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Germund Hesslow on cerebellum and pavlovian conditioning

Episode 1 15.03.2014

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Season 2014

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How does a single Purkinje cell receiving half a million inputs learn to produce a precisely timed eye blink, and why has the cerebellum been so difficult to understand despite its crystalline simplicity? Germund Hesslow reveals what decades of painstaking physiology have uncovered.

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Germund Hesslow describes his journey from Freudian psychology to hardcore cerebellar physiology, drawn by the exceptional quality of research in the Lund laboratory rather than the subject matter itself. The serendipitous discovery that Pavlovian conditioning occurs in the cerebellum united his interests in learning with his technical expertise, launching a 25-year investigation into how associative memory is formed at the cellular level. Working with a decerebrate preparation that retains only the cerebellum and brainstem, Hesslow’s group demonstrates that conditioning follows essentially the same rules as in intact animals, taking similar time to acquire and extinguish.

The episode provides a clear account of the cerebellar circuit for eye-blink conditioning. Conditioned stimulus information arrives via mossy fibers and parallel fibers, converging on Purkinje cells that also receive climbing fiber input carrying the unconditioned stimulus signal. With each Purkinje cell receiving up to half a million parallel fiber inputs carrying information about virtually everything happening to the organism, the system is ideally suited for forming associations. The learned response manifests as a precisely timed pause in the Purkinje cell’s tonic inhibitory output, which disinhibits the deep cerebellar nuclei to generate the conditioned eye blink.

The central unsolved problem is timing. The conditioned response is adaptively timed to the interstimulus interval: train with 300 milliseconds and the response peaks at 300 milliseconds; train with 500 milliseconds and it shifts accordingly. Hesslow’s recent experiments systematically eliminate candidate timing mechanisms. Stimulating mossy fibers directly still produces timed responses, ruling out delays in the input pathway. Stimulating parallel fibers directly yields the same result, eliminating delays in the granule cell layer. The timing mechanism must reside close to the Purkinje cell itself, either in cortical interneurons or in the cell’s intrinsic properties.

Hesslow also raises the provocative possibility that different zones of the cerebellum, despite their apparently uniform crystalline structure, may operate with different temporal and functional properties, potentially explaining decades of disagreement between researchers working on eye-blink conditioning, vestibulo-ocular reflex adaptation, and in vitro slice preparations in different cerebellar regions.

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Cell Receiving cerebellum pavlovian conditioning Receiving Half Timed

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Both the triumphs of humanity and its most evil deeds have resulted from collaboration. In a time where humanity is required to aspire to the former and minimize the latter, the question arises of how collaboration arises and why it fails. Surprisingly, this phenomenon, so central to who we are, is not well understood. Hence, a collaborative effort is required to understand collaboration in its full biological, psychological, sociological, cultural, and economic complexity and to translate this understanding into operational impact. This series of podcasts is one step toward achieving these complementary goals. The Collaboration Podcast presents interviews with people who are central orchestrators of collaboration in various domains including business, government, science, art, health, sustainability, and the military. The discussions were conducted by Prof. Dr. Paul F.M.J. Verschure and members of the Program Advisory Committee of the Ernst Strungmann Forum on Collaboration (https://www.esforum.de/forums/ESF32_Collaboration.html) during 2021 and had the goal to sketch a map of opportunities, challenges, and obstacles in human collaboration. The forum took place in May 2022, and now we would like to share this series of interviews with a broader audience. The full report of the Forum will be published in 2023 by MIT Press. The podcast was produced by the Convergent Science Network (https://www.convergentsciencenetwork.org/). Context: The stability of social systems depends critically on realizing sustainable methods of “collaboration,” yet how and by which means collaboration is achieved is not clearly understood; neither are the conditions or processes that lead to its breakdown or failure. Collaboration can be understood as cooperation between agents toward mutually constructed goals. Part of the reason for our lack of understanding is that the phenomenon of collaboration is, by nature, a highly multidisciplinary problem, and effective research into its complexities has been difficult to achieve across the broad range of scientific and technical disciplines involved. The need for a fundamental understanding of collaboration, however, has become increasingly important. Not only does humankind demand answers as it attempts to address critical challenges at multiple scales (e.g., climate change, migration, enhanced automation, social and economic inequality), but ever-increasing technological and economic means of interconnecting people and societies are disrupting long-established, familiar patterns of how we interact. Radical technological changes that are ongoing have the potential to reshape collaboration in ways that are currently hard to predict or influence (e.g., by altering configurations in interaction, information creation, and modes of communication). On one hand, such changes could disrupt hitherto stable forms of collaboration by affecting critical communication channels and traditional roles, as can be observed in the rapidly changing patterns in governance, commerce, and social interaction. Conversely, technology could lead to the emergence of novel, successful forms of collaboration that deviate from traditional “hierarchical” architectures. Evidence of this can be seen in areas as diverse as highly automated manufacturing plants, the open science movement, collaborative software repositories, user-centered services, and the sharing of economy-based modes of organization. Without a fundamental understanding of the mechanisms, processes, and boundary conditions of collaboration, it is not possible to evaluate or predict which of these possible scenarios are sustainable or even plausible. The Forum “How Collaboration Arises and Why it Fails” (May 8–13, 2022, Location: Frankfurt am Main, Germany) Chairs: Andreas Roepstorff and Paul Verschure Program Advisory Committee: Jenna Bednar, Julia R. Lupp, Bhavani R. Rao , Andreas Roepstorff, Ferdinand von Siemens, and Paul Verschure

Timestamp

00:00:01 - This is Paul Verschure with the Convergent Science Network podcast.
00:00:06 - And today I'm with one of the regular visitors to our summer school here in
00:00:11 - Barcelona, Jerry Haslow.
00:00:14 - And Jerry is with us now. He's visiting Barcelona. And he talked about his recent work on the cerebellum.
00:00:22 - And um so jerry one thing maybe as an introduction but what i always found fascinating
00:00:28 - in in your case is that sort of you moved from psychology and philosophy,
00:00:33 - into not just neuroscience but a very sort of hardcore version of of neuroscience
00:00:39 - right so so how do you how do you see that transition for yourself well i wanted
00:00:47 - when i started psychology I was in a department that was mainly Freudian,
00:00:50 - and I wanted to study psychology from a more scientific point of view.
00:00:56 - And I looked at various departments and laboratories, and I found that there
00:01:01 - was a group in my hometown in Lund working on the cerebellum.
00:01:06 - They were doing things that I found extremely boring.
00:01:08 - They were looking at pathways through the spinal cord up to the cerebellum.
00:01:15 - And I found that very, very boring since I was interested in learning and memory
00:01:21 - and stuff like that, physiological psychology.
00:01:23 - But the quality of the research was extremely good.
00:01:26 - And I've come to the view that this is really, really crucial for probably most of science.
00:01:34 - The quality of the research, when things are done in a careful, precise,
00:01:42 - painstaking, systematic way, this is much more important than working in trendy
00:01:49 - subjects and following fashion and so on.
00:01:52 - So even though I found it boring, I found that the quality of the research being
00:01:56 - done in that department was just so good.
00:01:59 - I felt that these guys know what they're doing. This is what I want to learn.
00:02:04 - So I started working on the cerebellum with Carl Friedrich Eckert,
00:02:12 - Gert Andersen, and a few others just to learn the techniques and to try and
00:02:18 - emulate their way of thinking,
00:02:20 - their carefulness, and the systematic way they were doing research.
00:02:25 - And then, just by luck, it turned out that a certain form of associative memory,
00:02:31 - Pavlovian conditioning, actually occurred in the cerebellum.
00:02:35 - So, for me, that was just fantastic because it meant that I could utilize my
00:02:40 - knowledge of cerebellar physiology and...
00:02:45 - Address a task that I felt was also very interesting, namely the formation of associative memory.
00:02:52 - So that's how I ended up doing work on the cerebellum on Poblovian eye-blinking conditioning.
00:02:58 - So that's basically what you've been doing for the last 25 years.
00:03:01 - Exactly. And it's been extremely difficult.
