Show Reference: "Learning the Optimal Control of Coordinated Eye and Head Movements"

Learning the Optimal Control of Coordinated Eye and Head Movements PLoS Comput Biol, Vol. 7, No. 11. (3 November 2011), e1002253, doi:10.1371/journal.pcbi.1002253 by Sohrab Saeb, Cornelius Weber, Jochen Triesch
    abstract = {Various optimality principles have been proposed to explain the characteristics of coordinated eye and head movements during visual orienting behavior. At the same time, researchers have suggested several neural models to underly the generation of saccades, but these do not include online learning as a mechanism of optimization. Here, we suggest an open-loop neural controller with a local adaptation mechanism that minimizes a proposed cost function. Simulations show that the characteristics of coordinated eye and head movements generated by this model match the experimental data in many aspects, including the relationship between amplitude, duration and peak velocity in head-restrained and the relative contribution of eye and head to the total gaze shift in head-free conditions. Our model is a first step towards bringing together an optimality principle and an incremental local learning mechanism into a unified control scheme for coordinated eye and head movements. Human beings and many other species redirect their gaze towards targets of interest through rapid gaze shifts known as saccades. These are made approximately three to four times every second, and larger saccades result from fast and concurrent movement of the animal's eyes and head. Experimental studies have revealed that during saccades, the motor system follows certain principles such as respecting a specific relationship between the relative contribution of eye and head motor systems to total gaze shift. Various researchers have hypothesized that these principles are implications of some optimality criteria in the brain, but it remains unclear how the brain can learn such an optimal behavior. We propose a new model that uses a plausible learning mechanism to satisfy an optimality criterion. We show that after learning, the model is able to reproduce motor behavior with biologically plausible properties. In addition, it predicts the nature of the learning signals. Further experimental research is necessary to test the validity of our model.},
    author = {Saeb, Sohrab and Weber, Cornelius and Triesch, Jochen},
    day = {3},
    doi = {10.1371/journal.pcbi.1002253},
    journal = {PLoS Comput Biol},
    keywords = {behaviour, computational, control, development, eye-movements, learning, math, model, motor, sc, visual},
    month = nov,
    number = {11},
    pages = {e1002253+},
    posted-at = {2012-09-17 16:45:43},
    priority = {2},
    publisher = {Public Library of Science},
    title = {Learning the Optimal Control of Coordinated Eye and Head Movements},
    url = {},
    volume = {7},
    year = {2011}

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