Yale Psychiatry Grand Rounds: October 2, 2020

Name: Yale Psychiatry Grand Rounds: October 2, 2020
Uploaded: 2020-10-02T16:27:03.54Z
Duration: 1 h 9 min 56 s
Description: Elliot A. Stein, PhD, Chief, Neuroimaging Research Branch; Chief, Cognitive and Affective Neuroscience of Addiction Section, National Institute on Drug Abuse: "State, trait and subtype considerations in SUD: a view from nicotine dependence"

October 02, 2020

Elliot A. Stein, PhD, Chief, Neuroimaging Research Branch; Chief, Cognitive and Affective Neuroscience of Addiction Section, National Institute on Drug Abuse:

"State, trait and subtype considerations in SUD: a view from nicotine dependence"

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00:00Get started, it is my real pleasure
00:03to welcome doctor Elliot Stein
00:05to the psychiatry grand rounds.
00:08Today, Doctor Stein is chief of the
00:11neuroimaging research branch and chief
00:13of cognitive and affective neuroscience
00:16of addiction section at the National
00:19Institute of drug abuse is intramural
00:21research program in Baltimore.
00:23He interesting Lee.
00:25This is a little nugget I didn't know,
00:29but Doctor Stein actually started his
00:32his post high school education here
00:34in Connecticut and got his bachelors
00:38at Quinnipiac University in Biology
00:40an completed a PhD in neurophysiology
00:43at the University of Maryland,
00:45School of Medicine and then did a
00:49postdoc in behavioral neurobiology at
00:51Caltech with doctor James Olds who.
00:54Many of you may recall was famous for
00:58discovering what would got labeled
01:00as the pleasure center in the brain.
01:03Doctor Olds is a psychologist who
01:05firmly believed that the answer to
01:08understanding various psychological
01:09processes like human motivation,
01:11which he was very interested in studying,
01:14and made big contributions on,
01:17needed,
01:17needed study of the central nervous
01:20system and and the brain.
01:22And this is all before image Ng.
01:25I say this because I think I
01:28think that this time has really
01:31epitomized that sort of spirit and
01:34goal in the work that he has done.
01:37After getting if completing his
01:39post doc with Doctor Olds that
01:42this time moved to Wisconsin,
01:44he was on the faculty at Marquette
01:47University and then on the faculty
01:49of Medical College of Wisconsin,
01:52and during the birth of
01:54functional neuroimaging,
01:55an he was promoted all the way to full
01:59professor. He was there for
02:01a long time and then in 2002 he joined
02:05the naida IRP as chief of the newly.
02:08Created neuroimaging research branch.
02:11This is really important because I think
02:16one of the real major contributions
02:19of doctor Stein is that he used
02:22a number of different MRI tools,
02:25both functional MRI NMR spectroscopy,
02:28functional connectivity,
02:29specially looking also at white
02:32matter tracks using diffusion tensor
02:35imaging and of course positive
02:38positive emission tomography pet.
02:40Studies as well,
02:41and most importantly,
02:42doing this both in humans and in animals,
02:46which you can do.
02:47I think at using the naida IRP
02:50strengths of having both animal basic
02:53scientists there as well as human,
02:56your scientists and this allowed
02:58him to map an image.
03:01The brain in rodents in animals,
03:03in nonhuman primates,
03:05but also then translate that,
03:07and consider how to move that into.
03:10The human brain imaging space,
03:12and I think that we benefited a lot from that
03:16kind of Translational back and forth work.
03:20The other thing that that he has,
03:24I think pioneered has been what
03:26he identifies as event related
03:28cognitive neuroscience designs,
03:30which allowed us to look
03:32at functional neuroimaging,
03:34meaning essentially understanding
03:35different brain functions,
03:37an understanding the circuits
03:39from a systems science.
03:40And understanding different networks that
03:43contribute to those different functions.
03:45One of the key ones that that he started to
03:48talk about was the executive control network,
03:52based on findings that he had,
03:55which showed the chronic drug use
03:57alters this executive control network.
03:59In addition to that he has.
04:02I would credit him with a lot of
04:05really critical work identifying
04:07the role of the insula,
04:09which is an int receptive.
04:11Hub in the brain for feelings in the body.
04:16Signals that coming from inside of
04:18the body and his work has really
04:22sort of move the field forward in
04:25addiction around understanding
04:27insulin networks as well.
04:30I think the since 2002 if we think
04:33back the last two decades there has
04:36been a lot of signs showing sort
04:39of addiction as a brain disease,
04:42so to speak.
04:43And doctor sign has really brought
04:45that home with translating the
04:47work from animal experiments to
04:50showing the long term changes that
04:52occur from chronic drug use in the
04:55brain and connecting that then too.
04:58Unical outcomes one of the things that
05:00I think has been really critical is
05:03he's also pushed the envelope trying
05:05to understand individual differences
05:08looking at genetic polymorphisms,
05:10but also affect if personality
05:12environmental interactions that
05:14are so important in affecting this.
05:17These alterations,
05:17long-term alterations as a function
05:20of chronic drug use as a function
05:23of drug withdrawal,
05:24and more recently now into what
05:27are the effects of treatment.
05:29And so he is plunged forward.
05:32An has been looking at how we can
05:34develop efficacious strategies
05:36for treating and reversing these
05:38long term effects of addiction.
05:40He has authored more than 250
05:43original research papers,
05:44reviews and book chapters.
05:45He's been cited more than 17,000
05:48times in the literature.
05:49About half of that in the last five years.
05:53So really continuing to have a
05:56major current impact on the field.
05:58And so it's my real pleasure.
06:00To give you doctor Elliot Stein and
06:03he's going to be speaking about state,
06:06trait and subtype consideration
06:07and substance use disorders of
06:09you from nicotine dependence.
06:11Well, thanks for Gina,
06:14thanks for that very kind,
06:17overly kind introduction.
06:18Thanks for everyone for attending
06:20today in this rather awkward talking
06:22to screen that we that we've been
06:24doing for the last couple of months.
06:27So what I'm going to try to do today
06:29is give you a bit of an overview
06:32not going to be able to touch on
06:35all of the things that Regina
06:37mentioned in her introduction,
06:38but a bit of an overview of our
06:40thinking the last few years on how
06:43we are approaching a substance,
06:45use disorder and maybe some insights
06:47and maybe some controversies as to why.
06:49Our treatment outcomes are still not
06:53particularly particularly favorable.
06:55So let's see if this works.
07:00Ah. OK, there we go.
07:04OK well smoking is bad so if
07:06smoking is bad then abstinence
07:09abstinence must be good.
07:11Well, most of the move my.
07:16Pictures of you guys to another
07:18part of the screen. There we go OK.
07:23That's better OK, so most of the folks in
07:26the in America have gotten that message.
07:29Went down to about 17 or 18% of the
07:33country still smoking, unfortunately.
07:35We're still doing very poorly in treatment
07:38outcomes with at least 50% of the of those
07:41who want to quit returning to active
07:44smoking within about a month or so.
07:47So what's going on?
07:49What are the bad things that are happening
07:51during abstinence and the basic message?
07:54Here is, it's the nicotine
07:56withdrawal syndrome.
07:57And as mariela dibiase has said,
07:59we get we precipitate both somatic
08:01and affect if symptoms of withdrawal
08:03during acute during acute abstinence,
08:06including things like craving,
08:07irritability, anxiety, loss,
08:08we've all been around folks who just
08:11quit smoking and then particularly
08:13fun to be around.
08:15But it's those negative affect of symptoms
08:18that account for can you see my pointer?
08:21Is that possible?
08:22Yeah, OK, so it's the negative affect of
08:25symptoms that account for most of this.
08:28This failure in treatment,
08:30so negative reinforcement and
08:31accidents really are not good friends.
08:34But you know,
08:35we've known that for quite some time.
08:39So given this,
08:40why are we still so bad at
08:42treatment and treatment outcomes?
08:44And so the position that I'm going
08:47to layout for you today is that
08:49that really a brain based approach.
08:52A systems based approach may be what
08:54it's been missing traditionally
08:56and without this,
08:57without these validated and I
08:59see and I emphasize validated,
09:01clinically validated biomarkers,
09:02we really can't.
09:03That this is sort of my coals
09:06to Newcastle slide.
09:07We can't really objectively assess.
09:09The severity of the level of dependence
09:12we can fractionate the phenotype.
09:13We can't do individual differences
09:15or personalized medicine were not
09:17able to assess drug development in
09:19treatment interventions of objectively,
09:21we can't really look at the efficacy
09:23of a treatment until it's too late
09:25until the individual relapses.
09:27So I would posit to you,
09:29if you can't measure it, how we really fix.
09:33And so Matt said, Wanna a former postdoc?
09:36And I wrote an opinion piece on this.
09:38And if you're interested was
09:40less came out last year.
09:43So This is why where I may,
09:45I may upset a few people.
09:48What is it that we currently
09:50doing an I took this this quote I
09:53can't remember which paper it is.
09:56It doesn't matter because we all really
09:59say this in the first paragraph about papers,
10:02prominent theories of addiction posit
10:04that deficits in prefrontal mode,
10:06cortical function,
10:07impaired cognitive control,
10:08inhibitory prepotent behaviors,
10:10biasing towards into receptor
10:11signals and craving.
10:13It's complicated.
10:13Right,
10:14we all say this in our first paragraph,
10:17but when we tried to develop new treatments,
10:20are basic working hypothesis is
10:22something like this better pharmaco
10:23therapies require more specific and
10:25selective receptor based agents
10:27abetter silver bullet if you will,
10:29to engage with these specific
10:31receptor based system which will
10:33further prevent drug taking.
10:35Indeed,
10:35perhaps universe eviction and
10:37this treatment based hypothesis is
10:40coming from the really tremendous
10:42progress that we made in
10:44a cellular and molecular basis in
10:47preclinical work over the last decade or so.
10:50But as you know, of course this
10:53monotherapy approaches fail.
10:55Recidivism remains just
10:56unacceptably high for our patients.
10:58Neither agonist or antagonist
11:00therapy really is fixed.
11:02The disease. Of course,
11:04some agonists and partial agonist.
11:06Can maintain some individuals.
11:08Offer some periods of time,
11:11some for extended periods of time,
11:14for example methadone across people,
11:16morphine.
11:17Our team for anything purpose
11:19smoking but but really in general
11:22these this agonist approach doesn't
11:25really lead to sustain accent.
11:28And then, even if it did,
11:30is is reducing drug intake and reversing
11:32addiction really the same thing?
11:34Can we treat them with the
11:37same single intervention?
11:39So of course,
11:40this hypothesis assumes that the absence of
11:42behavior reflects the absence of the disease,
11:44and again,
11:45this group knows that that's not not
11:47even close to the imagery sentence.
11:50So what might an alternative hypothesis be?
11:53Well,
11:53since indeed substance use disorder is
11:56a complex in a psychiatric disorder,
11:59high psychiatric comorbidity,
12:00dysregulated multiple systems or cognitive
12:02affective personality systems reward systems.
12:04As I'll show you later.
12:07Maybe rather than or at least in
12:09addition to a better molecular level.
12:13Medicinal chemistry,
12:13we really need to think about a systems
12:17level neuro biological treatment
12:18strategy that takes into consideration
12:21these multiple other prediction phases.
12:24Not George,
12:24proven Orville cast have come up
12:26with a cartoon reminding us that
12:28addiction is not a static disease,
12:31but rather a cyclotron.
12:32And while there's some potentially
12:34some issues with this model,
12:36I think it's a good one for touristically.
12:39Think about what we're what we're actually
12:42doing when a patient presents in front of us.
12:46And this binge intoxication phase,
12:48the phase that we think about it,
12:50certainly with our animal models of increases
12:52in dopamine in the nucleus accumbens,
12:54is really,
12:54if you think about it,
12:56is not a treatment.
13:08If you will has mode,
13:10it doesn't live in the new basic
13:12comments anymore due to plasticity.
13:15It's now in a number of
13:17other distributed systems.
13:18Many synapses removed and differentially
13:21manifest across these affected systems.
13:23So you know, I would ask you how?
13:26How could pharmacologic blockade
13:28or or agonist replacement of a
13:31sneeze or critical limbic dopamine
13:33system really reverse the disease?
13:35So you know the theme today is going to be.
13:38Maybe we don't really need
13:39a better silver bullet.
13:40Maybe what we need is a
13:43silver buckshot approach.
13:44And maybe we need to take into
13:46account both the acute state of the
13:49individual as well as the trait of
13:52addiction that they presented with.
13:54So the rest of the talk is going to
13:57be organized around that theme of
13:59looking at both the trait of addiction.
14:02If you will,
14:03the severity of addiction as well
14:05as the acute transition traits
14:07that we see during acute and
14:10long-term long-term accidents.
14:12And so I would posit that more
14:14treatment outcomes may be related to,
14:16at least in part,
14:17to focus on the results alleviating
14:19withdrawal rather than focusing
14:21on the cause of the problem.
14:23This drug induced neuroplasticity.
14:25And so we went into this a number
14:27of years ago with the hypothesis
14:29that addiction severity is linked
14:30to activity within and between the
14:32anterior singular and one of its players.
14:35This trail. Well, why the singular?
14:37Where did that come from?
14:39And there's a number of pieces of
14:41literature that I'm putting up here
14:43that justified for us time that single
14:46it might in fact be a common target
14:48for nicotine and other abuse drugs,
14:50and maybe a convergent region that's
14:52pivotal for nicotine's diverse effects.
14:54And when we get going in this,
14:56this was before any knowledge
14:58of large scale networks and the
15:00salience network that I'll be
15:02talking to you about later on.
15:04So let me put this into a bit of a
15:06perspective and a figure that I adopted
15:09from adapted from Suzanne Habren,
15:11Brian Knutson a few years ago,
15:14just to emphasize that these cortical
15:16striatal loops that Suzanne is
15:17beautifully elucidated over the years,
15:19let me put some function on top of
15:22that when we think about the VM Pfc,
15:25we think about value, reward,
15:26and decision making in the OSC,
15:28the Dorsal ACC.
15:29Then I'm going to be talking about now
15:32and ever monitoring and every detection.
15:35Executive control in the DL,
15:36Pfc and just to be complete,
15:38I think we have to only talk about addiction.
15:42Think about attention.
15:43Intentional processing.
15:43Basically in the posterior parietal
15:45cortex and one of the things that we've
15:48now had a over the last number of years.
15:51Kind of a Super Ordinal organization
15:53on top of these regions in these
15:56large scale brain networks that
15:58seem to be able to explain a lot
16:00of the nurse psychiatric symptoms
16:02that that will be talking about,
16:04at least from the perspective of.
16:06Of addiction and the other
16:09thing I wanted to point
16:11out is that many of these players,
16:13most of these players that I've
16:16just highlighted are just ripe
16:17with nicotinic receptor receptors
16:19and various receptors subtypes.
16:21And it's not surprising therefore that
16:24a lot of what we're seeing with tobacco
16:27use disorder is being biased by many
16:30many systems throughout the Neuraxis.
16:33OK, so with that introduction we began
16:36this sort of adventure 10 ish years ago.
16:40Now with this hypothesis that the
16:42singular was involved in addiction,
16:45and So what we did very simply,
16:48this is, I believe,
16:50the first wrestling state study done in,
16:54and certainly nicotine a number of
16:56years ago was we divided the singular
16:59into its cytoarchitectonic components.
17:027 seven areas.
17:03Answer if you Post Area 1 middle
17:05singular area bilaterally,
17:07so 14 areas each was a seed and we
17:10did a whole brain regression against
17:13the level of nicotine dependence
17:15against the practice from index and
17:18what we identified was a single area.
17:21Within the the ventral stratum,
17:23what was interesting when we looked
17:25at this data is that the that the
17:28strength of this circuit negatively
17:30correlated with with the nicotine
17:32addiction severity of the individual.
17:35But most importantly in this first study,
17:37when we scan these individuals
17:39on an off a nicotine Patch,
17:42there was no change to the to the circuit.
17:45These dime diamonds and triangles
17:47indicate a single subject scan on two
17:50different occasions on and off nicotine
17:53off nicotine on and off nicotine.
17:55And so this circuit appeared to be
17:57reflective of that rate of addiction and
18:00not the current state of the individual.
18:05About this time, Mr.
18:07Big the opera 5 polymorphism was
18:11becoming recognized as an important.
18:15Determinant in nicotine addiction.
18:17And so we wanted to see if you want to
18:20see what its role was in this circuit
18:23and so the next year together with
18:25David Goldman at the NI AAA it hung.
18:28We did essentially the same experiment.
18:30Now starting only the dorsal ACC because
18:33we knew that was sort of the answer and
18:35now did a whole brain regression not
18:38against the phenotype of Fagot Strong,
18:41but against the genotype of this
18:43A5 polymorphism and basically
18:44identified the same circuit.
18:46With the same relationship once one now with
18:49the phenotype and one against the genotype.
18:52And we thought these early data supported a
18:55role for the dorsal ACC and Strydom in trade,
18:58but not state dependence.
18:59So the next logical question was, well,
19:03are there pre dispositional differences in
19:05these circuits that potentiates smoking?
19:07Or does the smoking behavior over the
19:10over period of time change these service?
19:14Well, it's difficult to do in humans to
19:16do these long-term longitudinal studies,
19:18and it may be that Abcd in a few
19:20years will give us this answer,
19:22but an approach that we took at the
19:24time was at a conference back to
19:26remember when we used to be able to
19:29go to conferences and I was having
19:31a conversation with Rachel Tynedale
19:33and she was telling me about the
19:35sith to ASICS enzyme,
19:36which is a cytochrome p-450 liver enzyme.
19:38And it's the main enzyme that
19:40metabolizes nicotine for coating it.
19:41I didn't think that was
19:43particularly interesting,
19:43'cause I'm not a little guy.
19:45But until I started to take a look that a
19:48the same time is genetically regulated,
19:51is 26 different isozymes or
19:53so and and Rachel,
19:55it's lab has been able to provide people or
19:58categorize people into those with normal,
20:01intermediate and slow metabolic
20:03systems or nicotine and what became
20:06interesting to me as a brain guy
20:08is it looks like these that this
20:10liver enzyme changes behavior.
20:12Individuals that were better
20:14slow metabolizers have lower fat.
20:16Astronomy smoke, fewer cigarettes.
20:17And it can predict treatment matching out,
20:20so this became rather interesting
20:22and so we want to know if this
20:24situation it's Gina type actually
20:26shapes brain circuits differentially
20:28in smokers and non smokers.
20:30And would it offer alter brain
20:33connectivity and so we did that that
20:36study together with Rachel and Supinely
20:38who is a postdoc in the lab at the time.
20:42And perhaps the most important and
20:44interesting contrasts that we did
20:47looking at this data was a gene by was
20:49it gene by environment interaction?
20:52So three genotyped by smoking
20:54versus non smoking.
20:55And in this analysis we didn't want to
20:58have a hypothesis of looking under the
21:01same lamppost and so we used a data driven.
21:05Metric graph theory metrical
21:07functional connectivity strength and
21:10basically this analysis allows you
21:12to identify the hubs in the brain.
21:15The areas of highest ugliness
21:17that interconnect rain errors,
21:19and when we did that whole brain data driven,
21:24we identified two areas defense
21:27Australian in the dorsal ACC.
21:30We extracted those data and plotted
21:32them to see what was driving this
21:35relationship and what it was.
21:36What was driving the relationship was
21:39the slow metabolizers in smokers that
21:41we saw a less hub enis, if you will.
21:44In both of these areas in this
21:46genotype group in smokers only.
21:49And interesting enough that SES
21:52level that happiness level also
21:55predicted or correlated very nicely
21:58with the individuals level of trade
22:02dependence severity very consistent
22:05with something from the literature of.
22:09Smoking behavior.
22:11So, OK, we've identified a couple of hubs.
22:14The next question was, well,
22:16what are the tracks into these
22:18train stations?
22:19What are the circus that might be
22:21potentially biasing these hearts and
22:23one way to approach that was then to
22:26take each of these two areas and use
22:28each one is a seed into a separate
22:31standard resting state connectivity analysis.
22:33And when we did that,
22:34we identify from the dorsal ACC the insula,
22:37as well as the ACC and from the bench
22:40and stratum the insular and as as
22:42Regina mentioned in the introduction.
22:44This is become one of the main
22:46foci in the labs,
22:48and I emphasize insulin here because
22:50I'm going to come back to this in a
22:54few more times in a few more stage.
22:56OK,
22:57so this is pretty cool that that
22:59salience network components look
23:00like they may reflect your bias
23:02that traded diction severity.
23:04Well, that was nice, but who cares?
23:07Are there any functional consequences to
23:09having changed in Hoppiness in these smokers?
23:11So the way one way we approach that
23:14was we needed to probe both eventual
23:17stratum and the door sellers to see,
23:19and perhaps the best way to
23:22approach the ventral stratum Mr.
23:23User reward task.
23:25In this case the The Famous.
23:27Monetary incentive delay cast.
23:28Where we analyzed this data,
23:30just simply a simple contrast gains
23:33greater than neutral and we didn't
23:35have enough subjects to look at
23:37it and intermediate phenotype.
23:39So only the normal and the slow metabolizers.
23:43And when we plotted these data,
23:45we notice that when individuals
23:47were accident.
23:48This slow metabolizers just
23:50couldn't couldn't create enough of
23:53a signal in the ventral striatum.
23:56However, when we gave them a nicotine Patch,
24:00both the slow metabolizers as well as
24:03frankly the slow metabolizers and non
24:06smokers were able to increase their there.
24:09Interest rate or signal while
24:11they're performing a reward chest,
24:12not a particular surprise.
24:14We know that we know that nicotine
24:16is in fact a cognitive enhancer,
24:18and I'll show you some data in that
24:20in non smokers as well as we go along.
24:23Or what about probing the dorsal ACC?
24:25A great way to do that is with a go.
24:28No go type of the task and when we did
24:31that we saw exactly the same answer
24:33both in non smokers and smokers.
24:35And again when we gave them an
24:38acute nicotine Patch
24:39we reverse this.
24:40Deficit if you will,
24:42in nicotine absolute state.
24:44So these circuits and hugs and
24:46modified only in smokers suggesting
24:48a change in in putatively a change
24:50in nicotine concentrations in the
24:52brain so slow metabolizers presumably
24:54would have more nicotine off for
24:57longer periods of time in their brain,
24:59and this induced these circuit changes.
25:01That's the hypothesis coming in from
25:04this study and the same circuit seem
25:06to change both at rest and when
25:09the individual is doing a task,
25:11suggesting that this is
25:12functionally significant,
25:13and it looks like slower smokers
25:15with these slower Gina types.
25:17Are less responsive than to the
25:20anticipation of veins less responsive to.
25:24To to to errors,
25:25and this certainly seems to make
25:28sense when we think about it
25:30from a treatment perspective.
25:32Well,
25:32another way we can see if these
25:35circuits are pre dispositional is to
25:38induce them to try to change them.
25:41And so, with animal models,
25:43preclinical models are very good at this,
25:46and this was a challenge that Robin Healey,
25:49a postdoc in the lab,
25:51took on just recently,
25:52and what she did was she made a
25:55group of ratchet or three groups
25:57of rats dependent two different
25:59doses and doses Saline and implanted
26:01osmotic Minipump's for two weeks,
26:03and then let the pumps run out.
26:06And they were in another two weeks
26:08of Force Absolutes.
26:10We determined how dependent they were
26:12by giving them an injection of Mecamylamine.
26:14IP and then measuring a
26:16number of somatic signs.
26:17And this dependent score that
26:19I'm showing you here.
26:21We're going to use as as as our
26:24surrogate for the Fagots Room in use.
26:26So OK,
26:27so now we have to go back.
26:30So now we have a model to look
26:32at this if we could recapitulate
26:34this singular striatal circuit.
26:36But what's the homologous region in
26:39the rat in the rent of the human dorsal ACC?
26:42So we didn't know and we don't want to
26:45just look at the anatomic descriptors
26:48in the Atlas and So what we did.
26:51It was,
26:52it was another analytic trick or
26:54the modularity analysis where we
26:56simply took the entire frontal
26:58lobe of the rat and submitted it
27:01to this modularity approach to
27:02allow the computer to tell us
27:05how many divisions do you have?
27:07How many modules you have?
27:09Do you have,
27:10and the computer came back with
27:12five and we use each of these five
27:15modules that we gave names simply
27:17because they overlaid onto some
27:19major Atlas regions and we use.
27:22Each of these five modules, it seeds,
27:25and only one of those modules,
27:27the what we call the ACC middle region
27:30and only a circuit from there into into the.
27:34In this case in the dorsal stratum
27:37negatively correlated with the
27:39dependent scores of these animals.
27:41Very, very similar to the three
27:44studies that I just showed you.
27:48This is a very complicated slide.
27:50You only want to give you 1
27:52message from this paper.
27:53Just came out recently.
27:55And the question then was,
27:57are there in fact since I can
28:00induce these circuits in rats?
28:02Are their baseline circuits pre
28:05dispositional circuits that might
28:07modify or moderate the ability of
28:10nicotine to cause to cause dependence?
28:13And in a very complicated
28:15moderation analysis,
28:16I just want to highlight that two circuits
28:20an insula frontal circuit shown up here
28:23and insula striatal circuit down here,
28:27fully moderated the relationship between the
28:30ACC ventral stratum and nicotine dependence.
28:34More details on how we got to these
28:37these intrinsic circuits are on this
28:39paper that came out just a few months
28:42ago in the Journal of neuroscience,
28:44but it looks like again the
28:46conclusion would be that this.
28:48ACC striatal circuit seems to
28:50track it became dependent severity.
28:53It's moderated by individual differences,
28:56even individual differences
28:57in rats in from insula,
29:00frontal and executive insula.
29:02Striatal circuits trap.
29:06OK, so let's move on from nicotine
29:09trade trade circuits to looking at
29:13the consequences of acute nicotine
29:16withdrawal and state related circuitry.
29:19And as I said at the Abbey on
29:23said nicotine withdrawal is A,
29:25is it random, nasty syndrome,
29:27high anxiety, irritability, craving,
29:29lots of negative negative affect as
29:32well as executive control impairments.
29:35When we give nicotine replacement,
29:37at least to it, to some extent,
29:39it were those incorrectly we
29:41can reduce at least partially.
29:43Many of these acute withdrawal symptoms.
29:47And so our hypothesis going into this
29:49series of experiments was that state,
29:51like withdrawal,
29:52is centered on the insulin and
29:54its associated circuitry and may
29:56ultimately serve as as Rajeev
29:58Dimension as a frequent target.
30:02Well, OK, just like I said with
30:04the singular why the insulin?
30:07Where did this come from?
30:09And really it has to go back to
30:11this seminal paper by Nafion and
30:14Antoine Beshara and science within
30:16they noted that individuals who had
30:18strokes that were limited to or
30:21incorporated regions in the insula,
30:23if they were smokers before before
30:25the stroke, they spontaneously stopped
30:27smoking after the smoke at the stroke.
30:30At least many did.
30:32And probably the best sentence in this paper.
30:34If you haven't read it when they ask
30:36them individual why they stop smoking.
30:38The person said, well, it was.
30:40If my body forgot that I was a smoker
30:42and that really says everything
30:44about what the insular is doing.
30:46In our lab,
30:47we've also seen differences in Gray
30:49matter greater Gray matter density
30:51in the insula in smokers versus non
30:54smokers that very nicely relates to Alexa.
30:57Find me up in these individuals in
30:59these non Alexa find individuals.
31:02I also want to point out and in the
31:04scheme of the George Group is proposed
31:07in his three cycles that two of those cycles.
31:10Two of those aspects,
31:12both withdrawal and negative,
31:13affect as well as the anticipation
31:16preoccupation phase do include do
31:18include the installer in these circuits.
31:21Our data that I showed you a moment ago,
31:24a few moments ago,
31:26also implicated installer as biasing
31:28these trait related in solicitations.
31:30Let me summarize to other studies
31:33in the lab that have gotten us
31:36into this into this insular mode.
31:38Max subtle in a number of years ago,
31:42identified the amygdala using the
31:44Hariri basis task is being sensitive
31:46to state related changes in nicotine.
31:49He then used the amygdala that
31:52he identified functionally.
31:54As you seen and identified.
31:58Insula circuit continuing to
32:00walk this circuit.
32:01He now used the insular as a seed and
32:05identify the default mode network.
32:07The full network that we
32:10now know classically.
32:11PCC,
32:11eventual medial Pfc power,
32:13hippocampal gyrus and interesting
32:15Lee and importantly,
32:16this circuit does not change in
32:19non smokers but is enhanced when
32:22the individual is in absent.
32:24Matt also identified that this
32:26insula VM Pfc circuit fully mediated
32:29the relationship between trait
32:31Alexa Pinya and stayed crated,
32:34so we had enough evidence now going in
32:37that the incident was likely involved
32:41in this nicotine withdrawal syndrome.
32:44So the installation we all
32:46took neuroanatomy buried in the
32:47middle of this temporal lobe,
32:49yet to kind of crank open the
32:51brain and see it in there.
32:54Probably the best review paper and
32:56the breast best theoretical paper
32:58that that that I came across and
33:00I would really encourage those
33:01of you who might be interested in
33:04the insular regions.
33:05Bud Craig's paper, about 10 years ago,
33:07where he emphasized that the insula
33:09really has a gradient of processing
33:11from post theory and anterior
33:12insula from from interoceptive,
33:14processing homeostatic processing with.
33:16Amygdala and hypothalamic inputs.
33:17And as one goes more rostral, more anterija.
33:21This information is integrated
33:22and kick more forward,
33:24integrated, and kick more anteriorly where
33:27the most anterior regions of the of the
33:30insula are involved in hedonic processing.
33:33Motivational cognitive processing
33:34with inputs from areas that we
33:38think are players in the bank.
33:40And this review article by Craig
33:43LED us to hypothesize a number of
33:46years ago that the salience network,
33:49the ACC and anterior insular served as
33:52sort of the pivot of a Teeter Totter.
33:56And when an individual was in accidents,
33:59this salience network bias the
34:01individual to pay more attention
34:04to internal states to pay attention
34:06to that craving to that hunger.
34:09When the individual is sated.
34:11This bias system encourage the individual
34:14to spend more time in executive mode
34:17to be able to concentrate focus.
34:20It also allowed us to start to look
34:23at the fact that the insula has been
34:27divided into a number of different areas,
34:30whether it's by using functional
34:32connectivity or Cytoarchitectonic's
34:34or behavior for that matter,
34:36on this list, divide,
34:37then divide into three major three major,
34:40with subdivisions.
34:41And so the question we next had was
34:44how did these circuits from each of
34:46these regions of the insulin different
34:48as a function of nicotine withdrawal?
34:51And do these circuits have
34:53behavioral consequences?
34:55So this is the work of John Kadota
34:57and his research assistant,
34:59and what he did was he took of these
35:02three divisions and hypothesis
35:04driven fashion use each of these
35:07three regions of the insular seeds,
35:10and had each of these three large
35:12scale networks as as targets,
35:14and what he identified with three
35:17circuits that were biased as a
35:19function of acute accidents.
35:21This was 48 hour accents,
35:23one from the ventral insula too.
35:25Piece of the DL.
35:27Pfc from the posterior insula into the ACC,
35:30and from the dorsal insula into the DNA.
35:34And what was interesting is that they
35:37also had behavioral consequences.
35:39At least two of them did,
35:42and that with this,
35:43this first circuit negatively is very
35:45strongly negatively correlating with craving,
35:48and this salience network
35:50circuit correlating with.
35:52The WS WS,
35:54sadness and anger.
35:55There was no relationship with
35:58cognitive performance.
35:59During looking at these insular circuits.
36:03And so we've we've sort of think
36:05about these three circuits.
36:07Is 1 related to affect want interception?
36:09Want to cognition?
36:10And when we looked at the state
36:13of a little bit closer,
36:15we kind of looked at this this terminal
36:19region if you will and the DL Pfc and
36:22it's Mac on where this crosshairs on
36:25to where the F three 1020 placement
36:28is where we give TMS at the DL Pfc.
36:32So perhaps what we've identified
36:34serendipitously would be a
36:36location that we might be able to
36:39target and justify targeting our.
36:41TMS treatments to modify these circuits and
36:45involved in the negative consequences of.
36:50The nicotine withdrawal syndrome.
36:57OK.
36:58Tell me how we're doing.
37:00I've got a couple of more studies
37:02I'd like to quickly go through.
37:05Trish, Trish, are you have some time?
37:07OK,
37:08great.
37:08Just just I can't see you so wave
37:11at me or shut me off.
37:13OK so we want to start to look
37:15now at these state trade aspects
37:17in decision making and then an in
37:20reward learning very important
37:22process as you know in in substance
37:25use development and maintenance.
37:27And we began to look about at a
37:29test that hasn't been used very
37:31much in addiction are called the
37:34probabilistic reversal learning task,
37:36and we like this task.
37:38We suppressive captures two different
37:40constructs that are important
37:42in reward based decision making,
37:44reward sensitivity and cognitive flexibility.
37:46How an individual changes one's behavior
37:48in the face of negative outcomes
37:51versus maintaining a previous choice.
37:53And this task has been used because
37:56we used it because it relies on
37:59NCL circuitry and we've shown that
38:02this circuitry is changed with
38:05nicotine dependence.
38:06But how it's been,
38:08how it is involved in smoking in
38:10the state or trade at ameliorated by
38:13Pharmacotherapies is really unknown.
38:16So this is work of at least Lesage
38:18post dot dot in the lab and it's a
38:20task that we modify based on one that
38:22Roshan cools published a number of years ago,
38:25and again I would encourage people to think
38:27about this task is not used an awful lot,
38:30and certainly not in addiction and we
38:32really like it a lot and I'll show you why.
38:35It's a very simple task for the subject.
38:37They see two fractals and they
38:39have to pick one arbitrarily.
38:40The computer has decided what
38:42the right answer is.
38:43That's over here are the individual
38:45doesn't know and they get feedback.
38:46It's a probabilistic pass, so they get true.
38:49A true answer about 75% of the time,
38:52and they can make a decision to
38:55either stay when they make a win.
38:58All or if they lose their inside to
39:01stay or they can ship when they make.
39:04When they lose so Wednesday, Lucia.
39:07A type of behavior.
39:11We did this task in both smokers and
39:14non smokers in a very complicated
39:16fashion that you know we can do it.
39:18The at the IRP.
39:19We stand individual six times
39:21on and off and nicotine Patch.
39:23Two of those times was with a chronic
39:25of Renick Ling Pill and two of
39:28those times was with uh with it's a
39:30placebo pill because we wanted to
39:32look at this drug drug interaction.
39:34As you know varenna clean is
39:36generally given clinically while the
39:38individual is still is still smoking.
39:39So how would you analyze it past like
39:42this behavior you can't look at accuracy,
39:44you can trigger reaction time.
39:46And was at least did she use the
39:49computational model something called
39:50The Hidden Markov model and she did
39:53this as a function of group smokers
39:56and non smokers and treatment.
39:58And as you can see there were no
40:00effects of pharmacotherapy choose
40:02me in nonsmokers but since we're
40:05getting a little short on time I'm
40:07not going to detail with this bias
40:10this day or inverse temperature
40:12means but basically it tells us
40:14that in the absolute state and
40:16that's here. In in orange,
40:18in the absolute state and smokers,
40:21these individuals were more impulsive.
40:23In this task they made more rash
40:25decisions when facing negative outcomes.
40:28And Moreover this deficit if you will
40:31was reversed both when they put on a
40:35nicotine Patch and when they had on parent.
40:38So it's a really nice computational
40:41way to look at real world kind
40:44of decision making basis.
40:45How about when we bring this this
40:48task into the brain very quickly?
40:51When we look at reward greater than
40:53punishment is whole brain Maps.
40:55We see the very nice DMM map map as you
40:59see when we look at what punishment does
41:02very nicely activates the salience network.
41:05The dorsal ACC and eventual straight up.
41:09However, when we look at cognitive
41:12flexibility that we operationally
41:14define as loose shift minus loose stay,
41:17it's all about the salience network, right?
41:20There's negative outcomes activates activate
41:23beautifully on the salience network.
41:25Well, how about as a function
41:28of state and trade?
41:30Well when we look at rewards sensitivity.
41:34Smokers present with a
41:36hypoactive bilateral striatum.
41:38I hypoactive dorsal ACC similar
41:41to performance feedback that I'm
41:44going to show you in just a moment,
41:48and these impairments are not not
41:52modulated by nicotinic agonists.
41:55However,
41:56they are yet again another paradigm another.
42:01Way of looking at this,
42:04they deficits are also proportional
42:06to the level of nicotine dependence
42:09of the individual.
42:10However, in contrast,
42:13the cognitive flexibility contrast
42:15showed us a state related different
42:20such that in in smokers during
42:24abstinence they perform much worse.
42:27And this activation is reversed in
42:30the presence of acute of acute.
42:33So what did I just show you very quickly?
42:37I apologize.
42:37The study is published that acute absence
42:40that state smokers were excessively flexible.
42:43They will bias to shift their choices
42:46with neural activity in the dopamine
42:49systems and in the salience network.
42:52Areas.
42:52Reduced before this behavioral shift.
42:55Acute administration of nicotinic
42:57receptor agonist restored.
42:58These both behavioral and neural
43:00processes comparable to that in
43:02non smokers and what was really
43:04cool in this study and I love
43:07doubled Association studies.
43:08What we saw in this case though
43:11is that in trade of smoking we
43:13saw a lowest sensitivity in the
43:16dorsal striatum and dorsal ACC.
43:18The same players that we've been seeing,
43:21which was not alleviated by nicotinic
43:24stimulation but was associated with.
43:26And consistent with the message
43:28I'm trying to leave you with today,
43:31that different constructs different
43:33computations exist in the brain
43:35depending upon how you probe it
43:37and the state of the individual.
43:40So further evidence that maybe we
43:42need a multimodal type of approach
43:45rather than a monotherapy approach
43:47when we think about as you do.
43:50OK, one more very quick study.
43:52It's A kind of cool study that just
43:55came out a few months ago and it's
43:59about the Habenula and the reason we
44:02wanted to go into the habenula stress.
44:05This is an area that really
44:07thinks about really is
44:08involved in negative aversive processing.
44:11It's hypothesize be hyperactive and
44:13nicotine withdrawal and anhedonia and pull.
44:15Kenny is shown very nicely.
44:17A5 nicotinic receptor modulations
44:19within the within the Habenula.
44:21So this is a study that that started in the
44:24lab when when that southerns was there,
44:26like many things,
44:27life gets in the way we were finally
44:30able to publish this few months ago.
44:32But the venue is a really small areas,
44:36maybe 5 boxes big in humans.
44:39You know how do we activate it?
44:40How do we know we're really there?
44:42And this is another very novel
44:44task that I do not understand why
44:47it's never been used to that.
44:49Well, I do understand it's a very long test.
44:52Takes about 30 minutes in the Mac
44:54and this is a task that is burger
44:57published a number of years ago.
44:59Simple text,
45:002 balls appear on a screen of different
45:02positions and they start to move at
45:05different speeds and the the participant
45:07only sees them for 100 milliseconds.
45:09They go off and then they have to
45:12guess which ball would have hit.
45:14Would have hit the end
45:16if there was enough time.
45:18And the individual is given feedback,
45:20either informative feedback,
45:22a :) that they were correct,
45:24frowny face, if they were incorrect,
45:27to get enough jitter,
45:28we give them occasional non.
45:31Informative information and then often
45:34a noninformative feedback whether
45:36they were correct or incorrect.
45:39So because of time these were the
45:42same individuals that we scanned
45:44on multiple occasions. Task worked.
45:46It's biased like most of these
45:48kind of reward tasks or people are
45:51correct 65% of the time.
45:53There faster when they are correct.
45:55So the task did what it was supposed to do.
45:59But interesting Lee in smokers
46:00there were more errors of omission,
46:03number of no responses and these errors
46:05of omission were improved when we
46:08scan them up with either parent eccle.
46:10Or nicotine.
46:11They also got better than non smokers,
46:14got better with nicotine as well.
46:16Again not a surprise.
46:18So did the task work.
46:20The answer is yes.
46:22I'm outlining the habenula for you
46:24over here and these white circles.
46:27When the individual made an error,
46:29the habenula starts to scream
46:31increased activity.
46:32Insulet increased activity.
46:34The Strydom shows an increase
46:36activity when the individual gets is
46:38correct and gets positive feedback.
46:40So exactly what you would expect a
46:43task like this to do? Interesting Lee.
46:46The relationship between the
46:48insula screaming and the habenula
46:50screaming is almost one,
46:52and so these two structures are
46:54integrating their their processing very,
46:56very closely.
46:57So very quickly then when we re
47:01analyze this data with contrast
47:03as a function of group,
47:06what we found was that when we
47:09look at errors minus correct that.
47:13On that non smokers very nicely
47:16were able to process their error
47:19response but in the in the stratum
47:22but smokers were not.
47:24Conversely,
47:25on the initial response in smokers,
47:27or was much greater when they
47:30made errors than it
47:32was in non smokers. Does this
47:35change is a function of acute state?
47:37The answer is yes, that in smokers,
47:40but none but not non smokers when
47:42the individuals are absent the
47:44Habenula was screaming the VM.
47:46Pfc is screaming much more
47:49than in the state and state.
47:52We did a very quick anatomic
47:54Lorelei to demonstrate that,
47:56in fact, this really is true insula.
47:58I'm trying to have Angela and not. And
48:03another. He and she.
48:07I'm sorry.
48:11Keep going someones my commuted
48:13your OK. OK
48:14So what did I just show you too quickly
48:18that we see a differential pattern
48:20of brain activity in the Habenula
48:23the insula ACC eventual stratum,
48:26following positive and negative feedback,
48:28and we see again again at the Association
48:31between trait life addiction and state
48:34like withdrawal in that smokers show a
48:37reduced right or responsibility to positive
48:40feedback which was not ameliorated by.
48:43Nicotinic agonists was correlated
48:45with severity of addiction,
48:48and Conversely habenula activity following
48:51positive feedback was reversed by an RT.
48:55Which was correlated with with craving,
48:57which I didn't have a chance to show you.
49:00So this novel evidence again seems to
49:03suggest that why these monotherapies
49:06might not be overly effective.
49:08Alright, I'm going to skip the with
49:12the summary and one tickle only
49:14Becausw Regina said.
49:16We're moving into treatment.
49:19This is a study that just came out.
49:22MD, PhD screen in the lab of wanted
49:25to see theoretically if PVCS at least
49:28acutely could modify these service and
49:31with Sarah did was taking the hypothesis
49:34of this three network key to tar.
49:37And using this hypothesis,
49:39put Anodal T DCS let me show you where it is.
49:44Put TCS over the VM,
49:46Pfc and the DL Pfc and switch
49:49polarities with an oral DL,
49:51Pfc or cat photo DL Pfc to try
49:54to modify this three large scale
49:57networks again using the same power
50:00line we've been using in the lab.
50:03We scan smokers on and off
50:06and nicotine Patch with.
50:08See the sham stimulation or
50:10an Ola Catholic stimulation.
50:11We did the same thing and non
50:14smokers but only scanned them once.
50:16No drugs for these folks
50:18and importantly we scanned.
50:19We presented T DCS in the magnet so we
50:23were doing this online in real time
50:26to watch how the brain is changing
50:29as a function of this intervention.
50:32Because Sarah wanted to be a
50:34measure and not a mapper.
50:35We use tasks that we well knew what they,
50:38what they did. So she had a priority.
50:40Regions of interest to look
50:42at the effects of PVCS.
50:44She used the parametric flanker task
50:47that we developed in the lab that very
50:50nicely distinguishes smokers from non
50:53from non smokers and I don't have
50:55time to to go into that and perhaps I
50:58won't tell you simply that the tasks
51:01were parametric flanker task work and
51:04people did worse smokers be worse.
51:06They did worse when they were in abstinence
51:10but importantly for this piece of
51:12the presentation and a single 30 minute.
51:152 million add auto TVCS increase the.
51:22The rush or ACC activity when the
51:26individual is doing a conflict ask
51:30the effect was bigger and smokers
51:33than nonsmokers for the N back
51:37task again behaviourally the task
51:40worked and again acute T DCS.
51:43To the DLP FC enhanced the
51:46deactivation on a 3 backpacks,
51:49allowing that performance to be to be better.
51:53And it did so.
51:54And this was the main point.
51:56I want to leave you with it.
51:58Did so better in the savant
52:01nicotine Satan state than in
52:02the nicotine withdraw in state.
52:04So that suggests to us.
52:08Let me skip the E field mapping.
52:11This suggested to us that smokers
52:13would since they were more sensitive
52:16when they were sated than that and
52:19when they were cognitively engage.
52:21It may be that that this Admiral TV
52:24CS might be a useful ad on therapy
52:28alongside nicotine replacement
52:30to perhaps increase the gain
52:32of modifying these circuits.
52:35So I apologize for these last
52:36last few minutes of kind of
52:38rushing rushing through things.
52:39I just want to end with thanking the folks
52:42in the lab who really did all of the work,
52:45and I think I've mentioned those
52:47that were involved along the way.
52:49Some of my outside collaborators that
52:51I've also highlighted along the way.
52:53I want to thank my to for ITS support,
52:55and I want to thank you for your
52:57indulgence in your attention,
52:59thanks.
53:02Thank you so much, Elliott.
53:04That was just beautiful Ann.
53:06Really, such a such a Tour de force
53:08with with all of these details
53:11I mean functional mapping of the
53:13brain in the context of smoking in
53:16different state and trait effects.
53:18We're just we're just gorgeous.
53:20Let me just open this up now for
53:23questions and comments from all of you.
53:26I also want to just point out
53:29that in fact the CME links.
