Trait anxiety is linked to increased usage of priors in a perceptual decision making task

Temporal stability of Bayesian belief updating in perceptual decision-making

Bayesian inference suggests that perception is inferred from a weighted integration of prior contextual beliefs with current sensory evidence (likelihood) about the world around us. The perceived precision or uncertainty associated with prior and likelihood information is used to guide perceptual decision-making, such that more weight is placed on the source of information with greater precision. This provides a framework for understanding a spectrum of clinical transdiagnostic symptoms associated with aberrant perception, as well as individual differences in the general population. While behavioral paradigms are commonly used to characterize individual differences in perception as a stable characteristic, measurement reliability in these behavioral tasks is rarely assessed. To remedy this gap, we empirically evaluate the reliability of a perceptual decision-making task that quantifies individual differences in Bayesian belief updating in terms of the relative precision weighting afforded to prior and likelihood information (i.e., sensory weight). We analyzed data from participants (n = 37) who performed this task twice. We found that the precision afforded to prior and likelihood information showed high internal consistency and good test-retest reliability (ICC = 0.73, 95% CI [0.53, 0.85]) when averaged across participants, as well as at the individual level using hierarchical modeling. Our results provide support for the assumption that Bayesian belief updating operates as a stable characteristic in perceptual decision-making. We discuss the utility and applicability of reliable perceptual decision-making paradigms as a measure of individual differences in the general population, as well as a diagnostic tool in psychiatric research.

Experience-driven recalibration of learning from surprising events

Different environments favor different patterns of adaptive learning. A surprising event that in one context would accelerate belief updating might, in another context, be downweighted as a meaningless outlier. Here, we investigated whether people would spontaneously regulate the influence of surprise on learning in response to event-by-event experiential feedback. Across two experiments, we examined whether participants performing a perceptual judgment task under spatial uncertainty (n = 29, n = 63) adapted their patterns of predictive gaze according to the informativeness or uninformativeness of surprising events in their current environment. Uninstructed predictive eye movements exhibited a form of metalearning in which surprise came to modulate event-by-event learning rates in opposite directions across contexts. Participants later appropriately readjusted their patterns of adaptive learning when the statistics of the environment underwent an unsignaled reversal. Although significant adjustments occurred in both directions, performance was consistently superior in environments in which surprising events reflected meaningful change, potentially reflecting a bias towards interpreting surprise as informative and/or difficulty ignoring salient outliers. Our results provide evidence for spontaneous, context-appropriate recalibration of the role of surprise in adaptive learning.

Acute threat enhances perceptual sensitivity without affecting the decision criterion

Threatening situations ask for rapid and accurate perceptual decisions to optimize coping. Theoretical models have stated that psychophysiological states, such as bradycardia during threat-anticipatory freezing, may facilitate perception. However, it’s unclear if this occurs via enhanced bottom-up sensory processing or by relying more on prior expectations. To test this, 52 (26 female) participants completed a visual target-detection paradigm under threat-of-shock (15% reinforcement rate) with a manipulation of prior expectations. Participants judged the presence of a backward-masked grating (target presence rate 50%) after systematically manipulating their decision criterion with a rare (20%) or frequent (80%) target presence rate procedure. Threat-of-shock induced stronger heart rate deceleration compared to safe, indicative of threat-anticipatory freezing. Importantly, threat-of-shock enhanced perceptual sensitivity but we did not find evidence of an altered influence of the effect of prior expectations on current decisions. Correct target detection (hits) was furthermore accompanied by an increase in the magnitude of this heart rate deceleration compared to a missed target. While this was independent of threat-of-shock manipulation, only under threat-of-shock this increase was accompanied by more hits and increased sensitivity. Together, these findings suggest that under acute threat participants may rely more on bottom-up sensory processing versus prior expectations in perceptual decision-making. Critically, bradycardia may underlie such enhanced perceptual sensitivity.

Negative affect impedes perceptual filling-in in the uniformity illusion

The notion of cognitive penetrability, i.e., whether perceptual contents can in principle be influenced by non-perceptual factors, has sparked a significant debate over methodological concerns and the correct interpretation of existing findings. In this study, we combined predictive processing models of visual perception and affective states to investigate influences of affective valence on perceptual filling-in in extrafoveal vision. We tested how experimentally induced affect would influence the probability of perceptual filling-in occurring in the uniformity illusion (N = 50). Negative affect led to reduced occurrence rates and increased onset times of visual uniformity. This effect was selectively observed in illusionary trials, requiring perceptual filling-in, and not in control trials, where uniformity was the veridical percept, ruling out biased motor responses or deliberate judgments as confounding variables. This suggests an influential role of affective status on subsequent perceptual processing, specifically on how much weight is ascribed to priors as opposed to sensory evidence.

