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Yale Psychiatry Grand Rounds: June 11, 2021

June 11, 2021

Yale Psychiatry Grand Rounds: June 11, 2021

 .
  • 00:00For the annual Flynn Lecture an it's my
  • 00:03pleasure to be able to introduce both
  • 00:06the lecture and also our speaker today,
  • 00:10so the Flint Lecture is in honor of
  • 00:13a faculty member in our department.
  • 00:16Doctor John P. Flynn,
  • 00:17who was a pioneer in the understanding
  • 00:20how the brain contributes to behavior,
  • 00:23and it's hard to think now of
  • 00:26how revolutionary his work was,
  • 00:28but in particular.
  • 00:30I look back to this paper from 1964,
  • 00:34which Full disclosure I was already
  • 00:37born but just barely and what he and
  • 00:40his colleagues did was to stimulate
  • 00:43part of the cat brain and to find that
  • 00:47the cat would attack a rat or another.
  • 00:51Other rat sorry a cat would attacker at
  • 00:54yes and that this would be completely
  • 00:58independent of any other stimulus.
  • 01:01Any other thing happening in the environment?
  • 01:04Just this electrical stimulation
  • 01:06could result in attack,
  • 01:08and it began to form our concept
  • 01:11that aggression had a brain basis
  • 01:14and this work is still inspiring.
  • 01:16Today in 2011,
  • 01:18a paper in which the hypothalamus
  • 01:20was stimulated with light.
  • 01:23In using novel molecular genetic
  • 01:25tools was really based very much
  • 01:28on this 1964 paper and Alan Lewis,
  • 01:31who was a resident in our department
  • 01:34and who worked in our lab,
  • 01:37also followed up on this work
  • 01:40using molecular,
  • 01:41genetic and pharmacological tools.
  • 01:43Looking at Astro choline and its
  • 01:46receptors so seriously influential
  • 01:48from the time that this work
  • 01:51was done to the present day.
  • 01:53I also want to note that we have
  • 01:56Doctor Flynn's daughter Sarah Flynn.
  • 01:58Joining us today and it's always
  • 02:01been one of the real pleasures of
  • 02:03this of this lecture for me to
  • 02:06meet Doctor Flynn's late life,
  • 02:08Holda and his daughter Sarah.
  • 02:10I wish that we could be meeting in person,
  • 02:14but certainly in the coming years.
  • 02:16As as we move beyond this
  • 02:19pandemic will move back,
  • 02:20hopefully to to having
  • 02:22this lecture in person.
  • 02:24The winners of or the winners.
  • 02:27The presenters of this lecture have been
  • 02:30luminaries and our current presenter,
  • 02:33Doctor Campti is is no less of a
  • 02:37luminary than any of our previous
  • 02:40presenters Ann Dr Ty did her work.
  • 02:44Her undergraduate training at the at MIT,
  • 02:47where she graduated with a major in
  • 02:51brain and cognitive sciences in 2003.
  • 02:55After taking a year off to travel,
  • 02:58she joined Patricia Genics lab at UCSF
  • 03:01and began her work in electrophysiological
  • 03:04recording from brain areas.
  • 03:06Important for emotional behavior
  • 03:08and connecting those circuits too.
  • 03:10Important behavioral outputs.
  • 03:12She then moved to Carl Daesrath
  • 03:15Laboratory at Stanford University
  • 03:17as a postdoctoral fellow,
  • 03:19where she began to use the
  • 03:22molecular genetic approaches.
  • 03:23The labeling approaches to identify
  • 03:26specific neuronal subtypes.
  • 03:27These stimulate stimula Tori approaches that
  • 03:29allowed her to isolate specific sub circuits,
  • 03:32and these tools allowed her
  • 03:34to unleash your creativity.
  • 03:35Ann became the basis of the work
  • 03:37that her lab members she and
  • 03:40her lab members have been doing.
  • 03:42To this day,
  • 03:43she became an assistant professor
  • 03:45at MIT in 2012,
  • 03:46was rapidly promoted to
  • 03:48associate professor with tenure,
  • 03:49and then moved her laboratory
  • 03:51to the Salk Institute,
  • 03:53where she was promoted to professor.
  • 03:56Doctor Ty is currently professor
  • 03:58and the Wiley Veiled Chair of
  • 04:00Systems Neuroscience at the Salk
  • 04:03Institute for Biological Sciences.
  • 04:04She's also an adjunct faculty member at the
  • 04:08University of California at San Diego and,
  • 04:11as I mentioned,
  • 04:12her research broadly is focused on
  • 04:14understanding the neurobiological mechanisms
  • 04:16underlying social and emotional processes
  • 04:18at the circuit level at the cellular level,
  • 04:22at the synaptic level,
  • 04:24and particularly those relevant
  • 04:26to psychiatric illness.
  • 04:27Professor ties been recognized with a
  • 04:30number of prestigious research awards.
  • 04:32In fact,
  • 04:32it's hard to find out an award that has
  • 04:36not really pulled out her work to to honor.
  • 04:40She received the NIH Director's
  • 04:42New Innovator Award,
  • 04:43the presidential early Career award.
  • 04:45For scientists,
  • 04:46scientists and engineering
  • 04:47from the White House,
  • 04:49the Society for Neuroscience
  • 04:50is Young Investigator award.
  • 04:52She was listed as technology
  • 04:54reviews Top 35 in among.
  • 04:57The reviews top 35 innovators under 35.
  • 05:00She received the NIH
  • 05:01Director's Pioneer Award,
  • 05:03and she's also been recognized
  • 05:05with a number of awards.
  • 05:07From mentoring at the undergraduate,
  • 05:09graduate and postdoctoral level,
  • 05:11and this is a place where I know
  • 05:15that she really has made incredible
  • 05:18efforts and I want to highlight her
  • 05:21trainees who have been at the forefront
  • 05:24of the wiki project to recognize.
  • 05:27Scientists who are generally
  • 05:28under represented,
  • 05:29both women and members of
  • 05:31underrepresented groups in Wikipedia
  • 05:33for the work that they've done,
  • 05:35and it's no short.
  • 05:37Nothing short of a revolution.
  • 05:39What she and her trainees have done
  • 05:42to further the efforts of outreach,
  • 05:44diversity and inclusion in science.
  • 05:47So without any further ado,
  • 05:50I'm going to now.
  • 05:53Turn the podium over to doctor
  • 05:55ties presentation.
  • 05:56She will be joining us
  • 05:58for questions at the end,
  • 06:00so please do put them in the chat.
  • 06:04I will moderate the chat as after
  • 06:07the presentation is finished and
  • 06:09I hope that you will all join
  • 06:12me in welcoming doctor Thai.
  • 06:14And I will now. Share her presentation.
  • 06:26Hi, it's such a pleasure to be here
  • 06:28for the Flynn lecture at Yale,
  • 06:31where I'm going to tell you about
  • 06:33the neural circuits of motivational
  • 06:35processing focusing on violence.
  • 06:40Some stimuli carry innate emotional valence.
  • 06:45No training or learning is required
  • 06:47to have emotional responses to them.
  • 06:50Other stimuli are initially neutral,
  • 06:52unless paired with an emotionally
  • 06:54significant stimulus.
  • 06:55So to have an emotional response to this,
  • 06:58we need to learn the associations between the
  • 07:01Twin Towers and the horrific events of 911.
  • 07:05There's been quite a bit of controversy in my
  • 07:08field about whether emotion is experienced
  • 07:11by humans and by animals in the same way.
  • 07:15There is no way to ever really know
  • 07:17how an animal experiences emotion.
  • 07:19There is no way to say whether it
  • 07:22is the same as a humans experience.
  • 07:24There's also no way for me to ever
  • 07:27truly know whether my subjectively
  • 07:29experienced emotions are the same
  • 07:32or different as another humans.
  • 07:34So you know what I'm interested
  • 07:36in is emotion.
  • 07:37What I actually study is motivated behavior.
  • 07:42I've always been interested in how
  • 07:43we assign positive negative balance
  • 07:45to environmental cues. For example,
  • 07:47think of a track star and a war veteran.
  • 07:50They both had the same auditory stimulus,
  • 07:53bang a gunshot.
