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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Published in | 2010 IEEE International Symposium on Circuits and Systems (ISCAS) pp. 2789 - 2792 |
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Main Authors | , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.05.2010
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Subjects | |
Online Access | Get full text |
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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. |
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ISBN: | 1424453089 9781424453085 |
ISSN: | 0271-4302 2158-1525 |
DOI: | 10.1109/ISCAS.2010.5537007 |