A Neurodynamic Model of Feature-Based Spatial Selection.

Mateja Marić,Dražen Domijan

doi:10.3389/fpsyg.2018.00417

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.

Highlights

In the literature on visual attention, significant progress has been made in characterizing the principles of selection
We have proposed a new model of the WTA network that can simultaneously select multiple spatial locations based on a shared feature value
We have demonstrated how the feature-based WTA network achieves spatial selection of all locations that are occupied by the same feature value without suffering from capacity limitations

Summary

Introduction

In the literature on visual attention, significant progress has been made in characterizing the principles of selection. Visual attention can be allocated flexibly to a circumscribed region of space, the whole object or feature dimensions such as color and orientation (Nobre and Kastner, 2014). Early work suggested that a restricted circular region of space is a representational format of attentional selection. Posner (1980) proposed that attention operates like a spotlight that highlights a single circular region of space with a fixed radius. An extension of this proposal, which is called the zoomlens model, suggests that the spotlight of attention can change its radius depending on the spatial resolution that one wants to achieve (Eriksen and St. James, 1986). If high resolution is required, the spotlight can be narrowed to capture details in the selected region, whereas the radius of the spotlight can be widened when a lower resolution is sufficient

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Discussion

Conclusion