This topic was pulled out of another (Crazy quilting in the cortex). At this point I’m trying to focus this discussion on the 1000 Brains Theory (TBT). The post below is a sort of introduction to cortical columns in the cortex and the TBT says they are all performing object recognition at all levels of hierarchy.
I have reached the end of this investigation. A few things in my initial notes and preliminary findings were incorrect.
- The structure and topology of major sensory field projections can change with learning
- The patterns formed by “minor input property projections” and “low level input patterns” are not so different, they are both the expression / extraction of some feature at a location
I thought initially that striping patterns found in cortex were expressing some property of how cortical RFs responded to certain input patterns in sensory input. I was hoping that understanding these patterns would tell me something about cortical columns.
I now think it is more likely these artifacts are expressions of the structure of sensory input to the cortical sheet, not the lowest level responses to the input within the cortical sheet. I still like to think about all these response properties as “echoes” of sensory input into a vacant cortex.
These patterns seem to be a way biology has found to spread topological information across a substrate without dominating local spaces. For example it allows both eyes to project their topology across the same area of striate cortex, allowing it to have a more complete local picture. In somatic cortex, it allows different types of nerve input on the skin to express themselves across the somatic cortex substrate.
Another conclusion is that V1 and S1 are probably not as dissimilar as I thought. The cortical columns shown in Demonstration of Discrete Place-Defined Columns in the Cat CI are the cortical columns we are looking for.
I also think you can see some evidence of potential columnar structures in V1 as shown by H&W:
This looks to be the best evidence for columnar structures in visual cortex, although it doesn’t say anything about receptive field qualities of the columns. While V1 certainly has a nice continuous global projection of the FOV across striate cortex, hints of these columns are found in these echoes of orientation coming from the retina (I believe the retina might be doing some very low-level shape recognition before cortex is involved).
It is still unclear whether the RFs of these columns are nicely grouped for all neurons in the column as clearly seen in somatic cortex, or if each cell’s RF is more independent and not overlapping its neighbors in the cortical column.
@bitking with regards to level-skipping and your “well-shuffled” argument for these striping patterns, I’m no longer sure they apply. If these striping patterns are purely artifacts of sensory input as I believe they are, they would not be playing a role in hierarchical understanding. As the to sensor fusion problem this idea theoretically solves, I don’t see how you need it at all if each column is doing object representation independently of other levels in the hierarchy (1000 brains). If you allow that each cortical column in the cortex is doing object recognition, you solve the sensor fusion problem.