Spike-timing based neuronal information processing: applications to vision and speech

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Event details

Date 01.12.2011
Hour 15:15
Speaker Robert GÜTIG, Racah Institute of Physics, The Hebrew University
Location
Category Miscellaneous
The timing of action potentials of sensory neurons contains substantial information about the eliciting stimuli. Although computational advantages of spike-timing-based neuronal codes have long been recognized, it is unclear whether and how neurons can learn to read out such representations. We propose a novel biologically plausible supervised synaptic learning rule, the tempotron, enabling neurons to efficiently learn a broad range of decision rules, even when information is embedded in the spatio-temporal structure of spike patterns and not in mean firing rates. We demonstrate the enhanced performance of the tempotron over the rate-based perceptron in reading out spike patterns from retinal ganglion cell populations. Extending the tempotron to conductance-based voltage kinetics, we show that this model can subserve time-warp invariant processing of afferent spike patterns. Furthermore, we show that the conductance-based tempotron can learn to balance excitation and inhibition to match its integration time constant to the temporal scale of a given processing task. These mechanisms enable already small populations of model neurons to match the performance of state-of-the-art speech recognition systems on isolated word recognition tasks.

Practical information

  • General public
  • Free

Contact

  • Dr. Tim Vogels

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