  • 07:54The track star might have a rush of
  • 07:57excitement while the war veteran
  • 07:59might have sensations of panic or fear,
  • 08:02someone presented with these stimuli many
  • 08:04times without consequences may habituate.
  • 08:06An experienced neutral
  • 08:07valence and low arousal.
  • 08:09So why would the same sound produce
  • 08:11opposing reactions in different individuals?
  • 08:14Sure, they've had different
  • 08:16experiences in the past.
  • 08:18That have changed the way they experience
  • 08:20their environment now, but how?
  • 08:21How do our brains tell us if
  • 08:23something is good or bad?
  • 08:25What actually makes our brains different?
  • 08:27Solving this mystery would shed light on
  • 08:30the fundamental principles of survival,
  • 08:32as well as really help us understanding.
  • 08:34The key hallmark features of many
  • 08:37different psychiatric disease states.
  • 08:39So by plotting things here in
  • 08:41a simplified version of the two
  • 08:43dimensional theory of emotion,
  • 08:45where on one axis we have the
  • 08:47intensity or the arousal,
  • 08:49and on the other axis we have
  • 08:51balance orthodontic value.
  • 08:52This is the implication,
  • 08:54and this is we can also compare this.
  • 08:57Framework with another framework called
  • 08:59the two factor theory of emotion that
  • 09:02suggests an order of operations.
  • 09:04And then she got back to theory of motion.
  • 09:07We think about stimuli that coming
  • 09:08in and the first question we have to
  • 09:11ask ourselves is, is this stimulus important?
  • 09:13You can think of that as absolute
  • 09:15value if it's not important,
  • 09:16we ignore it.
  • 09:17If it is important,
  • 09:18the next question we need to ask
  • 09:20ourselves is how is it important?
  • 09:22Is it something that is good or bad?
  • 09:24Do we want to avoid this Daniels or
  • 09:27approach it?
  • 09:28And so this is what I want to focus on today.
  • 09:31Where is the fork in the road and
  • 09:33how do we determine what gets routed
  • 09:35down one path or another?
  • 09:39So if we think why am I so obsessed
  • 09:41with understanding the perturbations
  • 09:43that could occur with you know
  • 09:45of motivational valence, really?
  • 09:47Because I think this could be a
  • 09:49common thread between many different
  • 09:52psychiatric disease states.
  • 09:53For example, in the case of anxiety,
  • 09:56perhaps there is a shift to too
  • 09:58much motivation to avoid potential
  • 10:00negative consequences relative
  • 10:01to motivation to seek rewards.
  • 10:04The converse can also be true.
  • 10:06Too much motivation to seek potential
  • 10:08rewards and not enough motivation to
  • 10:10avoid potential negative consequences.
  • 10:12And you know, admittedly,
  • 10:13this is a very simplified perspective.
  • 10:16And then in the case of depression,
  • 10:18perhaps we just have reduced
  • 10:20motivation over all.
  • 10:22So how do we implement this process?
  • 10:24How does the brain carry out this very,
  • 10:27very simple process of asking
  • 10:29if something is good or bad?
  • 10:31So there are a few different neural
  • 10:33circuit motifs that we've seen,
  • 10:35you know,
  • 10:36recur and appear over and over
  • 10:38again as the field of circuit
  • 10:41neuroscience has developed and matured.
  • 10:43And I'm not going to really talk
  • 10:45about the labeled lines model just
  • 10:47because it's sort of a straw man.
  • 10:49When we think about balance processing
  • 10:51because it doesn't really allow for
  • 10:52learning to happen reversals to occur.
  • 10:54You know,
  • 10:55aside from just strengthening or
  • 10:56weakening the lines of information
  • 10:58flow as they already exist,
  • 10:59you know it doesn't.
  • 11:00It doesn't explain how we can learn to
  • 11:03like a bitter taste like coffee or beer,
  • 11:05or how we can adapt to changing
  • 11:07conditions in the environment.
  • 11:10So what we want other machines that
  • 11:13we have explored include divergent has
  • 11:16where a common scene is is coming on.
  • 11:19To posit that send information to
  • 11:21different downstream targets were
  • 11:23different processes may occur,
  • 11:24and pretty Danbury and Anabella
  • 11:26have worked on this in my lab.
  • 11:29Will talk about that momentarily.
  • 11:31Another possible motif is that opposing
  • 11:34components where the anatomical origin and
  • 11:37and target the point A&B are the same,
  • 11:39but the lines of.
  • 11:40But the circuits that are are
  • 11:42sending messages from point A to
  • 11:44point B are different functionally.
  • 11:46For example,
  • 11:47if there glutamate and GABA
  • 11:49going from point A to point B,
  • 11:51what really matters is is the
  • 11:53neurons integrate that information
  • 11:55of those opponent components to
  • 11:57sort of do a winner take all?
  • 11:59And for that, my graduate student,
  • 12:02former graduate student,
  • 12:03Edward now who's now at Princeton,
  • 12:05explored this in his thesis work,
  • 12:07and then the 4th would be
  • 12:09that of Neuromodulatory gain.
  • 12:11And so we've looked at this
  • 12:13in the prefrontal cortex,
  • 12:15Caitlin Vanderweel and Cody
  • 12:16Siciliano have explored this in and
  • 12:18today I'm going to tell you about
  • 12:20a new venture of understanding
  • 12:22how neuropeptides can influence
  • 12:24the divergent circuit motifs that
  • 12:26we already know about within the
  • 12:29basil lateral and make the left.
  • 12:31For today I'm going to be focusing
  • 12:33on these two motifs and how they're
  • 12:36relevant for balance processing.
  • 12:37So the road map for today are just three.
  • 12:41Sort of big general questions.
  • 12:43One is a little bit of review
  • 12:45where to circuits encoding positive
  • 12:47and negative bills diverge.
  • 12:49There's many places where they could diverge,
  • 12:52but will will go through one case study.
  • 12:55What are the local interactions between
  • 12:57these functionally distinct circuits?
  • 12:59Just form give rise to function
  • 13:01and then third how can narrow
  • 13:04modulation participate in the
  • 13:06process of valence assignment?
  • 13:08And then well.
  • 13:09Rabbit up,
  • 13:10so the first hints of the Amygdala's
  • 13:14involvement in emotional processing
  • 13:16came from temporal lobe activities
  • 13:18in primates over a century ago.
  • 13:21Following Brown and cheaper work,
  • 13:23Kluver Bucy coined the term
  • 13:25psychic blindness to refer to what
  • 13:27happens to these animals when they
  • 13:29lose their innate fear snakes,
  • 13:31or,
  • 13:31you know,
  • 13:32sort of lose interest in food and treat
  • 13:34sort of inanimate objects like light bulbs,
  • 13:37similarly to what would have been
  • 13:40previously fearful rewarding stimuli or
  • 13:42Larry Weiss grants then identified these.
  • 13:44These phenotypes were actually
  • 13:46specifically attributable to
  • 13:47selective amygdala lesions later on.
  • 13:50There's also the important
  • 13:51case study patient ** who,
  • 13:53following bilateral amygdala damage,
  • 13:55lost fear to snakes and spiders.
  • 13:58The ability to recognize
  • 13:59emotion in other peoples faces,
  • 14:01and even lost the fear.
  • 14:03Fear responses to being mugged,
  • 14:05which actually happened several
  • 14:07times in her life, however.
  • 14:09When she was at suffocation when
  • 14:13she's experiencing suffocation,
  • 14:14she still could have the autonomic
  • 14:17responses increase in autonomic arousal,
  • 14:20heart rate,
  • 14:20sweating, etc.
  • 14:21Suggesting the amygdala is important
  • 14:23for the assignment of environmental
  • 14:26significance to sensory stimuli,
  • 14:28but not necessarily the production
  • 14:31of the autonomic or arousal
  • 14:33and physiological responses.
  • 14:36So in my in my lab, we work in mice and
  • 14:39if you take a look at the mouse brain,
  • 14:41take a little section and look here,
  • 14:44there are 13 sub nuclei of the amygdala,
  • 14:46actually, but I'll just be focusing on
  • 14:48two of them for simplicity of today.
