In that paper, TRN (and corresponding L6 projections) seems a bit underestimated
How about the RAS? The ties to the the nest of thalamic nuclei? The other sub-cortical structures?
Where do you stop? It is all tied together into bowl of gooey spaghetti-like connections.
In the end these other systems will have to be addressed but it may be too much to expect that right out of the gate.
Part of why my own work is proceeding so slowly is that I am trying to tie together several models into a working whole. Connecting a subset of the whole requires “filling in the blanks” to make up for the bits that I am not incorporating; some of these band-aids get pretty sketchy.
I do see some value in trying to abstract some minimal stand-alone systems and work out how they function.
I understand that you need to prune unnecessary details . But the TRN role, IMHO, seems to be relevant.
A little interesting video about it
Thanks @vpuente. Being a visual person myself, I tend to absorb information from videos a lot easier. The process they described looks like a good candidate for addressing the “switching between objects without a reset” problem that has been discussed on some other threads. You can basically blast the new context when it appears in the input stream to quickly switch from one object to another, then resume normal operation.
The RAC/RAS has been postulated as the “Searchlight of Attention” since this paper by F. Crick:
If you google the term “searchlight of attention” you can see that many papers since this one explore this concept (pro and con) and add considerable insight to the workings of this structure.
It is certainly an important adjunct to the interplay between the Thalamus and Cortex - I am not sure if the attention function should be a stand-alone feature apart from the data path or an inseparably part of function of these structures.
My personal take runs something like this; I see that the thalamus does at least two different functions in relation to the cortex.
One is closely related to the feedback path in the general direction through various hierarchies as described in the first post above.
There is nothing controversial here. I will add that this path is in parallel with the direct corticocortical pathways. I see the cortico-thalamic-cortical loop as being a command and control pathway where the cortico-cortical pathway is an information pathway.
The second function is also a control function but with a very different purpose - to activate or coordinate the basic information processing method of the cortex. It would be very wasteful to activate large swaths of the cortex where this is no information to be processed. The signal that something is to be recognized and/or learned would be a widespread “surprise” signal from local areas of the cortex. I see that this would trigger the start of traveling waves in that area of the cortex. Due to the map-spanning connections of the thalamus this same C&C function would be relayed to corresponding areas of related maps.
You may have seen this before but I invite you to read it again in light of this discussion:
With these thoughts in mind - the RAS is positioned to compare the (relatively) local activity between the cortex and thalamus. Given the two functions I have outlined above - and assuming that form follows function - where would this fit in for comparing the activity levels of the two structures?
One uses bursting to signal surprise, one uses bursting to jump-start activity. The RAS is looking for something and bursting seems like a very easy to detect to signal that could be sensed. What if it is simply acting to equalize activity between the two structures? In the process it would act to detect surprise and activate processing on the related information pathway, all using simple and relatively local functions.
This is agnostic as the WHAT/WHERE functions and is instead - a cortex wide processing method. Please note: Hierarchy/pathways is established here by genetic programming and is outside the scope of this discussion.
This is a consciousness pointer that index through temporal memory.
Um, give this a read and get back to me …
Cool @Bitking. I see we have common thoughts. Have any thing new to tell? This from
a year ago.
I use pattern loop too. They are also a good way to compress data.
I am certainly into computers and have been programming for many years but on this forum everything should be based on the biology of the brain - that is the mission here. We try to restrict our hardware to the kind of processing that can be found in the brain.
The brain does not have the usual tools used in classic AI work. There have been many other methods tried (LISP/Symbolic AI, expert systems, heuristic systems, reasoning systems, block worlds, knowledge based systems [frames and scripts], decision trees, propositional and first order logic, inference engines, the list goes on and on) to make an AI but that is not what we do here.
We have “encoders” to simulate the transformations in the early sensory system to formats compatible with processing suspected to be performed by the brain.
I do my non-biological processing on other forums - as should you.
You are correct that I have posted most of my main ideas over the last year: this is the distilled results of study of the biology of the brain since the late 70’s. My main ideas are moving forward slowly as I refine some of the “iffy” areas; there are some sub-cortical areas that are still a complete mystery to me. It is unlikely that I will be adding any bold new concepts to the central big picture any time soon; mostly at this point I am tweaking around the edges.
My main focus now is to reduce these concepts to working programs.
