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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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.
|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||07 Faculty of Science > Institute of Neuroinformatics|
|Dewey Decimal Classification:||570 Life sciences; biology|
|Date:||1 March 2010|
|Deposited On:||07 Mar 2011 08:42|
|Last Modified:||05 Apr 2016 14:51|
|Publisher:||National Academy of Sciences|
|Series Name:||Proceedings of the National Academy of Sciences of the United States of America|
|Number of Pages:||5|
|Additional Information:||Copyright: National Academy of Sciences USA|
|Free access at:||Publisher DOI. An embargo period may apply.|
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