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P6: Characterization of Nonlinear Neuron Responses
Author: Matt Whiteway , Advisor: Daniel Butts (Neural Cog.Sci.)
Problem Statement Presentation
Project Proposal
Abstract
A common approach to characterizing a sensory neuron's response to stimuli is to use a probabilistic modeling approach. These models use both the stimulus and the neuron's response to the stimulus to estimate the probability of the neuron spiking. This project will investigate some of the well known approaches, starting with simple linear models and progressing to more complex nonlinear models. All models considered use the idea of a "linear receptive field" to characterize a feature subspace of the stimulus on which the neuron's response is dependent. Both moment-based estimators and maximum-likelihood estimators will be used for fitting parameters, dependent upon the model.
MidYear Progress Report and
Presentation
Final Presentation ,
Final Report
