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J Neurophysiol (November 5, 2003). doi:10.1152/jn.00796.2003
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Submitted on August 14, 2003
Accepted on October 29, 2003

Information Transmission Rates of Cat Retinal Ganglion Cells

Christopher L. Passaglia1* and John B. Troy2

1 Biomedical Engineering Department, Boston University, Boston, MA, USA; Biomedical Engineering Department and the Neuroscience Institute, Northwestern University, Evanston, IL, USA
2 Biomedical Engineering Department and the Neuroscience Institute, Northwestern University, Evanston, IL, USA

* To whom correspondence should be addressed. E-mail: psagls{at}bu.edu.

To assess the information encoded in retinal spike trains and how it might be decoded by recipient neurons in the brain, we recorded from individual cat X and Y ganglion cells and visually stimulated them with randomly modulated patterns of various contrast and spatial configuration. For each pattern we estimated the information rate of the cells using linear or nonlinear algorithms and for some patterns by directly measuring response probability distributions. We show that ganglion cell spike trains contain information from the receptive field center and surround, that the center and surround have similar signaling capacity, that antagonism between the mechanisms reduces information transmission, and that the total information rate is limited. We also show that a linear decoding algorithm can capture all of the information available in retinal spike trains about weak inputs but it misses a substantial amount about strong inputs. For the strongest stimulus we used, the information rate of the best linear decoder averaged 40-70 bits per second across ganglion cell types while the directly measured rate was around 20-40 bits per second greater. This implies that under certain stimulus conditions visual information is encoded in the temporal structure of retinal spike trains and that a nonlinear decoding algorithm is needed to extract the temporally coded information. Using simulated spike trains we demonstrate that much of the temporal structure may be explained by the threshold for spike generation and is not necessarily indicative of a complex coding scheme.




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