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Principles of goal-directed spatial robot navigation in biomimetic modelsParametric Anatomical Modeling: a method for modeling the anatomical layout of neurons and their projectionsMemory replay in balanced recurrent networksRecurrent Spiking Networks Solve Planning Tasks.Topological Schemas of Cognitive Maps and Spatial Learning.Re-encoding of associations by recurrent plasticity increases memory capacity.From grid cells to place cells with realistic field sizes.Self-organization of synchronous activity propagation in neuronal networks driven by local excitationPattern association and consolidation emerges from connectivity properties between cortex and hippocampus.Predictive Place-Cell Sequences for Goal-Finding Emerge from Goal Memory and the Cognitive Map: A Computational ModelThe Interaction between Semantic Representation and Episodic Memory.Dendrites, deep learning, and sequences in the hippocampus.The transformation from grid cells to place cells is robust to noise in the grid pattern.Unlocking neural complexity with a robotic key.Dynamic patterns in a two-dimensional neural field with refractoriness.The reduction of adult neurogenesis in depression impairs the retrieval of new as well as remote episodic memory.
P2860
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P2860
description
2013 nî lūn-bûn
@nan
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
2013年论文
@zh
2013年论文
@zh-cn
name
A computational model for preplay in the hippocampus.
@en
A computational model for preplay in the hippocampus.
@nl
type
label
A computational model for preplay in the hippocampus.
@en
A computational model for preplay in the hippocampus.
@nl
prefLabel
A computational model for preplay in the hippocampus.
@en
A computational model for preplay in the hippocampus.
@nl
P2860
P356
P1476
A computational model for preplay in the hippocampus.
@en
P2093
Amir H Azizi
P2860
P356
10.3389/FNCOM.2013.00161
P577
2013-11-12T00:00:00Z