I think that the thalamus is as closely related to the basal ganglia as it is to the cortex. The basal ganglia uses reinforcement learning to predict when the animal will receive rewards or penalties. Animals use the basal ganglia’s predictions to attempt to maximize their cumulative rewards, which drives behaviour. The basal ganglia however does not directly connect to the muscles which control behaviours, instead the cortex connects to the muscles. The thalamus is the major pathway from the basal ganglia to the cortex, and therefore is at the interface between unsupervised and reinforcement learning.
I hypothesize that the function of the thalamus is to control the cortex, with the goal of maximizing the animals cumulative rewards.
4 posts were split to a new topic: An alternate view of memory functions
I think that TRN is just a coincidence detector (i.e. a comparator) between L5 and L6 projections. Note that at very low level (such as auditory cortex A1) there is no notion of objects. Just frequency changes.
BTW (in my humble opinion) I think the pursuit of vision (or any other motor involved sensor) as the main goal is introducing a lot of unnecessary difficulties to understand this. Any “cognitive-level” consideration is way above the bottom of the hierarchy (perhaps 10s of levels). I think that the principles at the bottom are the same as that at the top, but “discover” those principles from “top” observations seem pretty hard to me.
Just my 2¢
By “object” above I was referring to the activity in the “output layer”. Numenta’s view is that object representations exist in all hierarchical levels.
Of course the highly abstract concepts are still going to be higher in the hierarchy as you would expect. But HTM proposes that even the very lowest levels are capable of doing a lot more than traditionally thought.
BTW, for reference (I just realized my previous post lacked context), I was referring to the process of “reseting the output layer when switching to a new object” from the Columns Paper. The circuit described in that video (or something similar to it) seems like a good candidate for triggering a “reset”.
Nevertheless, I have some doubts about that view. Seems quite cost-inefficient to do so; you will use multiple synapses across the hierarchy to store information from the same high-level object? Seems more synapse-efficient to collapse as much as possible common information from different objects in lower levels and produce the disambiguation across you move up and use local redundancy in synapses to increase resilence.
I agree with your view, and this is one area with HTM theory that I struggled with after I first encountered it in Matt’s “HTM Chat with Jeff”. I think where it started to click for me was after a couple of realizations. I described these ideas here, but a quick summary
- The logical boundary between hierarchical levels is actually between layers within the same region (not the connections between regions)
- When a new unfamiliar object is encountered, it may require a deeper hierarchy to initially represent it, but as it is encountered more and more frequently, the abstraction can be pushed further down the hierarchy
I believe it is this basic architecture which enables some of the less traditional forms of hierarchy that are seen in the brain (horizontal connections between apparently separate hierarchies, feed-forward skipping levels, and so-on).
This landed today, summarises and references a ton of recent papers on thalamus function:
Is it difficult to suppose that the extensive connections of the neocortex with the thalamus are there because thalamus is an integral part of the nervous system and not because it is essential for intelligence?
There is no functional theory supporting either and the only thing we have to go on is the circuitry, Why one approach and not the other?
The thalamus might be important for tuning the mechanism towards one aim or other purpose, which could be a supervisory element over neocortical functioning. Survival is what we need the intellect for and no one will be surprised if we come across organs that monitor just that.
I have heard that reciprocal connections to the thalamus can result in entrainment of temporal patterns within the cortex with those coming from external sources such as speech, and may ease processing or help with synchronization.
The thalamus could just serve oscillations, but that is unlikely because all inputs to the cortex pass through it. When you theorize about what things do what for intelligence, there’s always the possibility that the thing is not involved in intelligence, so I think you just have to wait and see how it fits into the bigger picture.
Hot off the presses:
Shepherd GMG, Yamawaki N. Untangling the cortico-thalamo-cortical loop: cellular pieces of a knotty circuit puzzle. Nat Rev Neurosci. 2021 Jul;22(7):389-406. doi: 10.1038/s41583-021-00459-3. Epub 2021 May 6. PMID: 33958775.
In the abstract “We consider recent findings in the context of established CTC and CC circuit models, and highlight current efforts to pinpoint cell type-specific mechanisms in CTC loops involved in consciousness and perception. As pieces of the connectivity puzzle fall increasingly into place, this knowledge can guide further efforts to understand structure-function relationships in CTC loops.”
Hits all of my buttons (circuits, loops and consciousness).