An oscillatory neural model of multiple object tracking (Kazanovich and Borisyuk 2006)

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An oscillatory neural network model of multiple object tracking is described. The model works with a set of identical visual objects moving around the screen. At the initial stage, the model selects into the focus of attention a subset of objects initially marked as targets. Other objects are used as distractors. The model aims to preserve the initial separation between targets and distractors while objects are moving. This is achieved by a proper interplay of synchronizing and desynchronizing interactions in a multilayer network, where each layer is responsible for tracking a single target. The results of the model simulation are presented and compared with experimental data. In agreement with experimental evidence, simulations with a larger number of targets have shown higher error rates. Also, the functioning of the model in the case of temporarily overlapping objects is presented.
1 . Kazanovich Y, Borisyuk R (2006) An oscillatory neural model of multiple object tracking. Neural Comput 18:1413-40 [PubMed]
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Model Type: Connectionist Network;
Brain Region(s)/Organism:
Cell Type(s):
Gap Junctions:
Simulation Environment: C or C++ program;
Model Concept(s): Oscillations; Spatio-temporal Activity Patterns; Simplified Models;
Implementer(s): Kazanovich, Yakov [yakov_k at]; Borisyuk, Roman [rborisyuk at];
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class CMainFrame : public CFrameWnd
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// Overrides
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// Implementation
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protected:  // control bar embedded members
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