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• W2765197487 abstract "Computational Explorations of Split Architecture in Modeling Face and Object Recognition Janet Hui-wen Hsiao (jhsiao@cs.ucsd.edu) Garrison W. Cottrell (gary@ucsd.edu) Department of Computer Science and Engineering, University of California San Diego 9500 Gilman Drive #0404, La Jolla, CA 92093, USA Danke Shieh (danke@ucsd.edu) Department of Cognitive Science, University of California San Diego 9500 Gilman Drive #0515, La Jolla, CA 92093, USA reported in face perception. The classical experiment is to ask participants to judge the similarity between a face and chimeric faces made from the two left halves (left chimeric face) or the two right halves (right chimeric face) of the original face (from the viewer’s perspective; Figure 1). The results show that the left chimeric face is usually judged more similar to the original face than the right chimeric face, especially for highly familiar faces (Brady, Campbell, & Flaherty, 2005). Consistent with this result, other studies have argued for a right hemisphere (RH) bias in face perception (e.g., Rossion, Joyce, Cottrell, & Tarr, 2003). Nevertheless, it remains unclear how far the split effect extends. Although it has been shown that our visual system is organized as a set of hierarchically connected regions, and the receptive field sizes of the neurons increase by a factor of about 2.5 at each succeeding stage (Rolls, 2000), the initial trajectory of visual activation flow is a fast and widespread sweep and continues through iterations of feedback loops for further processing in the sensory area (Foxe & Simpson, 2002); hence, it is unclear yet whether the split influences high-level cognition. In visual word recognition, Hsiao and Shillcock (2005a) showed that this split effect can reach far enough to interact with sex differences in brain laterality for phonological processing. Thus, the split seems to influence high-level cognition. Abstract Anatomical evidence shows that our visual field is initially split along the vertical axis and contralaterally projected to different hemispheres. It remains unclear at which stage the split information converges. In the current study, we applied the Double Filtering by Frequency (DFF) theory (Ivry & Robertson, 1998) to modeling the visual split; the theory assumes a right hemisphere/low frequency bias. We compared three cognitive architectures with different timing of convergence and examined their cognitive plausibility to account for the left side bias effect in face perception observed in human data. We show that the early convergence model failed to show the left side bias effect. The left side bias effect was also observed in Greeble recognition. The modeling hence suggests that the convergence may take place at an intermediate or late stage, at least after information has been extracted/transformed separately in the two hemispheres; it also provides testable predictions about whether the left side bias effect may also be observed in (expertise-level) object recognition. Keywords: Connectionist modeling; hemispheric differences; split modeling. face recognition; Introduction Because of the partial decussation of optic nerves, our visual system is initially vertically split and the two visual hemifields are initially contralaterally projected to different hemispheres. A fundamental question in cognitive science is whether this initial split has any functional significance; that is, whether the effect of initial splitting can extend far enough to influence our cognition? A second question is at what stage does the information converge? Figure 1: Left chimeric, original, and right chimeric faces. A functional split Split modeling & timing of convergence Evidence from visual word recognition supports a functional split. The general finding is that the two hemispheres have contralateral influence on responses driven by the first and last halves of the stimuli, which are initially projected to different visual hemifields (e.g., Lavidor, Ellis, Shillcock, & Bland, 2001; Lavidor & Walsh, 2003; Hsiao & Shillcock, 2005a; Hsiao, Shillcock, & Lavidor, 2006). There is also evidence from face recognition supporting a functional split. For example, a left side bias effect has been frequently In order to address the splitting effects observed in visual word recognition, Shillcock and Monaghan (2001) proposed a split fovea model (Figure 2) and showed that some psychological phenomena in visual word recognition can be better accounted for by the split architecture, such as exterior letter effects in English word recognition and eye fixation behavior in reading English (Shillcock, Monaghan, & Ellison, 2000). Hsiao and Shillcock (2005b) further showed that the split and nonsplit architectures in modeling" @default.
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• W2765197487 date "2007-01-01" @default.
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• W2765197487 title "Computational Explorations of Split Architecture in Modeling Face and Object Recognition" @default.
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