00:03:04 - We've spent a lot of time trying to create an experimental setup that is workable.
00:03:12 - There are many constraints when you do research. You have the ethical constraints, for instance.
00:03:17 - You cannot do this on any kind of animal. You cannot do it with any kind of anesthetics and so on.
00:03:24 - But we found a way to solve these problems.
00:03:27 - But it's taken, I would say, it took more than 15 years to almost 20 years to
00:03:35 - make the preparation really workable.
00:03:38 - Now, finally, results are pouring in. It's been a very long travel to get there.
00:03:46 - So how do you map Pavlovian conditioning onto the brain, and in particular onto the cerebellum?
00:03:52 - What's the relationship there?
00:03:55 - Well, Pavlovian conditioning is a very general phenomenon. There are many response
00:04:00 - systems in which you can get it.
00:04:02 - I mean, Pavlov used autonomic conditioning. He showed how you could train dogs
00:04:06 - to salivate when they heard a sound by pairing the sound with food in the dog's mouth.
00:04:13 - We can also use the same learning paradigm to.
00:04:22 - How should I put it, to look at how certain immune responses occur,
00:04:30 - cognitive aspects of learning, how your heart rate changes when you are told
00:04:37 - something frightening.
00:04:39 - How asthmatic patients can get asthmatic attacks when they look at pictures
00:04:45 - of flowers or smell flowers and things like that.
00:04:49 - There are many, many, many applications to this, and we are only studying one
00:04:54 - of them, namely Eibling conditioning, which is a motor response.
00:04:57 - We know that this is in the cerebellum, but probably the other forms of conditioning,
00:05:01 - or many of the other forms of conditioning, involve other parts of the brain.
00:05:06 - But it's a very simple and very basic form of learning. There is the Nobel Prize
00:05:11 - winner Peter Medawar once wrote a collection of essays called The Art of the Soluble.
00:05:17 - And by that he meant that scientists should
00:05:20 - not only address the important problems they should also choose
00:05:24 - problems that are really soluble and
00:05:27 - that often means you should
00:05:30 - start with the simple problems and wait with the really huge task like explaining
00:05:36 - cognition and consciousness and stuff like that okay but now in pavlovian conditioning
00:05:40 - we actually have a very reduced setup right you just have you're talking about
00:05:44 - two kinds of stimuli yes in the end one kind of response you're going to get
00:05:48 - out of the system, right?
00:05:49 - So how do you... And these are also very simple responses. They're stereotyped responses.
00:05:54 - Exactly. So how do you map that very reduced learning system now from the behavioral perspective?
00:06:01 - Onto the neural substrate, right? So how does something like this conditioned
00:06:05 - stimulus, this initially neutral stimulus, now map onto this preparation you developed?
00:06:09 - Or how do you map your unconditioned stimulus onto that system and so on?
00:06:13 - I'm not sure what you mean by how do I map it. Well, you have a functional relationship.
00:06:18 - You know that if you present this conditioned stimulus paired with an unconditioned
00:06:21 - stimulus, you will be able to trigger conditioned response over time.
00:06:24 - So that means you have to now identify the pathways that actually transduce
00:06:28 - this information to the brain.
00:06:30 - Yeah, but we know that we can, in our case, we map it on the cerebellum and
00:06:34 - there's a lot of experimental work before us where people have showed you can
00:06:40 - get these in animals that have no forebrain.
00:06:43 - You can remove a huge part of the brain and still get conditioning.
00:06:47 - Conditioning, we have developed this into a preparation where we remove most
00:06:55 - of the brain, all the parts of the brain that maintain cognitive function and
00:06:58 - consciousness and so on are removed,
00:07:00 - and we have the cerebellum and the brainstem left intact.
00:07:03 - We can still get conditioning, and it seems to follow basically the same rules
00:07:07 - that you find in the intact animal. It takes roughly the same amount of time
00:07:13 - and training to acquire the response.
00:07:17 - They extinguish in the same way and so on. So it looks very, very similar.
00:07:22 - And then we have tried to identify precisely which cells in the cerebellum learn this.
00:07:29 - And we show that these cells, they have particular properties,
00:07:32 - they have particular input characteristics and so on.
00:07:34 - So we can, within a few tens of a microns, we can localize the cells that learn this task.
00:07:46 - And we can record from precisely those cells. And we can...
00:07:51 - The findings we have can account for almost everything you find in the behavior.
00:07:57 - So we have cellular responses, responses in the particular group of Purkinje
00:08:03 - cells in the cerebellar cortex.
00:08:05 - They have the temporal properties of the behavior. They respond in the same
00:08:10 - way when you change various conditions during training.
00:08:14 - And that means that we we know within
00:08:17 - a very very very narrow area very
00:08:20 - small area where the learning takes
00:08:23 - place so how do these cells learn i mean on on
00:08:27 - these cells we have convergence pavlov already talked about looking
00:08:29 - for convergence to find the site of the n-gram or the memory trace
00:08:33 - so the condition stimulus information comes
00:08:37 - up to this perkinia cell through the parallel fibers
00:08:40 - there is a granule cells this might tell you something
00:08:43 - about the world now we have our climbing fiber coming
00:08:46 - in so it conversions on this Purkinje cell so you
00:08:49 - could argue well look that seems a fairly trivial setup to
00:08:52 - learn an association right well actually the Purkinje cells are ideally suited
00:08:57 - to make associative connections they are unique in the nervous system in the
00:09:02 - degree of convergence of inputs one Purkinje cell can receive several hundred
00:09:06 - thousand different inputs from the so-called parallel fibers.
00:09:11 - So a single Purkinje cell will be contacted by maybe a quarter of a million,
00:09:17 - maybe half a million parallel fibers.
00:09:20 - And the parallel fibers will signal everything that happens to the organism.
00:09:24 - All the sensory systems project via the parallel fibers of the Purkinje cell.
00:09:29 - Also, everything that happens in In the brain, when you think about things,
00:09:35 - when you plan ahead, when you imagine you're seeing things, all of that information
00:09:38 - is also sent via the parallel fibers to the Purkinje cells.
00:09:43 - So this is a perfect system for generating associations.
00:09:49 - And once you've seen this degree of convergence, it's not a surprise that this
00:09:55 - is where associative learning takes place.
00:09:57 - Well, but it seems a very special kind of associative learning because it's
00:10:01 - not that you just associate any idea with any other idea, to use a more Jungian interpretation,
00:10:07 - but you seem to associate in a very convergent fashion a large set of possible
00:10:14 - states onto one output state.
00:10:16 - Yeah. Right, so it's not just any form of associative learning,
00:10:19 - but it seems a very specific kind of associative learning. Yes,
00:10:22 - but you have many output channels also, small groups of Purkinje cells project to their own targets.
00:10:29 - Most of them project to muscles, but there are also Purkinje cells projecting
00:10:33 - to the prefrontal cortex and to the parts of the brain we believe are the centers
00:10:38 - of various cognitive functions.
00:10:43 - And since all these Purkinje cells projecting to small groups of muscles or
00:10:50 - areas of the cognitive parts of the forebrain,
00:10:54 - they all receive this convergent input from all the other systems.
00:10:58 - But what do you then see as the output unit?
00:11:02 - Because in the eye-blink conditioning case, which is a standard paradigm that
00:11:07 - you also have pursued vigorously, the output is a discrete movement in the end, right?
00:11:14 - So now you also say that, but other Purkinje cells would indirectly project
00:11:20 - towards the frontal cortex.
00:11:22 - Yes. So what's now this output unit of the system? Well, if you go,
00:11:27 - some of the projections from the cerebellum goes to the primary motor cortex.
00:11:30 - And there you have pyramidal cells projecting also to elementary movements or
00:11:36 - small groups of muscles.
00:11:38 - So that outward pathway is rather similar to what we're looking at in eye blink conditioning.
00:11:43 - But then as you go more forward in the forebrain, you will reach areas that
00:11:48 - control more global aspects of actions.
00:11:55 - Perhaps you shouldn't even call them movements because they are actions in a more abstract sense.
