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The Neuron as a Reprogrammable Computing Element
Synergistic Interactions Among Distinct Populations of Neurons
Competitive Activation Mechanisms in Connectionist Models
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activation level activation values agents algorithms arrows associated behavior biological cells cognitive map column competitive activation mechanisms component elements computational configuration connectionist model connections convergence correlation function corresponding database defined described distributed dynamics eigenvalue eigenvectors environment equation equilibrium event example Figure frequency functor Gagliano given grapheme Grossberg Hebb rule Hopfield IEEE implemented inhibitory initial input vector interaction iteration joint kinematic network layer learning matrix mental models method MIRRORS/II muscle natural transformation neural network neurons nodes operations orientation selectivity output parallel parameters path space pattern phoneme phoneme nodes pool population position processor pseudoinverse receptive fields Reggia relation represent representation Rumelhart schema second messenger sequence sequential ShR nodes simulation spatial specification stable stiffness strategies structure subset supervised learning synapses tion transformation Transputer update velocity visual visual cortex voting group weight