Accurate Path Integration in Continuous Attractor Network Models of Grid Cells
2009

Accurate Path Integration in Grid Cells

Sample size: 1282 publication Evidence: moderate

Author Information

Author(s): Burak Yoram, Fiete Ila R.

Primary Institution: Harvard University

Hypothesis

Can continuous attractor models of grid cell activity accurately integrate velocity inputs for path integration?

Conclusion

Continuous attractor models can generate regular triangular grid responses and accurately integrate velocity inputs over distances of 10-100 meters and durations of 1-10 minutes.

Supporting Evidence

  • Continuous attractor models can generate grid-cell-like responses based on inputs encoding the rat's velocity and heading direction.
  • Both periodic and aperiodic networks can achieve accurate path integration despite differences in their attractor manifolds.
  • The model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and 1-10 minutes.

Takeaway

The brain has special cells that help animals know where they are, even without looking around. This study shows how these cells can keep track of movement accurately.

Methodology

The study used simulations of continuous attractor networks to model grid cell activity and tested their ability to integrate velocity inputs.

Limitations

The accuracy of integration is sensitive to network size and noise, and the model does not account for potential inaccuracies in the velocity inputs themselves.

Digital Object Identifier (DOI)

10.1371/journal.pcbi.1000291

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