00:12:00 - So the more rostral, the more forward you come, the more complex the movements
00:12:06 - will be controlled by that area.
00:12:09 - And when you come, suppose that I said that I want to draw a triangle.
00:12:16 - Then on my primary motor cortex there
00:12:19 - will be commands for holding the pen
00:12:22 - and moving your arm
00:12:25 - in a certain direction if you go a little bit forward you will have a command
00:12:29 - signal controlling let's say draw a horizontal line and if you go even further
00:12:35 - forward than that you will have more global commands like drawing a triangle
00:12:39 - or even drawing a house or something like that And the more forward you go,
00:12:44 - the more global will the commands be, the more abstract will they be,
00:12:48 - or the more abstract will the actions be that are controlled from that area.
00:12:51 - So it looks as if the cerebellum can control not only the sort of the fine detailed
00:12:58 - parts of a movement like squeeze the pen to hold it,
00:13:03 - but also more global actions like draw a triangle or things like that.
00:13:07 - But would that not mean that, like in the eye-blink conditioning case,
00:13:12 - you were describing the output of the system as groups of muscles.
00:13:16 - But it actually is, this projection is only indirectly targeting these muscles
00:13:22 - because it hits brainstem motor nuclei.
00:13:27 - So also there wouldn't be fair to say that you control an action as opposed
00:13:30 - to groups of muscles? No.
00:13:32 - Well, you might, I suppose.
00:13:35 - And I also suppose that if you take eye blink conditioning, which is in some
00:13:41 - ways a special case, but it will activate the facial nucleus and send signals out of the eyelid.
00:13:46 - If you're looking at other forms, in a rabbit, for instance,
00:13:50 - it's retraction of the eyeball and not only the eyelid and so on.
00:13:53 - But in any case, the facial nucleus will not only respond then to change in
00:14:02 - its input signals controlling the movement of the eyelid.
00:14:06 - There must be other mechanisms controlling, let's say, the amplitude of the
00:14:09 - movement. That could also be the cerebellum in a different part of the cerebellum.
00:14:14 - And maybe that will also be controlled by signals coming from the forebrain.
00:14:19 - Like in this particular situation, it's not very good to close your eyes because
00:14:24 - you need to have a look at the dangerous environment you're being in at the
00:14:32 - moment, things like that.
00:14:34 - So, of course, in a certain sense, the facial nucleus will have to integrate
00:14:38 - or compromise between signals coming from the cerebellum but also coming from
00:14:42 - other parts of the brain and from the periphery.
00:14:47 - So now we have the whole setup, right? We have sort of our conditioned stimuli coming in.
00:14:53 - This is basically all possible states of the world or internal states of my
00:14:57 - brain that come in via the pons over these parallel fibers.
00:15:00 - I have these climbing fibers that are much more specifically targeting these
00:15:04 - Purkinje cells linked often to very specific events on the body,
00:15:09 - like unconditioned stimuli, painful stimuli, and noxious stimuli, and so on.
00:15:13 - And now we have this output pathway, which is a strong divergent pathway,
00:15:17 - or conversion pathway again, onto motor nuclei or onto frontal areas of the brain.
00:15:22 - Okay, so now you could argue, well, and indeed, because of this very almost
00:15:28 - clean, what people call crystalline design of this circuit,
00:15:32 - its operations, or some people like to call this its computations,
00:15:36 - might be fairly trivial.
00:15:39 - There have been models of this already by Marr and Albus and Ito since the 70s and early 80s.
00:15:46 - You could argue, okay, but given this anatomical arrangement and given this
00:15:49 - physiology, the computational principles appear clear because you just learned
00:15:54 - to trigger this response.
00:15:55 - You have to bridge some sort of little time interval between the onset of one stimulus and the other.
00:16:02 - What's really the problem of this system? Why is it so difficult to understand
00:16:05 - how this really works? Where are the problems coming in? I don't think it is very difficult. Okay.
00:16:09 - I think... Yeah, but still, you're performing experiments every day,
00:16:12 - so apparently they're on these old problems.
00:16:13 - I mean, we're trying to sort out many of the details, but I think that in some
00:16:17 - basic stuff, we understand pretty well now.
00:16:21 - We do. I think we do understand that all the sensory information is transmitted
00:16:25 - via the mossy fiber and the parallel fibers of the Purkinje cells.
00:16:28 - The climbing fibers provide a teaching signal to change the circuitry.
00:16:33 - The pre-kinder cell has the ability to output, to generate well-timed outputs that control behavior.
00:16:40 - I think this is now pretty clear.
00:16:43 - A lot of the controversy surrounding the cerebellum is that a lot of people
00:16:48 - who work, perhaps those who are working on different setups,
00:16:51 - don't accept the answers that I claim are the right ones.
00:16:57 - But there's another complication, And that is that the cerebellum,
00:17:01 - as you said, has a crystalline structure.
00:17:03 - It looks very similar throughout the cerebellar cortex, wherever you are in the cerebellum.
00:17:07 - And that has fostered the assumption
00:17:10 - that the cerebellum works in the same way in all different parts.
00:17:14 - However, it is known and has been for some time that there are biochemical differences
00:17:20 - between different zones in the cerebellum.
00:17:22 - And those biochemical differences must correspond to some sort of functional
00:17:27 - difference. Like what kind of difference would stand out?
00:17:31 - I'm not sure what they are. And this has not been investigated because almost
00:17:35 - all the in vitro work has been done in the vermis.
00:17:39 - People have taken out slices from the vermis and put them in a dish and try
00:17:43 - to explore learning properties and so on.
00:17:46 - But a large part of the cerebellum have never been subjected to that kind of
00:17:50 - analysis. And if you look at what different parts of the cerebellum do,
00:17:54 - it's not difficult to envisage that they might learn quite different things
00:17:59 - and respond in different ways.
00:18:02 - This is very speculative on my part, but if you take, for instance,
00:18:09 - a medial part of the cerebellum that controls posture and axial musculature.
00:18:15 - It's difficult to see that the cerebellum would be very useful if it only produced a kind of phasic,
00:18:27 - fairly short latency and very short lasting movements that are generated by
00:18:34 - a more lateral area that generates eye blink.
00:18:36 - So, pre-kinesio-cell controlling eye blink, you would expect it to generate
00:18:42 - a short-lasting fast movement or signal.
00:18:49 - But if you go to the part of the vermis controlling posture,
00:18:53 - you wouldn't want, you want someone to be able to stand still for a while.
00:18:58 - And it's not useful then to generate very, very short lasting fast movements.
00:19:03 - So my guess is that you would find that those parts of the cerebellum work in
00:19:07 - a slightly different way. They may have very different temporal properties.
00:19:11 - But look, you could also argue that that transformation is
00:19:14 - performed in these downstream brainstem stem nuclei that
00:19:17 - they sort of perform some sort of temporal matching
00:19:21 - of these output signals to the properties of the periphery you
00:19:23 - can but your original question was why has this and why
00:19:26 - has it been so difficult to agree on how the cerebellum works
00:19:30 - and one one guess that i have is that it has always been assumed that the cerebellum
00:19:35 - works in the same way everywhere but people working on eibling conditioning
00:19:39 - work in one part of the cerebellum those who work on in vitro on slices work
00:19:45 - in a different part of the cerebellum,
00:19:47 - and those working on the other main experimental paradigm,
00:19:52 - namely the adaptation of the vestibulo-ocular reflex,
00:19:55 - they work in a third area of the cerebellum.
00:19:58 - And maybe the properties of the cerebellum are different in all these areas.
00:20:02 - And that could also be one reason why it's been so difficult to reach agreement.
00:20:07 - But these three paradigms, how much of the cerebellum do they really cover?
00:20:11 - Well, they cover only a small part of the cerebellum. We are working in the
00:20:14 - intermediate part known as the C3 zone.
00:20:18 - The slice people work mainly on the A zone. Maybe they get some B zone.
00:20:22 - I don't know, depending on how careful they are.
00:20:25 - And the vestibular ocular reflex people are working on the flocculus,
00:20:31 - a very old part of the cerebellum.
00:20:33 - And it could be that there are significant differences between these areas.
