The Causes and Consequences of Drifting Expectations.

Awaiting news of uncertain outcomes is distressing because the news might be disappointing. To prevent such disappointments, people often "brace for the worst," pessimistically lowering expectations before news arrives to decrease the possibility of surprising disappointment (a negative prediction error, or PE). Computational decision-making research commonly assumes that expectations do not drift within trials, yet it is unclear whether expectations pessimistically drift in real-world, high-stakes settings, what factors influence expectation drift, and whether it effectively buffers emotional responses to goal-relevant outcomes. Moreover, individuals learn from PEs to accurately anticipate future outcomes, but it is unknown whether expectation drift also impedes PE-based learning. In a sample of students awaiting exam grades (N = 625), we found that expectations often drift and tend to drift pessimistically. We demonstrate that bracing is preferentially modulated by uncertainty; it transiently buffers the initial emotional impact of negative PEs but impairs PE-based learning, counterintuitively sustaining uncertainty into the future.

Depression is associated with blunted affective responses to naturalistic reward prediction errors.

BACKGROUND: Depression is characterized by abnormalities in emotional processing, but the specific drivers of such emotional abnormalities are unknown. Computational work indicates that both surprising outcomes (prediction errors; PEs) and outcomes (values) themselves drive emotional responses, but neither has been consistently linked to affective disturbances in depression. As a result, the computational mechanisms driving emotional abnormalities in depression remain unknown. METHODS: Here, in 687 individuals, one-third of whom qualify as depressed via a standard self-report measure (the PHQ-9), we use high-stakes, naturalistic events - the reveal of midterm exam grades - to test whether individuals with heightened depression display a specific reduction in emotional response to positive PEs. RESULTS: Using Bayesian mixed effects models, we find that individuals with heightened depression do not affectively benefit from surprising, good outcomes - that is, they display reduced affective responses to positive PEs. These results were highly specific: effects were not observed to negative PEs, value signals (grades), and were not related to generalized anxiety. This suggests that the computational drivers of abnormalities in emotion in depression may be specifically due to positive PE-based emotional responding. CONCLUSIONS: Affective abnormalities are core depression symptoms, but the computational mechanisms underlying such differences are unknown. This work suggests that blunted affective reactions to positive PEs are likely mechanistic drivers of emotional dysregulation in depression.

Real-World Exploration Increases Across Adolescence and Relates to Affect, Risk Taking, and Social Connectivity.

Cross-species research suggests that exploratory behaviors increase during adolescence and relate to the social, affective, and risky behaviors characteristic of this developmental stage. However, how these typical adolescent behaviors manifest and relate in real-world settings remains unclear. Using geolocation tracking to quantify exploration-variability in daily movement patterns-over a 3-month period in 58 adolescents and adults (ages 13-27) in New York City, we investigated whether daily exploration varied with age and whether exploration related to social connectivity, risk taking, and momentary positive affect. In our cross-sectional sample, we found an association between daily exploration and age, with individuals near the transition to legal adulthood exhibiting the highest exploration levels. Days of higher exploration were associated with greater positive affect irrespective of age. Higher mean exploration was associated with greater social connectivity in all participants but was linked to higher risk taking selectively among adolescents. Our results highlight the interplay of exploration and socioemotional behaviors across development and suggest that societal norms may modulate their expression in naturalistic contexts.

The affective benefits of real-world exploration during the COVID-19 pandemic.

Increasing daily exploration is linked to improvements in affective well-being. However, COVID-19 elevated uncertainty when leaving the home, altering the risk-reward of balance of geospatial novelty. To this end, we simultaneously collected real-world geospatial tracking and experience sampling of emotion, prior to and during the first year of the pandemic in 630 individuals. COVID-19 reduced exploration and subjective well-being. Yet, despite the health risks of exploring during the pandemic, the days of highest affective well-being were those when individuals explored the most. However, this was not true for everyone: during the first months of the pandemic, at the height of the uncertainty surrounding the transmissibility and prognosis of a COVID-19 infection, more anxious individuals experienced no affective benefit to leaving home. Taken together, real-world exploration improved well-being regardless of the presence of real-world threat, but anxiety mitigated these benefits. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Negative interpretation bias connects to real-world daily affect: A multistudy approach.