  • 14:54So where does circuits encoding
  • 14:56positive and negative balance diverge?
  • 14:58Well, I've already sort of hinted
  • 14:59to you that the bill is important.
  • 15:02Why you know what?
  • 15:03What else about the amygdala?
  • 15:05Do you make alot is kind of this
  • 15:08primitive analog of of the cortical
  • 15:10striatal circuit and some have
  • 15:12referred to it as the alligator brain.
  • 15:15It's it's primitive brain within the
  • 15:18brain because the amygdala days auto
  • 15:20mgla is 90% glutamatergic neurons
  • 15:22and described the cortical cortical
  • 15:24like in that it forms associations
  • 15:26is not a laminated structure like
  • 15:28the cortical like the cortex,
  • 15:30but other than that there
  • 15:32are some similarities.
  • 15:33The central amygdala is
  • 15:35striatal like because.
  • 15:36It's 95% Gabaergic medium spiny
  • 15:38neurons in a similar manner.
  • 15:40So there is a very rich body of
  • 15:43literature suggesting that the
  • 15:45PLA is well positioned to be where
  • 15:47valence encoding neurons exist.
  • 15:49So we know that neurons in the
  • 15:52PLA encode positive and negative
  • 15:54balance that all modalities of
  • 15:56sensory information converges in
  • 15:58the basal lateral make the love that
  • 16:01learning induces synaptic plasticity.
  • 16:03And just a brief didactic direction here,
  • 16:06so so.
  • 16:08We believe plasticity occurs in
  • 16:10synapses that were previously weak
  • 16:12synapses that might carry information
  • 16:14about the condition stimulus,
  • 16:16such as an auditory tone,
  • 16:18but once is paired with either
  • 16:20a reward or punishment,
  • 16:22will be strengthened,
  • 16:23and so just to I'll come back to this later,
  • 16:27but just very quickly.
  • 16:29We are using ampata NMJ ratio as a
  • 16:32proxy for glutamatergic synaptic strength,
  • 16:34because after your garden variety LTP occurs,
  • 16:37you will see an.
  • 16:38Increase in Emperor Scepter
  • 16:40mediated currents.
  • 16:47We have already seen that fear
  • 16:50conditioning increases Amp'd MD ratio
  • 16:54in putative flammable DLA synapses.
  • 16:57In this particular putative synapse
  • 16:59I've also found when I was a graduate
  • 17:03student that reward conditioning
  • 17:04also increased ampata MDA ratio in
  • 17:07putative clam Omega Listen apps is
  • 17:09in the same computer the senses,
  • 17:11and so when I was a grad student.
  • 17:15I presented these data.
  • 17:16This is my first time meeting and
  • 17:19one of my colleagues came up to
  • 17:21me afterwards and just, you know,
  • 17:22gave me gave me a lot of Flack about
  • 17:25you know how does this make sense?
  • 17:27How can the same mechanism underlying
  • 17:29fear and reward conditioning?
  • 17:33Well, there's a few different possibilities.
  • 17:36Maybe the amygdala just encode salients and
  • 17:39it it you know anything that's important,
  • 17:42good or bad, will induce plasticity.
  • 17:46Or maybe the amygdala is actually
  • 17:47the site of valence assignment,
  • 17:49but it occurs by a distinct projections
  • 17:51that we just didn't discriminate between
  • 17:52when we were patching blindly. So dumb.
  • 17:57We know that the essential medial nucleus
  • 18:00is critical for the expression of fear.
  • 18:03We know that up genetically stimulating,
  • 18:05central medial nucleus neurons
  • 18:07evokes freezing responses.
  • 18:09We also know that disconnecting the basal
  • 18:12lateral amygdala from the central medial
  • 18:15nucleus will abolished fear expression.
  • 18:17But of course,
  • 18:18the central amygdala does many other things,
  • 18:20and there are a number of
  • 18:23fantastic studies that show this.
  • 18:25So it's not this simple.
  • 18:26Same thing for the nucleus incumbents.
  • 18:28Of course we know that the nucleus income
  • 18:31is important for diversity of functions,
  • 18:33but it's best known for its importance
  • 18:36in reward related processes.
  • 18:39We know that Papa genetically
  • 18:40stimulating VLA terminals and
  • 18:42nuclear comments supports self
  • 18:43stimulation in place preference.
  • 18:48When Praneeth Embery Annabelle or
  • 18:49came to my lab, they came ready to
  • 18:52tackle this question about what the
  • 18:54circuit mechanism is for signing
  • 18:56positive and negative balance.
  • 18:58So the hypothesis is simple,
  • 19:00just that the specific downstream
  • 19:02projection neuron matters.
  • 19:03So if you pair a tone with
  • 19:05foot shock for example,
  • 19:07you'll see a strengthening of synapses.
  • 19:11Coming on to see M projectors.
  • 19:13Whereas if we are.
  • 19:16I'm going to pair the tone
  • 19:18with a reward like sucrose.
  • 19:20We would see strengthening of
  • 19:21synapses coming on to feeling neurons,
  • 19:23projecting the nucleus of
  • 19:25Commons so very simply,
  • 19:26we just used retrogradely traveling for us.
  • 19:28It feeds and check into them into
  • 19:30either the nucleus of comments
  • 19:32or the central medial nucleus,
  • 19:34then train animals and either
  • 19:35a fear conditioning task or
  • 19:37reward conditioning task.
  • 19:38Simulated putative built Alanic
  • 19:40inputs to the amygdala and
  • 19:42then recorded just as before.
  • 19:44Except now we just know where
  • 19:47the targets are very simple.
  • 19:50And what we found was that after fear
  • 19:53conditioning we see a button increase
  • 19:55in synaptic strength on to see M neurons,
  • 19:58CN projectors excuse me and decrease
  • 20:01in amber ratio on to PLA to see M
  • 20:04neurons after reward conditioning.
  • 20:08Conversely, for being
  • 20:09late to a Commons neurons,
  • 20:11we saw synaptic strengthening on to
  • 20:13them or some Excuse me Ltd a reduction
  • 20:16and Anthony ratio after fear conditioning,
  • 20:18but an increase in synaptic strength
  • 20:20after reward conditioning.
  • 20:21So just the opposite.
  • 20:24And importantly,
  • 20:25what I want to point out is that even
  • 20:29conditions like food restriction can
  • 20:31change the basil amput empty ratio.
  • 20:34So if the visa lottery legal is truly
  • 20:36the site at which we translate sensory
  • 20:39information into motivated behavior,
  • 20:40then be light inputs should be able to
  • 20:43drive motor behaviors in the naive animal.
  • 20:48OK, but is there a causal relationship
  • 20:51and we show that there is.
  • 20:53If we fail to stimulate
  • 20:55village Commons animals,
  • 20:56we get intracranial self stimulation.
  • 20:58Just replicating work that gets tuber
  • 21:01and John Britton have already shown.
  • 21:05And we also show that if we simulate dealing
  • 21:07arms protecting the central medial nucleus,
  • 21:10we actually get punishment
  • 21:11avoidance place avoidance.
  • 21:13So OK, if it's true that if this whole
  • 21:16hypothesis is true and this is relying
  • 21:19on an MDA receptor dependent mechanism,
  • 21:21what happens with with an MD or soldier LDP?
  • 21:25I'm sure you know,
  • 21:27but if you don't know glutamate is released,
  • 21:30it will bind to gloomy receptors,
  • 21:32including an perceptors.
  • 21:34An MDA receptors,
  • 21:35however NMD a receptors are have a
  • 21:38magnesium blockade that sits in the poor
  • 21:40of energy receptors and the depolarization.
  • 21:43Caused by glutamate binding
  • 21:44and amp receptors.
  • 21:45Allows the influx of sodium.
  • 21:47Then it becomes depolarized.
  • 21:49This allows the magnesium blockade to
  • 21:51come out of the NBA receptor poor,
  • 21:53allowing calcium influx to occur.
  • 21:56So if this is,
  • 21:58you know,
  • 21:59this is all true that this is
  • 22:01how energy receptors.
  • 22:02This is how NBA receptor dependent LTP works.
