Abstract

Journal Special Issue on Computational Neuroscience Meeting CNS 2013

Presented is further development of the architecture presented in [1] where a top-down feature-based and spatial attention have been incorporated in a large scale visual module and novelty and familiarity detectors based on the model presented in [2]. These have been developed in the perceptual (visual and auditory) and motor modalities. In addition to the novelty/familiarity detection shown in [2, 3], the architecture is able to partially recognise familiar features in each perceptual modality, and furthermore in a distributed fashion activate associated familiar features from one perceptual modality to another and/or to the motor programmes and affordances. The architecture is implemented on a mobile robot operating in a dynamic environment. The proposed distributed multi-modal familiarity detection integrated in the architecture improves the recognition and action performance in a noisy environment, as well as contributing to the multi-modal association and learning of novel objects and actions.