منابع مشابه
Temporal asynchrony and spatial perception
Collinear facilitation is an enhancement in the visibility of a target by laterally placed iso-oriented flankers in a collinear (COL) configuration. Iso-oriented flankers placed in a non-collinear configuration (side-by-side, SBS) produce less facilitation. Surprisingly, presentation of both configurations simultaneously (ISO-CROSS) abolishes the facilitation rather than increases it - a phenom...
متن کاملSpatial displacement, but not temporal asynchrony, destroys figural binding
What are the elementary features that the brain uses to bind spatially distinct parts in a visual scene into an unitary percept of an "object"? The Gestalt psychologists emphasized the extent to which motion, colour, luminance or spatial arrangement contribute towards object formation. Little is known about the role of time per se, rather than motion, in constituting an object. In particular, d...
متن کاملElectrophysiological correlates of individual differences in perception of audiovisual temporal asynchrony.
Sensitivity to the temporal relationship between auditory and visual stimuli is key to efficient audiovisual integration. However, even adults vary greatly in their ability to detect audiovisual temporal asynchrony. What underlies this variability is currently unknown. We recorded event-related potentials (ERPs) while participants performed a simultaneity judgment task on a range of audiovisual...
متن کاملRecalibration of temporal order perception by exposure to audio-visual asynchrony.
The perception of simultaneity between auditory and visual information is of crucial importance for maintaining a coordinated representation of a multisensory event. Here we show that the perceptual system is able to adaptively recalibrate itself to audio-visual temporal asynchronies. Participants were exposed to a train of sounds and light flashes with a constant time lag ranging from -200 (so...
متن کاملAn Artificial Intelligence Model that Combines Spatial and Temporal Perception
This paper proposes a continuous-time machine learning model that learns the chronological relationships and the intervals between events, stores and organises the learnt knowledge in different levels of abstraction in a network, and makes predictions about future events. The acquired knowledge is represented in a categorisation-like manner, in which events are categorised into categories of di...
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ژورنال
عنوان ژورنال: Scientific Reports
سال: 2016
ISSN: 2045-2322
DOI: 10.1038/srep30413