A. A. Lazar and E. A. Pnevmatikakis
Consistent Recovery of Sensory Stimuli Encoded with MIMO Neural Circuits
Computational Intelligence and Neuroscience , Hindawi Publishing Corporation , February 2010 , Article ID 469658, Special Issue on Signal Processing for Neural Spike Trains
Keywords:- sensory stimuli   time encoding   mimo   mimo neural circuits   stimulus reconstruction
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We consider the problem of reconstructing finite energy stimuli encoded with a population of spiking leaky integrate-and-fire neurons. The reconstructed signal satisfies a consistency condition: when passed through the same neuron, it triggers the same spike train as the original stimulus. The recovered stimulus has to also minimize a quadratic smoothness optimality criterion. We formulate the reconstruction as a spline interpolation problem for scalar as well as vector valued stimuli and show that the recovery has a unique solution. We provide explicit reconstruction algorithms for stimuli encoded with single as well as a population of integrate-and-fire neurons. We demonstrate how our reconstruction algorithms can be applied to stimuli encoded with ONOFF neural circuits with feedback. Finally, we extend the formalism to multi-input multi-output neural circuits and demonstrate that vector-valued finite energy signals can be efficiently encoded by a neural population provided that its size is beyond a threshold value. Examples are given that demonstrate the potential applications of our methodology to systems neuroscience and neuromorphic engineering.


  author = "A. A. Lazar and E. A. Pnevmatikakis",
  title = "Consistent Recovery of Sensory Stimuli Encoded with MIMO Neural Circuits",
  year = 2010,
  journal = "Computational Intelligence and Neuroscience",
  publisher = "Hindawi Publishing Corporation",
  month = "Feb",
  keywords = "sensory stimuli, time encoding, mimo, mimo neural circuits, stimulus reconstruction"