Monetary feedback modulates performance and electrophysiological indices of belief updating in reward learning

Dynamic brain entropy predicts risky decision-making across transdiagnostic dimensions of psychopathology

OBJECTIVES

Maladaptive risky decision-making is a common pathological behavior among patients with various psychiatric disorders. Brain entropy, which measures the complexity of brain time series signals, provides a novel approach to assessing brain health. Despite its potential, the dynamics of brain entropy have seldom been explored. This study aimed to construct a dynamic model of brain entropy and examine its predictive value for risky decision-making in patients with mental disorders, utilizing resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

This study analyzed the rs-fMRI data from a total of 198 subjects, including 48 patients with bipolar disorder (BD), 47 patients with schizophrenia (SZ), 40 patients with adult attention deficit hyperactivity disorder (ADHD), as well as 63 healthy controls (HC). Time series signals were extracted from 264 brain regions based on rs-fMRI. The traditional static entropy and dynamic entropy (coefficient of variation, CV; rate of change, Rate) were constructed, respectively. Support vector regression was employed to predict risky decision-making utilizing leave-one-out cross-validation within each group.

RESULTS

Our findings showed that CV achieved the best performances in HC and BD groups (r = -0.58, MAE = 6.43, R2 = 0.32; r = -0.78, MAE = 12.10, R2 = 0.61), while the Rate achieved the best in SZ and ADHD groups (r = -0.69, MAE = 10.20, R2 = 0.47; r = -0.78, MAE = 7.63, R2 = 0.60). For the dynamic entropy, the feature selection threshold rather than the time window length and overlapping ratio influenced predictive performance.

CONCLUSIONS

These results suggest that dynamic brain entropy could be a more effective predictor of risky decision-making than traditional static brain entropy. Our findings offer a novel perspective on exploring brain signal complexity and can serve as a reference for interventions targeting risky decision-making behaviors, particularly in individuals with psychiatric diagnoses.

Evidence for the Beneficial Effect of Reward on Working Memory: A Meta-Analytic Study

Rewards act as external motivators and can improve performance in various cognitive tasks. However, previous research demonstrated mixed findings regarding the effect of reward on working memory (WM) performance, and the question of whether reward enhances WM performance is arguable. It remains unclear how the effect of reward on WM can be influenced by various factors, such as types of reward and experimental paradigms. In this meta-analytic study, we systematically investigated the effect of reward on WM by analyzing data from 51 eligible studies involving a total of 1767 participants. Our results showed that reward robustly enhanced WM performance, with non-monetary rewards inducing more benefits than monetary rewards. This may be because, while both types of reward could induce extrinsic motivation, non-monetary rewards enhanced intrinsic motivation while monetary rewards reduced it. Notably, all three reward methods-reward binding, reward expectation, and subliminal reward-effectively improved WM performance, with the reward binding paradigm exhibiting the greatest effects. This finding suggests that the reward effect can be attributed to both increasing the total amount of WM resources and improving the flexibility of resource reallocation. Moreover, the type of WM, the experimental paradigms, and the outcome measures are three moderators that should be jointly considered when assessing the reward effects on WM. Overall, this meta-analytic study provides solid evidence that reward improves WM performance and reveals possible mechanisms underlying these improvements.

Explaining reversal learning deficits in anxiety with electrophysiological evidence

Reversal learning is a crucial aspect of behavioral flexibility that plays a significant role in environmental adaptation and development. While previous studies have established a link between anxiety and impaired reversal learning ability, the underlying mechanisms behind this association remain unclear. This study employed a probabilistic reversal learning task with electroencephalographic recording to investigate these mechanisms. Participants were divided into two groups based on their scores on Spielberger's State-Trait Anxiety Inventory: high trait-anxiety (HTA) and low trait-anxiety (LTA), consisting of 50 individuals in each group. The results showed that the HTA group had poorer reversal learning performance than the LTA group, including a lower tendency to shift to the new optimal option after rule reversals (reversal-shift). The study also examined event-related potentials elicited by reversals and found that although the N1 (related to attention allocation), feedback-related negativity (FRN: related to belief updating), and P3 (related to response inhibition) were all sensitive to the grouping factor, only the FRN elicited by reversal-shift mediated the relationship between anxiety and the number/reaction time of reversal-shift. From these findings, we suggest that abnormalities in belief updating may contribute to the impaired reversal learning performance observed in anxious individuals. In our opinion, this study sheds light on potential targets for interventions aimed at improving behavioral flexibility in anxious individuals.

