Brain Building - Q1. Define Intelligence

[Bitking]

@neubie

So can we at least conclude what this model is:

1. Perceiving Information => “joint sensory agency” and “invoke internal representations at will”
2. Memorizing Information => “a database of sorts, where indices of data entries are sparse partial representations”
3. De-memorizing Information => “a database of sorts, where indices of data entries are sparse partial representations”
4. Predicting Information => “All representations are massively associative, so you can easily travel from concept to concept via “train of thought” associations”

All in the cortex? No - I will not agree that we can park any of this exclusively in the isocortex.

1. What perceives? Just passing through the sensory apparatus really can’t be called perception. Recalling existing memorized fragments and standing that up to build a representation in maps of the cortex is actually close to perception but it misses the involvement of subcortical structures in the perception of emotional import.
   Mixing this with recall in this item is not appropriate as this should be grouped with using the indexes to recall representation below.
2. having “surprise” trigger local learning is the closest to a pure isocortex function but it is very likely that this also involves the thalamus.
3. I am not sure what you intend with”dememorizing” but having a partial memory (index in your terms) auto-complete to the nearest match reactivates the memory in the exact place where it was first experienced - Déjà vu. There is reason to suspect that this memory is shared with connected maps as part of normalization of memories during the sleeping process but I don’t think that this is what you are looking for. The feedback path through connected maps surely involves the thalamus but the driver for this has to be subcortical structures.
4. This bit, thinking, involves recall and re-perception in the isocortex but it also involves the thalamus, hypothalamus, HC/EC complex, and very likely the cerebellum. The cortex, by itself, is purely a passive structure that receives some input and either matches it or learns it if it is novel, with the attendant output of bursting to signal the novelty. Perception drives the cortex at one end and subcortical structures (primarily the hypothalamus and cerebellum) drives it from the other end.

By the time you get to these very high level concepts you are very far away from the basic cortical column computation and have moved on to the emergent behavior of large ensembles of hardware. As such, the are not going to be the pure functions you are looking at for your foundation.

As unpleasant as you may find this - Numenta has been working at the same goal as you but seem to have discovered that the cortical column computation is the fundamental unit and this is combined in useful ways that result in these emergent properties that you are trying to describe.