Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-41539
Indiveri, G; Stefanini, F; Chicca, E (2010). Spike-based learning with a generalized integrate and fire silicon neuron. In: 2010 IEEE International Symposium on Circuits and Systems (ISCAS 2010), Paris, FR, 30 May 2010 - 2 June 2010, 1951-1954.
Spike-based learning circuits have been typically used in conjunction with linear integrate-and-fire neurons. As
a new class of current-mode conductance-based silicon neurons has been recently developed, it is important to evaluate how the spike-based learning circuits perform, when interfaced to these new types of neuron circuits. Here, we describe a VLSI implementation of a current-mode conductance-based neuron, connected to synaptic circuits with spike-based learning capabilities. The conductance-based silicon neuron has built-in spike-frequency adaptation, refractory period mechanisms, and plasticity eligibility control circuits. The synaptic circuits exhibits realistic dynamics in the post-synaptic currents and comprise local spike-based learning circuits, controlled by the global post-synaptic eligibility circuits. We present experimental results which characterize the conductance-based neuron circuit properties and the spike-based learning circuits connected to it.
|Item Type:||Conference or Workshop Item (Lecture), refereed, original work|
|Communities & Collections:||07 Faculty of Science > Institute of Neuroinformatics|
|DDC:||570 Life sciences; biology|
|Event End Date:||2 June 2010|
|Deposited On:||12 Feb 2011 17:46|
|Last Modified:||11 Sep 2012 11:13|
|Publisher:||Institute of Electrical and Electronics Engineers Corporation (IEEE)|
|Series Name:||Proceedings of ... IEEE International Symposium on Circuits and Systems (ISCAS)|
|Related URLs:||http://www.iscas2010.org/ (Organisation)|
Scopus®. Citation Count: 11
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