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Toth-Faber, E.

Publications and source records attributed to Toth-Faber, E..

6 recordsLinked to original sources

Flexible belief updating drives the childhood advantage in statistical learning

Children often outperform adults in probabilistic statistical learning tasks, yet the mechanisms underlying this developmental advantage remain poorly understood. Here, we used eye-tracking measures of belief updating to examine how children and adults acquire and update predictions in a probabilistic sequence-learning task. Using the standard (oculomotor) reaction time measure, children showed stronger statistical learning than adults, replicating previous behavioral findings while revealing a more detailed profile of developmental differences in statistical learning. Critically, children updated their predictions more frequently: they were less likely to repeat previous predictions and more likely to shift their expectations in response to new input. Adults, in contrast, showed greater persistence, tending to maintain prior predictions even when those predictions were inconsistent with the underlying statistical structure. Despite these pronounced differences in updating behavior, the processing and use of prediction errors were remarkably similar across age groups. These findings indicate that developmental differences in statistical learning do not primarily arise from how prediction errors are computed, but rather from how prior beliefs and incoming information are weighted during belief updating. Childrens enhanced learning may therefore reflect reduced reliance on stable priors and greater sensitivity to current sensory evidence, supporting a more exploratory learning strategy. Adults, by contrast, appear to favor an exploitative strategy that stabilizes existing predictions but reduces flexibility in probabilistic environments. More broadly, the results suggest that developmental changes in statistical learning may reflect age-related differences in how readily learners revise their predictions in response to incoming evidence. By integrating sensitive oculomotor measures with analyses that probe the mechanisms underlying belief updating, the present study provides a more fine-grained account of how predictive learning changes across development and offers a framework for reconciling previously inconsistent developmental findings in statistical learning.

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Alpha and theta activity during reward anticipation are modulated by implicit expectations about sequential risk

Reward anticipation potentially guides sequential decision making, yet its underlying neural dynamics remain unclear. In this study, we investigated how within-trial escalating risk and contextual uncertainty modulate oscillatory brain activity during reward anticipation. EEG was recorded while participants (N = 44) performed a modified version of the Balloon Analogue Risk Task in which balloon burst probabilities changed across task phases, introducing contextual uncertainty. Spectral power was analyzed time-locked to three within-trial risk levels: early no-risk pumps, final successful pumps (preceding cash out), and unsuccessful pumps (preceding balloon burst). Time-frequency decomposition using Morlet wavelets revealed a parieto-occipital alpha power increase following early no-risk pumps, consistent with reduced deliberative engagement when anticipating certain rewards. In contrast, centroparietal alpha suppression emerged following final successful pumps, suggesting increased attentional engagement and reward expectancy at high within-trial risk levels. Frontocentral theta power also decreased following final successful pumps, with the strongest reduction observed when the burst probability function was shallower. Rather than reflecting simple reward encoding, this pattern may index reduced monitoring demands following commitment to the selected action. Overall, both alpha and theta dynamics tracked within-trial escalating risk, whereas theta activity was additionally modulated by contextual factors across task phases. These findings provide novel insights into the oscillatory mechanisms supporting reward anticipation in sequential decision environments.

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Individual differences in probabilistic learning and updating predictive representations in individuals with obsessive-compulsive tendencies

Obsessive-compulsive (OC) tendencies involve intrusive thoughts and rigid, repetitive behaviours that also manifest at the subclinical level in the general population. The neurocognitive factors driving the development and persistence of the excessive presence of these tendencies remain highly elusive, though emerging theories emphasize the role of implicit information processing. Despite various empirical studies on distinct neurocognitive processes, the incidental retrieval of environmental structures in dynamic and noisy environments, such as probabilistic learning, has received relatively little attention. In this study, we aimed to unravel potential individual differences in implicit probabilistic learning and the updating of predictive representations related to OC tendencies in the general population. We conducted two independent online experiments (NStudy1 = 164, NStudy2 = 257) with young adults. Probabilistic learning was assessed using a reliable implicit visuomotor probabilistic learning task, which involved sequences with second-order non-adjacent dependencies. Our findings revealed that even among individuals displaying a broad spectrum of OC tendencies within a non-clinical population, implicit probabilistic learning remained remarkably robust. Furthermore, the results highlighted effective updating capabilities of predictive representations, which were not influenced by OC tendencies. These results offer new insights into individual differences in probabilistic learning and updating in relation to OC tendencies, contributing to theoretical, methodological, and practical approaches for understanding the maladaptive behavioural manifestations of OC disorder and subclinical tendencies.

