The Computational Role of Inhibition

Dr Chris Christodoulou

Through our work in this area we have found that increasing inhibition leads to decreasing the slope of the neuron's transfer function due to the greater membrane potential fluctuations as well as the greater amplitude variations for a given level of mean input current (paper in Neural Networks, 2002). We have also shown that inhibition can be used for controlling the gain of the neuron. Further issues to be investigated in the future continuing from this work are: the effect of proximal and distal inhibition on concurrent excitation as well as the exact computational distinction between proximal and distal inhibition.

Publications

Christodoulou, C., Bugmann, G. and Clarkson, T. G. (2002). A Spiking Neuron Model: Applications and Learning. Neural Networks, 15, 891-908.

Revised on 9th September 2002

webmaster@dcs.bbk.ac.uk