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Relation between fixation disparity and the asymmetry between convergent and divergent disparity step responses

2007

Abstract The neural network model of Patel et al. [Patel, S. S., Jiang, B. C., & Ogmen, H. (2001). Vergence dynamics predict fixation disparity. Neural Computation, 13 (7), 1495–1525] predicts that fixation disparity, the vergence error for a stationary fusion stimulus, is the result of asymmetrical dynamic properties of disparity vergence mechanisms: faster (slower) convergent than divergent responses give rise to an eso (exo) fixation disparity, i.e., over-convergence (under-convergence) in stationary fixation. This hypothesis was tested in the present study with an inter-individual approach: in 16 subjects we estimated the vergence step response to a 1 deg disparity stimulus with a subje…

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