00:20:38 - So in total, this is not more than 10%, I would guess.
00:20:41 - No, less than that. Less, okay. Okay, I was being generous.
00:20:45 - Okay. Yeah. So the problem is that if you say, okay, it might not be a uniformly
00:20:52 - operating learning system, do you have any physiological or direct anatomical evidence for that?
00:20:59 - Or is it only in terms of functional considerations?
00:21:02 - Well, it's functional considerations coupled with the fact that we know that
00:21:06 - there are biochemical differences. People working with anatomical techniques
00:21:11 - have found that there are some clear chemical differences between different
00:21:16 - parts of the cerebellum.
00:21:17 - One of the most well-known is the zebrin bands, which correspond to an enzyme
00:21:24 - called aldolase, which is important for basic metabolism of the cells.
00:21:30 - And it's very difficult to understand why should there be bands of Purkinje
00:21:36 - cells with different levels of aldolase. Mm-hmm. Um.
00:21:40 - If it doesn't correspond to some sort of functional difference between them.
00:21:44 - Yeah, that's reasonable.
00:21:45 - So you said earlier, which I liked actually, you said, okay,
00:21:49 - I know how this system works, but they don't want to listen.
00:21:53 - So how does this system then work when we take the eye-blink conditioning example, right?
00:21:59 - So here comes the sound, a bit later comes the air puff to the cornea.
00:22:03 - Well, of course. What's happening in this system now? We don't know a lot about
00:22:06 - the details here, but what we know is that Sketch it out. Yeah,
00:22:09 - the Purkinje cell controlling the eyelid is only a small fraction of the Purkinje
00:22:14 - cells, but it is a distinct group of Purkinje cells.
00:22:18 - They will receive input from tones and light and skin pressure and everything
00:22:24 - that happens to the organism all the time.
00:22:26 - But now and then, a certain stimulus like a tone will occur and be followed
00:22:33 - by some kind of stimulus to the eye,
00:22:36 - like air on the cornea or an insect irritating the skin around the eye or something like that.
00:22:45 - And that will produce a signal in a particular pathway known as the climbing
00:22:51 - fibers going up to the same pre-kinder cells.
00:22:53 - And that climbing fiber impulse will change the synapses between the parallel
00:22:59 - fibers and the Purkinje cells.
00:23:02 - And it will only change those parallel fibers that were just active at the time
00:23:07 - we're considering. And those happen to be tone.
00:23:10 - So the synapses between the tone carrying signal and the climbing fiber input,
00:23:18 - those synapses will be changed by the climbing fiber input.
00:23:21 - And that will make the Purkinje cell more likely, the next time this happened,
00:23:26 - to generate an output signal in response to the tone, before the clavicle fiber,
00:23:33 - before the corneal or eye stimulation.
00:23:36 - But how does the Purkinje cell then trigger that response?
00:23:40 - That is totally unknown. Okay. And very controversial.
00:23:44 - Okay. Yeah. How come? What's the difficulty there? Well, one difficulty is to
00:23:49 - account for the timing. if the dominant idea...
00:23:54 - In the neurobiology of learning has been for many decades, I would say,
00:23:59 - the idea that you can change the strength of a synapse.
00:24:04 - Synapses can be depressed or they can be potentiated.
00:24:08 - And the terms long-term depression and long-term potentiation are usually used
00:24:13 - to designate these two forms of learning.
00:24:16 - And this has been the standard assumption in not only the cerebellum,
00:24:20 - but in all ideas about learning in the brain.
00:24:25 - The difficulty has been that the learned eye blink, the conditioned eye blink, is well-timed.
00:24:33 - It reaches, if you have a particular interval between the onset of the tone
00:24:38 - and the onset of the air puff, like 300 milliseconds or 500 milliseconds,
00:24:42 - the Purkinje cell response is adaptively timed to the interval between these
00:24:48 - two stimuli that occurred during training.
00:24:50 - And how can you account for the delay? If you use 300 milliseconds,
00:24:56 - the Purkinje cell will start firing or change its firing early,
00:25:00 - and it will reach a maximum amplitude at roughly the time when the unconditioned
00:25:05 - stimulus or the air puff comes on.
00:25:06 - If you use 500 milliseconds instead, the response will be delayed and adapted
00:25:13 - to the 500 millisecond interval.
00:25:15 - Now, how can you account for a timed response if you have only increases or
00:25:21 - decreases in stimulus strength?
00:25:25 - Just changing the strength of the response to the tone signal could explain
00:25:31 - why the Purkinje cell responds to tone, but it doesn't explain how that response
00:25:35 - can be delayed by a couple of hundred milliseconds or so.
00:25:38 - So this has been the main problem, that how do you account for the timing?
00:25:42 - And there have been many ideas about how this could be achieved.
00:25:46 - For instance, you could have delays in the input signal.
00:25:50 - This has been an idea that goes back many decades. It's called tapped delay lines.
00:25:55 - And the idea was that if you had a delay, let's say, in the mossy fibers going
00:26:00 - up to the cerebellum or delays in the granule cells and parallel fiber signal into the kidney cells,
00:26:05 - then you could have a synaptic change only between those parallel fibers Bruce.
00:26:12 - That had the right delay so that the signals would coincide with the input coming
00:26:18 - through the climbing fibers from the air puff.
00:26:20 - And that would give you an automatic way of timing because then only those parallel
00:26:24 - fibers would respond after learning. And that would give you automatic timing.
00:26:29 - We have in Lund conducted experiments suggesting that there are no such delays in the input signals.
00:26:37 - And even if we circumvent them by stimulating, Well, a few years ago,
00:26:42 - we tried to stimulate the mossy fibers, and we got well-timed responses showing
00:26:46 - that it couldn't be delays in the mossy fibers because we had delays after the mossy fibers.
00:26:52 - So then recently, we have stimulated the parallel fibers instead,
00:26:56 - and we still get nicely timed responses suggesting that it cannot be delays in the parallel fibers.
00:27:02 - It has to be something closer to the Bikindi cell, either cortical interneurons
00:27:08 - or the Bikindi cells themselves.
00:27:11 - Well, but what you're invalidating with these experiments is the notion of a
00:27:16 - tap-delay line, which would be that you have one spike basically traveling through
00:27:21 - this parallel fiber that signals, well, the interstimulus interval is 100 milliseconds.
00:27:25 - And it's on that one spike that you have to learn, right? But you cannot exclude
00:27:29 - the possibility that you have a more continuous fluctuating response on these
00:27:35 - parallel fibers that sort of represents interstem.
00:27:37 - This is also a problem for the LTD, LTP story that if you, yes,
00:27:45 - when you provide a tone signal,
00:27:47 - the mossy fibers and the parallel fibers will go on firing throughout the whole
00:27:52 - period that you have the tone.
00:27:53 - And you can get if the tone continues well after the air puff.
00:27:59 - The tone can continue several hundred milliseconds after the air puff,
00:28:02 - but that doesn't produce a continuous response.
00:28:06 - The response goes on at a certain time, but it also goes off at a certain time.
00:28:10 - Even if the condition simulates continuous of many hundreds of milliseconds,
00:28:14 - the response still goes off at the right time.
00:28:17 - But wait, I could argue that that is then accomplished by the climbing fiber signal.
00:28:21 - Yes, but the same thing happens if you give a C as alone or tone alone trial. the same thing happens.
00:28:28 - The response goes off at the time when the climbing fiber response usually comes
00:28:32 - in. So it doesn't really matter.
00:28:34 - And also you can elicit the response with a brief, if you train with several
00:28:40 - hundred millisecond tone, you can still elicit the conditioned response with
00:28:44 - just 10 milliseconds conditioned stimulus.
00:28:47 - So it looks as if it's only the initial part of the stimulus that matters from
00:28:51 - the learning point of view. Right.
00:28:53 - Okay, so this whole topic of how is the interstimulus interval represented so that you can learn it.
00:29:00 - This is one problem, right? And now you sketch some scenarios how we can think about this.
00:29:04 - But another issue might be how you transform this. Yeah, but I have to interrupt here. Yeah, please.
