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Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation.

, , , , and . PLoS Computational Biology, (2013)

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Behavioral analysis of differential hebbian learning in closed-loop systems., , , , and . Biological Cybernetics, 103 (4): 255-271 (2010)Time scales of memory, learning, and plasticity., , , and . Biological Cybernetics, 106 (11-12): 715-726 (2012)Adapting Predictive Feedback Chaos Control for Optimal Convergence Speed., , and . SIAM J. Applied Dynamical Systems, 11 (4): 1310-1324 (2012)Second Order Conditioning in the Sub-cortical Nuclei of the Limbic System., , , and . SAB, volume 5040 of Lecture Notes in Computer Science, page 189-198. Springer, (2008)Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation., , , , and . PLoS Computational Biology, (2013)Multiple chaotic central pattern generators for locomotion generation and leg damage compensation in a hexapod robot., , , , , and . IROS, page 2756-2761. IEEE, (2012)Analysis of Synaptic Scaling in Combination with Hebbian Plasticity in Several Simple Networks., , , and . Front. Comput. Neurosci., (2012)Synaptic Scaling in Combination with Many Generic Plasticity Mechanisms Stabilizes Circuit Connectivity., , , and . Front. Comput. Neurosci., (2011)On the asymptotic equivalence between differential Hebbian and temporal difference learning using a local third factor., , , and . NIPS, page 857-864. Curran Associates, Inc., (2008)Multiple chaotic central pattern generators with learning for legged locomotion and malfunction compensation., , , , , and . CoRR, (2014)