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D'Souza, P; Liu, S C; Hahnloser, R H R (2010). Perceptron learning rule derived from spike-frequency adaptation and spike-time-dependent plasticity. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 107(10):4722-4727.

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Abstract

It is widely believed that sensory and motor processing in the brain is based on simple computational primitives rooted in cellular and synaptic physiology. However, many gaps remain in our understanding of the connections between neural computations and biophysical properties of neurons. Here, we show that synaptic spike-time-dependent plasticity (STDP) combined with spike-frequency adaptation (SFA) in a single neuron together approximate the well-known perceptron learning rule. Our calculations and integrate-and-fire simulations reveal that delayed inputs to a neuron endowed with STDP and SFA precisely instruct neural responses to earlier arriving inputs. We demonstrate this mechanism on a developmental example of auditory map formation guided by visual inputs, as observed in the external nucleus of the inferior colliculus (ICX) of barn owls. The interplay of SFA and STDP in model ICX neurons precisely transfers the tuning curve from the visual modality onto the auditory modality, demonstrating a useful computation for multimodal and sensory-guided processing.

Citations

8 citations in Web of Science®
10 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
DDC:570 Life sciences; biology
Language:English
Date:1 March 2010
Deposited On:07 Mar 2011 08:42
Last Modified:27 Nov 2013 23:56
Publisher:National Academy of Sciences
Series Name:Proceedings of the National Academy of Sciences of the United States of America
Number of Pages:5
ISSN:0027-8424
Additional Information:Copyright: National Academy of Sciences USA
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:10.1073/pnas.0909394107

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