A new nonconvex variational approach for sensory neurons receptive field estimation

Abstract : Determining the receptive field of a visual sensory neuron is crucial to characterize the region of the visual field and the stimuli this neuron is sensitive to. We propose a new method to estimate receptive fields by a nonconvex variational approach, thus relaxing the simplifying and unrealistic assumption of convexity made by standard approaches. The method consists of solving a relaxed discrete energy minimization problem using a proximal alternating algorithm. We compare our approach with the classical spike-triggered-average technique on simulated data, considering a typical retinal ganglion cell as ground truth. Results show a high improvement in terms of accuracy and convergence with respect to the duration of the experiment.
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Submitted on : Wednesday, October 12, 2016 - 10:52:37 AM
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Audric Drogoul, Gilles Aubert, Bruno Cessac, Pierre Kornprobst. A new nonconvex variational approach for sensory neurons receptive field estimation. 6th International Workshop on New Computational Methods for Inverse Problems , May 2016, Cachan, France. pp.12006, ⟨10.1088/1742-6596/756/1/012006⟩. ⟨hal-01379952⟩



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