A new nonconvex variational approach for sensory neurons receptive field estimation
| Autor: | Bruno Cessac, Gilles Aubert, Pierre Kornprobst, Audric Drogoul |
|---|---|
| Přispěvatelé: | Biologically plausible Integrative mOdels of the Visual system : towards synergIstic Solutions for visually-Impaired people and artificial visiON (BIOVISION), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire Jean Alexandre Dieudonné (JAD), Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Jean Alexandre Dieudonné (LJAD), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
History Ground truth Mathematical optimization Quantitative Biology::Neurons and Cognition Sensory system Energy minimization Convexity Computer Science Applications Education Visual field 03 medical and health sciences 030104 developmental biology 0302 clinical medicine Receptive field Discrete optimization Convergence (routing) Algorithm 030217 neurology & neurosurgery [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA] Mathematics |
| Zdroj: | Journal of Physics: Conference Series 6th International Workshop on New Computational Methods for Inverse Problems 6th International Workshop on New Computational Methods for Inverse Problems, May 2016, Cachan, France. pp.12006, ⟨10.1088/1742-6596/756/1/012006⟩ |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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