A fast fixed-point algorithm for independent component analysis
Neural Computation
Independent component analysis by general nonlinear Hebbian-like learning rules
Signal Processing - Special issue on neural networks
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Real-time computation at the edge of chaos in recurrent neural networks
Neural Computation
Gain Control by Concerted Changes in IA and IH Conductances
Neural Computation
A gradient rule for the plasticity of a neuron’s intrinsic excitability
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Homeostatic synaptic scaling in self-organizing maps
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
Learning sensory representations with intrinsic plasticity
Neurocomputing
Improving reservoirs using intrinsic plasticity
Neurocomputing
A sparse generative model of v1 simple cells with intrinsic plasticity
Neural Computation
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Map-Based Spatial Navigation: A Cortical Column Model for Action Planning
Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space
Sleeping our way to weight normalization and stable learning
Neural Computation
Rules for information maximization in spiking neurons using intrinsic plasticity
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Goal-directed feature learning
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Cross-talk induces bifurcations in nonlinear models of synaptic plasticity
Neural Computation
Intrinsic adaptation in autonomous recurrent neural networks
Neural Computation
Survey: Reservoir computing approaches to recurrent neural network training
Computer Science Review
Learning features and predictive transformation encoding based on a horizontal product model
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Self-regulating neurons in the sensorimotor loop
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
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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.