A speed-accurate self-sustaining head direction cell path integration model without recurrent excitation

ABSTRACT

The head direction (HD) system signals HD in an allocentric frame of reference. The system is able to update firing based on internally derived information about self-motion, a process known as path integration. Of particular interest is how path integration might maintain concordance between true HD and internally represented HD. Here we present a self-sustaining two-layer model, capable of self-organizing, which produces extremely accurate path integration. The implications of this work for future investigations of HD system path integration are discussed.

KEYWORDS:

• Spatial cognition
• head direction cells
• path integration
• continuous attractor neural networks
• attractor dynamics

Acknowledgments

This work was funded by the Oxford Foundation for Theoretical Neuroscience and Artificial Intelligence.

Disclosure statement

No potential conflict of interest was reported by the authors.