Scene memory and spatial inhibition in visual search
| Autor: | Raul Grieben, Sebastian Schneegans, Jonas Lins, Jan Tekulve, Gregor Schöner, Stephan K. U. Zibner |
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| Přispěvatelé: | Grieben, Raul [0000-0003-1718-7679], Apollo - University of Cambridge Repository |
| Rok vydání: | 2020 |
| Předmět: |
Adult
Male Linguistics and Language Adolescent Computer science Speech recognition Models Neurological Experimental and Cognitive Psychology Spatial memory 050105 experimental psychology Language and Linguistics Young Adult 03 medical and health sciences 0302 clinical medicine Humans Attention 0501 psychology and cognitive sciences Set (psychology) Visual working memory TRACE (psycholinguistics) Visual search Working memory 05 social sciences Process (computing) Sensory Systems Inhibition Psychological Neural network modeling Memory Short-Term 40 Years of Feature Integration: Special Issue in Memory of Anne Treisman Feature (computer vision) Visual Perception Female Cues Photic Stimulation 030217 neurology & neurosurgery Change detection |
| Zdroj: | Attention, Perception & Psychophysics |
| ISSN: | 1943-393X 1943-3921 |
| DOI: | 10.3758/s13414-019-01898-y |
| Popis: | Any object-oriented action requires that the object be first brought into the attentional foreground, often through visual search. Outside the laboratory, this would always take place in the presence of a scene representation acquired from ongoing visual exploration. The interaction of scene memory with visual search is still not completely understood. Feature integration theory (FIT) has shaped both research on visual search, emphasizing the scaling of search times with set size when searches entail feature conjunctions, and research on visual working memory through the change detection paradigm. Despite its neural motivation, there is no consistently neural process account of FIT in both its dimensions. We propose such an account that integrates (1) visual exploration and the building of scene memory, (2) the attentional detection of visual transients and the extraction of search cues, and (3) visual search itself. The model uses dynamic field theory in which networks of neural dynamic populations supporting stable activation states are coupled to generate sequences of processing steps. The neural architecture accounts for basic findings in visual search and proposes a concrete mechanism for the integration of working memory into the search process. In a behavioral experiment, we address the long-standing question of whether both the overall speed and the efficiency of visual search can be improved by scene memory. We find both effects and provide model fits of the behavioral results. In a second experiment, we show that the increase in efficiency is fragile, and trace that fragility to the resetting of spatial working memory. |
| Databáze: | OpenAIRE |
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