00:29:11 - If you have the tone, and the tone goes on for many hundreds of milliseconds.
00:29:17 - Then there will be parallel fiber signals coming throughout this whole period.
00:29:22 - And that means the first parallel fiber signals, they will
00:29:25 - be matched with say if you
00:29:29 - have an interval of 300 milliseconds they will be followed after 300
00:29:31 - milliseconds by the complex back climbing fibers
00:29:34 - in the air path but if they can continue then there will be some parallel fiber
00:29:40 - signals will be followed at a shorter interval by the climbing fiber input and
00:29:45 - some will be followed even at an even yet shorter period and some will even
00:29:49 - coincide with the unconditioned stimulus.
00:29:52 - So this also creates a problem for the idea that you just have this long-term
00:30:00 - depression of synaptic strength.
00:30:03 - Okay. So one riddle, if you want, still in the system is, okay,
00:30:08 - where does the trace reside that correlates or that corresponds to the stimulus interval, right?
00:30:14 - It's just one problem. And indeed, I think your most recent experiments shed
00:30:19 - really an interesting light on that.
00:30:21 - But another question I think that's unresolved is really how do you now transform
00:30:25 - changes in peritoneal cell firing to actually triggering this eye blink?
00:30:31 - Because it's not that this peritoneal cell is directly driving this skeletal
00:30:36 - muscle system, right? It has to go through a number of steps.
00:30:40 - Moreover, the modulation might be inhibitory. Right.
00:30:43 - So you have a sign reversal problem. So how do we map now changes in Purkinje
00:30:47 - cell responses to actually triggering that eye blink?
00:30:52 - Well, we know that Purkinje cells are inhibitory, and they inhibit the cerebellar
00:30:57 - nuclei, and they are tonically active.
00:31:00 - That means that if a Purkinje cell that is tonically active has a certain stand...
00:31:06 - At a pretty high rate, I might add. At a pretty high rate, yeah.
00:31:09 - Tens of impulses per second, and even hundreds of impulses per second.
00:31:14 - And the nuclei to which they project also have a spontaneous background activity.
00:31:20 - So in order to generate an excitatory output, the Purkinje cell has to stop its firing.
00:31:25 - And that is what it actually does. When you apply a Pavlovian conditioning protocol
00:31:31 - to the Purkinje cell, it will respond with a pause to the input signal.
00:31:37 - Signal, and that pause means that the Purkinje cell, which is inhibitory,
00:31:43 - will stop inhibiting the nuclei.
00:31:45 - That means the nuclei will be excited and will generate an excitatory signal.
00:31:49 - Who excites the nucleus?
00:31:52 - What excites the nucleus? Nothing has to excite the nucleus.
00:31:55 - This was previously considered a problem, but it's now known that the nuclei
00:32:00 - have an intrinsic mechanism for generating a background activity,
00:32:04 - so nothing really has to excite So it's a form of rebound, a rebound excitation?
00:32:08 - You don't need that either. Okay. If the Purkinje cell stops firing,
00:32:12 - stops inhibiting the deep nuclei, they will immediately increase their firing rate.
00:32:18 - So that's not a problem. There may be problems, and this, of course,
00:32:22 - has to be addressed in a future physiology presentation.
00:32:26 - How is this transformation from the inhibitory perikinetic cell signal to the
00:32:31 - nuclei, to the red nucleus, to the facial nucleus?
00:32:35 - How is this transformation? What does it look like? Is it linear or is it something else?
00:32:40 - And this, of course, we don't yet know. And this has to be found out.
00:32:45 - And there are, of course, interesting aspects because the system also has to
00:32:49 - regulate the amplitude.
00:32:50 - The blink has to have, the eyelid movement has to have the right force.
00:32:54 - Right. If the eye is a little bit dry, for instance, it will need a larger force and so on.
00:32:59 - So that has to be regulated also. And that could well be downstream from the Purkinje cells.
00:33:05 - It could be in the nuclei, cerebellar nuclei.
00:33:09 - It could even be learned in the cerebellar nuclei. We don't know.
00:33:12 - Okay. But now there's another puzzling component of this story,
00:33:18 - which is that these deep nuclei.
00:33:20 - So now we have an idea of how we transform the pons and the Purkinje cell firing
00:33:24 - into triggering an action of the eyelid.
00:33:28 - But these deep nuclear cells also receive a collateral input from the pons, right?
00:33:35 - Well, no. So does it play any role of significance?
00:33:38 - I don't think so. Actually this has been a highly controversial subject.
00:33:43 - The nuclei do receive some mossy fabric collaterals from some sources.
00:33:50 - It's highly questionable if they do so from the pontine nuclei and from the
00:33:56 - mossy fibers arising in the pons.
00:33:59 - There have been some claims that they do. Other people have claimed they do not.
00:34:03 - And in any case, the number of such collaterals is likely to be very,
00:34:09 - very small compared to the convergence of input you have in the cerebellar cortex
00:34:14 - with a quarter of a million parallel fibers to a single Purkinje cell.
00:34:18 - So how many mossy fibers would collateral to the deep nucleus you think?
00:34:23 - I don't know. I mean some people have questioned that there are any at all. Oh really? Okay.
00:34:26 - So my guess is it wouldn't be near, I mean it would totally different order
00:34:33 - magnitude from what you have recorded.
00:34:35 - So we ignore this for now. It wouldn't be nearly enough to explain associative learning.
00:34:40 - But it might be enough to explain explain, for instance, a consistent modulation of reflex strength.
00:34:49 - Exactly right, yeah. So if you had mossy fibrous collateral,
00:34:52 - perhaps not from the pons, but from somewhere else, regulating,
00:34:55 - let's say, the background firing rate of the deep nuclei, that could mean that
00:35:01 - the eyelid response, the eye blink amplitude.
00:35:04 - Could be stronger or weaker.
00:35:06 - And that kind of learning could well... And this is a relevant issue, right?
00:35:09 - Because what you're conditioning is the amplitude time course of the response.
00:35:12 - And the Purkinje cells tell us how we can get the timing, but not this amplitude modulation.
00:35:18 - Precisely. And in other areas, for instance, in the vestibular ocular reflex,
00:35:23 - the Purkinje cell, or sorry, the cerebellum does modulate the amplitude of reflex.
00:35:29 - This has also been a view, if you go back decades, this has been the view of
00:35:36 - what the cerebellum does with all our spinal reflexes, that they modulate the reflex.
00:35:42 - Gain right so that the strength of
00:35:45 - the reflex it always has to be adapted when the
00:35:48 - body grows your muscle strength changes the
00:35:52 - mechanical properties changes all the time so you cannot these things cannot
00:35:59 - be inborn they have to be subject to modulation right as we grow and as we train
00:36:04 - as our muscles become stronger and then as we grow older as the muscles become
00:36:07 - weaker speaker, they will always have to adapt this.
00:36:09 - So you need some kind of adaptation of reflex gain throughout your life.
00:36:14 - Or even you could argue as soon as we start to use tools, for instance,
00:36:17 - if you talk about posture, posture control with tools, then you have to adapt
00:36:24 - very rapidly to that. Oh yes.
00:36:26 - But now, so okay, so let's say we're not going to worry too much about these
00:36:29 - mossy fiber collaterals, but another aspect of this downward pathway towards the action.
00:36:37 - Is that it also has a collateral from the deep nucleus back to the inferior
00:36:42 - olive, which seems puzzling, right?
00:36:44 - And you actually have been investigating this specific aspect of the whole circuit quite a bit.
00:36:49 - Because over the inferior olive, we have, if you want, our error signal coming
00:36:52 - in that tells you, okay, you just got a shock or you just got an air puff,
00:36:55 - something bad happened to you.
00:36:57 - But now in itself, these inferior olive neurons receive an inhibitory input
00:37:01 - from the deep nucleus, which we are triggering when we're saying,
00:37:04 - okay, close your eyelid now.
00:37:05 - So what's the role? How do you see the role of that connection, of that link?
00:37:11 - Well, we think that this is a negative feedback pathway for controlling learning,
00:37:17 - the amplitude of the learning.
