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A Real-Time, Event Driven Neuromorphic System for Goal-Directed Attentional Selection

 

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Opened Access A Real-Time, Event Driven Neuromorphic System for Goal-Directed Attentional Selection
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Author: Gallupi, Francesco
Brohan, Kevin
Davidson, Simón
Serrano Gotarredona, Teresa
Pérez Carrasco, José Antonio
Linares Barranco, Bernabé
Furber, Steve
Department: Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones
Date: 2012
Published in: Lectures notes in computer science, 7664 (2), 226-233.
Document type: Article
Abstract: Computation with spiking neurons takes advantage of the abstraction of action potentials into streams of stereotypical events, which encode information through their timing. This approach both reduces power consumption and alleviates communication bottlenecks. A number of such spiking custom mixed-signal address event representation (AER) chips have been developed in recent years. In this paper, we present i) a flexible event-driven platform consisting of the integration of a visual AER sensor and the SpiNNaker system, a programmable massively parallel digital architecture oriented to the simulation of spiking neural networks; ii) the implementation of a neural network for feature-based attentional selection on this platform
Cite: Gallupi, F., Brohan, K., Davidson, S., Serrano Gotarredona, T., Pérez Carrasco, J.A., Linares Barranco, B. y Furber, S. (2012). A Real-Time, Event Driven Neuromorphic System for Goal-Directed Attentional Selection. Lectures notes in computer science, 7664 (2), 226-233.
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URI: https://hdl.handle.net/11441/79688

DOI: 10.1007/978-3-642-34481-7_28

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