  • 22:06Then hyperpolarizing the postsynaptic
  • 22:07neuron at a critical time point here would
  • 22:10then prevent learning because we couldn't,
  • 22:13you wouldn't be able to remove
  • 22:16that that magnesium blockade.
  • 22:18So we did this experiment.
  • 22:20This is bilateral Weezer dual virus
  • 22:23approach to express halorhodopsin
  • 22:25in either Bealach na Si Productions
  • 22:27or belay to see M Productions
  • 22:29and then train them again on a
  • 22:32fear or reward conditioning task.
  • 22:34Photo inhibiting only when the
  • 22:36US the unconditioned stimulus was
  • 22:38presented either for shock or sucrose.
  • 22:41And what we found.
  • 22:44I've sort of what I said for the
  • 22:46fear conditioning and that when we
  • 22:48photo inhibited be late to a comment,
  • 22:50something happened.
  • 22:50But if we silenced Beladice
  • 22:52central medial nucleus projections,
  • 22:53we saw an impairment in fear conditioning.
  • 22:57When we looked at reward conditioning,
  • 22:59however, something sort
  • 23:01of unexpected happened.
  • 23:02It was surprising because we
  • 23:03actually didn't see an impairment
  • 23:05to belay and astie inhibition,
  • 23:07as I would have expected,
  • 23:09we actually saw in enhancement
  • 23:11when feeling to see an innovation.
  • 23:14OK, so that was a little confusing,
  • 23:16but it'll make sense later.
  • 23:18So so just an interim summary is
  • 23:21that I've told you that opposite
  • 23:23synaptic changes map onto
  • 23:25production following either fear,
  • 23:27conditioning or reward conditioning.
  • 23:29If we just, you know,
  • 23:31circumvent all of this upstream
  • 23:33plasticity and just cut right
  • 23:35to the chase and manipulate
  • 23:37these projector populations,
  • 23:38activation of projections will
  • 23:40either cause avoidance or approach.
  • 23:43If we then bilaterally inhibit
  • 23:45either of these productions,
  • 23:47will see that inhibition of central
  • 23:50medial projectors impairs fear
  • 23:53but enhances reward learning OK?
  • 23:56But is it really that simple?
  • 23:58And of course the answer is no.
  • 24:00There's a lot of heterogeneity.
  • 24:02It's it's, you know,
  • 24:03all these neurons that are
  • 24:05anatomically defined,
  • 24:05have a lot of functional heterogeneity.
  • 24:08We do address this that even though
  • 24:10it's really exciting that we can target
  • 24:12things more specifically than ever before,
  • 24:14we're still possibly only
  • 24:16observing a majority vote.
  • 24:17There you know,
  • 24:18just because an offer genetic
  • 24:20manipulation can produce only one
  • 24:22measurable behavior in a given task,
  • 24:24this does not in any way
  • 24:26suggest functional homogeneity.
  • 24:27Of neurons anymore than having you know,
  • 24:30one president of the country suggest
  • 24:33that everyone agrees who it should be.
  • 24:36So Eve Marder,
  • 24:37once said very wisely,
  • 24:39you know very artistic I
  • 24:40love I love this club,
  • 24:42that optic tools tell us what neurons can do,
  • 24:45not what neurons do do.
  • 24:47So it's very important we need to
  • 24:48be able to explore the endogenous
  • 24:50functional properties of neurons.
  • 24:52Really understand them.
  • 24:53So the minimal the absolute minimal
  • 24:56criteria for violence in coding
  • 24:58a single cells is that number 10,
  • 25:00and I should say before I get
  • 25:02into this set on one axis,
  • 25:04there's the response to rewarding CS is.
  • 25:07On the other access,
  • 25:08there's a response to aversive
  • 25:10CS is in either case,
  • 25:11and in both cases we can either have
  • 25:13innovation, no response or an excitation.
  • 25:16Uhm?
  • 25:19So the so,
  • 25:20given these combinations of responses.
  • 25:22Of course, if.
  • 25:25Just.
  • 25:28They conclude that it fails in
  • 25:29coding a little bit harder is to say
  • 25:32that it's differential responding.
  • 25:33You want to say if it's
  • 25:35responding in a similar,
  • 25:37indistinguishable manner to to
  • 25:38both positive and negative stimuli
  • 25:40that it is not encoding balance.
  • 25:41This is pretty important.
  • 25:43Oftentimes studies will only show or
  • 25:45response to one or the other within
  • 25:47a given cell an you really need
  • 25:49responses to both without seeing
  • 25:51responses to both in the same cell
  • 25:53you you can't differentiate between
  • 25:55salience responses and balance responses.
  • 25:58And then finally it needs to be
  • 26:00independent of sensory features.
  • 26:01It's not just tracking the modality
  • 26:04or the specific frequency of
  • 26:07the tone or whatever.
  • 26:08OK, so this just underscores the
  • 26:11importance of seller resolution recordings.
  • 26:13So on a baler performed this
  • 26:16and it had fixed task an.
  • 26:18In this task,
  • 26:20one tone predicts sucrose delivery.
  • 26:23As you can see here and then in another,
  • 26:25another town predicts quiet time delivery,
  • 26:27which is a no go trial.
  • 26:32So we did a match modality,
  • 26:35build task where both the CSS and
  • 26:38both US is were of the same modality.
  • 26:42Auditory stimuli and gusta Tori outcomes.
  • 26:46And generally speaking,
  • 26:47for the non specific PLA recordings,
  • 26:50we just reproduced publications that already
  • 26:52existed from Dan Saltzman and Trajanic slabs,
  • 26:55but we didn't, you know,
  • 26:56go through all this trouble.
  • 26:58We did record 1600 neurons,
  • 27:00just we producers,
  • 27:01although it's always nice,
  • 27:03we wanted to know what neurons
  • 27:05of Goan production target did.
  • 27:08And so we used an approach
  • 27:10developed in Tony Zeiders lab,
  • 27:12which he termed Photostimulation assisted
  • 27:14identification of neuronal populations
  • 27:16which many people would refer to as
  • 27:18photo identification or photo tagging.
  • 27:20And basically the idea is
  • 27:22you've got an electrode.
  • 27:23You've got an optical fiber,
  • 27:25and you've got some specific
  • 27:27cell population that you have are
  • 27:30expressing opposition and so first.
  • 27:32You know it's near on a spikes.
  • 27:35We can record that if neuron B spikes,
  • 27:37we can record that too and we just
  • 27:39want to record all the endogenous
  • 27:42naturally occurring activity during
  • 27:44the task after the task is over,
  • 27:46we can shine light and get
  • 27:48spikes out of the neuron.
  • 27:50That is expressing option.
  • 27:53Then we can look at that and determine
  • 27:55whether there was a photoresponse or not.
  • 27:57Importantly, very,
  • 27:58very importantly,
  • 27:58we need to control for recurrent excitation,
  • 28:01particularly if you're doing photo tagging
  • 28:04in any place known to have it like cortex,
  • 28:08hippocampus, amygdala.
  • 28:10What does this mean?
  • 28:11Well,
  • 28:11it's just referring to this compound
  • 28:13that can occur if you have secret to
  • 28:15expressing ones that are protected from,
  • 28:17for example, BL A2 incumbents.
  • 28:18Let's say that's great.
  • 28:19Where were expressing in those cells?
  • 28:21We can verify that anatomically post hoc,
  • 28:23and it's easy in vivo to tell the
  • 28:25difference between a teacher to expressing
  • 28:27cell and a non expressing neighbor
  • 28:29that is not responsive to light at all.
  • 28:32However,
  • 28:32there may also be non expressing neighbors
  • 28:36that receive recurrent excitation
  • 28:38from the opsin expressing neuron.
  • 28:41And so when we pass,
  • 28:42we can validate this.
  • 28:44That doesn't help us in vivo necessarily,
  • 28:46you'd think.
  • 28:47But let's look at this and we can.
  • 28:50We can patch.
  • 28:50We can look at different light
  • 28:52powers and determine a distribution
  • 28:54of photo response latency's,
  • 28:56because if it is through
  • 28:57recurrent excitation,
  • 28:58there's this added synapse.
  • 29:01So sometimes the response to non
  • 29:03expressing neighbors that are receiving
  • 29:05input which you can determine and
  • 29:07know about unequivocally ex vivo,
  • 29:09you get the distribution.
  • 29:11This distribution is completely
  • 29:12non overlapping with those cells
  • 29:14are actually trying to record from
  • 29:16this feature to expressing neurons.
  • 29:18That's great. That's often the case.
  • 29:21Sometimes, though,
  • 29:22the case is that there's some partial
  • 29:24overlap where you for wrestle with
  • 29:25once a pot with a false positive,
  • 29:27once a false negative,
  • 29:28and then some cases there's
  • 29:29so much overlap issues.
  • 29:30Different approach,
  • 29:31like maybe you know genetically incredible
  • 29:33calcium indicators or something.
  • 29:35So we did this.
  • 29:36I'm going to skip.
  • 29:37I'm going to skip to the
  • 29:38punchline of this story
  • 29:39to tell you about new,
  • 29:41unpublished data, but.
  • 29:42We use multiple different types
  • 29:44of analysis and found that in
  • 29:46general it's true that village,
  • 29:47an AC predominantly encodes positive balance.
  • 29:49Be latest central amygdala predominantly
  • 29:51encodes negative balance, and we've
  • 29:53shown this in a bunch of different ways.
  • 29:57So it is heterogeneous genius.
  • 29:58There is a lot of heterogeneity,
  • 30:00but the general trend is history.
  • 30:02So what about the local interactions between
  • 30:04these functionally distinct circuits?
  • 30:05Why do we have them all like salt
  • 30:07and pepper mingled together in
  • 30:09the basal lateral make alone?
  • 30:13What is the microcircuit architecture,
  • 30:16so to speak well?
  • 30:20If I have here in green reward encoding you
  • 30:22know principle drones or production runs,
  • 30:25fear encoding principles and then of course.
  • 30:29Some interneurons that are that
  • 30:32are Gabaergic interneurons,
  • 30:33you might have one motif where there's
  • 30:36mutual inhibition, where reward
  • 30:38encoding neurons can silence fear,
  • 30:40encoding neurons, and vice versa.
  • 30:43You might actually also have a uni
  • 30:46directional or asymmetric inhibition,
  • 30:47where fear encoding neurons would
  • 30:49silence reward encoding runs,
  • 30:50but not vice versa.
  • 30:51And honestly, when I first drew this picture,
  • 30:54I just drew it 'cause I thought like
  • 30:57technically it's another possibility.
  • 30:58I didn't actually think it was
  • 31:01going to be the answer.
  • 31:03And then of course,
  • 31:04like the third possibility,
  • 31:05being that there's a neutral
  • 31:07excitatory response.
  • 31:08Felt thanks to Klong Hoon Chung.
  • 31:10We were able to look at this and you
  • 31:12can see here some bling NEC ability
  • 31:14to see an cells within the lateral
  • 31:17nebula intermingled so much together,
  • 31:19but also you know there's a gradient.
  • 31:22So indeed there are gradients.
  • 31:25We can quantify them,
  • 31:27and they are intermingled.
  • 31:29So this sort of underscores the need
  • 31:32to think about the relationship between
  • 31:34these different populations of neurons,
  • 31:36so I'll just show you one little tidbit here.
  • 31:40But when we looked at the latest
  • 31:42central amygdala neurons that
  • 31:44were photo identified here,
  • 31:46we've got 33 units.
  • 31:47We can also see neurons that
  • 31:49are photo excited,
  • 31:51meaning they have slower latency,
  • 31:52excitation, and response to light.
  • 31:55Order on that were photo inhibited,
  • 31:58meaning they were silenced by the activation
  • 32:00of the late Essential Omega neurons.
  • 32:02So if you look at these numbers,
  • 32:05you can see that the the the amount
  • 32:08of neurons that it's silent.
  • 32:10These bileta CN neurons or silencing
  • 32:12is greater than them themselves,
  • 32:14and so there's this huge ability for them
  • 32:17to suppress the responses of other neurons.
  • 32:20So.
  • 32:21You know,
  • 32:22perhaps it's true,
  • 32:23like if we compare these numbers that
  • 32:25I just showed you for the normalizing
  • 32:28to the neurons that actually expressed
  • 32:30channelrhodopsin and then looking at
  • 32:32the proportion of neurons are excited
  • 32:34or inhibited by those projectors.
  • 32:36You can see that the latest Central
  • 32:39McDonald's inhibit far more neurons
  • 32:40than do either of the other productions.
  • 32:43So maybe when it comes down to
  • 32:45a majority vote, so so to speak,
  • 32:48at the Bellator CN population is
  • 32:50more influential than local network.
  • 32:52And maybe their votes count more similar,
  • 32:55you know,
  • 32:55so that might be like something
  • 32:57that we want to consider.
  • 32:59It's not necessarily that all
  • 33:01votes are equal,
  • 33:02not necessarily just a majority vote.
  • 33:04Some neurons are positioned to be
  • 33:06able to exert greater influence
  • 33:07over their neighbors, like be late,
  • 33:10essential in Glen Rose.
  • 33:13Now, why won't the brain work this way?
  • 33:16If we record from this is published
  • 33:18in in Gwendolyn Calhouns preprint.
  • 33:21But when we record from from NEC
  • 33:24Projectors and green Eyes,
  • 33:25just abbreviated it end and patch
  • 33:28a record from from any project and
  • 33:31stimulate CN protectors or vice versa.
  • 33:33You know, recording stimulate
  • 33:35from the opposite pairing you.
  • 33:37We actually see that they have
  • 33:39different asymmetric impact on
  • 33:41each other when you stimulate.
  • 33:43Uhm? A common projectors recording
  • 33:46from central appraisal of
  • 33:49projectors you actually facilitate.
  • 33:51Excitation, whereas in the other
  • 33:53direction you suppress it, so why would?
  • 33:55Why would the brain work this way?
  • 33:58I did not expect to see an asymmetric
  • 34:00unidirectional relationship,
  • 34:01but maybe that makes sense because you
  • 34:03know you can mate or eat or drink later.
  • 34:06You need to escape from that predator
  • 34:08right now that is the most immediate,
  • 34:11most urgent demand or threat
  • 34:12on your survival.
  • 34:13So you have to address that.
  • 34:18Further, maybe it makes sense 'cause
  • 34:19reward seeking is just inherently risky.
  • 34:21If I'm a mouse that lives in in my
  • 34:24borough and I need to, I need to.
  • 34:26I want to forage for food or water.
  • 34:28Then you know, providing a skip
  • 34:30could be a good insurance policy.
  • 34:33OK, so that's some speculation
  • 34:34and just contacts, but how does
  • 34:36neuromodulation play a role in here?
  • 34:38So this is the third final questions.
  • 34:41Main big question or focus on today.
  • 34:45And for that meeting that I want to
  • 34:47actually show you the the questions
  • 34:49that that make me lose sleep at night.
  • 34:51So it's great that we found that
  • 34:53you know after fear conditioning
  • 34:54we see strengthening of synapses
  • 34:56going down one path afterward,
  • 34:58conditioning with the strengthening of steps,
  • 35:00going down another path, but.
  • 35:02When this is happening in real life,
  • 35:05you know animals are capable of 1
  • 35:08trial learning. How is this possible?
  • 35:11You know?
  • 35:11So I think the timescales how do
  • 35:13the synapses know which postsynaptic
  • 35:15neurons are which,
  • 35:16and what you're supposed to do,
  • 35:18so you know if you think about
  • 35:21spike timing dependent plasticity,
  • 35:22you know shifting things from
  • 35:24just 50 or 100 milliseconds.
  • 35:26Can dramatically impact whether
  • 35:28it's LTP or Ltd.
  • 35:29If we record in vivo,
  • 35:31you can see that after the onset of
  • 35:33the Q this the the auditory tone
  • 35:36just 100 or 200 milliseconds later,
  • 35:38we're back down to baseline.
  • 35:40We don't have.
  • 35:41You know the neurons are no longer
  • 35:43active even as the Q continues to play.
  • 35:46And then let's think about the
  • 35:48most common paradigms used in the
  • 35:50field where condition stimulus
  • 35:52will play for 10 or 20 seconds,
  • 35:54the beeline neurons that are
  • 35:56critical for the plasticity.
  • 35:58Please tell a very transient activation
  • 36:00at the onset of the condition stimulus,
  • 36:03then then go back down to baseline and
  • 36:05you know could be 10 or 20 seconds.
  • 36:08The unconditioned stimulus is presented.
  • 36:10So how does the brain solve
  • 36:12the valence assignment problem?
  • 36:13How does the brain attach these things
  • 36:16that are so desperate in time together?
  • 36:18So first there's the question of how do they?
  • 36:22How does the brain know which
  • 36:24synapses route information to wear?
  • 36:25So there's a few different options here so.
  • 36:28In terms of knowing,
  • 36:29knowing who's who in terms
  • 36:31of the postsynaptic neuron,
  • 36:33we wanted to explore this and so we
  • 36:36sequenced violate any simulated CM neurons.
  • 36:38And look for surface receptor specifically.
  • 36:41Indeed,
  • 36:41one service provider that we identified as
  • 36:44interesting is the Neurotensin receptor,
  • 36:46one which we see to be enriched have
  • 36:49enriched expression and Sian projectors.
  • 36:51Now why am I going to focus in on
  • 36:54the nearest ends in one receptor?
  • 36:58Well,
  • 36:58we know that there is a one receptor
  • 37:01controls a G protein coupled receptor GP CR.
  • 37:04The function of this receptor has
  • 37:06been linked to both LDP in the PLA and
  • 37:09also contextual fear conditioning.
  • 37:11And the thing that really got me was
  • 37:13done by Kimberly Kempadoo and she found that.
  • 37:17Different concentrations of narrow tense,
  • 37:19and this is a different cell population,
  • 37:22but different concentrations are
  • 37:24intense and could actually either
  • 37:26facilitate glutamatergic transmission
  • 37:28or suppress glutamatergic transmission.
  • 37:31So if this is possible, you know then?
  • 37:35We hypothesize that but the same
  • 37:38concentration of their attention could then,
  • 37:41you know, drive effects differently on
  • 37:43these projector populations that have
  • 37:45different receptor expression profiles.
  • 37:47OK, so if different concentrations
  • 37:49are neurons at the same profile,
  • 37:51can can make glutamatergic transmission
  • 37:54either be facilitated or suppressed,
  • 37:56then maybe one concentration of their
  • 37:58attention can shift the balance from
  • 38:00one population to another if they have
  • 38:03different receptor expression profiles.
  • 38:08So first we want to explore
  • 38:10this an we performed.
  • 38:12We did some pharmacological manipulations
  • 38:14where we administered the audience
  • 38:17or want agonist in today's letter
  • 38:19will make the lab and we actually saw
  • 38:22an enhancement of reward learning.
  • 38:25We saw a nonsignificant trend towards
  • 38:27an impairment of fear conditioning.
  • 38:29OK, so that's potentially, you know,
  • 38:32suggested that narrative could
  • 38:33play a role in balance processing,
  • 38:35and we also see that indeed there
  • 38:38are different effects you know
  • 38:40match for credit concentration of
  • 38:42Billy and Acnb licien neurons.
  • 38:44We do indeed see different
  • 38:47dose response curves.
  • 38:49These differences at a given concentration
  • 38:51of tendon, animal or near attention,
  • 38:54we can see an increase of billet and AC.
  • 38:59Amplitudes EPS evoked from Billy the
  • 39:02NACS neurons, and a suppression of EPS,
  • 39:04sees a bug from the legacy M neurons,
  • 39:07and this is blocked by the NPS
  • 39:10are one antagonist.
  • 39:11OK, great, but where do we get near?
  • 39:14It ends in front.
  • 39:16Where does it come from?
  • 39:17So we we trace upstream and looked for
  • 39:20colocalization of Tracer suggesting
  • 39:21that you were protecting the leg as
  • 39:24well as expression of neural tension
  • 39:26in the New York Times and cream mask.
  • 39:30And so we found that the PDT was a
  • 39:33prime target and photo stimulating
  • 39:35PDT to belay neurons produces valence
  • 39:38specific effects that we actually.
  • 39:41If we stimulate this PT input to be alive,
  • 39:45which includes neurotensin neurons,
  • 39:47we see a facilitation of reward learning
  • 39:51and an impairment of fear looming.
  • 39:54Next to this huge body of work
  • 39:56that I'm about to tell you about to
  • 39:58get into is a by Hailee a postdoc
  • 40:01in my lab here at salt.
  • 40:03And what,
  • 40:03how found was that the PDT to bill a
  • 40:06nuro 10 synergic projection contributes
  • 40:09heavily to Billy computations,
  • 40:11and so he said to look at this and
  • 40:14interrogate the contribution of Neuro
  • 40:1610 synergic input from this specific pathway,
  • 40:20we first Chris Byrd.
  • 40:22We used CRISPR to knock down
  • 40:24that near attend and Gene.
  • 40:26And so the PDT input would either have
  • 40:29knocked down or control of your attention.
  • 40:33Then we wanted to be able to perform
  • 40:36recordings in the basil lateral amygdala,
  • 40:39in both control an crisper animals
  • 40:41and be able to photo identify
  • 40:43the different populations.
  • 40:45So first I'm just showing you that the
  • 40:48crisper works we can inactivate the
  • 40:50near 10s and gene and preserve glutamate.
  • 40:55Narrative the neurons coberly's glutamate.
  • 41:00And we found that the crisper animals
  • 41:02will be knocked down the narrow
  • 41:04Tenzin gene within the PD gbla we
  • 41:07see an impairment of reward learning,
  • 41:09and this also promotes fear.
  • 41:11Learning this is again suggesting this role
  • 41:14for near Tencent in Valence processing.
  • 41:17OK, but how is this role actually like?
  • 41:20What does this look like?
  • 41:22What? How does?
  • 41:23How do the computations that
  • 41:25are being performed in the PLA?
  • 41:27How are the computations being
  • 41:29modified when you know there's
  • 41:31more attention or not?
  • 41:35And so dumb. How recorded from hundreds of
  • 41:38neurons from the basal lateral amygdala,
  • 41:41in a task where animals had to just
  • 41:44differentiate between a reward and
  • 41:46shock predictive cues, as well as a
  • 41:49neutral Q that didn't predict anything,
  • 41:51and we perform functional agglomerative
  • 41:53clustering, and we can see that
  • 41:55across different types of clusters.
  • 41:57Here, Gray is controlled and blue is
  • 42:00crisper and across the board. But you know,
  • 42:03there's a diversity of responses.
  • 42:06But what you can see across the
  • 42:08board in each of these clusters
  • 42:11is that the response is blunted.
  • 42:13When we Chris Brown your
  • 42:15attention on both directions,
  • 42:16both for excitations an ambitions,
  • 42:18the absolute value of the
  • 42:20amplitude of the response,
  • 42:22the change in physical activity
  • 42:23in either direction to reward
  • 42:25or Punish Inc uses reduced,
  • 42:27so every all the valence
  • 42:29processing just looks blunted by
  • 42:31the knockdown of their attention.
  • 42:34OK, So what about specifically
  • 42:37to BLAN AC projectors?
  • 42:40We see that indeed.
  • 42:44Control animals we replicate this general
  • 42:46effect of having a reward you know,
  • 42:49a positive balance biased encoding
  • 42:52property which drops sort of to neutral.
  • 42:55When we Chris Brown are tense and
  • 42:57same thing central projectors.
  • 42:59We reproduced our initial response
  • 43:01of having a negative balance biased
  • 43:04response of this whole population,
  • 43:06which again is sort of neutralized
  • 43:09or attenuated with the knockdown
  • 43:11of crisper injustice.
  • 43:12Pacific PDT to be late input.
  • 43:15Neurotensin everywhere else
  • 43:17in the brain is intact.
  • 43:19OK,
  • 43:19so this is just showing the opposite effects
  • 43:22of the different projector populations.
  • 43:25And then what I want to show you here is,
  • 43:28this is what normally
  • 43:30happens for each trial type.
  • 43:31We've got sucrose neutral,
  • 43:33an shock condition stimuli,
  • 43:34and each trajectory begins here in time.
