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  • The information available through our senses is noisy, incomplete, and to varying degrees ambiguous. The perceptual system must create stable and reliable percepts out of this restricted information. It solves this perceptual inference problem by integrating memories of previous percepts and making predictions about the perceptual future. Using ambiguous figures and a new experimental approach, we studied whether generating predictions based on regularities in the past affects processing of the present and how this is done. Event-related potentials (ERPs) were measured to investigate whether a highly regular temporal context of either ambiguous or unambiguous stimulus variants differently affects processing of a current stimulus and/or task execution. Further, we tested whether symbolic announcements about the immediate perceptual future can replace the past experience of regularities as a source for making predictions. Both ERP and reaction time varied as a function of stimulus ambiguity in the temporal context of a present stimulus. No such effects were found with symbolic announcements. Our results indicate that predictions about the future automatically alter processing of the present, even if the predictions are irrelevant for the present percept and task. However, direct experiences of past regularities are necessary for predicting the future whereas symbolic information about the future is not sufficient.

  • During the observation of an ambiguous figure our perception alternates between mutually exclusive interpretations, although the stimulus itself remains unchanged. The rate of these endogenous reversals has been discussed as reflecting basic aspects of endogenous brain dynamics. Recent evidence indicates that extensive meditation practice evokes long-term functional and anatomic changes in the brain, also affecting the endogenous brain dynamics. As one of several consequences the rate of perceptual reversals during ambiguous figure perception decreases. In the present study we compared EEG-correlates of endogenous reversals of ambiguous figures between meditators and non-meditating controls in order to better understand timing and brain locations of this altered endogenous brain dynamics. A well-established EEG paradigm was used to measure the neural processes underlying endogenous perceptual reversals of ambiguous figures with high temporal precision. We compared reversal-related ERPs between experienced meditators and non-meditating controls. For both groups we found highly similar chains of reversal-related ERPs, starting early in visual areas, therewith replicating previous findings from the literature. Meditators, however, showed an additional frontal ERP signature already 160 ms after stimulus onset (Frontal Negativity). We interpret the additional, meditation-specific ERP results as evidence that extensive meditation practice provides control of frontal brain areas over early sensory processing steps. This may allow meditators to overcome phylogenetically evolved perceptual and attentional processing automatisms.

  • The worldwide fascination of da Vinci's Mona Lisa has been dedicated to the emotional ambiguity of her face expression. In the present study we manipulated Mona Lisa's mouth curvature as one potential source of ambiguity and studied how a range of happier and sadder face variants influences perception. In two experimental conditions we presented different stimulus ranges with different step sizes between stimuli along the happy-sad axis of emotional face expressions. Stimuli were presented in random order and participants indicated the perceived emotional face expression (first task) and the confidence of their response (second task). The probability of responding 'happy' to the original Mona Lisa was close to 100%. Furthermore, in both conditions the perceived happiness of Mona Lisa variants described sigmoidal functions of the mouth curvature. Participants' confidence was weakest around the sigmoidal inflection points. Remarkably, the sigmoidal functions, as well as confidence values and reaction times, differed significantly between experimental conditions. Finally, participants responded generally faster to happy than to sad faces. Overall, the original Mona Lisa seems to be less ambiguous than expected. However, perception of and reaction to the emotional face content is relative and strongly depends on the used stimulus range.

  • Temporally distributed ("spaced") learning can be twice as efficient as massed learning. This "spacing effect" occurs with a broad spectrum of learning materials, with humans of different ages, with non-human vertebrates and also invertebrates. This indicates, that very basic learning mechanisms are at work ("generality"). Although most studies so far focused on very narrow spacing interval ranges, there is some evidence for a non-monotonic behavior of this "spacing effect" ("nonlinearity") with optimal spacing intervals at different time scales. In the current study we focused both the nonlinearity aspect by using a broad range of spacing intervals and the generality aspect by using very different learning/practice domains: Participants learned German-Japanese word pairs and performed visual acuity tests. For each of six groups we used a different spacing interval between learning/practice units from 7 min to 24 h in logarithmic steps. Memory retention was studied in three consecutive final tests, one, seven and 28 days after the final learning unit. For both the vocabulary learning and visual acuity performance we found a highly significant effect of the factor spacing interval on the final test performance. In the 12 h-spacing-group about 85% of the learned words stayed in memory and nearly all of the visual acuity gain was preserved. In the 24 h-spacing-group, in contrast, only about 33% of the learned words were retained and the visual acuity gain dropped to zero. The very similar patterns of results from the two very different learning/practice domains point to similar underlying mechanisms. Further, our results indicate spacing in the range of 12 hours as optimal. A second peak may be around a spacing interval of 20 min but here the data are less clear. We discuss relations between our results and basic learning at the neuronal level.

Last update from database: 04.06.25, 15:35 (UTC)