Discussion about Emotions

@jake Personally, I am reluctant to take for granted that these things aren’t observer-bound descriptions rather than concretely existing entities within us?

For instance… How do I know that I’m in a funky mood? Well, I might have a tightening in my abdomen and a frown on my face. Now let’s just limit the “symptoms” of my mood to those 2 things for now.

So, if I ever again get the same tightening in my abdomen and frown on my face - is it always attributable to this thing called “funky mood”? I would say, “No”.

Is “Funky Mood” the same as those 2 symptoms? Well again, I would say no. Those two things are physical states and “Funky Mood” is a concept we agree has certain meanings. (I am no more those 2 symptoms then I am a mini van). Do I HAVE a thing called a “Funky Mood”? Well, again I have the 2 physical symptoms which I have placed a label on called “Funky Mood”, but I could just as well put another label on it like “irritated”? — And, can I point to “Funky Mood” in my brain? And is the thing I’m pointing to (assuming I can point to it) always due to this “Funky Mood” thing?

So there is no actual thing I can point to which is distinguishable as a “Funky Mood”, right? It lives in the domain of an interpreter giving an account (i.e. in the conceptual domain, not in the ontological domain where things are obviously what they are and live in “being”).

So if the additional rigor of what I’m saying is useful, that might mean that certain conceptual agreements exist only by virtue of our mutual cultural convention and don’t really have concrete existence. If the brain “lights up” a certain way when I’m using this label called “Funky Mood”, could it be called something else and is it really valuable in adding awareness or qualia to my AI?

Just some epistemological observations…

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In other words… I personally wonder if there are things which have become culturally accepted as “givens” - which are actually obsolete ways to observe ourselves? And I wonder if that’s so, do we want to put it into our AGIs?

Shame and Pride: Affect, Sex, and the Birth of the Self

This is a revolutionary book about the nature of emotion, about the way emotions are triggered in our private moments, in our relations with others, and by our biology.

Drawing on every theme of the modern life sciences, Donald Nathanson shows how nine basic affects―interest-excitement, enjoyment-joy, surprise-startle, fear-terror, distress-anguish, anger-rage, dissmell, disgust, and shame-humiliation―not only determine how we feel but shape our very sense of self.

For too long those who explain emotional discomfort on the basis of lived experience and those who blame chemistry have been at loggerheads. As Dr. Nathanson shows, chemicals and illnesses can affect our mood just as surely as an uncomfortable memory or a stern rebuke. Linking for the first time the affect theory of the pioneering researcher Silvan S. Thomkins with the entire world of biology, medicine, psychology, psychotherapy, religion, and the social sciences, Dr. Nathanson presents a completely new understanding of all emotion.

I will not pretend to have read the book…I am pretty sure there are major pieces I am missing. I wonder if neuroscience, psychology, and AI maybe suffering from the same problem that education is. Namely, we are all specialists looking at the problem from a specific angle. A mountain of research which gets put into an existing framework. The brain works…no question there, psychology works in the same way education does by assembling little bits and pieces into an existing framework, and AI is trying to marry psychology and neuroscience into it’s own framework. Education could be a third party in this arrangement, and perhaps an important one. We all learned through an education system which is largely the same, so we all assume we already know how that worked. I would argue that it’s a wonder it did work and that the fact it did at all is a testament to the biology of the brain. In other words, I think we all learned in spite of a system of education which could and should work much better than it does. How can we bring all three together to create synergy. Not enough brain theory in education, not enough despecialization (I know my word I made it up…take that zipf) in neuroscience and AI and psychology. Not enough lateral dendrites? Thoughts?

It’s all entirely context based in the individual which is why it’s so hard to pin down…initially I thought of it as rgb pixels making a complete picture but now I see that its rgb pixels which are somewhat different and somewhat similar in each individual…so your picture and mine could be somewhat similar if we both developed in similar circumstances or totally different if our contexts were divergent. Where is @Bitking…we need your guidance Yoda! Obi-wan of you prefer! Perhaps none of us are jedi master just padawan learners.

