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Information Maximization in Single Neurons
Martin Stemmler
Innovationskolleg Theoretische Biologie
Humboldt-Universität zu Berlin
Invalidenstr. 43
D-10115 Berlin
and
Christof Koch
Computation and Neural Systems Program
Caltech 139-74
Pasadena, CA 91125
January 27, 1998
Abstract:
Information from the senses must be compressed into
the limited range of firing rates generated by spiking nerve cells. Optimal
compression uses all firing rates equally often, implying that the nerve
cell's response matches the statistics of naturally occurring stimuli.
Since changing the voltage-dependent ionic conductances in the cell membrane
alters the flow of information, an unsupervised, non-Hebbian, developmental
learning rule is derived to adapt the conductances in Hodgkin-Huxley model
neurons. By maximizing the rate of information transmission, each firing
rate within the model neuron's limited dynamic range is used equally often.
Martin Stemmler
1/27/1998