What does the cerebellum do?
sarahconstantin.substack.com
sarahconstantin.substack.com
1. I'm very uncoordinated, with a noticeable intentional tremor
2. I'm particularly bad at sequencing dependencies for projects/errands/household tasks. I have to write down even fairly simple sequences of subtasks or get lost in yak-shaving loops
3. When flustered, I make very distinctive disfluencies in speech around conjugations (swapping "but"/"and"/"although") and sequencing (ie, placing objects before subjects/verbs) in sentences as well swapping relationships (referring to someone's parent as their child or vice versa, swapping "you" and "I/me", etc)
4. I tend to have a "ground up" approach to writing (building clauses first and then moving them around to construct sentences), which doesn't resemble the approach of other people I've shoulder-surfed.
All of these are fairly mild in terms of life impact, to be clear (or perhaps I'm just able to satisfactorily compensate for them in various ways) but I wonder if they all share some underlying minor cerebellar dysfunction.
Great ape brains are distinguished from monkey brains by their larger frontal and cerebellar lobes. The Neanderthals had bigger brains than us but smaller cerebella. And, most strikingly, modern humans have much bigger cerebella than “anatomically modern” Cro-Magnon humans of only 50,000 years ago (but relatively smaller cerebral hemispheres!)
https://ourworldindata.org/grapher/average-height-by-year-of...
https://www.dailymail.co.uk/health/article-12868421/american...
Worse for city kids:
https://www.scientificamerican.com/article/rural-children-no...
Having to think things through slowly step by step may reveal errors other's glossed over...
the cerebellum is important. But maybe, since we really know less about the brain than we think we do, differently wired does not equate 'stupider'. It takes all sorts to make a world.
I agree with the language part, tedious... but maybe in certain situations it might be useful.
One example is how the change from hunter/gatherer to agricultural lifestyles may have rendered the strengths of the hunter’s brain a weakness in an agricultural society.
But I can't imagine any change in this split in responsibilities will happen on human relevant timescales. The cerebellum is probably not evolving very fast anyway, while the cerebrum might evolve comparatively faster but it has no pressure to do it. And "faster" still means tens of thousands of years.
I don't know how it would impact our evolution long term.
Turns out studies have confirmed the overlap in these conditions and also linked it with reduced grey matter volume in the cerebellum:
https://psychcentral.com/adhd/postural-sway-adhd#postural-sw...
“The linguistic metaphors we use, at least, to talk about ideas and abstractions, are never more than one, maybe two, steps away from a hand moving or rearranging something”
And the Glasgow scale is exactly that, how people physically respond to stimulus with a body movement, and subsequent complex body movements - eg just humans vaguely deciding - is how we treat for levels of consciousness.
It’s not scientific at all is the point and is very “folk-physics mental model with objects” to the OPs original assertion
Kind of like how object permanence [0] must be learned by babies, slowly worked into their internal model, even though "things don't usually vanish when they go behind other things" seems like reliably low-hanging fruit for any process (whether evolutionary or meddling demigod) to wire up as instinctual physics knowledge.
In A.I., we see this with hard-coded, assembly FSM’s vs interpreters running high-level code. The former works with high-efficiency out of the box but can’t change behavior or improve much. The latter does nothing until it’s taught the extra knowledge (interpreted codes) which also might have new behaviors (functions). Many game developers switched from hard-coded assembly to interpreted code for AI agents for that reason.
So, it’s not under-developed: it’s a better-developed component with different tradeoffs.
Holy assumptions batman. Homo sapiens aren't "superior", that's a terrible starting place for a hypothesis. There are plenty of metrics a human will never beat other species. Reaction time is a great starting place.
It's like you're saying "We humans are the smartest in the world. Smarter animals are better than other animals, so we're better than all other animals."
A giraffe may just as well believe "We giraffes have the longest necks in the world. Animals with longer necks are better than others, so we're better than all other animals."
