Coordinated Learning of Entorhinal Grid Cells and Hippocampal Place Cells: Space, Time, Attention and Oscillations

  • Stephen GrossbergEmail author
Part of the Simulation Foundations, Methods and Applications book series (SFMA)


The GridPlaceMap neural model explains and simulates how both entorhinal grid cells and hippocampal place cells may develop as spatial categories in a hierarchy of self-organizing maps by detecting, learning and remembering the most frequent and energetic co-occurrences of their inputs. The model simulates challenging behavioural and neurobiological data by embodying several parsimonious neural designs: Similar ring attractor mechanisms process the linear and angular path integration inputs that drive map learning; the same self-organizing map mechanisms can learn grid cell and place cell receptive fields; and the learning of the dorsoventral organization of multiple spatial scale modules through medial entorhinal cortex to hippocampus may use mechanisms homologous to those for temporal learning (“time cells”) through lateral entorhinal cortex to hippocampus (“neural relativity”). Top-down hippocampus-to-entorhinal attentional mechanisms stabilize map learning, simulate how hippocampal inactivation may disrupt grid cells and help to explain data about theta, beta and gamma oscillations.


Grid cells Place cells Self-organizing map Spatial navigation Attention Adaptive timing 



This research is supported in part by the SyNAPSE program of DARPA (HR0011-09-C-0001).


  1. 1.
    Fortenberry B, Gorchetchnikov A, Grossberg S (2012) Learned integration of visual, vestibular, and motor cues in multiple brain regions computes head direction during visually-guided navigation. Hippocampus 22:2219–2237CrossRefGoogle Scholar
  2. 2.
    Gorchetchnikov A, Grossberg S (2007) Space, time, and learning in the hippocampus: how fine spatial and temporal scales are expanded into population codes for behavioral control. Neural Netw 20:182–193CrossRefzbMATHGoogle Scholar
  3. 3.
    Grossberg S (2009) Beta oscillations and hippocampal place cell learning during exploration of novel environments. Hippocampus 19:881–885CrossRefGoogle Scholar
  4. 4.
    Grossberg S (2013) Adaptive resonance theory: how a brain learns to consciously attend, learn, and recognize a changing world. Neural Netw 37:1–47CrossRefGoogle Scholar
  5. 5.
    Grossberg S, Merrill JWL (1992) A neural network model of adaptively timed reinforcement learning and hippocampal dynamics. Cogn Brain Res 1:3–38CrossRefGoogle Scholar
  6. 6.
    Grossberg S, Merrill JWL (l996). The hippocampus and cerebellum in adaptively timed learning, recognition, and movement. J Cogn Neurosci 8:257–277Google Scholar
  7. 7.
    Grossberg S, Pilly PK (2012) How entorhinal grid cells may learn multiple spatial scales from a dorsoventral gradient of cell response rates in a self-organizing map. PLoS Comput Biol 8(10):31002648. doi: 10.1371/journal.pcbi.1002648 MathSciNetCrossRefGoogle Scholar
  8. 8.
    Grossberg S, Pilly PK (2014) Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, and oscillations. Philos Trans R Soc B. 369:20120524CrossRefGoogle Scholar
  9. 9.
    Grossberg S, Versace M (2008) Spikes, synchrony, and attentive learning by laminar thalamocortical circuits. Brain Res 1218:278–312CrossRefGoogle Scholar
  10. 10.
    Grossberg S, Schmajuk NA (1989) Neural dynamics of adaptive timing and temporal discrimination during associative learning. Neural Netw 2:79–102CrossRefGoogle Scholar
  11. 11.
    Mhatre H, Gorchetchnikov A, Grossberg S (2012) Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex. Hippocampus 22:320–334CrossRefGoogle Scholar
  12. 12.
    Pilly PK, Grossberg S (2012) How do spatial learning and memory occur in the brain? Coordinated learning of entorhinal grid cells and hippocampal place cells. J Cogn Neurosci 24:1031–1054CrossRefGoogle Scholar
  13. 13.
    Pilly PK, Grossberg S (2013) How reduction of theta rhythm by medium septum inactivation may disrupt periodic spatial responses of entorhinal grid cells by reduced cholinergic transmission. Frontiers Neural Circu. doi: 10.3389/fncir.l2013.00173 Google Scholar
  14. 14.
    Pilly PK, Grossberg S (2013) Spiking neurons in a hierarchical model can learn to develop spatial and temporal properties of entorhinal grid cells and hippocampal place cells. PLoS ONE,
  15. 15.
    Pilly PK, Grossberg S (2014) How does the modular organization of entorhinal grid cells develop? Frontiers Human Neurosci. doi: 10.3389/fnhum.2014.0037 Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Center for Adaptive Systems, Graduate Program in Cognitive and Neural Systems, Departments of Mathematics, Psychology, and Biomedical EngineeringBoston UniversityBostonUSA

Personalised recommendations