Sentence examples for fictive prediction from inspiring English sources

Regret-related neural activity in the striatum (caudate nucleus and putamen) has been observed in tasks involving a choice between action and inaction (13,46 48) and may reflect a counterfactual or fictive prediction error that adjusts future behavior in light of counterfactual comparisons (49).

Overall, these findings suggest that the variable coupling of cognitive strategies to two important classes of learning signals (fictive, reward prediction error) represent one contributing substrate for the variable capacity of individuals to control their behavior based on foregone rewards.

These findings suggest that the variable interaction of cognitive strategies with two important classes of computational learning signals (fictive, reward prediction error) represent one contributing substrate for the variable capacity of individuals to control their behavior based on foregone rewards.

In the current sequential investment task, the Regulate strategy could modulate (1) neither fictive nor reward prediction errors, (2) both fictive and reward prediction errors, (3) fictive signals only, (4) reward prediction errors only.

We also explored individual differences in fictive and reward prediction error learning signals.

First, while both fictive and reward prediction errors serve as important learning signals, only fictive signals are susceptible to cognitive strategies both behaviorally and neurally.

In the current study, we investigated the impact of cognitive influences implemented through an emotion regulation strategy on fictive and reward prediction error signals in healthy adults.

These findings provide important insight into the dissociation in the nature of fictive and reward prediction error signals, the interaction between cognitive influences and these computational learning signals, and relevance to psychopathology and potential interventions.

In line with their behavioral differences, f-learners and TD-learners also showed different patterns of brain activations related to fictive and reward prediction errors (Fig. 4c,d, and Supporting Information Tables S9 S12).

In the current study, change in cognitive contexts modulates the behavioral and neural correlates of fictive, but not reward prediction errors.

Furthermore, individuals differ in the extent to which their behaviors are driven by fictive errors versus reward prediction errors, and the reappraisal strategy interacts with such individual differences; a finding also accompanied by distinct underlying neural mechanisms.