00:37:19 - The amplitude of learning? The amplitude of the learned response. Okay.
00:37:25 - This was very puzzling initially. We discovered this by chance that this pathway
00:37:30 - was inhibitory. It was always believed to be excitatory.
00:37:33 - And when it's inhibitory, it's very difficult because Bikini cells are also inhibitory.
00:37:39 - And the climbing fibers are excitatory.
00:37:42 - The net effect would be a positive feedback system which is unbiological and
00:37:49 - and it can never be stable and there are all sorts of problems with that but
00:37:53 - if and this so this looked as a problem when it was thought that the effect
00:37:59 - of the climbing fibers was the excitatory.
00:38:03 - Providing excitatory input to the pre-kindle cells but if the pre-kindle if
00:38:08 - the climbing fiber induces a weakening of the parallel fiber to Purkinje cell
00:38:16 - synapses or if they produce post-responses in the Purkinje cell,
00:38:20 - then it becomes a negative feedback pathway.
00:38:23 - And that makes sense because it might control learning.
00:38:26 - So the idea that
00:38:29 - we have tried to pursue has been that when
00:38:33 - the cerebellum the
00:38:36 - cerebellum learns to produce an excitatory output
00:38:39 - signal generating a learned
00:38:43 - movement like an eye blink it will at the same time send a signal to the inferior
00:38:48 - olive that is inhibitory and that weakens or turns off the learning the teaching
00:38:54 - signal coming from the olive so it means that when the learning has reached
00:38:58 - a certain level you turn off the learning machinery So,
00:39:02 - you would prevent a kind of overlearning.
00:39:05 - And that in itself might not seem to be so important, but it does have important consequences.
00:39:10 - And one of them is that if the subject learns to respond to a certain stimulus like a light.
00:39:20 - And then, or say, sorry, like a tone.
00:39:23 - And then you add. So suppose you learn to blink to a tone. So each time you
00:39:28 - hear the tone, you blink nicely, a conditioned blink.
00:39:30 - Then you add a light on every trial.
00:39:36 - And pair the light with the tone and the air puff.
00:39:40 - If you then test learning to the light afterwards, you will find that somebody hasn't learned.
00:39:46 - Now, that makes biological sense, because why should it
00:39:48 - learn to respond to the light when you already have
00:39:51 - the tone and the tone enables you to avoid
00:39:54 - the air puff without paying any
00:39:57 - attention to the light so it would be just a waste of circuitry
00:40:00 - a waste of energy and so on to also learn to respond
00:40:03 - to the light but this system this
00:40:06 - mechanism will do precisely that because whenever
00:40:09 - you have the tone and the air puff the
00:40:13 - the subject generates the condition blink an output signal you turn off the
00:40:18 - learning mechanism so when the light comes on the subject doesn't learn anymore
00:40:24 - it has already learned to respond to the tone so it doesn't need the learning
00:40:28 - machinery anymore and it will prevent the animal from forming.
00:40:32 - Associations that are of no use but they're like redundant yeah exactly they're
00:40:37 - redundant right but then information but the interesting implication of that
00:40:41 - is that this learning machine.
00:40:43 - Has set itself up to never be a perfect learner
00:40:47 - because as soon as you started and block this
00:40:50 - teaching signal of the the climbing fiber signal you are creating conditions
00:40:54 - for extinction yes right so in some sense the learning plateau is now defined
00:41:00 - by by let's say the correct prediction then setting in motion extinction that
00:41:05 - forces you again then to learn because you start to make mistakes, right?
00:41:08 - Well, my view is if you have a thermostat system, the system will,
00:41:16 - when the temperature increases, it will turn off the heating.
00:41:21 - The heating, temperature go down, heating will be turned on,
00:41:25 - and you will have an oscillation around a set point.
00:41:28 - And I guess the same thing happens here. You have a set point,
00:41:32 - and you reach some kind of equilibrium,
00:41:35 - and you get a little bit of extinction and that
00:41:38 - suffices to turn on the learning the teaching machinery
00:41:41 - and you will learn and you will
00:41:44 - oscillate around a certain certain level
00:41:47 - okay but it also means it's always testing the hypothesis is predicting right
00:41:52 - yeah by just this this if you want non-specific extinction that it imposes upon
00:41:58 - itself yeah okay but now another Another aspect of this circuit is that in turn
00:42:04 - the inferior olive also projects back to the deep nucleus.
00:42:08 - Right. Is that of any significance in this learning perspective? I just don't know.
00:42:14 - My guess is that you can have some other form of learning in the nuclei and
00:42:19 - maybe those are also elicited by these collaterals.
00:42:26 - I don't know. Another possibility is that when the teaching segment to brachyndosal
00:42:33 - will cause the brachyndosal to fire and provide an inhibitory signal down to the nucleus.
00:42:39 - And maybe that inhibitory signal interferes with the normal movement.
00:42:44 - So if you have a signal coming via the collateral, it would help to cancel that
00:42:50 - meaningless inhibitory signal coming from the Purkinje cell.
00:42:53 - I don't know. This is pure speculation.
00:42:56 - But on the other hand, what is intriguing about this is that the inferior olive
00:42:59 - has its own spontaneous activity, right?
00:43:03 - Which is about one hertz to 10 hertz, depends who who
00:43:05 - you talk to um but now so
00:43:08 - it's not the case that that you only have climbing fiber activity when
00:43:12 - you actually have this unconditioned stimulus it's actually interspersed with
00:43:16 - a spontaneous level of yes and and it looks as if the climbing fabric input
00:43:20 - not only teaches the perkin cell to respond to particular specific stimulus
00:43:26 - it also regulates the background firing rate of the Purkinje cell.
00:43:31 - So normally the olive will fire with around one hertz or so.
00:43:36 - If you increase that to just over two hertz, you will silence the background
00:43:41 - firing of the Purkinje cell. It will totally silent.
00:43:44 - And if you reduce the background firing rate of the olive down to half a hertz or zero,
00:43:51 - after half a minute or so, the Purkinje cell will start firing with very increased rate.
00:44:02 - But when that happens, when the Purkinje cell background firing goes up,
00:44:07 - it will suppress the nucleus.
00:44:12 - Which will reduce the inhibitory signal to the olive, which will increase the
00:44:17 - background firing rate of the olive, and that will depress the Purkinje cell
00:44:21 - background firing rate.
00:44:22 - So you have a negative feedback system, not only for controlling learning,
00:44:26 - but also have a negative feedback system for controlling the background firing
00:44:30 - rate of the Purkinje cell.
00:44:31 - But now, in some sense, you could argue that maybe, if you think about eyeballing
00:44:36 - conditioning, it's actually a very tiny perturbation on the intrinsic dynamics of this system.
00:44:42 - So, maybe this learning system is just trying to keep, let's say the Purkinje
00:44:46 - cells are just trying to keep the inferior olive at some optimal level of activity, right?
00:44:51 - And tries to regulate it up and down by regulating the deep nucleus essentially, right?
00:44:57 - So, it's really homostatic negative feedback. Yeah, this makes it very difficult
00:45:00 - to theorize about it because it's not clear to me what is regulating what.
00:45:04 - Okay. Is it the Purkinje cells that are regulating the olive or is it the olive
00:45:08 - that are regulating the Purkinje cells?
00:45:09 - Well, it would basically mean that if you have, let's say, this closed-loop
00:45:13 - homostatic system where the Purkinje cells are regulating the inhibition of a deep nucleus,
00:45:19 - so you in turn regulate the inhibition onto the inferior olive,
00:45:25 - so you can keep it at a fixed rate, somewhere between 1 to 10 hertz.
00:45:29 - Now, if I have a climbing fiber of an unconditioned stimulus coming in,
00:45:32 - I start to speed up my inferior olive, right? So that would say,
00:45:35 - okay, now I have to sort of start to increase my inhibition to an inferior level
00:45:39 - to bring it back to this baseline that I want to keep it at, you see.
00:45:42 - So this might be, in that context, you could also account for cluster conditioning.
00:45:48 - But then what the learning system is still trying to do is keep this inferior
00:45:51 - olive neurons at the right level of firing and it doesn't act.
