Hippocampally-Dependent Consolidation in a Hierarchical Model of Neocortex

In memory consolidation, declarative memories which initially require the hippocampus for their recall, ultimately become independent of it. Consolidation has been the focus of numerous experimental and qualitative modeling studies, but only little quantitative exploration. We present a consolidation model in which hierarchical connections in the cortex, that initially instantiate purely semantic information acquired through probabilistic unsupervised learning, come to instantiate episodic information as well. The hippocampus is responsible for helping complete partial input patterns before consolidation is complete, while also training the cortex to perform appropriate completion by itself.

[1]  Geoffrey E. Hinton,et al.  Learning and relearning in Boltzmann machines , 1986 .

[2]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[3]  David Haussler,et al.  Unsupervised learning of distributions on binary vectors using two layer networks , 1991, NIPS 1991.

[4]  L. Squire Memory and the hippocampus: a synthesis from findings with rats, monkeys, and humans. , 1992, Psychological review.

[5]  P Alvarez,et al.  Memory consolidation and the medial temporal lobe: a simple network model. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[6]  B. McNaughton,et al.  Reactivation of hippocampal ensemble memories during sleep. , 1994, Science.

[7]  James L. McClelland,et al.  Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. , 1995, Psychological review.

[8]  L. Nadel,et al.  Memory consolidation, retrograde amnesia and the hippocampal complex , 1997, Current Opinion in Neurobiology.

[9]  J. Murre Implicit and explicit memory in amnesia: some explanations and predictions by the TraceLink model. , 1997, Memory.

[10]  John J. Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities , 1999 .

[11]  Terrence J. Sejnowski,et al.  Unsupervised Learning , 2018, Encyclopedia of GIS.

[12]  Geoffrey E. Hinton Training Products of Experts by Minimizing Contrastive Divergence , 2002, Neural Computation.