On nonlinearity in neural encoding models applied to the primary visual cortex

Vidaurre Henche, Diego; Bielza, Concha y Larrañaga Múgica, Pedro (2011). On nonlinearity in neural encoding models applied to the primary visual cortex. "Network: Computation in Neural Systems", v. 22 (n. 1-4); pp. 97-125. ISSN 0954-898X.

Descripción

Título: On nonlinearity in neural encoding models applied to the primary visual cortex
Autor/es:
  • Vidaurre Henche, Diego
  • Bielza, Concha
  • Larrañaga Múgica, Pedro
Tipo de Documento: Artículo
Título de Revista/Publicación: Network: Computation in Neural Systems
Fecha: 2011
Volumen: 22
Materias:
Escuela: Facultad de Informática (UPM) [antigua denominación]
Departamento: Inteligencia Artificial
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Within the regression framework, we show how different levels of nonlinearity influence the instantaneous firing rate prediction of single neurons. Nonlinearity can be achieved in several ways. In particular, we can enrich the predictor set with basis expansions of the input variables (enlarging the number of inputs) or train a simple but different model for each area of the data domain. Spline-based models are popular within the first category. Kernel smoothing methods fall into the second category. Whereas the first choice is useful for globally characterizing complex functions, the second is very handy for temporal data and is able to include inner-state subject variations. Also, interactions among stimuli are considered. We compare state-of-the-art firing rate prediction methods with some more sophisticated spline-based nonlinear methods: multivariate adaptive regression splines and sparse additive models. We also study the impact of kernel smoothing. Finally, we explore the combination of various local models in an incremental learning procedure. Our goal is to demonstrate that appropriate nonlinearity treatment can greatly improve the results. We test our hypothesis on both synthetic data and real neuronal recordings in cat primary visual cortex, giving a plausible explanation of the results from a biological perspective.

Más información

ID de Registro: 10995
Identificador DC: http://oa.upm.es/10995/
Identificador OAI: oai:oa.upm.es:10995
URL Oficial: http://informahealthcare.com/doi/abs/10.3109/0954898X.2011.637606?journalCode=net
Depositado por: Memoria Investigacion
Depositado el: 05 Jun 2012 09:27
Ultima Modificación: 20 Abr 2016 19:10
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