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. Author manuscript; available in PMC: 2009 Aug 1.
Published in final edited form as: Curr Opin Neurobiol. 2008 Oct 27;18(4):396–402. doi: 10.1016/j.conb.2008.09.010

Figure 4.

Figure 4

Decoding the stimulus from population activity [35]. (a) A parametric model (generalized linear model) can capture the activity of a complete population of ON and OFF parasol retinal ganglion cells. Each model neuron spikes stochastically, with a probability equal to the exponentiated summed drive of a linearly filtered stimulus, a post-spike feedback current, and cross-currents from spikes in coupled cells. Because a tractable mathematical expression expresses the likelihood of a population response to any stimulus, P(response|stimulus), one can invert the expression using Bayes rule to optimally reconstruct the stimulus. A model which includes coupling filters captures synchronized firing more accurately, and is able to extract 20% more information about a stimulus, than a model which does not include coupling filters.