Despite our extensive knowledge of neuron physiology, there is no commonly accepted algorithmic theory of neural computation. We believe that such a theory is necessary for understanding the brain.

Here, we explore the hypothesis that neurons respond to like stimuli more similarly than to more disparate stimuli. Based on this hypothesis, we formulate mathematical objectives and derive online algorithms to solve them.

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