"Intelligence" itself is not well defined anyway. It may as well mean thinking like a human.
Yet what have they done with their long necks?
Of course humans define the metric. Who else could?! Lmao.
Let's ask the giraffes what intelligence means... oh wait.
Maybe we can't name it, make it's not a competition or leaderboard, but you can't deny Humans are at the top of something.
It's giving me lots to think about with regard to motor impairment. (Basically, I'm reviewing my prejudices and nodding due better understanding the plight of afflicted individuals.) [0]
My sister, who is a choreographer, had some interesting views on how movement could be used as therapy. (Specifically, crawling, as a base-level movement.) I thought that was woo-woo, but later I read that there was some medical support for this.
This is pretty widespread in controls, actually. The dominant control technique for legged robotics is model-predictive control ("MPC") which explicitly uses such a predictive model to determine the best inputs to the actuators.
https://www.npr.org/sections/health-shots/2015/03/16/3927897...
Now I guess I'll have to tell 'em
That I got no cerebellum> He was born with a parasitic twin growing out of his back, which was incompletely formed and surgically removed
Materially;
That’s bad news for anyone hoping to simulate a brain digitally. It means there’s a lot more relevant stuff to simulate (like the learning that goes on within cells) than the connectionist paradigm of treating each biological neuron like a neural-net “neuron” would imply, and thus the computational requirements of simulating a brain are higher — maybe vastly higher — than connectionists hope.
It's a model we have, it will get updated in order to be more useful. Every engineering field builds a model of reality. Who are the connectionists? Is this some kind of "they people" label for, what causes fear in a typical layperson?
Connectionism isn't and never was about trying to simulate the biological neural networks and other anatomy. As you said, it's about emphasizing the network and network emergent phenomena over isolated pieces (e.g. "grandmother neurons" or strict localization of brain function). At the information processing level the contrast is to classicism/symbolicism that tries to explain cognition as atomic and modular operations on symbols.
As a software engineer who did neurosurgery residency, my intuition/guess is that the cerebellum is kind of like the FPGA of the brain.
The cerebrum is great for doing very complicated novel tasks, but it takes time and energy. The cerebellum on the other hand is specialized in being able to encode common tasks so it can do them with quickly and efficiently. A lot of our motor learning is in fact wiring the cerebellum correctly.
This can actually lead to an interesting amnesia, where a person can learn a skill (cerebellum) but not remember learning the skill (cerebrum). So you could end up with a person who would think that he had never seen a basketball hoop or basketball before but could be doing layups, dunks, and 3 pointers with ease.
It just made me start thinking and then I realized perhaps another analogy is a just in time compiler where code or skills used often enough, your body manages to compile into native neurological code and stores that appropriately.
A less-volatile form of L2 cache.
Food pocketed in my cheeks are the CPU registers?
I would think fridge is RAM, L2 is table, L1 is plate. (I am deliberately ignoring the pun potential for Cold Storage.)
But other than bickering about the exact mapping, I don't see the problem with that analogy?
It's an analogy for a reason. It bothers me when people combat analogies so incredibly hard. Of course, it is not really fitting or the same thing - it's an analogy.
http://mechanism.ucsd.edu/teaching/w12/philneuro/metaphorsan...
There are a few that have started suggesting quantum mechanics playing a large role in cognition, but very few take them seriously (obviously it has an effect, but likely much can be understood more classically, etc).
The fact that few are moving toward that style of thinking seems to give a bit more credibility to NNs being closer to the correct model. If spiking NNs take off more, we'll probably see more arguments around that, and if Blue Brain's full in-silico modeling takes off we may see the succinct description given by those studies used to describe ideas. However, to first approximation, NNs and spiking NNs aren't really a bad way to reason about large descriptions of brain dynamics, in many circumstances.
Instead people seem to just equate two different complex things they don’t understand with each other.