Negative interpretation bias, the tendency to appraise ambiguous stimuli as threatening, shapes our emotional lives. Various laboratory tasks, which differ in stimuli features and task procedures, can quantify negative interpretation bias. However, it is unknown whether these tasks globally predict individual differences in real-world negative (NA) and positive (PA) affect. Across two studies, we tested whether different lab-based negative interpretation bias tasks predict daily NA and PA, measured via mobile phone across months. To quantify negative interpretation bias, Study 1 (N = 69) used a verbal, self-referential task whereas Study 2 (N = 110) used a perceptual, emotional image task with faces and scenes. Across tasks, negative interpretation bias was linked to heightened daily NA. However, only negative interpretation bias in response to ambiguous faces was related to decreased daily PA. These results illustrate the ecological validity of negative interpretation bias tasks and highlight converging and unique relationships between distinct tasks and naturalistic emotion. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Individual differences in naturalistic learning link negative emotionality to the development of anxiety.

Organisms learn from prediction errors (PEs) to predict the future. Laboratory studies using small financial outcomes find that humans use PEs to update expectations and link individual differences in PE-based learning to internalizing disorders. Because of the low-stakes outcomes in most tasks, it is unclear whether PE learning emerges in naturalistic, high-stakes contexts and whether individual differences in PE learning predict psychopathology risk. Using experience sampling to assess 625 college students' expected exam grades, we found evidence of PE-based learning and a general tendency to discount negative PEs, an "optimism bias." However, individuals with elevated negative emotionality, a personality trait linked to the development of anxiety disorders, displayed a global pessimism and learning differences that impeded accurate expectations and predicted future anxiety symptoms. A sensitivity to PEs combined with an aversion to negative PEs may result in a pessimistic and inaccurate model of the world, leading to anxiety.

Temporal dynamics of affect in the brain: Evidence from human imaging and animal models.

Emotions are time-varying internal states that promote survival in the face of dynamic environments and shifting homeostatic needs. Research in non-human organisms has recently afforded specific insights into the neural mechanisms that support the emergence, persistence, and decay of affective states. Concurrently, a separate affective neuroscience literature has begun to dissect the neural bases of affective dynamics in humans. However, the circuit-level mechanisms identified in animals lack a clear mapping to the human neuroscience literature. As a result, critical questions pertaining to the neural bases of affective dynamics in humans remain unanswered. To address these shortcomings, the present review integrates findings from humans and non-human organisms to highlight the neural mechanisms that govern the temporal features of emotional states. Using the theory of affective chronometry as an organizing framework, we describe the specific neural mechanisms and modulatory factors that arbitrate the rise-time, intensity, and duration of emotional states.

Temporal dynamics of real-world emotion are more strongly linked to prediction error than outcome.

Primarily based on laboratory studies, theories of affect propose that emotions are driven by the valence of outcomes as well as the difference between the outcome itself and the expected outcome (i.e., the prediction error [PE]). Yet no work has assessed the drivers of emotion using real-world, personally meaningful events on timescales over which human emotion unfolds. We developed an event-triggered, ecological momentary assessment procedure measuring positive and negative affect (PA and NA, respectively) in university students as they received exam grades for which they had made predictions. We split data into exploratory and confirmatory samples, and built computational models predicting the time course of PA and NA and demonstrate that a model incorporating both exam grade and grade PE accounted for the time course of PA and NA better than a model solely using exam grades. Further, grade PEs were stronger predictors of the time course of PA and NA than the grades themselves. Similarly, the effects of PEs also persisted longer for NA than PA. These data indicate that deviations from expectations are critical determinants of the temporal dynamics of real-world emotion. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Affective and physiological reactivity to emotional comments in individuals at elevated risk for psychosis.

BACKGROUND: Individuals with schizophrenia are at increased risk of relapse when they live in highly critical (i.e., high expressed emotion; EE) family environments. It remains less clear, however, how individuals at elevated risk for a psychotic disorder react to the social stress of EE. Here we examined whether individuals at elevated risk for developing schizophrenia report greater subjective changes in affect and have increased physiological reactivity after hearing critical, praising and neutral comments. METHOD: Measures of heart rate, heart rate variability, skin conductance, and self-reported affective ratings were used to assess differential responses to EE-type stimuli in 38 individuals at elevated-risk for psychosis and 38 low-risk controls. RESULTS: The elevated-risk group and low-risk controls, did not differ in their initial affective and physiological reactivity to criticism. However, during the recovery period following the criticism, the elevated-risk group demonstrated greater heart rate activation. They also showed more sensitivity to praise. Although elevated-risk participants initially had higher baseline levels of negative affect and heart rate, following praise, these levels reduced and became indistinguishable from the levels of low-risk controls. CONCLUSIONS: These findings suggest that at-risk individuals may have more difficulty recovering from criticism than their self-report data might suggest. They may also derive physiological and affective benefits from praise. Important clinical implications of these findings are discussed.