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Internal control beliefs shape positive affect and associated neural dynamics during outcome valuation.

ABSTRACT: Experiencing events as controllable is essential for human well-being. Based on classic psychological theory, we test how internal control beliefs impact the affective valuation of task outcomes, neural dynamics and ensuing behavioral preferences. In three consecutive studies we show that dynamics in positive affect increase, with a qualitative shift towards self-evaluative pride, when agents believe they caused a given outcome. We demonstrate that these outcomes engage brain networks processing self-referential information in the cortical midline. Here, activity in the ventromedial prefrontal cortex tracks outcome valence regarding both success as well as internal control, and covaries with positive affect in response to outcomes. These affective dynamics also relate to increased functional coupling between the ventral striatum and cortical midline structures. Finally, we show that pride predicts preferences for control, even at monetary costs. Our investigations extend recent models of positive affect and well-being, and emphasize that control beliefs drive intrinsic motivation.

SUBMITTER: Stolz DS

PROVIDER: S-EPMC7060341 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Internal control beliefs shape positive affect and associated neural dynamics during outcome valuation.

Stolz David S DS Müller-Pinzler Laura L Krach Sören S Paulus Frieder M FM

Nature communications 20200306 1

Experiencing events as controllable is essential for human well-being. Based on classic psychological theory, we test how internal control beliefs impact the affective valuation of task outcomes, neural dynamics and ensuing behavioral preferences. In three consecutive studies we show that dynamics in positive affect increase, with a qualitative shift towards self-evaluative pride, when agents believe they caused a given outcome. We demonstrate that these outcomes engage brain networks processing ...[more]

PMID: 32144259

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Project description:BackgroundThe network approach to psychopathology has become increasingly popular. Little research has examined the dynamic network structure of mental disorders, and, to date, no study has investigated the network dynamics of positive affect, negative affect, and physical activity in bipolar disorder. This represents the first study to estimate the dynamic network structure of affect and physical activity in individuals with and without bipolar I disorder.MethodsAn intensive longitudinal design was used to assess positive affect, negative affect, and actigraphy-based estimates of physical activity. The overall sample consisted of 32 adults with bipolar I disorder and 36 healthy control participants. Eligible participants underwent an 8-week assessment period, in which once-per-day ratings of affect and actigraphy estimates were obtained. Participants were re-assessed on baseline measures afterwards. Dynamic network analysis was used to examine the network structure of affect and physical activity over time. Multilevel models were used to examine the relationship between autocorrelation and changes in depression symptoms among participants with bipolar disorder.LimitationsThe network analyses assume stationarity. Future research should consider time-varying multilevel network models to better account for time trends.ResultsThe results of the temporal networks indicated that the directed edges between positive and negative affect were mostly positive among individuals with bipolar I disorder. Among healthy control participants, the directed edges between positive and negative affect were mostly negative in direction. Physical activity, as assessed by daily actigraphy indices, was more densely connected in the healthy control network than the bipolar disorder network. Furthermore, the results indicated that critical slowing down predicted worsening of mood symptoms in the bipolar I disorder group.ConclusionsThis study suggests that certain dynamic patterns of affect may be an underlying process that contributes to the maintenance of bipolar disorder. These results have both theoretical and practical implications.

Project description:There exists growing interest in understanding the dynamics of resting state functional magnetic resonance imaging (rs-fMRI) to establish mechanistic links between individual patterns of spontaneous neural activation and corresponding behavioral measures in both normative and clinical populations. Here we propose and validate a novel approach in which whole-brain rs-fMRI data are mapped to a specific low-dimensional representation-affective valence and arousal processing-prior to dynamic analysis. This mapping process constrains the state space such that both independent validation and visualization of the system's dynamics become tractable. To test this approach, we constructed neural decoding models of affective valence and arousal processing from brain states induced by International Affective Picture Set image stimuli during task-related fMRI in (n = 97) healthy control subjects. We applied these models to decode moment-to-moment affect processing in out-of-sample subjects' rs-fMRI data and computed first and second temporal derivatives of the resultant valence and arousal time-series. Finally, we fit a second set of neural decoding models to these derivatives, which function as neurally constrained ordinary differential equations (ODE) underlying affect processing dynamics. To validate these decodings, we simulated affect processing by numerical integration of the true temporal sequence of neurally decoded derivatives for each subject and demonstrated that these decodings generate significantly less (p < 0.05) group-level simulation error than integration based upon decoded derivatives sampled uniformly randomly from the true temporal sequence. Indeed, simulations of valence and arousal processing were significant for up to four steps of closed-loop simulation (Δt = 2.0 s) for both valence and arousal, respectively. Moreover, neural encoding representations of the ODE decodings include significant clusters of activation within brain regions associated with affective reactivity and regulation. Our work has methodological implications for efforts to identify unique and actionable biomarkers of possible future or current psychopathology, particularly those related to mood and emotional instability.

Dataset Information

Internal control beliefs shape positive affect and associated neural dynamics during outcome valuation.

Publications

Internal control beliefs shape positive affect and associated neural dynamics during outcome valuation.

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