The brain visual cortex and oscillatory neural networks

THE BRAIN VISUAL CORTEX AND OSCILLATORY NEURAL NETWORKS

1. Introduction

1.1 Traditional Methods of Visual Image Processing. Shortcomings.

1.2 Neuromorphic Methods. Advantages.

1.3 Visual Image segmentation Task: Posing of the Problem.

2. The Brain Visual System: Brief Neurophysiological Data.

2.1 The Visual Pathway: Retina, LGN, the Visual Cortex (VC).

2.2 Main Propetrties of Primary Visual Cortex: RFs, Columns, Connections.

2.3 The Role of Synchronized Oscillations in VC and in the Other Brain Structures. Experiments. Associative Binding.

2.4 Some Other Features of the Brain Visual System.

3. Models of VC

3.1 Different Levels of Modelling. Neural Oscillator.

3.2 Models, Based on Networks of Spiking Neurons.

3.3 Oscillatory Network Models.

3.4 The Model under Development: Tunable Oscillatory Network with Self-organized Dynamical Connections and Synchronization-Based Performance.

4. Method of Visual Image Segmentation Based on Cluster Synchronization of Oscillatory Network.

4.1 Reduced Network, Obtained from the Oscillatory Model of VC.

4.2 Method of Adaptation of Connections. Successive Cluster Synchronization of the Network.

4.3 Computer Realization of the Method. Experiments.

4.4 Advantages of the Algorithm. Futher Perspectives.

5. Concluding Remarks. Abilities of Neuromorphic Models.

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