Though not mentioned in the post, schizophrenia (oddly enough) is also tied to cerebellar dysfunction: https://neuro.psychiatryonline.org/doi/10.1176/jnp.12.2.193#...
Is there any way to induce that state exogenously?
Some thoughts include dopamine / pain receptor reinforced learning. Maybe there's a faster way?
Any signal, that's the point. The cerebellum learns the patterns of signals involved in motor control.
This is why you train your skills by doing the correct movement over and over again. Once the cerebellum has adjusted to the correct motor signal patterns the correct movement will become effortless.
Yes, but can you make this to go faster?
When a motion "feels good", or is painful, probably means you learn. So chase those.
For now, opportunity cost rules the day. I'm 120% maxed out.
Its a active area of research in sports and DoD. As you'd theoretically be able to train marksmen and athletes at a much faster and better rate. However, even really really fast computers aren't quite fast enough to apply the adverse stimulus to 'wrong' movements/firing.
Also, your computer better be really accurate and never mess up, or that person is going to have a hell of a time retraining their brain. Also, their brain may view that the clouds/temperature/itchy grass/breakfast are the reasons for the adverse stimulus, as this is all happening at in subconscious time frame. So, good luck there.
The feedback loops are often long. Getting a review on a performance, etc.
If a device were set up to trigger pain within some milliseconds of an incorrect activation, surely we could speed this up?
[0] https://pubmed.ncbi.nlm.nih.gov/37280397/
[1] https://www.nature.com/articles/s41386-022-01389-z
[2] https://www.frontiersin.org/articles/10.3389/fpsyt.2021.7246...
That got me interested: since the wiring is so long (from limbs to cerebellum), what kinds of motor learning?
Do we know, if cerebellum needs more energy than the rest of the brain?
I'd imagine it's things like training a dominant hand. The skills required for precise motor control, to produce the right movements for e.g. handwriting. Since the wiring is so long, and feedback is delayed, you need to be able to precalculate these movements.
Also imagine how e.g. an intent to move somewhere actually gets implemented. You don't always have to think about each individual step of walking, or pay explicit attention to things like your sense of balance. You probably don't even have to choose that you're going to walk, or think about how to get up. When you want to go somewhere, you just do it, and somehow it's all calculated for you and happens.
When you try to move a specific limb, how do you know which muscles correspond to that limb? In fact, how many of those muscles can you even individually address? You can learn to individually address them, but I bet you don't come with that ability by default.
Then of course there's the question of what even causes your limbs to move once you will them to move.
How about neurons in the gut, I've read somewhere that intestines are lined up with some neural "mesh". Is that only for signal transmission?
Fully autonomous muscle movements like heartbeat, or the peristaltic motion of the gut, are not directly controlled by the brain, but they certainly respond to signals sent by the brain – eg. brain processes sensory data, determines there’s a danger, upregulates the pituitary gland which starts secreting adrenocorticotrophic hormone, which once it reaches your adrenal glands, causes them to start producing adrenaline, which in turn causes all sorts of changes all over the body related to the fight-or-flee reaction.
The skeletal muscle, though – I don’t think its innervation is capable of anything but reflexive motion without the brain telling it what to do.
Obviously that’s one side of the equation, I don’t have any surgeon friends I know well enough to give the opposing view.
Though some people are less burdened by golden handcuffs and sunk-cost fallacy
Plus, I've never met a happy (or sane) neurosurgeon
Sure, the hemmhorage needs to be fixed, so you're preventing further damage, but every cut may cause unknown ramifications. Anyway, I'm postulating a neurosurgeon would be aware of this, and have to carry that around with them.
I value the former and find ways to discount the latter. So I am very happy. Though sane or not would be up to others.
Seems perfectly reasonably to switch to a lower stress career at some point.
I ended up becoming a radiologist. Never heard a radiology resident quiting, although have seen a few residents get kicked out for mental issues or gross incompetence.
How on Earth do you get to "resident" and have "gross incompetence"?
