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The surrounding modulation, hypothesized to be the basis of visual feature integration and figure-ground segregation, has drawn much attention in the field of neuroscience and engineering.
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This allowed us to target the sum of visual features that formed the necessary basis to successfully apply one of the two schemas (namely color and position).
This revealed perirhinal activation when the task required the integration of visual features into a view-invariant representation but not when it could be accomplished on the basis of simple features (e.g., color and shape).
We propose an approach to manage data associations in the context of visual features.
Among variety of visual features, color information is the most frequently used visual characteristic.
For the extraction of visual features, our visual saliency model uses biologically plausible spatio-temporal 3D Gabor filters.
In early visual areas, neurons representing nearby visual locations need to combine information to aid the identification of visual features.
We propose that (1) hunting responses are evoked by visual objects characterized by conjunctions of visual features.
By systematically varying four features of the visual stimuli, we found that prey-catching behavior was selectively evoked by specific conjunctions of visual features.
In summary, tectal NLMS neurons represent feature detectors that are selective for the conjunction of visual features that define optimal prey-like visual objects.
Are body parts individuated on the basis of their visual features like geons (Andersen, 1978; Biederman, 1987; Brown, 1976)?
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CEO of Professional Science Editing for Scientists @ prosciediting.com