Reward prediction error and declarative memory

Learning based on reward prediction error (RPE) was originally proposed in the context of nondeclarative memory. We postulate that RPE may support declarative memory as well. Indeed, recent years have witnessed a number of independent empirical studies reporting effects of RPE on declarative memory. We provide a brief overview of these studies, identify emerging patterns, and discuss open issues such as the role of signed versus unsigned RPEs in declarative learning

Spontaneous eyeblinks during breaking continuous flash suppression are associated with increased detection times

An eyeblink has a clear effect on low-level information processing because it temporarily occludes all visual information. Recent evidence suggests that eyeblinks can also modulate higher level processes (e.g. attentional resources), and vice versa. Despite these putative effects on different levels of information processing, eyeblinks are typically neglected in vision and in consciousness research. The main aim of this study was to investigate the timing and the effect of eyeblinks in an increasingly popular paradigm in consciousness research, namely breaking continuous flash suppression (b-CFS). Results show that participants generally refrain from blinking during a trial, that is, when they need to detect a suppressed stimulus. However, when they do blink during a trial, we observed a sharp increase in suppression time. This suggests that one needs to control for blinking when comparing detection times between conditions that could elicit phasic changes in blinking.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Ellen, Providence, Regina en New Astoria: een hotel-historie

<p><b>Experiment overview (a) and experimental design (b) for Experiment 2.</b> The general trial structure and experimental design of Experiment 2 are largely a replication of Experiment 1.</p

Predictive information speeds up visual awareness in an individuation task by modulating threshold setting, not processing efficiency

Theories on visual awareness claim that predicted stimuli reach awareness faster than unpredicted ones. In the current study, we disentangle whether prior information about the upcoming stimulus affects visual awareness of stimulus location (i.e. individuation) by modulating processing efficiency or threshold setting. Analogous research on stimulus identification revealed that prior information modulates threshold setting. However, as identification and individuation are two functionally and neurally distinct processes, the mechanisms underlying identification cannot simply be extrapolated directly to individuation. The goal of this study was therefore to investigate how individuation is influenced by prior information about the upcoming stimulus. To do so, a drift diffusion model was fitted to estimate the processing efficiency and threshold setting for predicted versus unpredicted stimuli in a cued individuation paradigm. Participants were asked to locate a picture, following a cue that was congruent, incongruent or neutral with respect to the picture's identity. Pictures were individuated faster in the congruent and neutral condition compared to the incongruent condition. In the diffusion model analysis, the processing efficiency was not significantly different across conditions. However, the threshold setting was significantly higher following an incongruent cue compared to both congruent and neutral cues. Our results indicate that predictive information about the upcoming stimulus influences visual awareness by shifting the threshold for individuation rather than by enhancing processing efficiency.SCOPUS: ar.jinfo:eu-repo/semantics/inPres

Reward prediction errors drive declarative learning irrespective of agency

Recent years have witnessed a steady increase in the number of studies investigating the role of reward prediction errors (RPEs) in declarative learning. Specifically, in several experimental paradigms, RPEs drive declarative learning, with larger and more positive RPEs enhancing declarative learning. However, it is unknown whether this RPE must derive from the participant's own response, or whether instead, any RPE is sufficient to obtain the learning effect. To test this, we generated RPEs in the same experimental paradigm where we combined an agency and a nonagency condition. We observed no interaction between RPE and agency, suggesting that any RPE (irrespective of its source) can drive declarative learning. This result holds implications for declarative learning theory

The sound of beauty : how complexity determines aesthetic preference

Stimulus complexity is an important determinant of aesthetic preference. An influential idea is that increases instimulus complexity lead to increased preference up to an optimal point after which preference decreases (in-verted-U pattern). However, whereas some studies indeed observed this pattern, most studies instead showed anincreased preference for more complexity. One complicating issue is that it remains unclear how to definecomplexity. To address this, we approached complexity and its relation to aesthetic preference from a predictivecoding perspective. Here, low- and high-complexity stimuli would correspond to low and high levels of pre-diction errors, respectively. We expected participants to prefer stimuli which are neither too easy to predict (lowprediction error), nor too difficult (high prediction error). To test this, we presented two sequences of tones oneach trial that varied in predictability from highly regular (low prediction error) to completely random (highprediction error), and participants had to indicate which of the two sequences they preferred in a two-intervalforced-choice task. The complexity of each tone sequence (amount of prediction error) was estimated usingentropy. Results showed that participants tended to choose stimuli with intermediate complexity over those ofhigh or low complexity. This confirms the century-old idea that stimulus complexity has an inverted-U re-lationship to aesthetic preference

Learning to synchronize : midfrontal theta dynamics during rule switching

In recent years, several hierarchical extensions of well-known learning algorithms have been proposed. For example, when stimulus-action mappings vary across time or context, the brain may learn two or more stimulus-action mappings in separate modules, and additionally (at a hierarchically higher level) learn to appropriately switch between those modules. However, how the brain mechanistically coordinates neural communication to implement such hierarchical learning remains unknown. Therefore, the current study tests a recent computational model that proposed how midfrontal theta oscillations implement such hierarchical learning via the principle of binding by synchrony (Sync model). More specifically, the Sync model uses bursts at theta frequency to flexibly bind appropriate task modules by synchrony. The 64-channel EEG signal was recorded while 27 human subjects (female: 21, male: 6) performed a probabilistic reversal learning task. In line with the Sync model, postfeedback theta power showed a linear relationship with negative prediction errors, but not with positive prediction errors. This relationship was especially pronounced for subjects with better behavioral fit (measured via Akaike information criterion) of the Sync model. Also consistent with Sync model simulations, theta phase-coupling between midfrontal electrodes and temporoparietal electrodes was stronger after negative feedback. Our data suggest that the brain uses theta power and synchronization for flexibly switching between task rule modules, as is useful, for example, when multiple stimulus action mappings must be retained and used

The time course of cognitive control implementation

Optimally recruiting cognitive control is a key factor in efficient task performance. In line with influential cognitive control theories, earlier work assumed that control is relatively slow. We challenge this notion and test whether control also can be implemented more rapidly by investigating the time course of cognitive control. In two experiments, a visual discrimination paradigm was applied. A reward cue was presented with variable intervals to target onset. The results showed that reward cues can rapidly improve performance. Importantly, the reward manipulation was orthogonal to the response, ensuring that the reward effect was due to fast cognitive control implementation rather than to automatic activation of rewarded S-R associations. We also empirically specify the temporal limits of cognitive control, because the reward cue had no effect when it was presented shortly after target onset, during task execution