00:45:55 - And that you get an eye blink associated with it is something you get for free.
00:46:00 - That is how this system is wired up. So the emphasis of the learning system
00:46:04 - is on the controlling the fear olive as opposed to controlling the periphery. Is that reasonable?
00:46:10 - Well, it's certainly consistent with what we know, and I just don't know.
00:46:15 - I find this a very difficult subject to speculate on. Okay. It has puzzled me
00:46:19 - for a long time and confused me. Right.
00:46:23 - But we have an idea now about what this circuit does, right, how this could operate.
00:46:27 - And what is interesting about this, and now we also know that all the data we
00:46:32 - have is actually only describing a tiny fraction of that system, right? Right.
00:46:37 - So, what's the rest of the cerebellum actually doing?
00:46:43 - Well, a large part of the cerebellum will control movements that are in a certain way similar to eyelid.
00:46:48 - It will control various muscles like leg withdrawal or finger movements and things like that.
00:46:55 - Some parts of the cerebellum will control the forebrain.
00:47:00 - You have a huge part of the cerebellum projecting to the forebrain.
00:47:05 - And what it does there we don't know but presumably at least to some extent
00:47:09 - what it does is it changes the.
00:47:15 - Excitability of pyramidal cells controlling movements so that for instance if
00:47:20 - you make an error when you try to reach something,
00:47:24 - the cerebellum can learn to correct your movements and exciting a little bit
00:47:29 - more those muscles that would tend to move your arm in a certain direction and
00:47:34 - so on So that is one thing that's happening.
00:47:38 - You have all the responses...
00:47:42 - Of the this your system of balance that the
00:47:45 - cerebellum controls it could operate in
00:47:48 - a way the similar type link conditioning but my guess is that there
00:47:51 - are significant differences but now a few years ago you also proposed that these
00:47:57 - kinds of learning systems could actually underlie our ability to simulate right
00:48:02 - to support internal simulation or because now your examples you seem to emphasize
00:48:07 - very strongly the motor aspect of this.
00:48:11 - Yes, but my view of internal simulation is that it's very similar to actual
00:48:15 - motions, just as you turn off the output signals from the primary motor cortex.
00:48:22 - And for all we know, it could well be the cerebellum that is doing it.
00:48:26 - It could be the cerebellum that turns off or prevents movement from coming out.
00:48:30 - We normally think of the cerebellum as producing signals to excite the motor
00:48:34 - neurons in the motor cortex. But it could just as well be the opposite.
00:48:38 - They could very well be there in order to inhibit or stop movements that could be dangerous to you.
00:48:44 - So just as the cerebellum can produce a movement of the eyelid in anticipation
00:48:49 - of something that might be harmful,
00:48:54 - like an air puff or an insect coming into your eyes or something,
00:48:57 - It could very well also project to stop or prevent movements that might be harmful.
00:49:06 - For instance, you are walking, you are approaching something that is dangerous,
00:49:10 - you should stop walking before you fall off a cliff or something.
00:49:15 - Maybe the cerebellum is producing a signal that will enable you to stop the
00:49:22 - ongoing movement before something dangerous happens.
00:49:25 - Happens and the cerebellum is very good at it because it's
00:49:28 - so well timed and it's very fast compared to these signals
00:49:31 - coming from let's say the visual cortex to the fore to the forebrain it's very
00:49:35 - very slow and you need for quick adaptation anticipating dangerous events you
00:49:44 - need a fast system and the cerebellum is good at that but now do you believe that this um that
00:49:50 - also plays a role in, let's say, conscious states or conscious processing.
00:49:56 - Do you see this kind of simulation that you describe occurring in the cerebellum
00:50:01 - or being supported by cerebellar processing also feeding back into conscious
00:50:06 - states or do you really see those as completely distinct subsystems?
00:50:10 - I don't think the cerebellum in itself could be conscious, But I do think that
00:50:15 - the cerebellum is an integral part of what is going on in the cerebral cortex.
00:50:23 - And I think that consciousness has to do, well, consciousness is a term that
00:50:29 - covers too many different things.
00:50:30 - But in my view, the most critical part of consciousness is the fact that we
00:50:35 - have an inner reality that we can perform movements and see things and hear things.
00:50:43 - Internally in the brain without connection to the external world and that is
00:50:47 - what i mean by simulation so the cerebellum would play the same role in simulated
00:50:52 - movements as it does in overt movements and it would generate anticipated movements
00:50:58 - even if they are not and it would stop.
00:51:04 - Continuation of a movement that just incipient and you just started start doing
00:51:09 - the cerebellum could prevent that from occurring.
00:51:12 - And by doing that, it will always modulate the internal simulation.
00:51:18 - It will also, in that sense, modulate what's going on in your inner reality
00:51:22 - and, if you want, in your consciousness.
00:51:24 - Okay, but then it's more, let's say, an assistive function that then presents
00:51:31 - this information to the conscious scene.
00:51:33 - It's not really directly, let's say, it's not directly carrying that conscious scene. No, it's not.
00:51:40 - But it has a particular kind of importance because one of the important aspects
00:51:44 - of consciousness is your ability to anticipate what is going to happen.
00:51:48 - And you are aware of something might be dangerous. If I do this, then that will happen.
00:51:55 - This is something you're always aware of and it's a very important part of the
00:52:00 - function of consciousness, I think.
00:52:01 - And the cerebellum is very good at anticipation, and therefore I think that
00:52:07 - the input from the cerebellum to the frontal cortex is very important for consciousness.
00:52:12 - But I could argue that also unconscious functions have predictive components
00:52:17 - to them. Oh, absolutely, absolutely. Absolutely.
00:52:19 - And in fact, when you, I don't know if you've ever experienced being subjected
00:52:25 - to eye blink conditioning, but
00:52:27 - when you, if you do, you will notice how surprised you are when you blink.
00:52:33 - Okay. It's not, it's not as if you're aware that, that, oh.
00:52:39 - I hear the tone soon there will be an air puff i'd better
00:52:42 - blink so that i i avoid the air puff it's actually
00:52:45 - when you notice that the movement you're really surprised and i think the same
00:52:50 - thing happens when you learn let's say to play the piano or any musical instrument
00:52:55 - that that you you train and then suddenly you reach a point where your fingers
00:53:01 - move by themselves you're not really.
00:53:04 - You don't feel that you are moving the fingers you feel as if they are doing it themselves.
00:53:09 - Because of an unconscious process and what has happened is that the cerebellum
00:53:13 - has taken over into doing right exactly but so another so now that we solve
00:53:17 - the puzzle of consciousness,
00:53:18 - let's let's try another one which which i find
00:53:21 - very very intriguing with respect to the cerebellum which is the one of causality
00:53:25 - because which actually you also studied prior to entering into neuroscience
00:53:29 - yes i worked in philosophy for a few years before yes and and so what's interesting
00:53:33 - there is in the amount of conditioning we have this debate between contingency
00:53:37 - and contiguity being dominant in conditioning.
00:53:40 - That means either it has a specific order of events that matters,
00:53:44 - or is it just that events co-occur in space and time, right?
00:53:48 - So now in some sense, you could argue that the cerebellum is actually wired
00:53:52 - up to be sensitive to a very specific order of events, right?
00:53:57 - So that would be the contiguity view of conditioning.
00:54:00 - But I could also now make an argument. You could argue that from an evolutionary perspective,
00:54:06 - what is wired into this learning system is that causal relationships do exist
00:54:11 - out there in the world because I have wired myself up to pick them up within
00:54:16 - a timeframe of up to one second, right?
00:54:19 - So do you feel that this wiring of the cerebellum from a sort of evolutionary
00:54:24 - epistemological perspective tells us that causality is actually out there in
00:54:29 - the real world and that this is the way of the brain to deal with it?
00:54:37 - Well, you are now touching some extremely difficult questions.
00:54:42 - I mean, we are really entering deep waters here.
00:54:51 - And I can't comment on everything you said here, but let me first say that in
00:54:58 - any behavior, the order of different components of your behavior is very important.
