It seems clear that objects are being stored in cortical layers. In the TM layer(s), these objects are sequences. In the sensorimotor layer(s), these objects are spatial. I have been brainstorming about ways to retrieve these objects. Here are my thoughts about it. Please correct me if I’m wrong.
In Temporal Memory ™, objects are ordered lists of active columns (sequences of spatial patterns).
In Sensorimotor Inference (SMI), objects are sets of active columns (allocentric information).
In either case, distal context is not a part of the object representation, although it plays a crucial role in learning the objects. In the TM, distal connections are what arrange spatial patterns into objects by recognizing their temporal order. In SMI, distal connections restrict object expression by enforcing a motor context for spatial patterns.
Each spatial input could represent many objects, and I would like to identify and extract potential objects given a set of active columns representing one spatial input. This seems like it must be possible, but I’m not sure how to do it.
- Would I also need distal context to properly identify potential objects?
- Is a pooling layer required to identify an object?