Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

April 2007, Vol. 19, No. 4, Pages 885-909
(doi: 10.1162/neco.2007.19.4.885)
© 2007 Massachusetts Institute of Technology
Synergies Between Intrinsic and Synaptic Plasticity Mechanisms
Article PDF (1.75 MB)
Abstract

We propose a model of intrinsic plasticity for a continuous activation model neuron based on information theory. We then show how intrinsic and synaptic plasticity mechanisms interact and allow the neuron to discover heavy-tailed directions in the input. We also demonstrate that intrinsic plasticity may be an alternative explanation for the sliding threshold postulated in the BCM theory of synaptic plasticity. We present a theoretical analysis of the interaction of intrinsic plasticity with different Hebbian learning rules for the case of clustered inputs. Finally, we perform experiments on the “bars” problem, a popular nonlinear independent component analysis problem.