On 2018 Jan 26, Jason Climer commented:

Zutshi et al present an interesting framework that explains the phenomenon of grid cell phase precession as a code for movement direction to reduce path integration error in the grid cell circuit. While the hypothesis that precession stabilizes the grid cell code is an intriguing one, there are several caveats to their interpretations from extant data that should be considered.

Phase precession in the open field has been characterized by several groups (Climer et al, 2013; Jeewajee et al, 2013; Reifenstein et al, 2014). Notably, all three groups demonstrated that precession relative to the distance traveled occurs faster as an animal’s path crosses further away from the center of the field. This causes sequences to sweep past each other in a way that would make decoding the distance traveled more complex. It may be possible to encode additional trajectory information in this family of sequences, but how the brain would read that out physiologically remains an open question.

There are other minor concerns that are relevant to the field. Attractor network dynamics have yet to generate phase precession during open field movement. The claim that the slower spatial sequences in the absence of temporal sequences would be “adequate if travelling in a particular direction for distances that correspond to approximately the minimum grid spacing” may be misleading, as the ability of the brain to read out such long timescale dynamics has not been demonstrated.

Altogether, it is an interesting idea, and it will be interesting to see what testable predictions fall out of it.

On 2018 Jan 26, Jason Climer commented:

Zutshi et al present an interesting framework that explains the phenomenon of grid cell phase precession as a code for movement direction to reduce path integration error in the grid cell circuit. While the hypothesis that precession stabilizes the grid cell code is an intriguing one, there are several caveats to their interpretations from extant data that should be considered.

Phase precession in the open field has been characterized by several groups (Climer et al, 2013; Jeewajee et al, 2013; Reifenstein et al, 2014). Notably, all three groups demonstrated that precession relative to the distance traveled occurs faster as an animal’s path crosses further away from the center of the field. This causes sequences to sweep past each other in a way that would make decoding the distance traveled more complex. It may be possible to encode additional trajectory information in this family of sequences, but how the brain would read that out physiologically remains an open question.

There are other minor concerns that are relevant to the field. Attractor network dynamics have yet to generate phase precession during open field movement. The claim that the slower spatial sequences in the absence of temporal sequences would be “adequate if travelling in a particular direction for distances that correspond to approximately the minimum grid spacing” may be misleading, as the ability of the brain to read out such long timescale dynamics has not been demonstrated.

Altogether, it is an interesting idea, and it will be interesting to see what testable predictions fall out of it.