  • 43:36Then the Q will be on set and
  • 43:39then the response will occur.
  • 43:41And what am I showing you here?
  • 43:43This is looking at the neural ensemble
  • 43:45as visualized as a neural trajectory.
  • 43:47So what does that mean?
  • 43:50How do you?
  • 43:51How do we think about an ensemble of neurons?
  • 43:52So if you if you had 100 neurons,
  • 43:54I mean here we have.
  • 43:56Sam called 700 rounds,
  • 43:57but if you have 100 rounds and you want
  • 44:00to see what the whole population is doing,
  • 44:02you could plot that in 100 dimensional
  • 44:04space and then just look at each neuron
  • 44:07as representing a dimension and then
  • 44:09just look at the trajectory of that
  • 44:11ensemble in activity space across time.
  • 44:13It's an aerial trajectory.
  • 44:15It's hard to plot 100 dimensional space,
  • 44:17so of course what we can do is perform
  • 44:20dimensionality reduction principle
  • 44:22components analysis and then reduce
  • 44:24reduce the dimensions down to those
  • 44:27that can offer the most covariance.
  • 44:29So that's what we're doing here.
  • 44:31Principal component one principal
  • 44:32component to it that you
  • 44:34components that offer contributed
  • 44:36most covariance here and then.
  • 44:37You can see that the sucrose trajectory's
  • 44:40once the the tone comes on you can
  • 44:43see the animals are showing this.
  • 44:45This divergent of the trajectory's.
  • 44:48These are the control animals,
  • 44:49though. What happens when you put Chris Rock,
  • 44:52Chris Brown? You say?
  • 44:53Well actually it's this little blob right
  • 44:55here that you can't even see anything.
  • 44:58It's so small, so I'm going to
  • 45:00blow it up in this inset,
  • 45:02but here the arbitrary units were on
  • 45:04a different scale. It's so small.
  • 45:06So basically all of these trajectories
  • 45:08shrivel up into into nothing, so when when,
  • 45:10when trajectory length shrink,
  • 45:12that suggests that the ensemble
  • 45:13is either less dynamic,
  • 45:14changing less or changing less quickly.
  • 45:17So. The dynamics of the of
  • 45:20amygdala neurons are blunted
  • 45:22when we knocked down or Tencent.
  • 45:27OK, so Chris bring out the New York Times
  • 45:30and Gene in specifically the PDT tibial.
  • 45:33A population reduces decoding accuracy
  • 45:35of behavior from feeling relativity,
  • 45:37so control animals.
  • 45:38Once the Q comes on, it's very clear
  • 45:41like what what trial type it was.
  • 45:45However, if we do this with crisper
  • 45:47animals and this is, you know,
  • 45:49training with controls testing controls,
  • 45:51you know different different
  • 45:52training and testing of course.
  • 45:54But from the same group.
  • 45:58If we train and test on crisper animals,
  • 46:01they perform significantly less well,
  • 46:03but still are able to code above chance.
  • 46:06Importantly, if we train the decoder
  • 46:08with data from the control and then
  • 46:11test on crisper or train with CRISPER
  • 46:14data and then test on the control data,
  • 46:16we get chance essentially.
  • 46:19Suggesting that crisper and control
  • 46:21animals are using different coding rules
  • 46:25to determine what's going on. OK Anna.
  • 46:28Nice ball in my lab who has has done a
  • 46:31lot of work on another project relating
  • 46:33to a real time Alpha tracker which I
  • 46:36don't have time to talk about right now.
  • 46:39Explored this for analyzing,
  • 46:41analyzing BLTS with more regularity
  • 46:43here and so this is pretty simple.
  • 46:45We're looking at reward trials
  • 46:46and shock trials.
  • 46:47Should be simple, right?
  • 46:49Just punishment and reward,
  • 46:50but yet, even with the responses
  • 46:52that we get from punishment reward,
  • 46:54there are different responses.
  • 46:56For example in with shock conditioning.
  • 46:58You could either get freezing a passive,
  • 47:00you know coping state,
  • 47:01or you can get darting,
  • 47:03which might be thought of as
  • 47:05a more active state.
  • 47:07Similarly,
  • 47:07this is true for reward trials
  • 47:09could be hanging out,
  • 47:11or you can come and actively
  • 47:13approach the port.
  • 47:16So what we found here is that the
  • 47:19neural responses to the rewards,
  • 47:22yes, or the shocks, yes.
  • 47:24For each type each behavioral.
  • 47:29Type of response is is blunted overall,
  • 47:32but specific to each type,
  • 47:33and if we quantify this,
  • 47:35what you can see.
  • 47:37Is that there's a greater impact of
  • 47:41Christopher ING out near attention
  • 47:44in these low motivation States and
  • 47:48or active avoidance states here.
  • 47:51OK, so back to the outline.
  • 47:54Where does circuits you know encoding
  • 47:56positive and negative balance diverge?
  • 47:58The basil lateral make list
  • 48:00one of these prime targets,
  • 48:02but now you know what criteria to look for.
  • 48:06What are the local interactions?
  • 48:08There are absolutely lots of microcircuit
  • 48:11interactions of inhibition and or
  • 48:13facilitation locally at the level of the
  • 48:15lay of these functionally distinct circuits.
  • 48:18And now we're beginning to
  • 48:20explore how narrow modulation.
  • 48:22Can play a role in balance assignment
  • 48:25specially in these sort of initial trials,
  • 48:28and so I don't really think
  • 48:30neuromodulatory systems or neuropeptides
  • 48:32will contribute within trial per say,
  • 48:34but between trials, certainly.
  • 48:38OK, so where are we now?
  • 48:40What?
  • 48:41What can we take away?
  • 48:43What's the takeaway message from a,
  • 48:46you know therapeutic standpoint here.
  • 48:48Well, just that identifying
  • 48:50differentially expressed genes and
  • 48:52functionally characterized functionally
  • 48:53distinct circuits can be leveraged
  • 48:55for selective control of neuronal population.
  • 48:58So instead of a shooting in the dark,
  • 49:01like trial and error
  • 49:03strategy for drug discovery,
  • 49:05why don't we use a circuit based?
  • 49:08Just drug discovery.
  • 49:10Find small molecule targets on circuit
  • 49:14components with known function.
  • 49:16So again, this is just bringing things back.
  • 49:20We've in the amygdala,
  • 49:21Howley, Praneeth, Ambrian,
  • 49:23Jake Olson are contributing to understanding
  • 49:26the role of Neuromodulatory gang.
  • 49:29OK,
  • 49:30so why should you even care about all this?
  • 49:34How does this ultimately matter for people?
  • 49:37Well,
  • 49:37despite the prevalence of anxiety disorders
  • 49:40and other mental health disorders.
  • 49:43Current treatments are not effective
  • 49:45for the entire patient population,
  • 49:46or at least have a lot of
  • 49:49undesirable side effects.
  • 49:51So how do we get to where we are now?
  • 49:54From you know where we are now
  • 49:55with with these sort of no no
  • 49:57treatment is perfect that works.
  • 49:59There's no such thing as a team that works
  • 50:01for everyone that is free of side effects.
  • 50:03How do we get from that to something
  • 50:05where that is possible with every
  • 50:07single individual will find a treatment
  • 50:09that is effective for them that
  • 50:10lasts and doesn't have side effects?
  • 50:12Sounds like.
  • 50:13You know, far away,
  • 50:15how do we get there?
  • 50:17Well,
  • 50:17we have to change our current approach,
  • 50:20which currently involves testing
  • 50:22drugs that act nonspecifically
  • 50:23throughout the entire brain and body,
  • 50:26and doing so in a sort of
  • 50:28again trial and error way.
  • 50:30I think another huge problem with
  • 50:33the way that we're tackling this.
  • 50:35This challenge is poor
  • 50:37disease classification,
  • 50:38poor understanding of what actually
  • 50:40gives rise to the disease,
  • 50:42comorbidity that we see.
