Linear decoder analysis applied to multineuronal records of retinal ganglion cells

Abstract

Achieving a thorough understanding about the neural code is one of the neuroscientists’ greatest challenges. One way to evaluate our current knowledge about the neural code is trying to reconstruct sensorial stimuli from neuronal responses. In spite of nowadays there are several types of decoding techniques, few of them have been used and analyzed in actual multi neuronal records of retinal ganglion cells. In this work, we had employed and analyzed a linear decoder to reconstruct different visual stimulus, white noise scramble and natural image, from multi neuronal records of retinal ganglion cells. The efficiency of the reconstruction depends on two factors: one the one hand, the type of visual stimulus, if parameters used were calculated since white noise, scramble or natural image , and on the other hand, the numbers of cells employed in the reconstruction.