I was wondering why would we need so many grid modules and possible simplification of Naive implementation.
What I have in mind ?
As you know every module represent a grid. The brain uses many overlapping grids to pinpoint the exact location.
When we get excitation of more grid modules we can be sure the position is more exact.
The more the better.
My speculation is the reason for this behaviour is because those are Sensor-grids not Enviroment-reality-grid.
And the sensors are sensors, not reality i.e. they are unreliable and fuzzy.
Thats why we need many overlapping grids.
If it was the case that we have virtual environment where everything is known with precision then what we need
is a single grid (scaled to our current scale) OR at most two one linear and one radial.
Now to get to my ask. If my thoughts are somewhat correct. I’m looking for simplification of TBT CC algorithm in virtual environment.
The idea is to use jut one/two grids with exact locations.
In addition the inner-loops L4<->L6b and L5<->L6b are also simplified, where the “kalman-filter”-like behaviour is unnecessary
i.e. I can work with EXACT predictions rather than with UNIONS of locations.
Can I make those assumptions for my goal : Initial naive implementation of the CC algorithm ?