Population coding in spike trains of simultaneously recorded retinal ganglion cells

To achieve a better understanding of the parallel information processing th at takes place in the nervous system, many researchers have recently begun to use multielectrode techniques to obtain high spatial- and temporal-resol ution recordings of the firing patterns of neural ensembles. Apart from the complexities of acquiring and storing single unit responses from large num bers of neurons, the multielectrode technique has provided new challenges i n the analysis of the responses from many simultaneously recorded neurons. This paper provides insights into the problem of coding/decoding of retinal images by ensembles of retinal ganglion cells. We have simultaneously reco rded the responses of 15 ganglion cells to visual stimuli of various intens ities and wavelengths and analyzed the data using discriminant analysis. Mo dels of stimulus encoding were generated and discriminant analysis used to estimate the wavelength and intensity of the stimuli. We find that the gang lion cells we have recorded from are non-redundant encoders of these stimul us features. While single ganglion cells are poor classifiers of the stimul us parameters, examination of the responses of only a few ganglion cells gr eatly enhances our ability to specify the stimulus wavelength and intensity . Of the parameters studied, we find that the rate of firing of the ganglio n cells provides the most information about these stimulus parameters, whil e the timing of the first action potential provides almost as much informat ion. While we are not suggesting that the brain is using these variables, o ur results show how a population of sensory neurons can encode stimulus fea tures and suggest that the brain could potentially deduce reliable informat ion about stimulus features from response patterns of retinal ganglion cell populations. (C) 2000 Elsevier Science B.V. All rights reserved.