Considering the limbic system or cortex in isolation really misses the point. As I said earlier - you have to look at it from a system point of view to make any sense of this whole thing.

Some points to consider before I try to put it all together:

  1. What exactly does it mean for a section of the cortex to “recognize” something?
    I know that the Numenta people are putting a lot of effort to get the backward flow to be some kind of location signal so that the sense of touch can be locally combined with a mysterious location signal so that all your bits of fingertips can say - CUP! So what listens to this CUP message? How does the “listener” know what to do with the CUP message?
  2. This might be a bit of a stretch but ask the same question about the fibers from the limbic system. Either we accept the concept that cortex is cortex or we have to say that different parts of the cortex work in different ways. Does the limbic system have changes that we can detect? Can you turn it over and feel edges? That sounds kind of silly to say it and I think that it is just silly when I try to fit it into any kind of workable model.
  3. Now try the same thing with the visual system. The middle of V1 is somewhat the same as the bits sensing the tips of your fingers. For the visual cortex, we have some very good research that documents that it is sensing edges and such but that does not seem to have models of CUP in every bit of the visual field.

Maybe it works differently?

Let’s Identify some of the system components.
First - the larger structures

  • Sensory cortex.
  • Association areas (hubs)
  • All the bits of cortex between the sensory areas and the hubs.
  • Limbic system - thalamus.
  • Major fiber tracts. - sensory to hub direction. (both the WHAT and WHERE streams.)
  • Major fiber tracts - frontal to sensory direction.

On a more local level

  • Layer II Grid-forming cells.
  • Inhibitory cells with a grid scale effective range.
  • Layer IV temporal-sensing cells.
  • Inhibitory cells with a column scale effective range.

For this introductory chat, I am skipping many other system level components that I feel play important parts such as the hippocampus/cortex interface (entorhinal cortex), hippocampus, RAC and the pulvinar. I will try to paint a fuller picture with these and other parts later. That will cover attention and learning including one-shot learning

Talking local but thinking global - the pyramidal cells genetic programming can control the branching density, reach, and targets of each of the major dendrite groups: proximal and distal. The cells can also control the targets of the axons.
By varying these parameters you have the same pyramidal cells but very different behaviors.
The connections of inhibitory cells further tailor this behavior. Taken together, these variables give at least the two types that I will use in the following discussion but I am not excluding the probability that there are other highly useful behaviors in various regions of the cortex.

temporal-sensing (Numenta model) cells have distinct populations of the proximal and distal clusters. The long neck of the distal cluster allows the cell to be biased to firing faster giving the predictive state. The axon projects to the limbic system. There are interconnections with the grid-forming cells and short-range inhibitory cells. These inhibitory cells keep the action local - within the column. This allows the various cells within the column to compete to say that their prediction of the future is the best and suppresses other cells in the column.

Grid-forming cells are the communication specialists. The shorter distance to the distal fibers means that the sensed pattern has no time delay properties - these cells are simple pattern sensors. The communication output is both grid range inter-cell communications and cortical map-to-map signaling. This grid range cell to cell activity is shaped by the longer range inhibitory cells. The competition here is for the grid forming activity. See my HTM Columns into Grids post for more details.There are also connections to the temporal sensing cells.

On a slightly longer scale but still within a single map we have the sensory cells being bombarded with stimulus but no coordinated activity yet. As the real world comes in all of the layer II pattern sensors are all competing to recognize some sort of pattern. As the BAMI paper points to the trained SDRs embedded in the dendrites are like a key that only matches the pattern that they have trained to match. The possibility of matching some other pattern is vanishing low. If the cells do match some bit of a pattern they give the neighbors at “grid range” a kick. If that neighbor is also matching on a pattern it kicks back. Note that this mutual reinforcement will be VERY strong if a large population of cells are all seeing parts of a pattern that they have all learned - rapidly establishing a grid with the related inhibitory cells smothering competing patterns. This also produces a naturally sparse pattern.

