Visual-Spatial Processingdoi:10.1007/978-0-387-79948-3_4578Spatial ProcessingSpringer New YorkEncyclopedia of Clinical Neuropsychology
Visual processingis a core cognitive element of sensory and consumer science. Consumers visually attend to food types, packaging, label design, advertisements, supermarket shelves, food menus, and other visible information. During the past decade, sensory and consumer science have used eye tracking to...
In their model, the cortical visual system is anatomically and functionally subdivided into the ventral and dorsal processing pathways or streams (see Fig. 17.1). The ventral stream is dominant for processing information about patterns and objects, while the dorsal stream mediates spatial processing ...
We took advantage of a spatial alignment effect paradigm, which typically refers to a decrease of reaction times when subjects perform an action (e.g., a reach-to-grasp pantomime) congruent with that afforded by a presented object. To systematically examine peripersonal space mapping, we ...
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Data processing in biomedical imaging domain is complex: many steps of registration (temporal, spatial) and reconciliation are required to get readable images, and even more steps to analyze them. Obviously, biomedical PLM users cannot set up processing provenance by hand, neither analyze it at a...
in order to describe the slow modulation of the bifurcating patterns under the effect of spatial periodic forcing due to the long-range connections. there are, however, some experimental observations which suggest that in fact, due to synaptic plasticity, the periods of the pinwheel lattice and of...
(1) Soft spatial attention: Soft spatial attention is used to map the output 𝐗CNN𝑖XiCNN of the shared feature extraction module into K attention feature maps. A 1 × 1 convolution is first used to perform a convolution operation with 𝐗CNN𝑖XiCNN and generate K attention mask maps...
These signs determine the spatial symmetry—the subgroup K that fixes every point on the periodic orbit. From this we can read off the sign pattern of the corresponding critical eigenvector. Changes of sign in entries of the critical eigenvector in pairs ± u or ± v correspond to relative ...
processing stage together with convolutional neural networks that helps to extract some of the distinctive spectral features, which are more predominant in the sub band levels of the image in addition to the spatial, semantic as well as channel details. This helps to include more finer details of...