A State Space Model for Spatial Updating of Remembered Visual Targets during Eye Movements.

ABSTRACT: In the oculomotor system, spatial updating is the ability to aim a saccade toward a remembered visual target position despite intervening eye movements. Although this has been the subject of extensive experimental investigation, there is still no unifying theoretical framework to explain the neural mechanism for this phenomenon, and how it influences visual signals in the brain. Here, we propose a unified state-space model (SSM) to account for the dynamics of spatial updating during two types of eye movement; saccades and smooth pursuit. Our proposed model is a non-linear SSM and implemented through a recurrent radial-basis-function neural network in a dual Extended Kalman filter (EKF) structure. The model parameters and internal states (remembered target position) are estimated sequential

SUBMITTER: Mohsenzadeh Y 

PROVIDER: S-EPMC4867689 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature