This is the Convergent Science Network podcast. Leading researchers in the domain
of neuroscience, brain theory and technology are interviewed by Paul Verschure and Tony Prescott.
This is Paul Verschure with the Convergent Science Network podcast and we're
here at the 10th anniversary summer school, the Barcelona Cognition,
Brain and Technology Summer School.
And I'm here with Lynn Jurek and Bashir Yaraya, who are presenting this morning
their collaborative work on anesthesia, the brain, the thalamic cortical system,
and also how we can develop animal models of this.
So now Lynn how do you think the kinds of systems you're looking at are helping
us understand how the brain works so the particular angle that you take of anesthesia
how is this really helping and how is it strategic,
I think it's very important to know what we are doing in everyday clinical work
because so I'm an anesthesiologist at the beginning and when I started my My
residency in anesthesia,
the first question I asked was at one moment,
how anesthesia works on the brain?
And the answer I got at the very beginning was, okay, it works,
why do you ask this question?
So that's why I came to the idea to study anesthesia, because at some moment
the problem of anesthesia was to make it safe for patients.
So there was a lot of improvement in the hemodynamics of anesthesia,
in the respiratory field of anesthesia
and so on, but not really in the neuroscience fields of anesthesia.
So it was like at some moment you can get a shutdown of the brain. Okay, it's nice.
People don't remember what happens, but then at the beginning when I started
my residency, there was not much more that was known about anesthesia.
And so at some moment it was like I want to know better what I'm doing to take
at some moment perhaps better care of the patients I have in charge.
So it's fair to say that actually we don't really know why anesthesia works.
No, I think today we know more than 10 or 15 years ago.
Okay, but still today we don't really know why people lose consciousness with
different drugs we use in everyday life.
And so what was really impressive in also your talk is the overview you gave
of the different, let's say, interventions we have available today. Okay.
To induce these states of consciousness that you might use in the surgery ward.
So what are the most dominant interventions that you're using?
I think between the most dominant drugs we use in everyday clinical practice, there's propofol.
Propofol is used everywhere in the operating room.
Also for the volatile agents is most sevoflurane, sometimes isoflurane, which is an older drug.
And then if you have patients in the intensive care unit that are not very stable,
you use ketamine because it doesn't act on the hemodynamics of the patient.
So I think these three are mostly used and probably in the future what will
be used at least in the intensive care unit probably dexmetadometin because
it's thought to induce a sleep-like state.
But would perhaps be more physiological condition for the patient.
But that's right now more in experimental phase, so that's already being used?
It's already being used in intensive care units, yes. When you wake up patients
at some moment to induce like a sleep-like state. Right.
But now the pathway of action of propofol and ketamine, and this also will be
relevant later when we look at you and understand and analyze your data, is rather opposite.
Yes, yeah. It's completely the opposite on the brain. So we can say propofol
is essentially driving the inhibitory system.
Yes. Right? This is fair to say in a rather nonspecific way.
Yes. Okay. Well, ketamine is more specifically acting on the excitation on the inhibitory system.
Yes. Right? Because it acts on the NMDA receptors on the GABAergic cells.
But is there some sort of regional specificity to that in any way?
Let's say for the ketamine drugs, it's mainly acting on the cortex,
not on the subcortical regions and on regions like the amygdala of the hippocampus.
And for propofolates, it's thought that at the beginning it acts on the cortex
and in a second phase of action, it acts on the subcortical regions.
There are human studies, So one human study by Leonel Bede who showed this like 10 years ago.
Right. Patients. So this is really one mystery that we should try to clarify,
right? We have these two drugs.
They in some have an opposite effect on the inhibitory system of the cortex
while still leading to the same outcome with loss of consciousness.
So we have to solve that one before this podcast is over.
And this is also what you have been trying to do, following very specifically
a very unique paradigm that has been pioneered in the lab where you both are
working, which is a local and global paradigm.
Right. So I don't know.
Which of you two would like to speak for the local global paradigm?
But Bashir, you have been very active in that.
So what's so interesting or unique about this local global paradigm?
The local global paradigm is a series of sounds that you can listen to.
This is what we call a paradigm.
The idea came in from our friends and colleagues, Sénissas Dehaene and Yonel Nakache.
What does it mean, local versus global?
So if you listen to small sounds like beep, beep, beep, boop,
you have the same sound, identical sound coming in, and then what you call a
deviant, so you violate a rule at the local level,
because it is a small, tiny scale of time.
But this has been investigated for decades, and if you do an EEG called ERP,
Nathaniel described what we call famously the mismatched negativity.
People were excited about it, tried to perform this paradigm in anesthetized
people, in people emerging from coma, but unfortunately was not discriminative
of loss of consciousness.
So even without consciousness, your brain, you can still process this mismatch
negativity or the local part of this local global paradigm.
So the trick there was to multiply the sequence, this local sequence,
several times, and this time introduce a violating sequence.
So the new sequence that comes by the end, like for example,
this last sequence, is violating the other one.
This is the global violation. And it turns out that it works fantastically because
you really need to be conscious to process this global effect and to have your
brain realizing this sequence violation.
If you have, for example, a vegetative state with a patient that never recovered
any consciousness, then you definitely cannot realize this global part of it.
And do you think you can stack these sequences indefinitely? Is it like recursive?
Currently, the structure of the sequence by itself is not aimed at recursive detection.
This is definitely, there are variety, we are developing varieties of this paradigm
to check for syntax, for numerosity. We did that even in animals.
But so far, we consider that as a marker of conscious access.
So...
So now we have this paradigm where in some ways we have local and we have global deviations, right?
So you see this as a specific probe of states of consciousness or aspects of consciousness.
The global part of it as opposed to the local.
This was demonstrated by Tristan Bekenstein, a paper with Dylan Akesh and Seyes Doan.
And they showed that in humans, at least,
healthy people distinguish very nicely the global effect from the local effect,
meaning that the global effect will need a large-scale cortical activation,
will induce large-scale activation.
Actually, our contribution came in with the animal aspect of it.
The question was in that time, there were two questions.
First, could we infer the same thing in non-human animals and our closest cousins,
let's say non-human primates?
And second, starting from an animal model in which we can induce anesthesia,
could we manipulate this global detection with the manipulation of consciousness?
Right, okay. So if we now look at this, the human case, what we look at is now
a paradigm that allows you to access, if you want, informational aspects of conscious processing.
So we're not saying much about the experiential, phenomenological aspects of
consciousness, right? This is not part of the discussion now.
Exactly. So we're really focused on access consciousness.
And then what you see is a very distinct correlation between,
let's say, these local sequences and, let's say, A1 processing in the temporal loop,
or more broad activation in what in your center is called the global neural
workspace. Absolutely. Right?
So what are then the core nodes in that global workspace that you observe in this paradigm?
So if the regions be activated with this local global paradigm,
and especially for this global effect, There are parts of the prefrontal cortex,
there are parts of the parietal cortex,
there is the anterior cingulate cortex and the posterior cingulate cortex,
at least for the cortical regions that we activate with this paradigm.
If you go to deeper structures, there are structures of the thalamus,
like the paraphysical and the nuclei of the thalamus, and part of the striatum
that you can activate with this paradigm. that.
Okay, so now we have a starting point, right? So then you say,
look, there's a form of conscious processing we can now manipulate.
We have a neural substrate and indeed the big step, as you also earlier said
Bashir, the big step was now to bring that to an animal model because then you
would have more experimental control, right?
So how well did that generalization to the animal model really work? Lynn?
I think it worked quite well because at the beginning we had no idea if the
animal could detect this global effect.
What was quite true that it could detect the local effect because there were
older studies with electrophysiology that showed that if you,
do invasive electrophysiological studies in the auditory cortex that you can
get mismatch negativity that you can record in the auditory cortex. So we.
That at least what we expected. Then was the question, could
it detect something more complex because
if you want yes to learn like a rule like if you have like five identical sounds
then you get this as a rule and at some moment you get this global deviant and
in all the animals that were tested,
they were tested several times in the scanner there are three animals in total
because for monkeys often you it's difficult to have more animals because you
have to be trained at the beginning And the data we show where group analysis of this monkey,
but if you look at the individual level, all the monkeys could get activations
in the prefrontal cortex, the parietal cortex,
anterior cingulate, posterior cingulate, and some also had activations in the hippocampus.
But now, what's the magnitude of these differences between the local and the
global variations of the task? and how does this magnitude compare to what you observe in humans?
There's actually two remarks there. First, there is a strong hierarchy.
So, the local global paradigm introduces the notion of hierarchical levels of
violations, of sequence violations.
And that is really important. This is in line with what we call the predictive coding theory,
and what we saw already in humans, we see exactly the same homology in monkeys,
is that because the global violation is hierarchically superior to the local violation,
it also activates a high cortically organized the frontal parietal network,
whereas the local effect was really activating the low-level auditory pathway,
including within the brainstem until A1.
And we saw that exactly in a homologous way in the macaque.
Meaning that in the macaque, we saw the auditory pathway from the brainstem
nuclei until A1 for this low-level deviant, which is a local effect,
while when we go to the global violation,
the second level of hierarchy, you see involvement of both prefrontal and parietal cortex.
And we went even a little bit further to see how much this is really specific
to the global effect by doing a technique in fMRI data called psychophysiology, interaction,
PPI, and this put in a seed in A1, PPI could show that really global effect
increased specifically,
brain activity increased specifically in these frontal parietal singular areas
when the global deviant comes to the macaque auditory system.
Okay, so in the human case, we see some frontal parietal signature of the global task, right?
And then in the macaque, you see something similar, also in fMRI,
right? Exactly. We're doing fMRI in the macaque.
But now we have, of course, this whole conundrum of homologues,
right? What are homologues between macaque brain and human brain?
And actually, if you just look at the pictures that you present,
also in your work, it would appear that, for instance, these spots of activity
are a bit more lateral in the macaw case as compared to the human case.
Maybe I misinterpret, but how do you deal with the issue of homologue,
of homology? It's really a tough issue.
I like the question because we are interested in that, in brain-monkey comparisons,
because this sheds light eventually on the uniqueness of the human brain, of course.
And technically, it remains very, very challenging to do direct homology studies
between the anatomy of the primate brain and the human brain.
There are already some tools existing in the literature.
There are still a lot of work to do there. And we are interested to do that in the future.
Because it's tough to compare brain maps by direct visual, our visual system basically.
And the notion of homology is not that trivial that we could think.
What was important in our case is really to see that the two orders of violations,
the two hierarchical orders of violations in monkeys, just like in humans,
were paralleled by two...
Hierarchical order of cortical activations. That was important in our case.
Right. But now imagine we do something stupid, which I like because these are things I'm good at.
And we just inflate or sort of in a very linear way map this macaque brain to a human brain.
Would you predict that then the nodes in this global network in the macaque
would align with those in the human brain or not?
I'm not sure we can really fix the problem this way. There are tools in Caret,
for example, Caret software offers tools to do just this direct alignment by simple inflation.
However, you need to keep in mind that the human development of a human brain
was not just about inflation of volume, as you know, but also of specification
and local specification.
And on top of it, all the education and training. meaning.
This is clearly one of the challenges of the next years is how to develop really,
proper tools to do these direct comparisons.
Because with the ability to train monkeys and especially cac monkeys to sit
in the scanner and to listen to the exact same paradigm in the same condition
than the human counterparts,
we start to, for a while already, with Vandafil, Nikos Drogathidis and Dois
Tsao and other people we start to have this unique opportunity,
we have two maps for exactly the same experimental setup, how can I deal to
have a direct comparison, a computational,
comparison, that's something we are also working on But what is interesting
is that it might mean that,
that the midline structures of the macaque brain might be organized somewhat
differently as compared to those of the human brain, even though,
let's say, from a phylogenetic perspective, they're relatively close.
Would you agree with that?
Again, I would say that not only comparative anatomy is needed there,
But we need to automatize tools based on tracer studies, for example,
to match the two brains.
Will there be a clear transform between the two brains?
If we think about all the millions and years of evolution that made this strong
job, I'm not quite sure that we have an easy transform, direct easy transform. Right. Okay.
So we have this paradigm. We see that we go from a local process to a more global process.
But now what you're relying on is a paradigm that assumes that the animal is
basically passive but aware.
More as the human is passive and aware in this resting
state paradigm and it's not that the resting state was invented because it's
behaviorally so interesting it's just the simplest thing that people can do
as they sit in a scanner or lay in a scanner uh right surrounded with this noisy
equipment so now we're forced into the monkey as well so that means and also i brought this up in
the talk right that the monkey is sitting there we assume the monkey is sort of at rest and aware.
But we have actually no real idea whether this is in any way pertaining to the
consciousness of this macaque monkey, right?
So how do you, do you see this as a limitation of these studies that we have
no way, that there's no reportability, that there's no overt behavior coming out of this monkey?
Do you see this as a limitation or you don't think this is a problem?
It is, of course, a limitation, very clearly. so
how to do to fix
the problem one way is to
train massively the monkeys to report for the detection of the local violation
versus the global violation of course we thought about that the problem with
that is that it implies a lot of training with the paradigm And in our case,
we try to, at least this was our strategy, we discussed a lot before starting
this research program. Yes.
We try to keep really the monkeys naive to the paradigm because overtraining
with the paradigm is always a profounding source for the interpretation.
Now, I agree, you pronounce the word reportability.
But I would say also that we start to accept fMRI as a reportability now in
humans with disorders of consciousness.
When you see all this work by the Liège and Cambridge groups showing with this
tennis imagery paradigm in highly disabled people with minimal conscious state,
actually these people really do not report except through fMRI.
So fMRI activation is also being acceptable reportability.
Well, but that's maybe more a message of hope, right? Because it doesn't work in all patients.
No, no, no, no, it doesn't. So, but okay, so here we have our paradigm.
We have a local global effect.
It's sort of, let's say, let's call it weakly analog to what you see in a human.
I mean it weakly because we cannot really nail whether it's homologues or not,
but you see a local global effect involving frontal and parietal systems.
So fantastic, right? Great. So now we have calibrated, we mapped the paradigm
to the macaque monkey, But now the real stuff starts because now you start to
manipulate these states of consciousness with propofol and ketamine and other drugs.
So, Lynn, what happened when you started to do that?
So, at the very beginning, we had to make sure already that the anesthesia protocol
would work because you cannot like put your monkey in the scanner,
put one drug and then see what happens.
Happened there was a lot of work that was done outside the cancer scanner before
going to the scanner to make sure that already the anesthesia level was stable
at every during the whole experiments so the anesthesia model was based like
for propofol it was and also for kadamine after,
it was based on behavioral scale of the monkey because he want to go to general
anesthesia so So normally general anesthesia, you are not conscious.
And then we had like behavioral tested with it in the monkey.
And also you had to make sure that you have a stable EEG pattern for your anesthesia.
Because you cannot say that you use like X milligram per kilo of a drug and
then it will work for everybody.
Of course, it didn't work for the monkeys. So we had to adapt the anesthesia
concentrations on the behavioral scale and on the EEG before doing the whole
paradigm after in the scanner.
And then, but, so, okay, first you have to fine-tune the paradigm,
you have to get to the right dosage, so you sort of nailed that problem.
Of course, it's a very hard one, right?
But then, in some way, you saw a differential effect of the ketamine and the
propofol was not identical in its impact, right? No, no.
It was like really closely, for the local effect was quite close.
But let's say we weren't really interested in this local effect because there's
a lot of literature showing that if you do electrophysiology,
even in humans, that if you go to general anesthesia, often you lose some mismatch negativity.
So we're not surprised that at some moment you don't get a local effect in these animals.
What was quite surprising was for the global effect, because it could have been
that, okay, you have no local effect, you will have no global effect at all, and so you have nothing.
You will activate your auditory system when we present all the sounds or do
the contrast for all the sounds for fMRI.
That was at least what we were expecting, because it is reported in literature
that the sensory cortexes are still active under anesthesia, but not beyond.
And then at the beginning, we were quite surprised that we had no global effect
at all for ketamine, and that still we had activations, especially in the prefrontal cortex of propofol.
So that was one explanation could be that they act on different receptors,
and what gives us explanations, but it's not completely sure.
We cannot completely make sure that this… So the main thing that you observed,
that you also described, is that with ketamine, you don't see the activation
of this frontal parietal network, right? Well, with Propofol you do.
But now in the Propofol case, is this frontal parietal network then still identical
to what you might see in the control case?
No, no. When you compare it to the wake state, what you see that you still get
activations in the prefrontal cortex, but activations you never get is in the parietal cortex.
So whatever condition you test, whatever analysis you do, all the time with
popofol you block the activations of this global effect in the parietal cortex.
You can get it in auditory system, you can get it in prefrontal regions,
but never in the parietal cortex.
Is that a significant observation in your mind, that it is in particular affecting the parietal cortex?
Part of this frontal parietal network? I think it's quite significant because
there is a lot of literature showing that you have a prefrontal parietal deconnection with anesthesia.
There's a lot of work done by George Meshour in the US showing that you have
really a deconnection with all the anesthetics, whatever anesthetics you use, like Propofol.
He showed it with ketamine, with sebofluron on EEG data.
And he shows that all the time you get a deconnection between the prefrontal
cortex and the parietal. But you show a bit more, right? It's not disconnection,
it's disappearance. Yeah, it's disappearance of activation.
It's actually more extreme than that, right? Yeah, it's disappearance of activation.
But that would suggest that it's often maybe something we can get back to later,
that this parietal part of the frontal parietal is maybe much more of a hub
in that system than the frontal part.
Would you agree with that? Yeah. That's a working hypothesis?
Yeah, yeah. Okay. So, okay. okay, so we have this differential effect of ketamine
and propofol, and then you start to analyze in much more detail,
which is really very interesting, the specific organization that responds.
So I just started to look at the effect of connectivity, how is the effect of
connectivity then changed due to propofol in the context of this task.
So because then you could use that then again as also a marker for reinstating
this excess consciousness, right? This is where we're going with that.
So how useful was that analysis?
We look at this effective connectivity and how it is then changed by these different
drugs. What did you observe there?
Interestingly, if you want to study anesthesia or even consciousness,
there are basically two different ways.
There's a way where you challenge the brain with a task, auditory stimuli.
It's even easier in people with eyes shut down.
As Lina mentioned people should
really be aware of that under anesthesia obviously
there is no shutdown of the brain there is
still a strong brain processing of a lot of information a lot of information
does it mean that there is a conscious access does it mean that there is a memorization
of this data processing but there is at least for example with the sound we display and with fMRI,
we see very strong activation of all the auditory pathway.
Very strong. So I said a word to my colleagues, surgeons, be careful of what
you are talking during operations because patient is listening.
Well, now another way is to study the spontaneous fluctuations of brain activity, the so-called,
resting state, a very, very extended field of neuroscience now,
since the pioneer work of Marcus Reiko and St. Louis.
And if you look at these spontaneous fluctuations, there have been work in re-anesthesia,
but here we introduced a new way of analysis of these resting state networks
called dynamic resting states.
What does it mean? It means that people who are familiar with resting states
know that you scan your subject or your animal for 10 or 20 minutes without a specific task,
and then you analyze what we call functional correlations.
We would prefer the world of functional correlations over functional connectivity
because it's more objective, but still.
And you will describe networks that we call, for example, default mode network,
attention network that will pop out very easily through some code. And here.
Here, you're dealing with the whole picture of your 10 or 20 minutes of acquisition
at once, while we know that even the functional correlation between two areas
fluctuates during all the session of acquisition,
sometimes could be stable.
So, here comes what we call dynamic resting state, because through a sliding
window phenomena, it can also be done without the sliding window,
you can cluster brain states.
Here we used an unsupervised method called K-means.
Cluster all this resting state data into several brain states.
And these brain states prove to be extremely useful. What happens there?
So we could see that if we, let's say there's seven brain states that explain
your resting state configurations.
And with the clustering of your resting state, you will do the same clustering
in the awake state, then androanesthesia, then propofol, ketamine,
whatever the anesthetic, and with different dosages also of these tracts.
Suddenly, we saw that there are brain states that are very close to the anatomical
connectivity of the brain.
And those states, we will call them rigid states because at that moment when
your brain is in this state for say a few seconds, your resting state is 100%
explained by your connectomics.
You have no freedom. You are jailed by your structure, your brain anatomy.
So you have a high similarity between structure and function.
And when it comes to the other part of the spectrum, we found a state that is
completely the opposite.
This is a configuration of resting state that is completely uncorrelated to the structure.
And we called a flexible, it's a very high, highly flexible brain state.
It means that at some point, your brain jumped from a state to another. other.
And these states have completely different properties.
Now, the nice finding we made in the group is that when you are awake,
most of the configuration of your brain can be explained by many,
many brain states and not only one with a heavy shift to these flexible states.
Whereas when you go to endo-anesthesia propofol,
ketamine even others you see
the exact opposite it means that your resting state
is explained mainly by the rigid state and it means that you have a strong influence
of your connectomics to explain your spontaneous brain fluctuations it means
that these spontaneous brain fluctuations are not so spontaneous,
they are shaped heavily by the structure.
So to summarize this description, let's say that we could say somehow that being
conscious, meaning being completely free out of our brain structure.
Right. But the thing is, if you go to the brain structure itself,
that's an estimate of a DTI. Yes. Right?
And DTI is relatively incomplete in sort of assessing the structure of the brain.
Absolutely. That's why actually in our study, we used a database that is not a DTI-based database.
This is COCOMAC that summarizes all the literature of tracing in macaques.
And there's a strong literature of neuroanatomy.
And so in our case, this structure matrix, we're coming from these studies.
Okay, so then we have these seven dynamical states in which you could cluster
the resting state activity that you measured in the macaque brain.
Then we see that in the low entropy case, and you also showed that,
let's say we're not conscious or we're close to sleep or we're on severe sedation.
It's perfectly matched to the structure. and in the case of wakefulness,
we have a much higher variability that cannot be related to the structure directly.
But do you see then a very discrete transition in those seven states?
Like, is there a sharp threshold? Like, if I'm mildly sedated,
I'm immediately below that threshold somewhere or it's a more gradual transition?
It's a very good question. I think for the moment with the data we have,
we cannot answer the question because when we did these experiments,
the animals were either in one state or another state. We didn't do transition studies.
I think it's something very important. We had a lot of discussions to do future
experiments with transition states, so to going from awake state,
but very slowly to an anesthesia state, even during SED, which can last for several minutes.
So to go from one state to the other, and also the other way around,
to see what happens when you are in anesthesia and you wake up,
but I think it's studies we have to do to really to know if it's something you
go from one conscious state to the unconscious state until you lose some of
these brain states we described or if there is a transition that could be slowly.
Okay. But then they also highlighted the fact that you see very specific kinds
of correlations disappear under sedation and then it seems to be dependent on
the kind of drug you are using.
Right, so we talk about the positive correlations or the negative correlations.
So here we have this dysfunctional connectivity diagram. That means I look at
the correlations across all the voxels that I'm looking at.
So how is this then specifically affected by either ketamine or propofol?
What we saw for this correlation study is with propofol and with ketamine,
especially when you look at stationary connectivity, connectivity,
but also when you look at the brain states that are still present in anesthesia, that you mostly use,
that you have a loss of mostly the negative correlations in the brain.
There are still a lot of positive correlations that are still present in the brain.
They are less compared to awake state, but there are still many that are present
and what you lose completely, at least for these two drugs, are the negative
correlations. Do you find it surprising?
Not completely, because there is a thing like one hypothesis that negative correlations
could be important for information processing on the brain.
And then when you're not conscious, you have no information processing, and then we lose them.
So that's one idea. That's why I was not completely surprised to find this.
But you could also argue that since you are manipulating the inhibitory system,
right, that that might have a specific effect on your negative correlation because
these are the guys who are sort of managing that part of the process.
Yeah. Would that be reasonable as well or you think that doesn't make sense?
No, that could be another explanation. I never thought I'd think of this one,
but it could be a good explanation too. Okay.
Let's try that. You tell me next time. But now the other thing is that then,
which was really exciting because you are coming from, both of you are fully
committed to the global neuronal workspace idea.
And so you then started to look at the nodes, the frontal parietal nodes that
would make up this global neuronal workspace.
And you started to look at how they would be specifically affected by either propofol or ketamine.
I mean, and then in some sense, surprisingly, the effect was sort of like indistinguishable,
like coupling across the global
workspace nodes disappeared in both cases sort of in a comparable way.
This is a fair summary, I think, though. Yeah.
So, if you want to link both findings, for example, with the task,
with the local global task, and in the resting state,
it's true that findings were more homogeneous with the resting state approach.
So all anesthetics share the same signature, which is the loss of independence
of resting state from brain structure.
Whereas with the task, it was more subtle and more, there's a myriad of possibilities.
But actually, there is an apparent paradox.
And a way to match both is that the idea that the integrity of this global neural
workspace is really key.
If you take a piece of it, then the whole system falls down.
And it looks like, I mean, there was always a mystery.
How can anesthetics that have completely different molecular targets,
different neuronal population targets, different pharmacology and post-receptor
molecular events converge to the same result?
I mean, it looks impossible in terms of pharmacology. And actually,
one of the potential explanations could be that because they deprive the global
neural workspace in a different manner, partly,
completely from its information processing,
but it's enough to disorganize part of it to lose completely the conscious access.
Okay. But what I found surprising is that the effect is so non-specific, right?
So here we have two pharmacological agents that have very different impact on neural circuits.
And at this very macroscopic level in which we analyze the system,
the impact is actually indistinguishable, which worries me a bit.
Because from a global workspace perspective, it's an information processing
view on the brain where you say, well, we have all these processors that are
competing for access into the conscious buffer, if you want.
And they start to broadcast into this buffer when they are sufficiently driven, right?
But now, in some sense, here there's no signature really of such a buffer being
maintained in any systematic way. It's sort of it's there, it's not there.
It might be also, Paul, that the measure of resting state and its relation to
structure is not really specific to the agent.
It's just because you end up having a complete loss of consciousness.
Consciousness is like a phenotypic biomarker, let's say.
This is also a way to explain why when you do tasks, you have more subtle differences,
and while when we do the resting state approach, it looks all the same.
This is actually an important point, right? Because for instance,
in other studies of consciousness in humans,
you might see very distinct kinds of subnetworks for consciousness that's more
metacognitive oriented towards the self and conscious states that are more oriented
towards the external world, right?
So if you have actually the kind of paradigm you're using here,
none of that is being controlled.
So maybe you're not driving the system efficiently enough to actually see anything
that is really specifically impacting that excess consciousness that you're after.
Because again, something I like to say is that consciousness is an ambiguous word also.
So you mentioned metacognition and self-monitoring, which is not necessarily
what Local Global is probing.
This is again another view of consciousness of self consciousness even though
maybe it didn't appear like that but I was trying to support your point,
by basically I would not be surprised if this sort of resting state paradigm is not helping you,
it's more pulling you away from where you want to be because there's no specific
the brain is not configured towards a certain goal so do you also see that as
a challenge I agree and actually what goes also in this direction is that this
signature with resting state similarity,
is now explored by other groups for other circumstances with loss of consciousness
the group of Oxford who sleep for example and at ICM with.
People with disorders of consciousness consciousness, and they are very exciting
data, finding again this same signature.
And here we are beyond different pharmacological agents.
We have different conditions, different even brain anatomy, sometimes with lesions. Right. Okay.
So to close this part up, and then we go towards the thalamic cortical system,
the other thing that I find really interesting about the data you present,
because it's so specific, is that since you're also in the global workspace tribe,
in some sense, your data shows that we should take global a bit with a grain of salt, right?
Because like in the macaque brain, we talk about 12 identified nodes, more or less, right?
So how global, in your opinion, should we really think about this global neuronal
workspace in the context of the task and the kind of manipulations that you have been using?
The term global actually refers also to the global broadcasting of information.
And actually there is no single paradigm that activates all the global neuronal workspace.
So, obviously, if you are assessing, for example, an auditory paradigm,
you don't see visual activations and vice versa.
So, the GNW theory should not be seen as just a clear anatomical network,
as DMN, for example, or so forth, but as a general idea of cortical broadcasting of an information.
And the fact that here the auditory information went much beyond when there was a global violation.
And went to prefrontal areas close to frontal eye fields, for example,
to intraparietal sulcus with area VIP, shows this second level broadcasting of information.
But it doesn't necessarily tell you that we have X nodes or Y nodes in specific species.
This is the way I see it. Well, but I understand that you could argue that the
global workspace in the end is talking about broadcasting it to some sort of buffer.
You broadcast it to some sort of memory system, right?
And then the question is, is that memory system what you now actually reveal
in these paradigms, frontal parietal, as a memory buffer in which these broadcasts land?
Or is this frontal parietal system you visualize, let's say,
an auditory specialization of a much larger kind of buffer in which you can
potentially broadcast?
It's really impossible to answer definitely this question. But if you would
speculate, what's your hypothesis?
If I speculate, I would say that the apparent homology we see between the macaque response,
the macaque cortical response, and the human cortical response,
Let me know that we are really having a description of, between brackets,
a macaque global general workspace.
Okay. So we have a starting point now to start to look at the details of the
mechanisms of anesthesia, right?
So this local global paradigm has helped you in doing that. You revealed it
now in the macaque. So now we have an animal model.
So now we can become more specific in manipulating it. That's also what you
do with your deep brain stimulation, right?
So why do you believe deep brain stimulation might help you to then manipulate
these states of excess consciousness?
So, just let me say a little bit about the story and why we got into there.
From a personal perspective, I'm a neurosurgeon and when I started my residency
neurosurgery end of the 90s,
early 2000, I was surprised by a category of patients that have a strong,
big trauma or catastrophic stroke.
Many of them die, unfortunately, but some of them, and more and more,
thanks to modern medicine, we are making these patients living.
But unfortunately, many of them are in very bad conditions.
And here, it's not about motor recovery, but actually it's about consciousness recovery.
It's an increasing issue in our modern world. Think about it.
Fifty years ago, there were no such patients. It's like almost an invention of modern medicine.
Because these patients, until the 50s, with the appearance of the modern intensive
care, and surgical techniques, died in 100% of the cases.
I mean, the stroke was so strong, the trauma was so ugly and dangerous, all of them died.
So modern medicine is producing a new medical condition, which is a vegetative
state and or minimal conscious state.
And it's really intriguing, because once the acute phase is done and they survive,
they start opening eyes.
Family are happy, but unfortunately it doesn't mean they are conscious, they are aware.
They are awake, they have wakefulness, but not necessarily aware.
And I wasn't tried by these patients because they could stay weeks,
months in the department.
Of course, rehab centers don't take them. And now they start to have specialized
centers for these patients.
So there is an issue. There is an issue. And at the same time,
there are famous personalities.
We think about Aaron Sharon, who passed away a few years ago.
Currently, Michael Schumacher.
So in the headlines, we see more and more these conditions of what we call disorders of consciousness.
In the same time, deep brain stimulation, which is a surgical technique that
consists of implanting electrodes inside the brain,
became more and more fashionable and more and more effective in another disease
called Parkinson's disease.
And thanks to the work of Prof.
Annemarie Benhabide in Grenoble, this makes it very popular and now there's
something like 150,000 people in the world who are walking around you with these
electrodes with Parkinson's disease or tremor.
So, because this revealed to be a powerful mean to recover from Parkinson's, one of the ideas was,
could we actually identify brain targets to do brain simulation to recover from consciousness loss?
Of course, it's much more challenging, but because consciousness now becomes
a neuroscience issue and not only a philosophical question,
and now it's in the lab, in many, many labs in the world, it starts to be considered
as a function, like motor function,
like language, and because the patient lost this function, it might be that
there are techniques to recover from that.
This is general context. And actually, there are already some few reports in
literature back to some decades ago with some groups in the world who tried
to do thalamic stimulation to make vegetative patients recover.
Why thalamic? Actually...
Thalamus have very strong connections, very widespread, to large-scale cortical networks.
Frontal, prefrontal, parietal, so, singular cortex, precuneus,
all these key areas for conscious treatment.
So, the idea was there. And we know also that thalamus is highly involved because
some strokes of the thalamus can, even small strokes inside the thalamus,
can make consciousness disappear without any other neurological problems.
That's how there's a convergence toward these DBS of thalamus to try to restore consciousness.
So then, how successful have you been so far in restoring consciousness with
deep brain stimulation?
In our lab, we are doing preclinical work.
We are not doing a clinical trial, but we are using exactly the model that has
been developed by Lynn using the anesthesia.
Of course, anesthesia is not the perfect model of a vegetative state or a minimal
conscious state after stroke,
but this is still a model where now we control very well, including with behavior, with fMRI, with EEG,
the level of conscious access and conscious state with the local global paradigm on top of it.
So we started from these models in the mechanics and we inserted
deep electrodes within the thalamus with several areas actually of the thalamus
to test the specificity, which part of the thalamus.
And to our big surprise, actually, we found that the manipulation,
the electrical stimulation of antralaminar thalamic nuclei could suddenly induce
very strong phenomena, a very strong reaction in the monkey.
It means that the monkey who was deeply sedated, really with deep general anesthesia,
starts having twitches with sometimes strong movement that were not seizures
because we controlled with EEG.
They start to have a spontaneous breathing reaction, increased heart rate,
as if they were awakened from the anesthesia while they still receive in their veins a lot of propofol.
But how can we be sure that you are now not in the same position as the family
members of the coma patient that opened the eyes? Excellent question.
So, this is the advantage of the lab also, is to control the experiment and
to add experimental tools.
There are several ways. So first, we have an EEG monitoring,
and we see clearly that we enhance cortical activity with dynamic DBS to a level
that starts to resemble to wakefulness of the same macaque when he's completely awake and conscious.
This is not enough. And here comes again our local global paradigm.
That is, as you could guess, our favorite paradigm,
because the global paradigm is a very good way to interrogate the conscious
access of the animal during this awakening by DBS.
So we performed local global paradigm in this period of time when the animal starts to be,
I cannot tell all the results because this is ongoing work, but I can say that's
very encouraging results there.
Right. Of course, in that sense, it's fantastic how systematic you have been in building this up.
This is really taking a lot of discipline and effort.
This is really not easy, and I respect that a lot. But one thing that you also
shared with us this morning was that you also found an explanation of why the
stimulation intensity has to be so high.
Because interestingly enough, you could sort of only induce this sort of reawakening,
these reawakening signatures, but high levels of stimulation of 100 hertz and
above and not with lower frequencies.
So, in the interlaminar nucleus or close by in the thalamus,
you must be stimulating at a huge intensity to trigger the system to start to
reawaken. Why is that? Yes.
So, in term of frequency, even if movement disorders, with Parkinson's,
you need to be higher than 100 Hz.
Then comes the intensity issue. The intensity actually will play with the activated tissue volume.
So, we can now model that and have an idea about which nuclei of the thalamus
are involved with this stimulation.
Very importantly, we control this condition.
It means that with the same setting and programming parameters,
with the same high intensity and high frequency,
we manipulated areas of the brain that are really close on the same electrode,
actually, the same condition with absolutely no behavioral manifestation and no EEG changes.
That is really key in these kind of experiments.
But how do you then explain that we need these huge intensities?
So why don't you get this kind of reawakening at lower intensities of stimulation?
So in terms of frequency, for example, this is actually a general question.
It's still not solved, even for Parkinson's patients who receive the same therapy,
DBS, every day in many places in the world.
We did some pretty many work in our models, not the anesthesia models,
but in another program, and we could see that if we compare high-frequency versus low-frequency...
Using fMRI again, which is also a favorite tool, only higher frequency could
activate cortical areas.
And now in the field of DBS, there are a lot of arguments and a lot of evidence
that explain that most of DBS effect is not deep, it's superficial.
It's large cortical networks activations. And it looks like you need higher
frequency so that this retrograde solicitation of cortical areas happens with DBS.
And that might explain why interlaminar would be particularly well-placed to do that. Absolutely.
Okay. But on the other hand, you could also argue that what you see are just,
let's say, more the brainstem systems reacting to the stimulation,
and the signal travels downward towards midbrain and brainstem,
And indeed, what you're looking at is a monkey that is comparable to that coma
patient. So how can you exclude that interpretation?
Actually, it might very be that it also happens.
However, we have evidence of cortical strong changes in cortex through EEG and through fMRI.
So it would even be the best scenario that you have both reticular activating
system modulation and cortical modulation. Okay.
But still the variability that you see under propofol and deep brain stimulation in a macaque,
the kind of effective connectivity in cortex looks a lot more regular than in
the awake state. It's not really identical.
Yes, because actually I showed very preliminary data. Okay.
The work is ongoing and we have also another animal.
We have much more acquired data now that is being analyzed.
It's extremely interesting because maybe by driving this interlibrary system,
you are reawakening cortex, but still in a more, let's say, structure-dependent way.
And that's why I have these much more restricted islands of activation that
you showed in your functional connectivity than the more broad connectivity
you might observe under normal conditions. You mean in non-specific way?
Yeah, exactly. Actually. In the resting state. Absolutely. And we do see that.
If we do just resting state without any behavioral consequence,
resting state on minus resting state off, we see cortical activations.
However, here, what we could see is.
The controlled cortical activation for the global effect versus the global deviant.
So the global deviant versus the global standard.
So it's double controlled because you have within the paradigm global deviant
versus global standards.
And we control also, we have two conditions of stimulation at different intensities,
both of them inducing cortical activations.
And it shows a real specific difference for the DBS condition as compared to the other one.
Okay. Fantastic. Lynn, do you think that we can ever get away from using drugs
to get people anesthetized?
I hope so that one day we will not use drugs to anesthetize people because it
would be much easier because then you don't need to intubate your patients to
have mechanical ventilation or to have side effects on the hemodynamic part.
So I'd hope that it could work one day,
perhaps not with DBS because we will not implant DBS systems to the patients
who go to surgery for another reason,
but perhaps like systems with, I don't know,
perhaps TDCS or so on, perhaps with specific parameters. But what do you think
is a realistic target here?
Let's say 50 years from now, let's take a reasonable time window.
I don't know. For the time window, I have no idea. Okay, but what do you see as the next big step?
The next big step, I think it's already understanding the consciousness better
as we do now because there's still a lot of things we don't know about,
about consciousness and consciousness processing.
For the anesthesia part, what could be reasonable is to do all the analyzes
we did also on EEG because we will not put fMRI in the operating room.
And then to get analyzes to get like a closed-loop anesthesia with anesthetic
drugs that are completely,
that the EEG pattern or the ERP patterns control the anesthetics drug delivery
and so in a closed-loop manner.
I think that it could be reasonable in a few years. There are already devices
on the market who can do it based on the spectral index, but perhaps like a
better organization of this.
Okay. So, Bixi, one problem I'm still having, and then we're going to the finish line.
So, okay, we start with proper fault ketamine. We know what it does.
We're manipulating the GABAergic system, and the GABAergic system is actually
pretty fast. The time constant is there in milliseconds.
And now we try to make inferences about what this does to consciousness,
also at the mechanistic level, using a measurement technique that has time constants of seconds.
So we're order of magnitudes away from it.
So isn't this possibly a problem?
And also with the animal model you have, you could use other techniques that
bring you closer to the time constants of the systems being manipulated.
So first, do you see this as an obstacle that you use these techniques that
are so slow that maybe you have
no idea what's going on really at the mechanistic level in this brain?
So how do you square that circle?
It's true that fMRI scans the brain every two seconds, and that's obviously a different timescale.
I firmly believe like many
neuroscientists that there is no technique in neuroscience that
can solve all the problems and only multiple approaches
are there to move forward
so in our case we also have
EEG monitoring of these
animals which have a quicker life time scale but definitely our objective is
to go further and to have access to the intracranial recording with the,
challenge to have multi-site recording simultaneously.
And that's one of our next moves. Okay, right.
So you leave the option open that maybe everything we discussed so far is irrelevant
because of dynamics that we have to understand is faster.
I don't think so. Because take, for example, the intracranial electrophysiology.
If you combine fMRI and electrophysiology, if you know, for example,
through fMRI, the most relevant science to record, then this is...
Clearly the way to go to O4. Otherwise, you would not put thousands of electrodes
on the mechanic brain to have access to the whole brain.
And second, the dynamic resting state is now being modeled at the multi-second level.
People, groups like Gustavo Deco are doing that.
Of course, it's a model that is put on the fMRI signal, No, but it's there,
and there are some interesting results.
Okay. But, of course, it's also a matter of how good the predictions are of
these models and how well they can be validated and so on. Absolutely.
But it's an incremental step. This is where we… Absolutely. But I believe firmly
in these models, providing that there is a mutual exchange with biological data.
That's one of, let's say, my dreams, is that we are able to model,
for example, the consequence of DBS almost whatever the site in the brain.
Look, DBS is now expanding for psychiatry disorders,
for consciousness disorders, on top of Parkinson's and other diseases,
eating disorders, and the current paradigm in medicine in neurosurgery is mainly
to rely on single observations,
because one day there was a stroke here, there is a stimulation there, in unwanted nuclei.
So we move almost by chance. And the idea is to change completely the paradigm,
is to say, well, if I have a kind of flight simulator of the brain for DBS,
then this model, if it is well established, and I believe we can achieve that,
Then, I start defining and rationalize and suggest targets for diseases in a
completely rationalized manner.
And here, artificial intelligence, of course, will play a big role because it
will really can say and suggest,
well, for this disease, with all what we know about brain imaging in this disease,
very clearly these two targets are key.
Or this one is probably the most efficient or the most convenient.
So I see it as a main way and a shift in paradigm in terms of normal duration
and neurosurgery in the future.
Right. Very good. So, Lynn, you are now in this field also as a physician, right?
On the one hand, you have these concerns about your patients,
then you understand these animal models, you look at the mechanisms of anesthesia.
What do you see as Lynn's law that we should follow to understand the brain?
That's a very good question. Don't look at Bashir. Yeah, that's a very good question.
I'm not sure that I have a law to follow. At least not for the moment. Perhaps one day.
I don't know. It's a very tough question. So I think I have to… Okay,
yet a bit more time. Bashir, what's Bashir's law?
So again, for anesthesia, I think this field… For the study of the brain in general, right?
Yes. We're going macroscopic now. Yes.
Something I find interesting from a philosophical point of view is the finding
that consciousness emerges when resting state is freed from the structure.
Think about we are building neural networks, machines, robots.
Robots, we may start inducing some resting state activity in these circuits.
What would happen if we start inducing ship configurations that are completely
independent from the structure of the microprocessors and the transistors?
Would we, at least at some time, assist at the emergence of an artificial consciousness?
That's a law? You see this as a law?
It sounds like a prediction. I don't know, but this would be a huge change,
because if machines start to acquire consciousness,
then there is a big shift, I think, in that case. Absolutely.
Does it worry you when machines… No. Okay.
But that means what you're talking about is some sort of virtualization, right? Absolutely.
It's a virtualized system. Absolutely. virtual machine absolutely okay so then
lynn um now that we don't have lynn's law which is a real failure so we should
work on that um now five years from now i'm going to come to paris,
i'm going to visit you at neurospin and um i want to see whether a prediction
you make today was falsified or verified five years from now so what's the one prediction
that you feel is most important to see tested in that time frame.
I think what we want at least to test in the five years or the few years that
will come is to see how the feed-forward and the feedback works under anesthesia.
Because if you use all the fMRI studies, you can make prediction about feedback
feed-forward, but it doesn't give you a real answer.
So the only thing that you can do is during invasive electrophysiological studies
to verify is that you have really,
that feed forward is present on anesthesia as to what the assumption is today
that feedback is completely blocked so I hope that in the next five years we
can get answers on this Great, very good. And Bashir, what's your prediction?
Because I'm going to find you in the same room five years from now Pleasure
But then with another prediction What is it?
Prediction is the following I'm not sure we'll keep Thalamic DPS as the ultimate
goal of consciousness restoration.
I believe the computational model would predict where should we stimulate.
It would be deep, it would be superficial, to be combined with non-invasive
and invasive, and being able to build on this technology for consciousness restoration
based on the computational model.
Okay, very good. Well, then Ulrich, and Rochelle Yarriott, thank you very much for this conversation.
Thank you. Thank you very much. The CSN podcast was produced by the Convergent
Science Network of Biometrics and Biohybrid Systems, a project funded by the
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