Cortical grid cells and Abstract ideas


I assume you are talking about presaccadic remapping and whether RFs jump or spread.

I haven’t read this source fully. It’s on LIP rather than FEF.

There are a lot of possible complications though.

Methods are pretty indirect for remapping studies so there are other ways to interpret results. It might be a spread sometimes and a jump other times depending on the thing being studied (layer, region, cell type, time before the saccade, subthreshold vs. firing, etc.) since it’s different in different layers. On average although with a lot of variation by cell, cells projecting to superior colliculus lose their response to the current visual stimulus as they gain their response to the upcoming post-saccade stimulus, unlike some other layers. It could be a purely attentional effect, so possibly just revealing parts of receptive fields which are less influential normally but still are functionally important.

It might not even make sense to think about this system just in terms of receptive fields, which could make hypotheses about remapping more self-confirming especially because remapping seems very noisy. For example, if you recorded from HTM’s temporal memory, you could argue that all cells in the same minicolumn have exactly the same receptive fields so minicolumns are therefore for robustness to noise (but the noise is actually sequence context). You could find particular activation patterns (which are actually representations of places in sequences) and make arguments about what those activation patterns are for, such as correlations between the activity patterns and pretty much anything (since a lot of things produce different sequences) and claim a result.

That’s not to say that remapping isn’t interesting and useful evidence. It’s a big clue but hard to work with.


Bitking, thanks for this, it is giving me tons to think about.


Thanks for the link!
Different paper but the same general information.


A definition of abstract is “disassociated from any specific instance” (source: Merriam Webster). Numenta’s 2017 Columns & Layers paper explains one form of abstractions: view-point invariance. Viewpoint invariance is abstraction because there is a single abstract representation which responds to many concrete sensory representations of an object. And this does happen in the cortex, in layers 2/3.

My hypothesis is that the basal ganglia drives the frontal cortex. The basal ganglia is known to perform reinforcement learning, meaning that it predicts rewards and penalties. One of the outputs of the basal ganglia is decisions, and the basal ganglia is capable of turning motor areas on/off to enact those decisions. The Striatum is the first piece of the Basal Ganglia; it receives input from the entire cortex in a topologically precise manner and this is the only pathway from the cortex into the basal ganglia. Therefore all information which you use to make a decision needs to pass through the Striatum. The Striatum helps the basal ganglia by identifying relevant information and filtering out irrelevant info. I hypothesize that the Striatum projects to the frontal cortex via thalamic relay cells. I don’t have a lot of evidence but I think that this hypothesis explains a lot. It explains how the frontal cortex can use unsupervised learning and also understand rewards. Under this hypothesis, the frontal cortex only sees things which you’ve identified as either rewarding or punishing.

The reason I say that the magic step of abstraction happens outside of the neocortex is because the Striatum is responsible for seeing attributes such as danger, attractiveness, and reliability. The frontal-cortex is responsible for building a model of these important attributes, and that model includes grid cells which encode locations in this “emotional space”. An example of a location which frontal-cortical-grid-cells might encode is the reliability of a tool, which degrades as the tool is used. The frontal-cortex identifies when the tool is likely to break; and the Striatum sees the frontal-cortical model and evaluates when its time to stop working and replace the tool (before it breaks).


Probably you are right there (I can’t fully understand it). Nevertheless, if we take a look back at HM case (Henry Molaison), the 2/3 of the HC/EC/ complex was removed (

Being a bit naïve here, my take is that EC and grid cells are mostly involved in new episodic memory formation. HM kept the capacity to form procedural memory. I think that hippocampal replays use the grid cells to determine where in the cortex the replay should be done (and where the sensory stream should be fast-stored in the HC). Therefore, is just a translation mechanism from HC addresses to cortex addresses (some sort of TLB :slight_smile: ) You might observe grid alike behavior elsewhere because the “TLB” can have multiple levels (?)

I don’t think that HM lost the capacity of using abstract ideas. Only the ability to create new episodic memories. Replays are needed because up in the hierarchy the events are really sparse in time. Note that replays even occur when we are awake.

Just my 2 cents


That’s not completely true if I recall correctly. The cortex also projects to the subthalamic nucleus. It’s not part of the basal ganglia but the cortex also projects to zona incerta, which inhibits the thalamus or can disinhibit by cells inhibiting other cells in ZI. These are just nitpicks intended to help expand ideas.

The striatum indirectly (via other parts of the basal ganglia) projects to thalamus. A small number (one?) of thalamic nuclei are thought to lack any proximal excitatory inputs, meaning they are driven by the basal ganglia (or rather, driven right when inhibition from the basal ganglia turns off because of tonic/burst mode).

The prefrontal cortex has some regions involved in identifying different types of value (like intrinsic value like food or value not determined beforehand like food brand preferences). I don’t think all PFC regions exclusively encode things with positive or negative value, but there are at least some regions with strong bias towards responding to those things.

In what you describe, I see the model building part as the abstraction step and the value-detecting step as a gate. Maybe that gate is what makes the cortex do abstraction rather than just encoding what it sees, but I don’t see how that works. I think of abstraction as things like recognizing two completely different objects as the same category (like a cup you’ve never seen before or whether something is food) or making inferences, like understanding the idea conveyed by a sentence or figuring out where an object might be. I think these things require representations of predictions and making predictions from predictions, probably imagination. Two objects are in the same category if they share predictions (which is basically context except it doesn’t have to occur every time it is represented).


Well, the best way to check a hypothesis is to build a working model :slight_smile:
At the end of the day, from the computational perspective, it’s not so important where, but what and how it’s happening. If you believe you understand how it works, it’s a good idea to implement it in code.


Regarding ideas and navigation, a new paper co-authored by Moser (Nobel Prize for his work on grid cells) has just been published in Science.

“Researchers find evidence that our experiences and knowledge are oganized in the brain in a spatial fashion”

Probably worth reading, but behind a paywall… :slightly_frowning_face:


I have been reading this paper.

Yup - paywall.


I’m sure that the brain uses spatial coding for abstract patterns. My two points in this respect are as follows:

  1. The grid cells aren’t the foundation of this organization and play supporting role only.
  2. There isn’t a need in the six-fold symmetry of grid cells in computer modelling to get the same functionality.

And thank you for the link!
BTW, the first time I heard that it’s not about the grid sells in the first place from Edvard Moser - I thought if he was thinking about it in this direction, it couldn’t be a biased point of view :slight_smile:


Not paywalled article: