Biomedical subjects
Publications and source records attributed to I Biederman.
When a briefly presented real-world scene was jumbled, the accuracy of identifying a single, cued object was less than that when the scene was coherent. Jumbling remained an effective variable even when the subject knew where to look and what to look for. Thus an object's meaningful context may affect the course of perceptual recognition and not just peripheral scanning or memory.
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We present a prototype of a recently proposed two stage model of the entorhinal-hippocampal loop. Our aim is to form a general computational model of the sensory neocortex. The model--grounded on pure information theoretic principles--accounts for the most characteristic features of long-term memory (LTM), performs bottom-up novelty detection, and supports noise filtering. Noise filtering can also serve to correct the temporal ordering of information processing. Surprisingly, as we examine the temporal characteristics of the model, the emergent dynamics can be interpreted as perceptual priming, a fundamental type of implicit memory. In the model's framework, computational results support the hypothesis of a strong correlation between perceptual priming and repetition suppression and this correlation is a direct consequence of the temporal ordering in forming the LTM. We also argue that our prototype offers a relatively simple and coherent explanation of priming and its relation to a general model of information processing by the brain.