00:55:06 - I mean, in language it's very obvious that the order of words is extremely important
00:55:11 - for the comprehensiveness of the message.
00:55:14 - Order can be achieved by a temporal code.
00:55:19 - If every component of your speech has a specific time, then order will be secondary.
00:55:26 - It will impose an order on it because if
00:55:30 - if the first phonemes
00:55:34 - are are generated early and the
00:55:37 - later phonemes are generated late then the order of the
00:55:40 - phonemes become sort of an unavoidable consequence but
00:55:44 - of course it's also possible that
00:55:47 - the cerebellum and the cerebellum might be
00:55:50 - important for that but it's also possible that the cerebellum imposes an
00:55:53 - order you can you can imagine for instance either you
00:55:56 - have let's say that you play a piano and you have you're moving a certain a
00:56:02 - certain finger in a certain number of times on a key and each key press has
00:56:07 - a specific time on it so you can
00:56:11 - imagine the purkinje cell sending out controlling that muscle sending out.
00:56:16 - Temporal signals to to press the key now
00:56:20 - and now and now and now but you could also imagine you had a chain of responses
00:56:25 - so the first response would cause the second response which causes the third
00:56:30 - response right and that is a very different kind of phenomenon and one of the
00:56:37 - The difference is that in this case,
00:56:39 - you could scale up and down the speed of the movement.
00:56:46 - So an interesting thing is that you can talk a little bit slower,
00:56:51 - but the order of the various components of your speech will be the same.
00:56:57 - This is difficult to understand if you have timed signals coming all the time,
00:57:04 - determining the exact time of each component.
00:57:10 - It's much easier to understand it if you have a sequence of cause-effect relationship
00:57:15 - as if one conditioned response triggers
00:57:18 - a second conditioned response that triggers a third one and so on.
00:57:21 - But what I was after was also to look at just the anatomy of this system, right?
00:57:26 - Because it's very peculiar that you have these widely divergent parallel fibers
00:57:32 - conveying states of the world and of the brain itself converging with these
00:57:40 - highly specific climbing fibers and really tell you something,
00:57:43 - let's say, intrinsically meaningful,
00:57:45 - right? Okay, now this was painful, right?
00:57:48 - And it is already structured in a way to deal with.
00:57:51 - Time, right? That something happens before something else, but they can co-occur, right?
00:57:58 - So isn't that one of the necessary conditions of a causal relationship? Yes, of course.
00:58:03 - So this is why I was wondering whether we could not argue that really the cerebellum
00:58:08 - is really biased towards, let's say, picking up.
00:58:12 - Causal relations but in a very permissive
00:58:15 - fashion right so it can also pick up illusory i wouldn't
00:58:19 - necessarily say causal because i because i think
00:58:22 - this would happen whether the whether the relationship is causal or pseudo correlation
00:58:25 - from the point of view of the cerebellum it doesn't really matter what matters
00:58:30 - is that the air puff tends to follow the tone even if the tone is not even if
00:58:36 - the air puff is not caused by the tone so but that's a force in the lab right Yeah,
00:58:42 - but from the biological point of view, if you look at it in sort of infunctional terms,
00:58:49 - the important thing is that you have a predictive relationship,
00:58:52 - which could be a pseudo-correlation that doesn't have to be causal.
00:58:56 - So my guess is that the cerebellum would learn a non-causal correlation just
00:59:01 - as well as a causal one, and it doesn't really matter.
00:59:06 - Okay, the only thing I could then say in my defense is that,
00:59:09 - of course, given that the system always learns to extinction,
00:59:13 - right, it does with time zoom in on truly causal relations because these will
00:59:19 - be the only one that are persistent in an interaction with an environment.
00:59:22 - That's true, that's true.
00:59:23 - And this is what is, yeah, and this is what often happens with pseudo-correlations.
00:59:27 - They break down eventually.
00:59:29 - Right, exactly. Because they are, because they're not causal,
00:59:32 - it's possible to interfere with them in a different way.
00:59:33 - That's exactly right yeah okay great so now that we also solved the causality
00:59:37 - problem that's wonderful Jerry we're making great progress here so let's finish up with.
00:59:43 - My last two questions so look you're in the business for a long time 25 years
00:59:48 - working your way through the cerebellum and I think we made amazing progress
00:59:52 - understanding cerebellum.
00:59:55 - Also if you have farmed out to issues in consciousness so based on your experience
01:00:01 - and your knowledge what would be jerry's law in our study of the brain,
01:00:08 - pre-kinder cells learn temporal relationships not only changing strength of synapses okay,
01:00:17 - okay that's my punchline all right and then if i'm going to visit you five years
01:00:24 - from now at lund and i'm going to say okay jerry you made the prediction five
01:00:28 - years ago and i want to see what happened with it what's the one prediction
01:00:31 - you would like to sort of commit yourself to today.
01:00:38 - That is very difficult to say because I can see before me a lot of some very,
01:00:43 - very interesting avenues of research.
01:00:46 - You have to give me one prediction. I don't know what they will generate,
01:00:52 - but I suppose I can tell you what I think we will have learned.
01:00:57 - We will have learned something about the molecular underpinnings of learning
01:01:03 - a temperate relationship.
01:01:04 - Relationship so i think we will have gone much deeper into receptor physiology
01:01:09 - and second messenger systems and so on in the pre-kinder cells but there are
01:01:14 - also a number of very difficult and,
01:01:19 - at the moment unsolved problems about how the cerebellum interacts with the
01:01:24 - cerebral cortex and if you take one very nice example prism adaptation if you
01:01:31 - wear prisms that displace the outside world laterally.
01:01:36 - Then if you try to point to a certain point at a certain object, there will be an error.
01:01:42 - You will point to the side of that object.
01:01:46 - And pretty soon, if you train to do pointing, wearing these goggles with displace
01:01:52 - the outside world, you can fairly quickly adapt to it and you can point in the right direction.
01:01:57 - The same thing happens if you have prisms that turn the world upside down.
01:02:00 - Adapt to that also pretty fast.
01:02:03 - Now, this is believed to be done by the cerebellum. And given what we now believe
01:02:09 - about learning in the cerebellum, it means that pre-kindi cells controlling
01:02:13 - the muscles that point your arm and finger,
01:02:19 - those pre-kindi cells will send some kind of corrective signals up to the motor cortex.
01:02:25 - Now, how do these pre-kindi cells learn to do that? they would need climbing
01:02:32 - fiber signals to change their responses and where do the climbing fiber signals come from.
01:02:39 - What triggers the learning is the mismatch between the intended movement and the actual movement.
01:02:45 - You're pointing not where you intended. There's nothing wrong in pointing in a certain direction.
01:02:50 - It's wrong only when you intend to point at something else.
01:02:54 - So there must be some way for the brain to detect a mismatch between what you
01:03:00 - intend and what you actually do.
01:03:01 - And that mismatch has to generate, activate inferior olives so that you get
01:03:07 - a climbing fiber signal to the cerebellum.
01:03:09 - This is extremely intriguing and we just don't know.
01:03:13 - We don't even know how the intended movement is encoded. We don't know really what that means.
01:03:20 - And how do we detect the mismatch? Where does that occur?
01:03:24 - And it seems to me that this will, if you can answer those questions,
01:03:28 - you would have gone a very long way to understanding how the cerebellum interacts
01:03:31 - with the forebrain because as you know
01:03:34 - the cerebellum takes part in all your movement and probably
01:03:37 - also in your cognitive function when you just simulate movement but but
01:03:41 - it it takes part in all of it it fine-tunes the
01:03:44 - amplitude the precision the timing and so on but it in order to learn it it
01:03:50 - will have to to receive climbing fiber input not only when you do something
01:03:55 - painful but also when you do something that you didn't intend to do and how
01:03:59 - is that signal being generated.
01:04:01 - And this is something that I believe we will know perhaps not in five years, but in 10 years.
01:04:07 - That's great. Well, Jerry Haslow, thank you very much for this conversation.
01:04:11 - Thank you. It's very nice.

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Germund Hesslow on cerebellum and pavlovian conditioning

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