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IJON
2000
86views more  IJON 2000»
14 years 10 months ago
Gain modulation of recurrent networks
Gain modulation is an important mechanism by which attentional and other inputs modify the amplitude of neuronal responses without changing their selectivity. Gain modulation has ...
Jian Zhang 0004, L. F. Abbott
AIPRF
2007
14 years 12 months ago
Instinct and Learning Synergy in Simulated Foraging Using a Neural Network
Instinct and experience are shown to form a potent combination to achieve effective foraging in a simulated environment. A neural network capable of evolving instinct-related neur...
Thomas E. Portegys
IJON
2007
73views more  IJON 2007»
14 years 10 months ago
Improvement of spike coincidence detection with facilitating synapses
A realistic model of activity dependent dynamical synapses is used to study the conditions in which a postsynaptic neuron detects temporal coincidences of spikes arriving from N d...
Jorge F. Mejías, Joaquín J. Torres
IJCNN
2000
IEEE
15 years 2 months ago
Analysis of Fluctuation-Induced Firing in the Presence of Inhibition
This paper examines the computational role of inhibition as it moves towards balancing concurrent excitation using the biologically-inspired Temporal Noisy-Leaky Integrator (TNLI) ...
Chris Christodoulou, Trevor G. Clarkson, John G. T...
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ICANN
2010
Springer
14 years 11 months ago
Reinforcement Learning Based Neural Controllers for Dynamic Processes without Exploration
Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...
Frank-Florian Steege, André Hartmann, Erik ...