53:32Are in the chat box.
53:33If you need to get for CME credit,
53:36so please make sure and get that,
53:38but I'm opening it up to questions.
53:42You can use the chat
53:44function or raise your hand.
53:47Let me start actually Elliot.
53:49That was really gorgeous an it's just
53:52beautiful how you use different tasks
53:54that focus in on different aspects of
53:57function to sort of dissect the brain
54:00under under a different drug related states.
54:03The question I have is actually twofold.
54:05One is there's a lot of blunting
54:08under these acute withdrawal.
54:10Sort of chronic drug use
54:12states that you showed.
54:14It made me start to think
54:16of whether that's tolerance.
54:18Or just a lower level of functioning and?
54:22Anan therefore you know the
54:24flip side would be there.
54:25Is there sort of you know you're in
54:28the trap where if you try to reverse
54:30that you might have sensitization.
54:33So what was sort of worried
54:35about that piece of it?
54:36So how do you think about that?
54:39But the second thing you know
54:40I'm going back to your silver
54:42buckshot and the notion that even
54:44in studying this it because so many
54:47regions an networks are affected,
54:49different networks are affected.
54:50If we wanted to reverse this sort
54:52of like your brain stimulation.
54:54Approach even in studying it do need
54:57tasks that are not so focused in fact,
55:00that I'm not just focused on
55:02a uni dimensional aspect,
55:04but rather because drugs of abuse are
55:07affecting so many regions that we need.
55:10Some things that are more widespread in
55:12their effects of activating the brain.
55:16Yeah yeah. So let me take that.
55:18That second question first
55:19'cause I can remember it.
55:21So you know when we think about so
55:24why would DL Pfc TMS work right?
55:26Why? Why does it seem to be
55:29reasonably efficacious in depression?
55:30Maybe in another nurse?
55:32Psychiatric disorders OC D is
55:34going to prove this, you know.
55:36What is it about the DL Pfc it happens to?
55:40Of course be something accessible
55:41by TMS which doesn't go very deep,
55:44but when you think about the
55:45circuitry in one of the one pieces
55:47that I showed you in bed circuitry
55:50between there and the insula right,
55:52maybe we can think of this as being
55:54sort of top of funnel that what we're
55:56what we're doing is we're accessing a
55:59lodging network from this from this.
56:01Or maybe it's an inverse funnel than that
56:04I'm accessing it from this point that I mean,
56:06the DL Pfc is a sketch pad.
56:09This is where we are.
56:10Lots of things are going in and
56:12out of brain for processing.
56:14You know,
56:14executive function talking to
56:16a lot of downstream components.
56:18And so it may be that these multifaceted
56:21aspects of Sud that we all acknowledge
56:25with come together in these large
56:28scale logical networks that may be
56:31amenable to to an intervention like that.
56:36It's uh.
56:37You know the you're right there,
56:40there's some of the things
56:42that are that we wonder about.
56:45From the one hand going on,
56:47uh, thinking about specificity,
56:49event of anatomy and specificity of
56:52the receptor target, versus perhaps,
56:54you know,
56:55the most efficacious treatment we have
56:57in psychiatry today is the least specific,
57:00right.
57:01So ECT works on, you know, 70% ish of.
57:05Medication resistant depression.
57:06And there's no,
57:08there's no localization there.
57:10So you know the other thing I would point
57:15out is if we look carefully at Suzanne
57:18Hager's work and the loop structure,
57:21and again if you get beyond
57:24the cortical striedl piece,
57:26but the pieces that are talking into this,
57:29that what we're doing is we're
57:32really bringing into into play.
57:34You know many many downstream
57:36structures in both in the disease,
57:38and perhaps in this intervention.
57:41Now to your first question.
57:43What's going on during this acute
57:47accidents versus versus satiety, right so?
57:50Is it?
57:51Is it simply a matter of well,
57:55so you talked about tolerance
57:58and sensitization right when?
58:00When an acutely abstinent smoker?
58:03Smokes or gets a Patch.
58:06They're not gonna smoke then
58:09not going on a on a bench.
58:12They're not,
58:13they're not trying to to overcome.
58:15Some deficit state beyond an
58:17equilibrium point, right?
58:18They seem to,
58:19and in fact there is almost no
58:22tolerance to smoking people that smoke
58:25a pack a day smoker pack a day and
58:28for 20 years they smoke a pack a day.
58:31That's very different than the profile
58:33to see with opioids with alcohol.
58:36So it's a very different,
58:37very different drug.
58:38And So what we're thinking is
58:41happening is there really isn't
58:42a cute an acute deprivation state
58:45that's that's simply reverse.
58:46Ameliorated by the replacement of
58:48nicotine, and that's an that's
58:50shown cognitively as well as
58:52in these circuits, right?
58:54Right? Thank you. That's great.
58:56We have a question in the chat box.
58:59How well do would behavioral interventions?
59:02Hypnotherapy versus more Pfc
59:03based ones like CBT effect these
59:06networks? I think all interventions are
59:09going to change if you change the brain.
59:12You're going to change the networks and
59:15whether we change them pharmacologically.
59:18Using noninvasive brain stimulation.
59:19Whether we use CBT or other
59:21behavioral interventions.
59:23Of course, these circuits
59:25will change absolutely. My my.
59:27My long-term hope is that it's going
59:30to be a combination therapy and you
59:33and I would talk about this over
59:36the years that it's going to be.
59:39You know, supportive pharmacotherapy,
59:41interventional behavioral interventions,
59:42and with potentially neural modulation,
59:45then that might enhance these
59:47these these approaches.
59:49Yeah. Any other thoughts and comments?
59:57Hi if it's OK, I don't
59:59really have a question just
01:00:01like a feel good moment for a second.
01:00:03My name is Justin Morales,
01:00:05I'm actually a fourth year
01:00:07medical student at Howard.
01:00:08Fortunate to join this
01:00:10call to Doctor
01:00:11Schottenfeld who passed it along and
01:00:13really I joined the call.
01:00:14Doctor Stein.
01:00:15You might not recall this.
01:00:17I worked in your lab 10 years
01:00:19ago as a high school student.
01:00:21Now in my 4th year medical school.
01:00:24So very proud and happy to be able
01:00:27to join a listening to everything
01:00:29that you've done over these past 10 years.
01:00:31Continuing to, you know,
01:00:33pursue science and medicine,
01:00:34and I think it's great.
01:00:36So I just wanted to join it and just
01:00:38kind of say hi blast from the past.
01:00:41Justin thanks.
01:00:41Thanks for introducing yourself.
01:00:43I will say one of the best parts of this job.
01:00:46The absolute best parts of this job.
01:00:48Other students working in the lab,
01:00:50whether they're they're coming
01:00:51through in high school or college,
01:00:53we have a number of programs at
01:00:56the intramural program and we
01:00:57get students in at all levels,
01:00:59and it's it's absolutely the best part of.
01:01:02Doing science, I
01:01:03think wonderful.
01:01:04Well, thank you Justin.
01:01:05I hope we can interact you over to Yale
01:01:08for your post medical school years.
01:01:11We have two questions,
01:01:12one from Shelly Ament, Shelly.
01:01:15Go ahead and then Suchitra. Hey
01:01:18Elliot, wonderful to see you again.
01:01:21Also, one of your previous
01:01:23MD PhD students in your lab.
01:01:25I have a question since more
01:01:28more lately I'm focused on
01:01:30ambiguity and decision making.
01:01:32I'm wondering in your habenula
01:01:34study when you had the error made
01:01:37and you gave the feedback of the
01:01:40negative frowny phase versus the
01:01:42error made an ambiguous feedback.
01:01:44Did you look at that to see what
01:01:48the ambiguous feedback would
01:01:50activate? We we, we did and and I.
01:01:54Yet again, apologize for
01:01:55the speed that I that I.