Going Map to map - the early stages The temporal cells are excited by their companion grid cells and start predicting. This fires down to the limbic system. Things start to get more interesting now. The thalamocortical reciprocal connection comes back to layer IV and sets up the thalamocortical resonance cycles. Lateral connections in the thalamus spread this activation over the entire area of the grid activation area forming a pool of recognition. This excitation is now propagated to other maps via two pathways:
One is a general activation signal through the thalamus, the second is the projections from the grid-forming cells. The thalamus connection is a simple tonic priming the receiving map with a specific temporal wave to be in sync with the very specific message from the grid-forming cells.

Map to map spreads out This activation of synchronized activity ripples from the original sensory area - relatively weakly at this stage - on it’s way to the sensory hub in the parietal lobe. This projection of axons from the grid-forming cells is likely to be spatially coherent but it is possibly spread out to “smear” the pattern over a larger space. If you are familiar with the FFT process time is converted to space by the arrangement of sampling that groups related signal together by some temporal relationship. It is possible that the same sort of transformation is performed by the arrangement of interconnecting fiber bundles. For example - the spacing of the projecting fibers could give different spatial scaling to different target maps.

Meanwhile - in the limbic system the various need sensors in the body are sorting out which need is the most important. The dozens of interconnected clusters are competing to signal that what they want is the most important thing that needs attention. These cells are more like bundles of oscillators. The needs are not a static pattern but a dance of activity that the frontal cortex registers as an activation pattern. This is the sensory stream that the frontal lobe is sensing and has trained on. This activity ripples to the hub of the frontal lobe.

Meeting of the minds! These hubs (raw sensory, needs, parsed sensory) have long reciprocal connections. These connections of activity go up and down the paths adding very strong activation energy to patterns that match; at a minimum, there is twice as much activity for matching patterns! If the needs of the frontal lobe match up with the sensed environment there is a strong reinforcement that triggers a Global workspace Ignition[1]. Various “side chains” of connections shape this workspace but the counter-flowing river of reinforcement raises this pattern to the level of awareness and tend to suppress all other activity.

Perhaps you are familiar with the cocktail effect. This is a very good way to understand what this reinforcement is like - it is the most accessible part of this process. As you listen to a conversation in a noisy room the recognition of a single stream of words sharpens and shapes your perception stream. As your brain tunes to this pattern, all others are filtered out.

Now what? In the frontal lobe - the best match for a pattern is reinforced and elaborated to some activity. This may be internal to the brain (thinking) or some motor program (acting). Some of these motor programs can be directing the eyes (visual attention) or extracting some sound (listening) As I have stated before - one of the side chains of activity is the loop from the early motor stages to the corresponding sensory stages that form your internal consciousness loop. This Global Workspace can chain to other related activity patterns in a continuous process as the needs sensors continue to prime the frontal cortex. (goal directed activity)

This is so much more but I will stop at this introductory system description.

[1] The Global Neuronal Workspace Model


@abshej - any comments?

@rhyolight - Any thoughts on this?

I’m not looking at in isolation…just not at the same resolution. I see something I try something. I have some stories to tell…I need some researchers to verify. You have much knowledge but the granularity is too high for me… I’m trying to keep up but our goals are different. I was hoping you could tell me if the idea fits with brain theory in a general way…assuming a feed forward feed backward system between NC limbic and AMG

In the system I just outlined - your sensory cortex learns stuff. Your need sensors (the limbic system) riffs on the sensory systems to drive attention and activity.

Which need sensor wins depends on where you are in a “Maslow space” and your prior experience which shapes your perception of the environment.


