T2 - Center for Neural Basis of Cognition
... The spatial representation of an attended location is remapped when the eyes move. Remapping is initiated by a corollary discharge of the eye movement command. Remapping produces a representation that is oculocentric: a location is represented in the coordinates of the movement needed to acquire the ...
... The spatial representation of an attended location is remapped when the eyes move. Remapping is initiated by a corollary discharge of the eye movement command. Remapping produces a representation that is oculocentric: a location is represented in the coordinates of the movement needed to acquire the ...
Depth perception by the active observer
... of the visual perception of depth. Although sources of 3D information are available on our 2D retinas, we can obtain much richer knowledge of the third dimension by coordinating the gaze directions of the two eyes, by moving the head to produce parallax, by walking to get a different view of a scene ...
... of the visual perception of depth. Although sources of 3D information are available on our 2D retinas, we can obtain much richer knowledge of the third dimension by coordinating the gaze directions of the two eyes, by moving the head to produce parallax, by walking to get a different view of a scene ...
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... the model consists of 15 areas each modelled as a spiking associative memory of 400 neurons. As shown in Figure 8 the language component of the model can roughly be divided into three parts. (1) Primary cortical auditory areas A1,A2, and A3: First auditory input is represented in area A1 by primary ...
... the model consists of 15 areas each modelled as a spiking associative memory of 400 neurons. As shown in Figure 8 the language component of the model can roughly be divided into three parts. (1) Primary cortical auditory areas A1,A2, and A3: First auditory input is represented in area A1 by primary ...
Visual Fields
... Although there are many ways to measure visual field function, we will concentrate our efforts from this point forward on automated perimetry because of its widespread use in “Visual Fields” 2 ...
... Although there are many ways to measure visual field function, we will concentrate our efforts from this point forward on automated perimetry because of its widespread use in “Visual Fields” 2 ...
Background Presentation
... • Attention is the ability to select objects of interest from the surrounding environment • A reliable measure of attention is eye movement during object (target) selection • Early studies show that there are specific brain regions that are involved in the process of target selection – Superior Coll ...
... • Attention is the ability to select objects of interest from the surrounding environment • A reliable measure of attention is eye movement during object (target) selection • Early studies show that there are specific brain regions that are involved in the process of target selection – Superior Coll ...
Modeling Visual Cognition
... Visual identification of stimuli is achieved through a series of processing steps, beginning with early sensory processing in the retina and continuing in the lateral geniculate nuclei of the thalamus and early visual areas in the occipital cortex (e.g., Wandell, 1995). During these early stages, vi ...
... Visual identification of stimuli is achieved through a series of processing steps, beginning with early sensory processing in the retina and continuing in the lateral geniculate nuclei of the thalamus and early visual areas in the occipital cortex (e.g., Wandell, 1995). During these early stages, vi ...
A Committee of Neural Networks for Traffic Sign Classification
... HE most successful hierarchical visual object recognition systems extract localized features from input images, convolving image patches with filters whose responses are then repeatedly sub-sampled and re-filtered, resulting in a deep feed-forward network architecture whose output feature vectors ar ...
... HE most successful hierarchical visual object recognition systems extract localized features from input images, convolving image patches with filters whose responses are then repeatedly sub-sampled and re-filtered, resulting in a deep feed-forward network architecture whose output feature vectors ar ...