01:01:57I thought the study was cool,
01:01:59so I just wanted to just came out
01:02:01so I wanted to tease you with it.
01:02:04Yeah there were two bars.
01:02:05If you can think of the slide there
01:02:07are two bars to the right that
01:02:09we're both yellow and those were
01:02:11the those were the non informative
01:02:13feedback and it was sort of a
01:02:15neutral activity activation.
01:02:18They don't wanna separate Unity Center.
01:02:21You didn't pull out a separate
01:02:23like locus of ambiguity. OK,
01:02:25thank you, it's really interesting.
01:02:29Suchitra
01:02:34Sorry I'm trying to unmute myself
01:02:36later. That was a wonderful talk.
01:02:38Thank you so much. It's it's.
01:02:40It's great to see such a nice
01:02:42series of studies that you know
01:02:44are all connect and makes sense.
01:02:46I wish we were also lucky to have results
01:02:49which kind of all fit together so well.
01:02:52So thank you for that.
01:02:54I guess my question is more of a general one,
01:02:57which is a lot of the studies that you
01:03:01presented were in the adult brain.
01:03:03If I understand correctly.
01:03:04You know now we are in the
01:03:06in the US and World Wide.
01:03:08We are facing this huge problem with
01:03:11nicotine use through E cigarettes
01:03:12in youth and have you know I would.
01:03:15I would think knowing little bit that
01:03:17I do about the youth brain that you
01:03:19would anticipate that a lot of the
01:03:21flexibility or inflexibility that
01:03:23you're seeing in the adult brain would
01:03:25reflect very differently in the youth
01:03:27brain is what my understanding is.
01:03:29Could you maybe speak a little
01:03:31bit to what you would expect?
01:03:33How some of these processes would work there?
01:03:37Yeah, that's right,
01:03:38that's a great question.
01:03:40So we have studied only adults as you,
01:03:42as you alluded to. 18 to 60 year olds.
01:03:45I think our our in our studies.
01:03:48Um? And we know certainly the case
01:03:52of smoking that nobody thought
01:03:54smoking as an adult, right?
01:03:55If you can get your kids through
01:03:58high school and not be a smoker,
01:04:00the likelihood of them smoking is very,
01:04:02very small, right?
01:04:03Almost everybody starts at 13,
01:04:05fourteen, 15 years old,
01:04:06and we know that you as you just alluded to,
01:04:09that that's the time of greatest
01:04:11flexibility in the brain,
01:04:12greatest developmental plasticity.
01:04:14And so we have two things going
01:04:16on right with beating the brain
01:04:18up with this foreign substance at
01:04:20the same time that the brain is.
01:04:22Is maturing.
01:04:23And so you would expect that
01:04:25one of the reasons perhaps why,
01:04:28as an adult,
01:04:30this is such an insidious disease
01:04:32and failure rates are so high,
01:04:35is that that plasticity is
01:04:37well locked in right now.
01:04:39Which of those circuits potentially were
01:04:42affected the most at that at that time?
01:04:45I do have data in my pocket
01:04:48that is not ready for primetime.
01:04:52The the animal studies that I showed
01:04:56you that that Robin Keeley did.
01:04:59We repeated in in neonatal rats.
01:05:03So we we started this at P.
01:05:08He 20 I think and we gave rats
01:05:12different amounts of nicotine at
01:05:15different starting points along
01:05:17development and we allowed them
01:05:20to grow up with the nicotine.
01:05:23Again, it I think chronic nicotine,
01:05:26and then we scan them along the
01:05:28developmental trajectory right?
01:05:30And so again,
01:05:31one of the nice things we have in
01:05:34animal magnet. We can do scanning.
01:05:36I think we scan these these rats
01:05:39four times across the development.
01:05:42It's a humongous data set and we're just.
01:05:48Thinking We're wrapping our
01:05:49heads around itself,
01:05:50give me a call in a couple of months
01:05:52an I'll have some data for you,
01:05:54but it's a critical question that
01:05:56we think that this really is.
01:05:58Something that that's very relevant
01:06:00clinically to smoking use disorder.
01:06:04Thank you yeah my I was really
01:06:06curious to know whether this process
01:06:09that is changing that you're
01:06:11describing you know with nicotine.
01:06:13The timeliness of that and how it
01:06:16changes in younger populations will be
01:06:19very interesting to examine because
01:06:21you know you don't get the same
01:06:24profile of nicotine withdrawal in
01:06:26younger populations too, so.
01:06:28Really, I'm really glad you mentioned that.
01:06:30So kids when they stop smoking do
01:06:32not have a very serious effective
01:06:35withdrawal syndrome. I. That that's.
01:06:40Fascinating. Any other there
01:06:44is another question in chat.
01:06:46Regina is there data on relation between
01:06:50forms of therapy, neuro modulation,
01:06:53behavioral intervention or pharmacology
01:06:55age and or individual differences?
01:06:59Wow, Ahah. I don't know.
01:07:08I don't know. We don't and I sort of
01:07:12alluded to and I had had a slide at
01:07:15the end that I didn't punish you with
01:07:19to look at at fractionating as we're
01:07:21beginning to fractionate the phenotype,
01:07:23so we're not doing a particularly good
01:07:26job at looking at individual differences
01:07:28with with interventions of any sort,
01:07:31there is the nicotine metabolism
01:07:33ratio work that Karen Lerman has
01:07:35shown for individual differences
01:07:37with slow versus fast metabolizers.
01:07:39And we know that slow metabolizers
01:07:42seem to do better with, well,
01:07:45buitron fast metabolizers seem
01:07:47to do better with NRT.
01:07:49That's one of the best examples I
01:07:53know of fractionating the phenotype.
01:07:55I would hope that.
01:07:57If we all get to do this wonderful
01:08:00job for a few more years that we we
01:08:04can get down the road to begin to do.
01:08:07I think some pretreatment phenotyping
01:08:08to be able to say you are in
01:08:11fact the well buitron person,
01:08:13your NRT Europe or rent a clean.
01:08:15I mean if you think about it.
01:08:18NRT works in 1015% of the people.
01:08:21Well buitron, 20 ish percent.
01:08:23Varenna clean thirtyish percent
01:08:25if you keep them on for a year.
01:08:29So if we can fix 60% of the
01:08:32people 100% of the time.
01:08:35We've done.
01:08:36I mean, this is great,
01:08:37but we just don't know who they are right?
01:08:39And we also don't know if they're
01:08:41the same people or if these are
01:08:43in fact independent Co boards.
01:08:44So it's a great question.
01:08:46We're not there yet.
01:08:47It's sort of the Holy Grail,
01:08:48at least in my.
01:08:49In my thinking that we can
01:08:51do that at some point.
01:08:57Wonderful, we really engage the audience.
01:09:00So beautiful. You've got some
01:09:02wonderful questions and answers.
01:09:04I think we are almost
01:09:07more question Ridata.
01:09:08OK, Pittenger has his hand raised.
01:09:11Go ahead, Chris.
01:09:13That wasn't my hand raised.
01:09:15That was me
01:09:16clapping. Oh, it was the clap.
01:09:18Christmas planning. Do you
01:09:20see any good options? Trisha. I
01:09:24think we are all set.
01:09:26I don't see any other hands
01:09:28raised and nothing else in chat.
01:09:31Yeah, well, Elliot that was just beautiful.
01:09:34Thank you for such a wonderful,
01:09:36stimulating talk.
01:09:37It's got everybody's juices going and we.
01:09:40Now we will be following up on
01:09:42your papers and things like that.
01:09:44Thanks so much.
01:09:45I know it's really early where you
01:09:47are and you've taken the you woken
01:09:49up early and we couldn't tell any
01:09:51difference about sleep sleep deprivation.
01:09:53You would just
01:09:54fantastic thanks so much.
01:09:55Thank you everyone, thanks.