title: The coarse-to-fine hypothesis revisited: evidence from neuro-computational modeling.
abstract: The human perceptual system seems to be driven by a coarse-to-fine integration of visual information. Different results have shown a faster integration of low-spatial frequency compared with high-spatial frequency (HSF) information, starting at early retinal processes. The difference in spatial scale decomposition remains throughout the lateral geniculate nucleus (Hubel & Wiesel, 1977) and V1 (Tootell, Silverman, & De Valois, 1981). During the last decade, a debate has emerged concerning the origin of the coarse-to-fine integration. Is it a constant, perceptually driven integration (Parker et al., 1992 and Parker et al., 1996)? Instead, the flexible use hypothesis suggests that different spatial frequency channels could be enhanced depending on the requirement of the task for high-level cognitive processes like categorization (Oliva and Schyns, 1997 and Schyns and Oliva, 1999). In two connectionist simulations, we have shown that global categorization performance could actually be better performed with HSF information when the amount of information is normalized across the different spatial frequency channels. Those results suggest that high-level requirement alone could not explain the coarse-to-fine bias toward LSF information. A hypothesis is proposed concerning the possible implication of the amount of data provided by different spatial frequency channel that might provide the perceptual bias toward LSF information.
authors.affiliation: Cognitive Science Department, Université de Liège, Belgium. mmermillod@ulg.ac.be
authors.forename: Martial
authors.initials: M
authors.lastname: Mermillod
authors.forename: Nathalie
authors.initials: N
authors.lastname: Guyader
authors.forename: Alan
authors.initials: A
authors.lastname: Chauvin
mesh_terms: D000465:Algorithms; D001245:Association Learning; D001288:Attention / Q000502:physiology*; D002540:Cerebral Cortex / Q000502:physiology; D004193:Discrimination Learning / Q000502:physiology*; D005829:Geniculate Bodies / Q000502:physiology*; D006801:Humans; D008432:Mathematical Computing; D016571:Neural Networks, Computer; D009949:Orientation / Q000502:physiology; D010364:Pattern Recognition, Visual / Q000502:physiology*; D012160:Retina / Q000502:physiology*; D012858:Size Perception / Q000502:physiology*; D014793:Visual Cortex / Q000502:physiology*; D014795:Visual Pathways / Q000502:physiology