The translational gap remains in clinical treatments based on neural substrates of anhedonia. Our pilot study found that depressed individuals depended less on goal-directed (GD) reward learning (RL), with reduced reward prediction error (RPE) BOLD signal. Previous studies have found that anhedonia is related to abnormal activities and/or functional connectivities of the central executive network (CEN) and salience network (SN), both of which belong to the goal-directed system. In addition, it was found that real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF) could improve the balance between CEN and SN in healthy individuals. Therefore, we speculate that rt-fMRI NF of the CEN and SN associated with the GD system may improve depressive and/or anhedonic symptoms. Therefore, this study (1) will examine individuals with anhedonic depression using GD-RL behavioral task, combined with functional magnetic resonance imaging and computational modeling to explore the role of CEN/SN deficits in anhedonic depression; and (2) will utilize network-based rt-fMRI NF to investigate whether it is feasible to regulate the differential signals of brain CEN/SN of GD system through rt-fMRI NF to alleviate depressive and/or anhedonic symptoms. This study highlights the need to elucidate the intervention effects of rt-fMRI NF and the underlying computational network neural mechanisms.

show abstract

Section: Discussionmentioning

confidence: 99%

A feasibility study of goal-directed network-based real-time fMRI neurofeedback for anhedonic depression

Wang,

Zhou,

et al. 2023

Front. Psychiatry

View full text Add to dashboard Cite

show abstract

“…Importantly, the research efforts that attempt to understand affect as a temporally dependent and continuous state may enable researchers to gain insights into mental health and well-being. A recent review argued that measuring and modeling momentary subjective feeling states during decision-making paradigms may provide insights into psychiatric disorders 20 . Understanding how affective dynamics change during well-controlled decision tasks 20 as well as everyday settings 53 in clinical populations may contribute to a better understanding of the underlying psychiatric disorders.…”

Section: Affective Integration In Experiencementioning

confidence: 99%

“…However, there are open questions about how a stream of input is dynamically represented in affective experience. Recent advances make it possible to use formal computational models to interpret and analyze affective fluctuations over time as a function of events, stimuli, and actions 16,17,20 . Computational models are flexible tools that can be used as data analysis methods to investigate complex patterns and validate hypotheses 103 .…”

Section: Box 2 Modeling Affective Experiencementioning

confidence: 99%

“…Hence, there is great potential in measuring and modeling affective integration over time together with carefully defined formal decision models to provide mechanistic explanations for the role of affect in judgment and decisionmaking. The recent advances in computational modeling of subjective feeling states [15][16][17][18][19][20] (see also BOX.2) and continuous measurement techniques 21,22 make it possible to study changes in affect over time and its continuous involvement in decisions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Affective integration in experience, judgment, and decision-making

Asutay,

Västfjäll

2024

Preprint

View full text Add to dashboard Cite

Research on the role of affect in judgment and decision-making has attracted an increasing interest in recent decades. However, most current approaches ignore the temporal dependence of mental states and focus on effects rather than on mechanisms. This effectively leads to an approach of mapping a relatively well-defined, but largely static, feeling state to a tendency for a certain response. Recent evidence shows that affective consequences of multiple events are integrated over time into a unified overall affective experience reflecting current resources under current demands. This affective integration is shaped by contextual factors and continually modulates judgments and decisions. Here, based on a few promising recent advances, we advocate for an approach to studying the role of affect in judgment and decision-making that integrates affective dynamics into decision-making paradigms and explicitly models the temporal variation in decision processes that result from changing affective states. This approach, by identifying the key variables explaining how changes in affect influence information processing, may provide new insights into the role of affective dynamics in behavior.

show abstract

“…Recently, the nascent field of computational psychiatry has provided compelling theoretical frameworks for modeling both choice behaviors and subjective states, including craving (Kao et al, 2023;Redish, 2004;Sprevak & Columbo, 2019;Gu et al, 2019). Indeed, with the high degree of complexity, heterogeneity, and multidimensionality of symptomatology in psychiatric disorders, a deeper understanding of these latent mental states may be key to breakthroughs in targets for clinical interventions.…”

mentioning

confidence: 99%

A generalizable computational mechanism underlying the interaction between momentary craving and decision-making

Kulkarni

Berner

Schiller

et al. 2023

Preprint

View full text Add to dashboard Cite

All addictive disorders consist of two key, interacting features: persistent subjective craving and maladaptive choice behaviors. However, the computations underlying the bidirectional relationship between craving and decision-making remain unknown. Here, we tested a hypothesis that momentary craving and value-based decision-making dynamically influence each other across addictive domains. We sampled momentary craving as three groups of participants (alcohol drinkers, cannabis users, and binge eaters; total n=202) performed a probabilistic learning task in which they received either monetary or group-specific addictive cue rewards. Using computational modeling, we found that momentary craving dynamically biased towards faster learning during addictive but not monetary decision-making across all groups. Conversely, we also found that prediction errors modulated perceived craving. Computational parameters underlying these latent mechanisms were reliably predictive of clinical severity. These findings provide a computational mechanism for the interaction between craving and choice behavior that is generalizable across addictive domains.

show abstract

Computational models of subjective feelings in psychiatry

Cited by 14 publications

References 141 publications

A feasibility study of goal-directed network-based real-time fMRI neurofeedback for anhedonic depression

A feasibility study of goal-directed network-based real-time fMRI neurofeedback for anhedonic depression

Affective integration in experience, judgment, and decision-making

A generalizable computational mechanism underlying the interaction between momentary craving and decision-making

Contact Info

Product

Resources

About