visual receptive field

visual receptive field

[¦vizh·ə·wəl ri¦sep·tiv ‚fēld]
(physiology)
That area of the retina within which stimulation with light or a light pattern causes a response in a particular receptor or neuron in the visual pathway.
McGraw-Hill Dictionary of Scientific & Technical Terms, 6E, Copyright © 2003 by The McGraw-Hill Companies, Inc.
References in periodicals archive ?
The visual responsiveness of each neuron was firstly evaluated moving a white luminous bar (3 cd/m) on the screen; this also allowed mapping the visual receptive field. Then, the neuronal activity was recorded with the optic flow paradigm described below.
It could be proposed that the phasic pattern would arise from the functional characteristics of the visual receptive fields. As already reported, the majority of PEc visual neurons have very large receptive fields usually extending over 30[degrees] with a broad directional selectivity [4, 27], with some of them showing a foveal-sparing receptive field with a robust response to both inward and outward directions [1].
A visual receptive field is the portion of the visual field that must be stimulated for a given neuron to fire.
This may lead to a more reliable selection regarding available parameters dedicated to the visual receptive field, with the primary goal of estimating a user's interest.
In order to analyze the perceiving mechanism, visual selective attention must be taken into consideration since a visual receptive field is comprised of different visual features that are added together and subsequently used for selection of objects.
The visual receptive field has originally been computed by a machine learning network, called the redial basis function (RBF) to estimate each parameter, which approximated a visual receptive field (e.g.
In order to compute eye gaze patterns related to a user's interest, a statistical learning algorithm has been incorporated to compute a visual receptive field so as to estimate interest [10][2].
The general setting of the problem of statistical learning is to estimate some function, which depends on an unknown distribution in a (probabilistic) visual receptive field, as previously explained.
After a visual neuron was found, the computer screen was moved to a location and height that aligned the center of the visual receptive field approximately at the center of the screen.
Treue, "Dynamic shifts of visual receptive fields in cortical area MT by spatial attention," Nature Neuroscience, vol.