Literature DB >> 17222533

Space, time and learning in the hippocampus: how fine spatial and temporal scales are expanded into population codes for behavioral control.

Anatoli Gorchetchnikov1, Stephen Grossberg.   

Abstract

The hippocampus participates in multiple functions, including spatial navigation, adaptive timing and declarative (notably, episodic) memory. How does it carry out these particular functions? The present article proposes that hippocampal spatial and temporal processing are carried out by parallel circuits within entorhinal cortex, dentate gyrus and CA3 that are variations of the same circuit design. In particular, interactions between these brain regions transform fine spatial and temporal scales into population codes that are capable of representing the much larger spatial and temporal scales that are needed to control adaptive behaviors. Previous models of adaptively timed learning propose how a spectrum of cells tuned to brief but different delays are combined and modulated by learning to create a population code for controlling goal-oriented behaviors that span hundreds of milliseconds or even seconds. Here it is proposed how projections from entorhinal grid cells can undergo a similar learning process to create hippocampal place cells that can cover a space of many meters that are needed to control navigational behaviors. The suggested homology between spatial and temporal processing may clarify how spatial and temporal information may be integrated into an episodic memory. The model proposes how a path integration process activates a spatial map of grid cells. Path integration has a limited spatial capacity, and must be reset periodically, leading to the observed grid cell periodicity. Integration-to-map transformations have been proposed to exist in other brain systems. These include cortical mechanisms for numerical representation in the parietal cortex. As in the grid-to-place cell spatial expansion, the analog representation of number is extended by additional mechanisms to represent much larger numbers. The model also suggests how visual landmarks may influence grid cell activities via feedback projections from hippocampal place cells to the entorhinal cortex.

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Year:  2007        PMID: 17222533     DOI: 10.1016/j.neunet.2006.11.007

Source DB:  PubMed          Journal:  Neural Netw        ISSN: 0893-6080


  32 in total

1.  Cosine directional tuning of theta cell burst frequencies: evidence for spatial coding by oscillatory interference.

Authors:  Adam C Welday; I Gary Shlifer; Matthew L Bloom; Kechen Zhang; Hugh T Blair
Journal:  J Neurosci       Date:  2011-11-09       Impact factor: 6.167

2.  KInNeSS: a modular framework for computational neuroscience.

Authors:  Massimiliano Versace; Heather Ames; Jasmin Léveillé; Bret Fortenberry; Anatoli Gorchetchnikov
Journal:  Neuroinformatics       Date:  2008-08-10

Review 3.  Cortical and subcortical predictive dynamics and learning during perception, cognition, emotion and action.

Authors:  Stephen Grossberg
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2009-05-12       Impact factor: 6.237

4.  Grid cell firing may arise from interference of theta frequency membrane potential oscillations in single neurons.

Authors:  Michael E Hasselmo; Lisa M Giocomo; Eric A Zilli
Journal:  Hippocampus       Date:  2007       Impact factor: 3.899

5.  Chronic Hypertension Leads to Neurodegeneration in the TgSwDI Mouse Model of Alzheimer's Disease.

Authors:  Anna Kruyer; Nadine Soplop; Sidney Strickland; Erin H Norris
Journal:  Hypertension       Date:  2015-05-04       Impact factor: 10.190

6.  Perirhinal and postrhinal, but not lateral entorhinal, cortices are essential for acquisition of trace eyeblink conditioning.

Authors:  Eugénie E Suter; Craig Weiss; John F Disterhoft
Journal:  Learn Mem       Date:  2013-01-15       Impact factor: 2.460

7.  Modeling inheritance of phase precession in the hippocampal formation.

Authors:  Jorge Jaramillo; Robert Schmidt; Richard Kempter
Journal:  J Neurosci       Date:  2014-05-28       Impact factor: 6.167

Review 8.  Cellular dynamical mechanisms for encoding the time and place of events along spatiotemporal trajectories in episodic memory.

Authors:  Michael E Hasselmo; Lisa M Giocomo; Mark P Brandon; Motoharu Yoshida
Journal:  Behav Brain Res       Date:  2009-12-16       Impact factor: 3.332

9.  Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, attention and oscillations.

Authors:  Stephen Grossberg; Praveen K Pilly
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2013-12-23       Impact factor: 6.237

10.  A model of episodic memory: mental time travel along encoded trajectories using grid cells.

Authors:  Michael E Hasselmo
Journal:  Neurobiol Learn Mem       Date:  2009-07-15       Impact factor: 2.877

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