Max Bennett: An Attempt to Model The Neocortical Microcircuit in Sensory Neocortex - Sept 9, 2020

This week, we invited Max Bennett to discuss his recently published model of cortical columns, sequences with precise time scales, and working memory. His work builds on and extends our past work in several interesting directions. Max explains his unusual background, and then discusses the key elements of his paper.
Link to his paper:

This is a long article and I think it would greatly benefit if it were more focused on a single or few aspects of the brain, instead of proposing a grand theory.

I think it is a mistake to focus on delayed input tasks. These tasks are challenging and performing them involves many brain regions and many different mechanisms. This means they are not great for studying an individual phenomena in isolation.

This article proposes a hypothesis for how the neocortex learns viewpoint invariant representations (“unique sequence codes”). A projection from the hippocampus to cortical layer 5 will hold a set of layer 5 cells active throughout the duration of a sequence, and Hebbian plasticity will cause those active cells to associate with all of the elements in the sequence. There are several issues with this hypothesis:

  1. This does not actually solve the problem of viewpoint invariance, rather it moves the challenge from the cortex to the hippocampus. How does the hippocampus know when to hold the cortical activity constant versus allowing it to change?
  2. Sequence learning (viewpoint invariance) is a critical function of the cortex, and you’re proposing that it happens far away in a smaller brain region. This seems like an information bottleneck. There are many cortical regions, all operating independently and in parallel, but there is only one hippocampus.

I have a competing hypothesis for how the neocortex learns viewpoint invariant representations. I have described it in this video: Video Lecture of Kropff & Treves, 2008


I think that this is a mayor problem for the proposal, too.

Nevertheless, HC is playing a mayor role in the learning process. You might be unable to reach a practical system without it. In fact, I think that BG/Thal and other subcortical structures/HC are required to “digest” any complex sensory flow.

You can’t have a “practical” hierarchy without them. Perhaps this model is not the right approach to it, but you can’t ignore them. It’s all or nothing system.


I don’t know if Max is watching the forum, but I would be more than happy to work with him on developing simulations to test out his ideas.

I’ve done a variety of simple code sketches to teach myself the basic SP/TM algorithms and to visualize the evolution of the resulting networks. I feel like I’m ready to start working on a more detailed C++ implementation, but I think I’ve been waiting for the right motivation and/or collaborator to come along. It sounds like we both have about the same amount of free time to spend on the project, so maybe it would be a good collaboration.

Max; Feel free to reach out if you’re interested.

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