There are sooo many gates before getting to be a "resident" that this completely baffles me.
Residency: move to a different location away from family, no longer living in a dormitory environment with the expectations associated with being a student but are now a real adult making your way in the world. Suddenly you have to make the whole package work on your own without laundry/cooking/mental health/financial support.
Now you can no longer put 100% of yourself into your studies, but instead can only manage the 60 or 70% that most people can muster when they have to actually maintain their physical existence while also meeting their professional expectations.
I'm an anesthesiologist. There are people who wash out because they just don't have the temperament for it. They're not dumb, they're not even bad doctors, they just aren't mentally equipped to sit back and relax while running a code.
However think of it more like switch or a router between the PNS/CNS (minus vision) and the “higher brain“ longer term planning systems.
I know a lot of people with the opposite problem.
I also wonder if neurodivergency affects this region. I'm autistic, so my brain is detail-oriented. Sometimes it feels like I can perceive "neural circuits" that are implemented by the so-called FPGA. When I have a compulsive behavior or trigger, I can sometimes observe the entire execution flow, not just the result. I think that's neat.
Out of curiosity, having the kind of weird symptoms not far from what you describe as weird amnesia, do you know any books / resources to understand advanced brain neurology like this ?
Thanks in advance
I was also a supervisor in a competitive company with people gunning for my job. The Recession was not a good time to be disabled. I feared demotion or termination. I hid my injury while trying to get back in mental shape. They chalked up occasional forgetfulness to the stress we were all under and my constant partying. (That was before I was in a relationship with Jesus Christ and gave up those sins.)
Eventually, one of my recovery strategies was to take note of the specific things I did on instinct, think about why I did them, and re-create the mental models. I’d also just ask people how they did things and what they learned works best. Many were people I trained with my prior techniques who re-taught them to me. By practicing those, I both re-learned my mental model of how to do the job and connected it with the instinctual wiring.
There were one or two other trucks that helped. That was the part relevant to your comment, though. I never quite got back to my old level of performance. Capitalizing on how intuitive memory is different than conscious memory has helped me in many places ever since. I just keep breaking it into simple things that I repeat over and over to. Then, keep applying those pieces in new ways to keep my brain fresh.
AI, on the other hand, is designed to solve specific problems efficiently, and it can be engineered to mimic certain aspects of human cognition without necessarily needing to understand the underlying mechanisms.
While it's possible that AI could eventually help us better understand the brain, I believe that advancements in neuroscience will continue to be crucial for unlocking the full potential of AI. Understanding how the brain processes information, learns, and makes decisions could lead to the development of more sophisticated and human-like AI systems.
The brain is not like a neural network where the only thing that is “learned” or “updated” is the weights between neurons. At least some learning evidently happens within individual neurons.
That’s bad news for anyone hoping to simulate a brain digitally. It means there’s a lot more relevant stuff to simulate (like the learning that goes on within cells) than the connectionist paradigm of treating each biological neuron like a neural-net “neuron” would imply, and thus the computational requirements of simulating a brain are higher — maybe vastly higher — than connectionists hope.
I had heard this as well close to ten years ago on some NPR radio show: That researchers had reasons to suspect that a whole lot more processing happens within the synapses themselves.
Does it? I’d think this was an absolute gimme.
There is a second kidney, lung, eye etc, but a hot spare isn’t quite the same as a completely different structure.
Or a tail, an entire extra limb just to keep balance a bit better.
Or ears, you can hear without them but they help capture sound a bit better.
There are certain ANN architectures that relied on, essentially, classical conditioning based on Hobbian learning rules and variants thereof. Kohonen self-organizing maps are an example of that.
Not that such historical systems are popular today, though.