Association of Brain Reward Response With Body Mass Index and Ventral Striatal-Hypothalamic Circuitry Among Young Women With Eating Disorders

IMPORTANCE

Eating disorders are severe psychiatric disorders; however, disease models that cross subtypes and integrate behavior and neurobiologic factors are lacking.

OBJECTIVE

To assess brain response during unexpected receipt or omission of a salient sweet stimulus across a large sample of individuals with eating disorders and healthy controls and test for evidence of whether this brain response is associated with the ventral striatal-hypothalamic circuitry, which has been associated with food intake control, and whether salient stimulus response and eating disorder related behaviors are associated.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional functional brain imaging study, young adults across the eating disorder spectrum were matched with healthy controls at a university brain imaging facility and eating disorder treatment program. During a sucrose taste classic conditioning paradigm, violations of learned associations between conditioned visual and unconditioned taste stimuli evoked the dopamine-related prediction error. Dynamic effective connectivity during expected sweet taste receipt was studied to investigate hierarchical brain activation between food intake relevant brain regions. The study was conducted from June 2014 to November 2019. Data were analyzed from December 2019 to February 2020.

MAIN OUTCOMES AND MEASURES

Prediction error brain reward response across insula and striatum; dynamic effective connectivity between hypothalamus and ventral striatum; and demographic and behavior variables and their correlations with prediction error brain response and connectivity edge coefficients.

RESULTS

Of 317 female participants (197 with eating disorders and 120 healthy controls), the mean (SD) age was 23.8 (5.6) years and mean (SD) body mass index was 20.8 (5.4). Prediction error response was elevated in participants with anorexia nervosa (Wilks λ, 0.843; P = .001) and in participants with eating disorders inversely correlated with body mass index (left nucleus accumbens: r = -0.291; 95% CI, -0.413 to -0.167; P < .001; right dorsal anterior insula: r = -0.228; 95% CI, -0.366 to -0.089; P = .001), eating disorder inventory-3 binge eating tendency (left nucleus accumbens: r = -0.207; 95% CI, -0.333 to -0.073; P = .004; right dorsal anterior insula: r = -0.220; 95% CI, -0.354 to -0.073; P = .002), and trait anxiety (left nucleus accumbens: r = -0.148; 95% CI, -0.288 to -0.003; P = .04; right dorsal anterior insula: r = -0.221; 95% CI, -0.357 to -0.076; P = .002). Ventral striatal to hypothalamus directed connectivity was positively correlated with ventral striatal prediction error in eating disorders (r = 0.189; 95% CI, 0.045-0.324; P = .01) and negatively correlated with feeling out of control after eating (right side: r = -0.328; 95% CI, -0.480 to -0.164; P < .001; left side: r = -0.297; 95% CI, -0.439 to -0.142; P = .001).

CONCLUSIONS AND RELEVANCE

The results of this cross-sectional imaging study support that body mass index modulates prediction error and food intake control circuitry in the brain. Once altered, this circuitry may reinforce eating disorder behaviors when paired with behavioral traits associated with overeating or undereating.

Musicality as a predictive process

Savage et al. argue for musicality as having evolved for the overarching purpose of social bonding. By way of contrast, we highlight contemporary predictive processing models of human cognitive functioning in which the production and enjoyment of music follows directly from the principle of prediction error minimization.

Affective Bias Through the Lens of Signal Detection Theory

Affective bias – a propensity to focus on negative information at the expense of positive information – is a core feature of many mental health problems. However, it can be caused by wide range of possible underlying cognitive mechanisms. Here we illustrate this by focusing on one particular behavioural signature of affective bias – increased tendency of anxious/depressed individuals to predict lower rewards – in the context of the Signal Detection Theory (SDT) modelling framework. Specifically, we show how to apply this framework to measure affective bias and compare it to the behaviour of an optimal observer. We also show how to extend the framework to make predictions about bias when the individual holds incorrect assumptions about the decision context. Building on this theoretical foundation, we propose five experiments to test five hypothetical sources of this affective bias: beliefs about prior probabilities, beliefs about performance, subjective value of reward, learning differences, and need for accuracy differences. We argue that greater precision about the mechanisms driving affective bias may eventually enable us to better understand the mechanisms underlying mood and anxiety disorders.