Article ID Journal Published Year Pages File Type
405629 Neural Networks 2009 11 Pages PDF
Abstract

Embodied action representation and action understanding are the first steps to understand what it means to communicate. We present a biologically plausible mechanism to the representation and the recognition of actions in a neural network with spiking neurons based on the learning mechanism of spike-timing-dependent plasticity (STDP). We show how grasping is represented through the multi-modal integration between the vision and tactile maps across multiple temporal scales. The network evolves into a small-world organization with scale-free dynamics promoting efficient inter-modal binding of the neural assemblies with accurate timing. Finally, it acquires the qualitative properties of the mirror neuron system to trigger an observed action performed by someone else.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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