Abstract
The human mirror neuron system (MNS) is supposed to be involved in recognition of observed action sequences. However, it remains unclear how such a system could learn to recognise a large variety of action sequences. Here we investigated a neural network with mirror properties, the Recurrent Neural Network with Parametric Bias (RNNPB). We show that the network is capable of recognising noisy action sequences and that
it is capable of generalising from a few learnt examples. Such a mechanism may explain how the human brain is capable of dealing with an infinite variety of action sequences.
| Original language | English |
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| Title of host publication | ESANN'2009 proceedings : European Symposium on Artificial Neural Networks |
| Pages | 251-256 |
| Publication status | Published - 2009 |
| Event | 17th European Symposium on Artificial Neural Networks Computational Intelligence and Machine Learning (ESANN 2009) - Bruges, Belgium Duration: 22 Apr 2009 → 24 Apr 2009 Conference number: 17 |
Conference
| Conference | 17th European Symposium on Artificial Neural Networks Computational Intelligence and Machine Learning (ESANN 2009) |
|---|---|
| Abbreviated title | ESANN 2009 |
| Country/Territory | Belgium |
| City | Bruges |
| Period | 22/04/09 → 24/04/09 |
| Other | "Advances in Computational Intelligence and Learning" |