Social Context and Rejection Expectations Modulate Neural and Behavioral Responses to Social Feedback

When meeting other people, some are optimistic and expect to be accepted by others, whereas others are pessimistic and expect mostly rejections. How social feedback is evaluated in situations that meet or do not meet these biases and how people differ in their response to rejection and acceptance depending on the social situation are unknown. In this study, participants experienced rejection and acceptance by peers in two different social contexts, one with high (negative context) and the other with low probability of rejection (positive context). We examined how the neural and behavioral responses to rejection are altered by this context and whether it depends on the individual's sensitivity to rejection. Behavioral results show that, on average, people maintain an optimistic bias even when mostly experiencing rejection. Importantly, personality differences in rejection sensitivity affected both prior expectations to be rejected in the paradigm and the extent to which expectations changed during the paradigm. The context also strongly modulated ERPs and theta responses to rejection and acceptance feedback. Specifically, valence effects on neural responses were enhanced in the negative context, suggesting a greater relevance to monitor social feedback in such a situation. Moreover, midfrontal theta predicted how expectations were changed in response to prediction errors, stressing a role for theta in learning from social feedback. Surprisingly, interindividual differences in rejection sensitivity did not affect neural responses to feedback. Our results stress the importance of considering the interaction between subjective expectations and the social context for behavioral and neural responses to social rejection.

Shared increased entropy of brain signals across patients with different mental illnesses: A coordinate-based activation likelihood estimation meta-analysis

Entropy is a measurement of brain signal complexity. Studies have found increased/decreased entropy of brain signals in psychiatric patients. There is no consistent conclusion regarding the relationship between the entropy of brain signals and mental illness. Therefore, this meta-analysis aimed to identify consistent abnormalities in the brain signal entropy in patients with different mental illnesses. We conducted a systematic search to collect resting-state functional magnetic resonance imaging (rs-fMRI) studies in patients with psychiatric disorders. This work identified 9 eligible rs-fMRI studies, which included a total of 14 experiments, 67 activation foci, and 1383 subjects. We tested the convergence across their findings by using the activation likelihood estimation method. P-value maps were corrected by using cluster-level family-wise error p < 0.05 and permuting 2000 times. Results showed that patients with different psychiatric disorders shared commonly increased entropy of brain signals in the left inferior and middle frontal gyri, and the right fusiform gyrus, cuneus, precuneus. No shared alterations were found in the subcortical regions and cerebellum in the patient group. Our findings suggested that the increased entropy of brain signals in the cortex, not subcortical regions and cerebellum, might have associations with the pathophysiology across mental illnesses. This meta-analysis study provided the first comprehensive understanding of the abnormality in brain signal complexity across patients with different psychiatric disorders.

How predictability affects habituation to novelty

One becomes accustomed to repeated exposures, even for a novel event. In the present study, we investigated how predictability affects habituation to novelty by applying a mathematical model of arousal that we previously developed, and through the use of psychophysiological experiments to test the model's prediction. We formalized habituation to novelty as a decrement in Kullback-Leibler divergence from Bayesian prior to posterior (i.e., information gain) representing arousal evoked from a novel event through Bayesian update. The model predicted an interaction effect between initial uncertainty and initial prediction error (i.e., predictability) on habituation to novelty: the greater the initial uncertainty, the faster the decrease in information gain (i.e., the sooner habituation occurs). This prediction was supported by experimental results using subjective reports of surprise and event-related potential (P300) evoked by visual-auditory incongruity. Our findings suggest that in highly uncertain situations, repeated exposure to stimuli can enhance habituation to novel stimuli.