Jeff Hawkins and Marcus Lewis on Grid Cell Oscillators - February 3, 2021

Building upon his prior grid cell model, Marcus Lewis explores ways to transform an array of 1D grid cell oscillators to 2D grid cell modules. He evaluates and explains one possible deterministic mapping technique that could be used to achieve this.

In the second part, Jeff Hawkins attempts to explain the physical structure of minicolumns and how they might interact. He proposes a new mechanism that introduces the idea of a voltage controlled oscillator in dendrites for dimensional movement in grid cells. With this mechanism, the grid cell will represent much more complex interactions and could possibly explain how the cells make connections to each other.

Research meeting on Marcus’s new grid cell model: Marcus Lewis on Using Grid Cells as a Prediction-Enabling Basis - December 21, 2020 - YouTube

Paper Jeff referenced on oscillatory interference:

Paper Subutai mentioned on gap junctions between pyramidal cells: Gap Junctions Between Pyramidal Cells Account for a Variety of Very Fast Network Oscillations (>80 Hz) in Cortical Structures - ScienceDirect



One question, in the Jeff’s drawing - dendritic tree, the green circles stands for minicolumns. But to what exactly is the dentritic branches connected? The last cell in the minicolumn? To some cell in minicolumn?


While @jhawkins said there are loads of details still to be worked out, at about 28m51s and 30m35s he speculates the connection to be a bipolar cell in each minicolumn.

(I also heard him mention spindle cells, but I couldn’t find the time mark. Maybe I’m mistaken).

Of course, what exactly triggers these bipolar cells is the other side of the grid cell puzzle.


This might be relevant for the discussion. It is a paper published Feb 9, 2021.

Frequency of theta rhythm is controlled by acceleration, but not speed, in running rats

Emilio Kropff,James E. Carmichael, Edvard I. Moser, and May-Britt Moser


The theta rhythm organizes neural activity across hippocampus and entorhinal cortex. A role for theta oscillations in spatial navigation is supported by half a century of research reporting that theta frequency encodes running speed linearly so that displacement can be estimated through theta frequency integration. We show that this relationship is an artifact caused by the fact that the speed of freely moving animals could not be systematically disentangled from acceleration. Using an experimental procedure that clamps running speed at pre-set values, we find that the theta frequency of local field potentials and spike activity is linearly related to positive acceleration, but not negative acceleration or speed. The modulation by positive-only acceleration makes rhythmic activity at theta frequency unfit as a code to compute displacement or any other kinematic variable. Temporally precise variations in theta frequency may instead serve as a mechanism for speeding up entorhinal-hippocampal computations during accelerated movement.