3 research outputs found

    Right hemisphere advantage in statistical learning: evidence from a probabilistic sequence learning task

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    Picking up statistical regularities of patterns from the environment is essential for predictive and adaptive behavior. One of the most important challenges is to understand how statistical learning occurs and how the acquired information consolidates and stabilizes in the brain. Evidence suggests that the prefrontal cortex (PFC) has a critical role in these processes; the division of labor between hemispheres, however, is less characterized. The aim of the present study was to directly investigate the causal role of the right and left PFC in statistical learning and its consolidation. Healthy, young adults were trained on a probabilistic sequence learning task. Anodal transcranial direct current stimulation (tDCS) over the right or left dorsolateral PFC (DLPFC) was applied during the training in order to modify learning-related cortical plasticity in the targeted brain regions by increasing neural excitability. Performance was tested during and immediately after the stimulation, 2-hour and 24-hour later. We found that the anodal tDCS over the right DLPFC led to enhanced learning performance both after the 2-hour and 24-hour retention periods, suggesting the causal role of this area in statistical learning. In contrast, we did not find any effect of left DLPFC stimulation on learning. These results highlight the role of the right fronto-striatal network in statistical learning and its consolidation

    Characterizing the shared signals of face familiarity: long-term acquaintance, voluntary control, and concealed knowledge

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    In a recent study using cross-experiment multivariate classification of EEG patterns, we found evidence for a shared familiarity signal for faces, patterns of neural activity that successfully separate trials for familiar and unfamiliar faces across participants and modes of familiarization. Here, our aim was to expand upon this research to further characterize the spatio-temporal properties of this signal. By utilizing the information content present for incidental exposure to personally familiar and unfamiliar faces, we tested how the information content in the neural signal unfolds over time under different task demands – giving truthful or deceptive responses to photographs of genuinely familiar and unfamiliar individuals. For this goal, we re-analyzed data from two previously published experiments using within-experiment leave-one-subject-out and cross-experiment classification of face familiarity. We observed that the general face familiarity signal, consistent with its previously described spatio-temporal properties, is present for long-term personally familiar faces under passive viewing, as well as for acknowledged and concealed familiarity responses. Also, central-posterior regions contain information related to deception. We propose that signals in the 200–400 ms window are modulated by top-down task-related anticipation, while the patterns in the 400–600 ms window are influenced by conscious effort to deceive. To our knowledge, this is the first report describing the representational dynamics of concealed knowledge for faces, using time-resolved multivariate classification
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