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Initial experience has lasting effect on repeated risky decisions

Both primarily and recently encountered information have been shown to influence experience-based risky decision making. The primacy effect predicts that initial experience will influence later choices even if outcome probabilities change and reward is ultimately more or less sparse than primarily experienced. However, it has not been investigated whether extended initial experience would induce a more profound primacy effect upon risky choices than brief experience. Therefore, the present study tested in two experiments whether young adults adjusted their risk-taking behavior in the Balloon Analogue Risk task after an unsignaled and unexpected change point. The change point separated early "good luck" or "bad luck" trials from subsequent ones. While mostly positive (more reward) or mostly negative (no reward) events characterized the early trials, subsequent trials were unbiased. In Experiment 1, the change point occurred after one-sixth or one-third of the trials (brief vs. extended experience) without intermittence, whereas in Experiment 2, it occurred between separate task phases. In Experiment 1, if negative events characterized the early trials, after the change point, risk-taking behavior increased as compared with the early trials. Conversely, if positive events characterized the early trials, risk-taking behavior decreased after the change point. Although the adjustment of risk-taking behavior occurred due to integrating recent experiences, the impact of initial experience was simultaneously observed. The length of initial experience did not reliably influence the adjustment of behavior. In Experiment 2, participants became more prone to take risks as the task progressed, indicating that the impact of initial experience could be overcome. Altogether, we suggest that initial beliefs about outcome probabilities can be updated by recent experiences to adapt to the continuously changing decision environment.

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Procedural learning under stress: boosted statistical learning but unaffected sequence learning

Acute stress can crucially influence learning and memory processes. One of the key processes underlying human learning and memory is the ability of our brain to rapidly detect and extract regularities from sensory input across time and space leading to effective predictive processing. Here, we aimed to get an in-depth look into the effect of stress on the acquisition of two aspects of regularity extraction. We examined whether and how stress affects (1) processes and learning of probability-based, statistical regularities and (2) serial order-based, sequential regularities in the same experimental design, and (3) explicit access to the acquired information. Considering that the acquisition of statistical regularities is a rapid process, we primarily focused on the early phases of the task. We induced stress with the Socially Evaluated Cold Pressor Test in 27 young adults, while 26 participants were enrolled in the control group. Salivary cortisol levels and subjective ratings of affective states showed successful stress induction. After the stress induction, we measured regularity extraction with the cued Alternating Serial Reaction Time task. We found that stress promoted the acquisition of statistical regularities and did not alter the learning of sequential regularities. Post-block reports showed weaker explicit access to the sequential regularities in the stress group. Our results give a process-level understanding on how stress alters learning and memory functions related to predictive processes.

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Do adolescents take more risks? Not when facing a novel uncertain situation

In real-life decision-making, sub-optimal risk-taking seems characteristic of adolescents. Such behavior increases the chance of serious negative, and at times, irreversible outcomes for this population (e.g., road traffic accidents, addictions). We are still lacking conclusive evidence, however, for an inverted U-shaped developmental trajectory for risk-taking. This raises the question whether adolescents are really more risk-prone or when facing a novel risky situation, they behave just as children and adults do. To answer this question, we used the Balloon Analogue Risk Task (BART) to assess the risky decision making of 188 individuals ranging in age from 7 to 30. The BART provided useful data for characterizing multiple aspects of risk-taking. Surprisingly, we found that adolescents were not more inclined to take risks than children or young adults. Participants in all age groups were able to adapt their learning processes to the probabilistic environment and improve their performance during the sequential risky choice. There were no age-related differences in risk-taking at any stage of the task. Likewise, neither negative feedback reactivity nor overall task performance distinguished adolescents from the younger and older age groups. Our findings prompt 1) methodological considerations about the validity of the BART and 2) theoretical debate whether the amount of experience on its own may account for age-related changes in real-life risk-taking, since risk-taking in a novel and uncertain situation was invariant across developmental stages.

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