- Poster presentation
- Open Access
Object-based biasing for attentional control of gaze: a comparison of biologically plausible mechanisms
© Cope et al; licensee BioMed Central Ltd. 2009
- Published: 13 July 2009
- Visual Search
- Visual Search Task
- Dorsal Stream
- Ventral Stream
- Feedback Model
In the visual system, attending to important objects in the visual field relies on the transfer of top-down, object-based task information to the spatially organised areas of cortex. How this occurs and the method by which this information can influence the dorsal stream and redirect gaze are not well understood. Current models of the ventral stream mostly focus on the feed-forward mechanisms involved and current feedback models do not seem to address the issue of object-space binding in a comprehensive and plausible manner.
We investigated these questions using the following modeling framework. A bidirectional, ventral stream object recognition hierarchy up to anterior inferior temporal cortex (AIT) from primary visual cortex (V1) and a model of dorsal stream to frontal eye fields (FEF) with our previously developed oculomotor system . Selection is performed in both the object-based mapping of AIT  and the spatial mapping of FEF  by basal ganglia loops . Modeling of the ventral stream consists of a hierarchy of increasingly spatially invariant cortical areas linked by both feed-forward excitatory and feedback connections. Within each receptive field, there is a competition to represent the strongest and thus most likely representation for that region, which can be biased by the feedback from higher visual areas. Three models of feedback attention mechanism were tested: additive feedback, shunting (multiplicative) feedback and a shunt "gating" of feedback by feed-forward. The model was tested using a simple visual world (colored "flags") that nevertheless challenged all the main competencies being investigated. Performance was measured by (i) eliciting saccadic "behavior" in simulated visual search with different numbers of distractors, and (ii) target segmentation in cluttered scenes within a fixed time window.
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