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Behavior and neural basis of near-optimal visual search

Ma, Wei Ji
Navalpakkam, Vidhya
Beck, Jeffrey M
Berg, Ronald van den
Published in Nature Neuroscience. 2011, vol. 14, no. 6, p. 783-90
Abstract The ability to search efficiently for a target in a cluttered environment is one of the most remarkable functions of the nervous system. This task is difficult under natural circumstances, as the reliability of sensory information can vary greatly across space and time and is typically a priori unknown to the observer. In contrast, visual-search experiments commonly use stimuli of equal and known reliability. In a target detection task, we randomly assigned high or low reliability to each item on a trial-by-trial basis. An optimal observer would weight the observations by their trial-to-trial reliability and combine them using a specific nonlinear integration rule. We found that humans were near-optimal, regardless of whether distractors were homogeneous or heterogeneous and whether reliability was manipulated through contrast or shape. We present a neural-network implementation of near-optimal visual search based on probabilistic population coding. The network matched human performance.
Keywords Discrimination (Psychology)HumansModels, NeurologicalObservation/methodsPhotic Stimulation/methodsReproducibility of ResultsVisual Perception
PMID: 21552276
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Research group Groupe Alexandre Pouget (938)
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MA, Wei Ji et al. Behavior and neural basis of near-optimal visual search. In: Nature Neuroscience, 2011, vol. 14, n° 6, p. 783-90. doi: 10.1038/nn.2814 https://archive-ouverte.unige.ch/unige:25811

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Deposited on : 2013-01-22

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