Time-warp-invariant neuronal processing (Gutig & Sompolinsky 2009)


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Accession:154288
" ... Here, we report that time-warp-invariant neuronal processing can be subserved by the shunting action of synaptic conductances that automatically rescales the effective integration time of postsynaptic neurons. We propose a novel spike-based learning rule for synaptic conductances that adjusts the degree of synaptic shunting to the temporal processing requirements of a given task. Applying this general biophysical mechanism to the example of speech processing, we propose a neuronal network model for time-warp-invariant word discrimination and demonstrate its excellent performance on a standard benchmark speech-recognition task. ..."
Reference:
1 . Gutig R, Sompolinsky H (2009) Time-warp-invariant neuronal processing. PLoS Biol 7:e1000141 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Connectionist Network;
Brain Region(s)/Organism:
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Simulation Environment: Brian (web link to method); Python (web link to model);
Model Concept(s): Pattern Recognition;
Implementer(s): Brette R;
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