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Thanks…now I have the motivation to sift through all that you’ve given me…I’ll take it as a yes as far as pursuing…the line of thought. I really do appreciate the detail and breadth of knowledge …far more time efficient than sifting through journals randomly…you could say you’re my own AI. I only need to get close to understanding and if I try a few things in the classroom and they work then I’ll go from there. I trust that the biology makes it happen in humans… I don’t think it’s a teaching or a learning problem but a communication problem…Thanks

I really liked the way you said that @Bitking…the limbic system riffs…do you see the different parts of the cortex riffing on one another too? Could that be how the sdr is formed? I guess I’m just having a problem with understanding the structure here…are the hexagons doing the riffing to produce the chord… and then does the chord then get riffed with other chords?

On a different note…a few key takeaways for the psychology fans.

Emotions were, and are, the semantic representations of the language we used to communicate before there was language.

This emotional communication still exists today but we humans largely are illiterate in it and as a result we automatically filter it out, or grossly misinterpret it except for some very explicit situations.

The emotional dialogue can be understood if both participants are honest and open…and they use words to Express things more precisely.

I think the above explains a lot about us, and our percieved limitations.

In a nutshell:
The SDRs are the little pattern each dendrite senses. One cell may have dozens of dendrites - each is keyed to record a few patterns. Please note that these patterns are local to the cell - they only extend as far as the dendrite arbor can reach. For cells in the cortex that range is between 0.3 mm and 3.0 mm.
Each column (a cluster of 100 or so cells) may sense hundreds or thousands of little patterns local to the column. The grid is the structures that tie these little pattern sensors together into a larger pattern on a single map. Grid spacing is about 0.5 mm.

The entire cortex after unfolding is about 1000 mm x 1000 mm so the individual SDRs don’t cover very much of the brain. The brain is thought to be composed of about 100 areas of local processing; doing the math gives each area about 100 mm x 100 mm area. Since the reach of individual cells is small even in relation to the smaller maps the grid structure gives a mechanism where the cells can work together to recognize a pattern that covers the larger area of an area map.

Not all areas work to form these larger patterns - some work to refine a local pattern.

If you compare a grid forming area to one that is not grid-forming I see the primary difference as whether or not the layer II neurons have reciprocal connections at 0.5 mm spacing. Without these connections, there is still competitive action to recognize a local pattern but no influence to extend that pattern beyond the local area.

And yes - I think these larger patterns do a riff on each other in the cortex.

@gmirey - you may find this bit interesting.


If this topic interests, you don’t forget to check out the links in the article. I found them very informative.

I think I’m starting to get it in a global sense now…man is it elegant. The way things kind of layer one on top of another.

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Totally makes sense … could these perceived preferences have more to do with which cortical regions are at higher states of development at that particular moment (when the vark was taken) because of the context of the individual. Example two learners, one learner spent a great deal of time outside playing in the woods, the other spent a great deal of time playing video games. Should it really be a surprise that the outdoor kid has a more developed motor cortex and the indoor kid has a better ability with his/her visual cortex, but it doesn’t mean that the other regions can’t develop just that those particular regions are further along at that moment because they got used more. The unsupervised learning creates the context…since the teacher was not present during the unsupervised learning the teacher doesn’t know the context.

Thanks for those thoughts. I still need lots of info about this kind of stuff. The reciprocal thing is indeed one of the questions I had. Is it known by direct experiment that whole areas have such reciprocity and some others don’t, or is it only inferred from the preferred receptacle areas for grid cells against others ?

I somehow have difficulty to find precise diagrams or descriptions showing both axonal connectivity “rules” together with dendrite extent. Even the very “look” of axonal branching is quite blurry to me. Some vulgarization source would say “generally a single axon per cell” without telling anything of its branching abilities at the tip, while others would present it as an already quite well stocked tree. My ability to derive anything certain for topological interactions is thus quite impaired there.

But now that I’m writing it, I believe guys at, for example, Blue Brain would have data for most of that stuff… ? Dunno where to look in fact.


Looks like the axon has some arbor. Maybe for depressing the neighbors?



See page 48 and diagram on top of page 51.


The best papers on this are behind paywalls or in books.

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Thanks @Ed_Pell and awesome material @bitking, as usual.