Tracking smooth eye displacements in darkness: A model that integrates eye velocity commands.

G. Blohm^1,2,3, L.M. Optican⁴, P. Lefèvre^1,2,4

¹CESAME, Université catholique de Louvain, Louvain-la-Neuve, Belgium

²Laboratory of Neurophysiology, Université catholique de Louvain, Brussels, Belgium

³Centre for Vision Research, York University, Toronto, Ontario, Canada

⁴Laboratory of Sensorimotor Research, National Eye Institute, NIH, Bethesda, MD, USA

Contradictory results have been reported in the literature concerning the oculomotor system’s ability to keep track of smooth eye movements in darkness. Whereas some results indicated that saccades could not compensate for smooth eye displacements, others reported spatially correct memory guided saccades during smooth pursuit. Recently it has been proposed that those findings could be explained by the presence of a delay in the mechanism that keeps track of smooth eye displacements (Blohm et al. 2003, 2005).

Current saccadic models are unable to account for those findings. Here, we propose a model of the saccadic system that can explain the available experimental data. The novel part of this model consists of two alternative physiologically realistic neural mechanisms for a delayed integration of smooth eye velocity commands. The first hypothesized mechanism is based on an accumulation of the time during which the eyes moved at a certain velocity and is proposed to be compatible with the known physiology of the Lateral Intraparietal Cortex. The alternative hypothesis uses an eye velocity modulated neural activity displacement map and could be implemented in the Cerebellum. The read-out of both mechanisms provides an estimation of the smooth eye displacement. This signal is then used to update the spatial representation of a memorized target in retinotopic coordinates.

Both eye velocity integration mechanisms can estimate equally well the smooth eye displacement during a memory period of a previously presented target. Therefore, we fitted our model to two previously analyzed behavioral data sets (Blohm et al. 2003, 2005). In addition, we tested the model simulations on prior results from the literature and accurately predicted those previous findings. Thus, this model reconciles the initially contradictory reports from the literature.

Citation: Blohm G, Optican LM and Lefèvre P, "Tracking smooth eye displacements in darkness: A model that integrates eye velocity commands", 15th Annual Meeting of the Neural Control of Movement Society, Key Biscayne, Florida, USA, 2005