Literature DB >> 11918209

From view cells and place cells to cognitive map learning: processing stages of the hippocampal system.

P Gaussier1, A Revel, J P Banquet, V Babeau.   

Abstract

The goal of this paper is to propose a model of the hippocampal system that reconciles the presence of neurons that look like "place cells" with the implication of the hippocampus (Hs) in other cognitive tasks (e.g., complex conditioning acquisition and memory tasks). In the proposed model, "place cells" or "view cells" are learned in the perirhinal and entorhinal cortex. The role of the Hs is not fundamentally dedicated to navigation or map building, the Hs is used to learn, store, and predict transitions between multimodal states. This transition prediction mechanism could be important for novelty detection but, above all, it is crucial to merge planning and sensory-motor functions in a single and coherent system. A neural architecture embedding this model has been successfully tested on an autonomous robot, during navigation and planning in an open environment.

Mesh:

Year:  2002        PMID: 11918209     DOI: 10.1007/s004220100269

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  18 in total

1.  Characterizing functional hippocampal pathways in a brain-based device as it solves a spatial memory task.

Authors:  Jeffrey L Krichmar; Douglas A Nitz; Joseph A Gally; Gerald M Edelman
Journal:  Proc Natl Acad Sci U S A       Date:  2005-01-31       Impact factor: 11.205

2.  Spatial navigation and causal analysis in a brain-based device modeling cortical-hippocampal interactions.

Authors:  Jeffrey L Krichmar; Anil K Seth; Douglas A Nitz; Jason G Fleischer; Gerald M Edelman
Journal:  Neuroinformatics       Date:  2005

3.  Modeling the role of working memory and episodic memory in behavioral tasks.

Authors:  Eric A Zilli; Michael E Hasselmo
Journal:  Hippocampus       Date:  2008       Impact factor: 3.899

4.  Goal-directed decision making as probabilistic inference: a computational framework and potential neural correlates.

Authors:  Alec Solway; Matthew M Botvinick
Journal:  Psychol Rev       Date:  2012-01       Impact factor: 8.934

5.  Anterior hippocampus and goal-directed spatial decision making.

Authors:  Armelle Viard; Christian F Doeller; Tom Hartley; Chris M Bird; Neil Burgess
Journal:  J Neurosci       Date:  2011-03-23       Impact factor: 6.167

6.  Unsupervised learning of reflexive and action-based affordances to model adaptive navigational behavior.

Authors:  Daniel Weiller; Leonhard Läer; Andreas K Engel; Peter König
Journal:  Front Neurorobot       Date:  2010-05-12       Impact factor: 2.650

7.  Odor supported place cell model and goal navigation in rodents.

Authors:  Tomas Kulvicius; Minija Tamosiunaite; James Ainge; Paul Dudchenko; Florentin Wörgötter
Journal:  J Comput Neurosci       Date:  2008-04-23       Impact factor: 1.621

8.  Different CA1 and CA3 representations of novel routes in a shortcut situation.

Authors:  Alice Alvernhe; Tiffany Van Cauter; Etienne Save; Bruno Poucet
Journal:  J Neurosci       Date:  2008-07-16       Impact factor: 6.167

9.  Integrating cortico-limbic-basal ganglia architectures for learning model-based and model-free navigation strategies.

Authors:  Mehdi Khamassi; Mark D Humphries
Journal:  Front Behav Neurosci       Date:  2012-11-27       Impact factor: 3.558

10.  Neurobiologically inspired mobile robot navigation and planning.

Authors:  Nicolas Cuperlier; Mathias Quoy; Philippe Gaussier
Journal:  Front Neurorobot       Date:  2007-11-02       Impact factor: 2.650

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.