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Fred H Hamker, Arnold Ziesche; Computational mechanisms of predictive remapping and visual stability. Journal of Vision 2011;11(11):523. doi: https://doi.org/10.1167/11.11.523.
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© ARVO (1962-2015); The Authors (2016-present)
Cells in many visual areas are retinotopically organized, i.e. their receptive fields (RFs) are fixed on the retina and thus shift when the eye moves. Thus, their input changes with each eye movement, posing the question of how we construct our subjective experience of a stable world. It has been proposed that predictive remapping could provide a potential solution (Duhamel et al., Science, 255, 90–92 1992; Melcher & Colby, Trends in Cog. Sci., 12, 466–473, 2008; Wurtz, Vis. Res., 48, 2070–2089, 2008). Predictive remapping refers to the observation that for some neurons RFs anticipate the eye movement and become responsive to stimuli which are presented in their future receptive field (FRF) already prior to saccade. Recent evidence from investigations in the frontal eye field suggests that the anticipatory updating is brought about by the corollary discharge (CD) to move the eyes (Sommer & Wurtz, Nature, 444, 374–377, 2006). However, at present it is unclear how CD could alter the RF profile. Moreover, there exists no clear theory let alone a computational model of how predictive remapping contributes to the subjective experience of visual stability. Based on a realistic systems neuroscience model of area LIP and using CD of eye displacement and proprioceptive eye position as inputs, we show that predictive remapping emerges within a model of coordinate transformation by means of the interaction of feedback and CD. Moreover, we demonstrate the influence of predictive remapping on visual stability as objectified by a suppression of saccadic displacement task (Deubel et al., Vis Res, 36, 985–996, 1996). The model predicts that an absent CD signal leads to a bias negative to saccade direction in SSD. Remapping introduces a feedback loop which stabilizes perisaccadic activity and thus leads to the typical increase in displacement detection threshold.
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