Research on the hippocampus

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Table of contents

Introduction 
1 Computational Neuroscience, Statistical Mechanics and the hippocampus 
1.1 Methods in Computational Neuroscience
1.2 The Statistical Mechanics Approach
1.3 The Attractor Neural Network Theory
1.4 The Hippocampus
2 A model for place cells 
2.1 On models
2.2 Description
2.3 Phase diagram
2.4 Transitions between maps
2.5 Diusion within one map
2.6 Comparison with previous models
2.7 Estimation of the parameters from experimental data
3 Decoding 
3.1 Stating the decoding problem
3.2 Experimental data
3.3 Rate-based decoding methods
3.4 The inverse-Ising approach to decoding
3.5 Structure of the inferred eective networks
3.6 Decoding an environment
3.7 Decoded transitions between maps
3.8 Correspondence between the \Ising – coupled » and the \rate – max. posterior »methods
4 Conclusions & Extensions 
4.1 Summary of results
4.2 Rening the model
4.3 Future work on the decoding issue
4.4 Concluding remarks
Appendix A Publications
Appendix B Résumé en francais
Bibliography