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Literature DB >> 16977716

Do we understand the emergent dynamics of grid cell activity?

Yoram Burak¹, Ila Fiete.

Abstract

Mesh：

Year: 2006 PMID： 16977716 PMCID： PMC6674593 DOI： 10.1523/jneurosci.2857-06.2006

Source DB: PubMed Journal: J Neurosci ISSN： 0270-6474 Impact factor: 6.167

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Cited

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14 in total

1. Grid cell mechanisms and function: contributions of entorhinal persistent spiking and phase resetting.

Authors: Michael E Hasselmo
Journal: Hippocampus Date: 2008 Impact factor: 3.899

2. Time constants of h current in layer ii stellate cells differ along the dorsal to ventral axis of medial entorhinal cortex.

Authors: Lisa M Giocomo; Michael E Hasselmo
Journal: J Neurosci Date: 2008-09-17 Impact factor: 6.167

3. Inferring circuit mechanisms from sparse neural recording and global perturbation in grid cells.

Authors: John Widloski; Michael P Marder; Ila R Fiete
Journal: Elife Date: 2018-07-09 Impact factor: 8.140

Review 4. How to build a cognitive map.

Authors: James C R Whittington; David McCaffary; Jacob J W Bakermans; Timothy E J Behrens
Journal: Nat Neurosci Date: 2022-09-26 Impact factor: 28.771

5. Solving navigational uncertainty using grid cells on robots.

Authors: Michael J Milford; Janet Wiles; Gordon F Wyeth
Journal: PLoS Comput Biol Date: 2010-11-11 Impact factor: 4.475

6. 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

Do we understand the emergent dynamics of grid cell activity?

1. Grid cell mechanisms and function: contributions of entorhinal persistent spiking and phase resetting.

2. Time constants of h current in layer ii stellate cells differ along the dorsal to ventral axis of medial entorhinal cortex.

3. Inferring circuit mechanisms from sparse neural recording and global perturbation in grid cells.

Review 4. How to build a cognitive map.

5. Solving navigational uncertainty using grid cells on robots.

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

7. Grid cell co-activity patterns during sleep reflect spatial overlap of grid fields during active behaviors.

8. Place-cell capacity and volatility with grid-like inputs.

9. Models of grid cell spatial firing published 2005-2011.

10. Accurate path integration in continuous attractor network models of grid cells.