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by padolsey·4y ago·view on hn ↗
I see this is about point-to-point navigation optimization but it's very curious this article doesn't mention grid cells – essentially, neurological ~1:~1 representations of physical space.

> They were awarded the 2014 Nobel Prize in Physiology or Medicine together with John O'Keefe for their discoveries of cells that constitute a positioning system in the brain. The arrangement of spatial firing fields, all at equal distances from their neighbors, led to a hypothesis that these cells encode a neural representation of Euclidean space.[1] The discovery also suggested a mechanism for dynamic computation of self-position based on continuously updated information about position and direction.

https://en.wikipedia.org/wiki/Grid_cell

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This article indicates a 1:1 relationship doesn't apply in 3D. I haven't had time to read and understand this enough but it seems worth passing on the article since its something on my list to dig into this weekend.

"But when researchers were finally able to record from grid cells in animals navigating 3D spaces, the findings got “much more dramatic,” Ulanovsky said — seeming to demonstrate not just deviations from the framework, but departures from it. ... To their surprise, the hexagonal patterns that defined the cells’ behavior in 2D were gone entirely: The researchers couldn’t find even traces of that global order. Instead, the clumps of grid cell activity seemed to be distributed throughout the three-dimensional space at random. “Some properties were preserved,” Jeffery said, “but the most visually striking property of grid cells was not.”"

https://www.quantamagazine.org/how-animals-map-3d-spaces-sur...

there are also "vector cells" https://www.nature.com/articles/s41593-020-00761-w

Neuronal vector coding in spatial cognition: https://www.nature.com/articles/s41583-020-0336-9?proof=t