Thousand Brains Hangout with Jeff & Subutai

Education Live Streaming
14

Hi, I also have 5 questions. I’ll try to be there live as well. @rhyolight thanks for organizing this session!

Learning new objects / environments

  1. What triggers the re-anchoring of grid cells? What precisely makes an object/environment “new”? Sustained bursting of minicolumns somewhere, and where?
    Can the re-anchoring fail, thus new object?
    In the 2017 columns paper, the model was explicitly being told that it was seeing new objects (reset to learn a new object). Maybe a re-anchoring failure can inform the object layer (L2/3), and how?

  2. Also, the model description says that “During learning, the location layer doesn’t update in response to sensory input”. Is this separation of learning and inferencing neurologically plausible?

Displacement cells

Me too. Furthermore:

  1. Displacement cells reference 2 locations (or unions of locations). Within a single cortical column at each time one union of locations is represented. How do displacement cells reference the 2nd location? Where do they find it, do they have any long-range input and get it from another column?

  2. In the 2017 columns paper, L5 is proposed to have long-range connections. Within the displacement cells model what is their purpose? Or are they not considered any more?

Composite objects in the hierarchy

In these models, objects are formed by (feature x location) pairs, where the features are implied to be low-level sensorial features.

  1. In the case of a composite object that is made from already-learned pieces, can the exact same mechanism represent the object in a cortical column further up the hierarchy? Where:
  • “feature” inputs are the activations of the object layers (L2/3) of the lower columns
  • The movement vectors to update the “location” inputs are derived from the lower columns’ displacement cells
2 Likes