But when you do have such a problem conditioning is not very complicated. The normal algorithms and neural structures are designed to learn stuff like "when a given input happens a certain action must be taken" and thats all you really need for conditioning. How it actually does it? Well I guess with gradient descent it would work something like this: Every time there is a puff of air the network will be like "damn I should have blinked to avoid this" and so it makes its current internal statement a little more likely to lead to blinking. Gradually as it happens more times it will learn a strong association for the ringing bell or whatever.
A small RNN could learn this.
Neural networks don't have instinctive behavior like that.
As a neuroscience novice, I've always assumed that something about the gross model of the neuron, as far as I understand it, cannot be correct or is incomplete. Because I never understood why single cells aren't already performing single cell learning, given that there are always far more dendrites than axons.
Since this characteristic turns each neuron into a lossy compression function, there has to be some process by which certain dendrites are considered 'more important' carriers of information than others, in order to make a tie-breaking decision about what to include in the compressed signal, and what to throw out, as the cell decedes whether or not to transmit an impulse (including whether or not to override prior inhibitory signals) back up the axon.
I think this is above and beyond a simple mathematical weight and the nueron structures around these dendrite-axon pathways change or express their genes differently over time.
It's like asking which part of a bat makes it fly. The wings? Well kind of, but you need more than that. I guess you can fly without feet... it's just not a well formed question.
Its true that a particular function may mot be localizable more specifically than the brain (or even the whole body), because defining it as a distinct function may not reflect the organization of conponents within the body. But that's still performed by a defined physical system, and there are still sub-functions necessary to perform that function that are localizable to narrower components.
> It's like asking which part of a bat makes it fly.
Its like that in that we absolutely can describe specific parts of the bat and what each contributes to flight.
We use text embeddings to represent concepts written words. They lack the nuance, when the same word has different meaning in different concepts. LLM's use text embeddings and enrich it with the Attention mechanism.
For words, that in reality are used to represent a single concept, a text embedding is working perfectly on it's own.
For those concepts that are context dependent, we're using the attention mechanism to gently guide the text embedding closer to the intended, identified by surrounding words, meaning. That's the role of the Value vector of the K, Q, V triplet in the Attention mechanism to be precise.
So, this is a simplistic approach, which corresponds to the "first approximation", which could be good enough for some cases. We don't know which exactly yet, but we'll know, once enough evidence is given to the contrary.
It's not a good model, but a very good approach in order to do research in a stepwise manner. With time, it'll get more and more nuanced, one approximation at a time.
Apples and oranges, but that's so reminiscent of MLPs in Transformers. A similarly large fraction of the weights in transformers come from the MLPs in each layer.
(He's talking about sensing the 3D environment using electric fields)
I wonder whether binaural hearing is such a sensory system. You can blindfold someone, then lead them into a space. They can tell whether they're outdoors, or in a small, bare room, or a concert hall, or a room with furniture and drapes. Perhaps they can tell whether they're near or far from a wall, and in which direction.
When talking to someone with whom we have a good rapport and good context, this conversation can be done faster. Basically, I/O is slower than the CPU.
Some of the other sentences can also be explained in similar manner.
> Results revealed that children with DCD had reduced grey matter volume in several regions, namely: the brainstem, right/left crus I, right crus II, left VI, right VIIb, and right VIIIa lobules
Note that time perception is distorted so that we don't notice how slow conscious response is.
So the feeling of "competence" is when your cerebellum is anticipating correctly.
"Are cerebellar Purkinje cells the only individual neurons capable of single-cell learning?"
What he described is definitely not single cell learning, it is normal long term depression caused by specific inputs
Just my point of view
As Jackson is to E&M, Kandel is to neuro. It's the text.
- cognitivescience.substack.com
- seantrott.substack.com
- understandingai.substack.com
- neuralnews.substack.com
- brain2mind.substack.com
- biomedworks.substack.com
Why do we NOT think so? It must be capable of thinking alone, as only mammals have the neocortex. It would only be logical to expect the more universal cognitive abilities to happen in the cerebellum, and only those that are specific to mammals alone to happen in the neocortex.