Amodal completion of partly occluded figures is analyzed as natural computation. Here amodal completion is shown to consist of four subproblems: representation, parsing, correspondence, and interpolation. Second, each problem is shown to be basically solvable on the basis of the generic-viewpoint assumption. It is also argued that the interpolation problem might be the key problem because of mutual interdependence among the subproblems. Third, a theory is described for the interpolation problem, in which the generic-viewpoint assumption and the curvature-consistency assumption are presumed. The generic-viewpoint assumption entails that the orientation and the curvature should not change at the point of occlusion. The curvature-consistency assumption entails that the hidden contour should have the minimum number of inflections to maintain continuity in orientation and curvature. The shape of the interpolated contour represented qualitatively in terms of the number of inflections can uniquely be determined when the location of the terminators and local orientation and curvature of the visible contours at the terminators are given. Fourth, it is shown in an instant psychophysics that the theory is highly consistent with human performance.

A novel kind of depth-spreading effect which should be distinguished in various aspects from the known interpolation, averaging, or ‘filling-in’ phenomena is reported. The demonstrations and experiments suggest that depth from an uncrossed disparity can be extrapolated from, not just interpolated between, illusory or real contours to form perceptually a background surface. In addition, the form of the illusory contour itself could be drastically changed in configuration and sharpness, contingently with perceptual background-surface formation. No such effects of surface and contour formation were observed in the crossed disparity case. Because the illusory contours were enhanced and perceived as illusory ‘occluding contours’, these effects may be closely related to the ‘occlusion constraints’ in the real world.

Magneto/electroencephalography (M/EEG) studies of dreaming are an essential paradigm in the investigation of neurocognitive processes of human consciousness during sleep, but they are limited by the number of observations that can be collected per study. Dream research also involves substantial methodological and conceptual variability, which poses problems for the integration of results. To address these issues, here we present the DREAM database—an expanding collection of standardized datasets on human sleep M/EEG combined with dream report data—with an initial release comprising 20 datasets, 505 participants, and 2643 awakenings. Each awakening consists, at minimum, of sleep M/EEG ( ≥ 20 s, ≥100 Hz, ≥2 electrodes) up to the time of waking and a standardized dream report classification of the subject’s experience during sleep. We observed that reports of conscious experiences can be predicted with objective features extracted from EEG recordings in both Rapid Eye Movement (REM) and non-REM (NREM) sleep. We also provide several examples of analyses, showcasing the database’s high potential in paving the way for new research questions at a scale beyond the capacity of any single research group.

Understanding the neural mechanisms underlying speech production has a number of potential practical applications. Speech production involves multiple feedback loops. An audio-vocal monitoring system plays an important role in speech production, based on auditory feedback about the speaker’s own voice. Here we investigated the mu-rhythm activity associated with speech production by examining event-related desynchronization and synchronization in conditions of delayed auditory feedback (DAF) and noise feedback (Lombard). In Experiment 1, we confirmed that the mu-rhythms were detectable for a conventional finger-tapping task, and vocalization. In Experiment 2, we examined the mu-rhythms for imagined speech production. We tested whether the same motor-related mu-rhythm activity was exhibited while participants listened to their own voice, and while reading. The mu-rhythms were observed for overt vocalization and covert reading, while listening to simulated auditory feedback of the participants’ own voice reading text. In addition, we found that the mu-rhythm associated with listening was boosted and attenuated under the DAF and Lombard conditions, respectively. This is consistent with the notion that auditory feedback is important for the audio-vocal monitoring system in speech production. This paradigm may help clarify the way in which auditory feedback supports motor planning, as indexed by the motor-related mu-rhythm.