a neurodynamic model of feature-based spatial selection
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ID: 181102
2018
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Abstract
Huang and Pashler (2007) suggested that feature-based attention creates a special form of spatial representation, which is termed a Boolean map. It partitions the visual scene into two distinct and complementary regions: selected and not selected. Here, we developed a model of a recurrent competitive network that is capable of state-dependent computation. It selects multiple winning locations based on a joint top-down cue. We augmented a model of the WTA circuit that is based on linear-threshold units with two computational elements: dendritic non-linearity that acts on the excitatory units and activity-dependent modulation of synaptic transmission between excitatory and inhibitory units. Computer simulations showed that the proposed model could create a Boolean map in response to a featured cue and elaborate it using the logical operations of intersection and union. In addition, it was shown that in the absence of top-down guidance, the model is sensitive to bottom-up cues such as saliency and abrupt visual onset.
| Reference Key |
mari2018frontiersa
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|---|---|
| Authors | ;Mateja Marić;Dražen Domijan |
| Journal | accounts of chemical research |
| Year | 2018 |
| DOI |
10.3389/fpsyg.2018.00417
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| URL | |
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