State-dependent sensory processing in networks of VLSI spiking neurons

An increasing number of research groups develop dedicated hybrid analog/digital very large scale integration (VLSI) devices implementing hundreds of spiking neurons with bio-physically realistic dynamics. However, despite the significant progress in their design, there is still little insight in tra...

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Bibliographic Details
Published in2010 IEEE International Symposium on Circuits and Systems (ISCAS) pp. 2789 - 2792
Main Authors Neftci, E, Chicca, E, Cook, M, Indiveri, G, Douglas, R
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2010
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Summary:An increasing number of research groups develop dedicated hybrid analog/digital very large scale integration (VLSI) devices implementing hundreds of spiking neurons with bio-physically realistic dynamics. However, despite the significant progress in their design, there is still little insight in translating circuitry of neural assemblies into desired (non-trivial) function. In this work, we propose to use neural circuits implementing the soft Winner-Take-All (WTA) function. By showing that recurrently connected instances of them can have persistent activity states, which can be used as a form of working memory, we argue that such circuits can perform state-dependent computation. We demonstrate such a network in a distributed neuromorphic system consisting of two multi-neuron chips implementing soft WTA, stimulated by an event-based vision sensor. The resulting network is able to track and remember the position of a localized stimulus along a trajectory previously encoded in the system.
ISBN:1424453089
9781424453085
ISSN:0271-4302
2158-1525
DOI:10.1109/ISCAS.2010.5537007