  • 50:44We currently rely on symptom
  • 50:46based categorical definitions of
  • 50:48mental illness and this is just
  • 50:49a barrier to a true
  • 50:50biological understanding of psychiatric
  • 50:52diseases as researchers are sort of
  • 50:55discouraged from exploring comorbid
  • 50:56Lee Express symptoms when they may
  • 50:59in fact be meaningful clues that
  • 51:01guide us to distinct ideologies
  • 51:03that call for different treatments.
  • 51:05All these issues route back to the
  • 51:08inadequate understanding that we
  • 51:10currently have of how the brain
  • 51:12even gives rise to behavior.
  • 51:14Super BASIC, but fortunately we
  • 51:16now have the ability to identify
  • 51:18specific neuronal or synaptic targets
  • 51:21and test their role in behavior.
  • 51:23That's what modern neuroscience
  • 51:25technologies will allow,
  • 51:26and perhaps high rates of
  • 51:28comorbidity can be explained by
  • 51:31common neural circuit perturbations.
  • 51:33And then to translate our basic
  • 51:36insights into a better type of therapy,
  • 51:38we will need to apply the knowledge
  • 51:40we gained informed therapeutic
  • 51:42development and take advantage
  • 51:44of we know about plasticity,
  • 51:46resilience and the new adaptations
  • 51:47that occur with stress and
  • 51:49basically focus on a neural circuit
  • 51:51based therapeutic development.
  • 51:53It may be pharmacological,
  • 51:54it may not be.
  • 51:58OK, so regardless of if you're
  • 52:00listening to this talk with,
  • 52:02you know translation here
  • 52:04or basic science here.
  • 52:05I guess I would say from a
  • 52:08basic science perspective.
  • 52:10If we can't understand simple
  • 52:11circuits like those in the amygdala,
  • 52:14and simple questions like,
  • 52:15how do we tell if something is good or bad?
  • 52:19How are we going to understand more complex
  • 52:21circuits and more complex questions and
  • 52:23then from a translational perspective,
  • 52:25the amygdala has been so well
  • 52:27conserved across evolution,
  • 52:29and you know,
  • 52:29a lot of these circuits are still
  • 52:32consistent in species that have
  • 52:34scarcely changed for 70 million years.
  • 52:36This this gives this lens a lot of hope,
  • 52:39that the.
  • 52:40The changes that we see in in mice
  • 52:42will also have relevance to humans,
  • 52:45given the common homology.
  • 52:47OK, so with that I will thank
  • 52:49all the members of my laboratory
  • 52:52and you for your attention.
  • 52:54My collaborators,
  • 52:55my funding sources,
  • 52:56and thanks for listening and I believe
  • 52:59I will take some questions right now.
  • 53:03Thanks.
  • 53:09Thank you very much everyone
  • 53:12for joining us for the talk.
  • 53:14Thank you Kate for a great talk.
  • 53:17I believe that we are going to have to wait
  • 53:22a few moments for Doctor Tide to join us.
  • 53:26She is in California and is on a delay.
  • 53:29I do see that there is one message in
  • 53:33the chat from Doctor Clayton Barnes.
  • 53:36But if you have any other questions,
  • 53:38please add them in.
  • 53:40And Trisha, if you can,
  • 53:42let me know when Doctor Ty joins us.
  • 53:45We will switch to the question
  • 53:47and answer portion of the talk.
  • 53:49And there are a couple of
  • 53:52questions for you in the chat.
  • 53:54If I can read them out to you, I will.
  • 53:58I will start out by has the KAYTIE has
  • 54:00that I lab thought about developing
  • 54:03a dynamical systems model of the
  • 54:05interactions between projection
  • 54:07specific subpopulations in the VLA.
  • 54:12And you're muted.
  • 54:14Thank you, great question.
  • 54:15I think we've approached looking at
  • 54:17predicted dynamical models in other systems.
  • 54:19We have not yet begun to build one
  • 54:21in the DLA, but we absolutely should.
  • 54:23I think you're absolutely right.
  • 54:25Like you know there are these
  • 54:26projections that exist.
  • 54:27There are neurons that have hard wiring,
  • 54:29but you can think of that as the
  • 54:31roads that exist and we want
  • 54:33to think about the traffic.
  • 54:35So coming to that is something we want to do.
  • 54:38We started to do that in the prefrontal
  • 54:40cortex and you know we're able to
  • 54:42predict a lot of different people.
  • 54:44Cortex VLA data is a little bit different.
  • 54:47Not to say that we couldn't do it, but.
  • 54:50We haven't done it yet,
  • 54:51but we we absolutely
  • 54:52should. Thanks Kate,
  • 54:54the next question is about the
  • 54:56recruitment of the central amygdala
  • 54:59projections during rewarding conditions.
  • 55:01It looks like it might be a check
  • 55:04on reward behaviors are there?
  • 55:07Is there evidence of deficits
  • 55:09in central amygdala projections
  • 55:11in unchecked reward behaviors,
  • 55:13like an addiction?
  • 55:15Well, interesting. Interesting, you know.
  • 55:18So first the projections to Central
  • 55:21central itself is super complicated
  • 55:23and I think of it as a ministrator.
  • 55:25There's so many different mirror
  • 55:27peptidergic neurons there,
  • 55:28and we found a lot of different
  • 55:31roles from central amygdala that are,
  • 55:33you know, widely varying from, you know,
  • 55:36aversive behavior to social behavior
  • 55:37and other other components, but.
  • 55:41Or the specific projection from
  • 55:43the PLA to the central limit,
  • 55:45which is predominantly coding for a version,
  • 55:48but it's not exclusively doing so.
  • 55:50We haven't seen that in.
  • 55:52We haven't looked in addiction
  • 55:54to see if it is,
  • 55:56it is specifically modified in terms
  • 55:58of firing rates we have looked.
  • 56:05Look and actually this is something I
  • 56:07didn't talk about in this particular talk.
  • 56:09It's pretty new data,
  • 56:11but with social isolation,
  • 56:12a stress in this can potentiate the minerals
  • 56:14and correlate's with increased drinking.
  • 56:16So when we stimulate the light
  • 56:18inputs to the prefrontal cortex,
  • 56:20we now find that this this is sufficient
  • 56:22to drive alcohol drinking as opposed
  • 56:24to water in a 2 bottle choice.
  • 56:26So that's something, but it's,
  • 56:28you know, still super preliminary
  • 56:29and thinking about this particular
  • 56:31projection from DLA decentral,
  • 56:32we haven't studied that one.
  • 56:35In in the in the context of addiction,
  • 56:38it is sort of this projection.
  • 56:40These neurons have the capacity to sort of.
  • 56:43Ubiquitously inhibit
  • 56:49birthday very broadly, and had,
  • 56:50of course also recruit another local network,
  • 56:52but the local feedforward inhibition
  • 56:54coming from the latest central England
  • 56:56is is much more potent than other
  • 56:58other productions that we've studied.
  • 56:59So I guess I don't know the
  • 57:01answer to that question either.
  • 57:03That's a great question.
  • 57:04We haven't done that specific experiment.
  • 57:07Next question is sort of related to that.
  • 57:10Do you see individual differences among.
  • 57:13Subjects in the balance
  • 57:15between the two circuits.
  • 57:16Have you been able to match that in
  • 57:19any way to susceptible ability versus
  • 57:22resilience for stress disorders?
  • 57:23That's a great question.
  • 57:25That's great, but so we definitely
  • 57:27do see individual variability.
  • 57:29We have not systematically correlated
  • 57:31that with pre-existing behavioral.
  • 57:33Features, but we should do that.
  • 57:35That's a very good expansion
  • 57:37that's I love that idea. The next
  • 57:40question is more clinical,
  • 57:41so I will actually ask John Crystal to
  • 57:44jump in and help or ask other clinicians
  • 57:47in the audience to help with K.
  • 57:49You may have some ideas.
  • 57:51So the question is help me translate
  • 57:53this into clinical practice of patient
  • 57:55presents with generalized anxiety disorder.
  • 57:58How do you know whether the treatment of
  • 58:00choice is pharmacology psychoanalysis,
  • 58:02cognitive therapy, behavioral therapy?
  • 58:03Learning theory,
  • 58:04or a combination of all of these approaches,
  • 58:07with the theories that you put forward
  • 58:10around looking at a circuit analysis help to
  • 58:13make those kinds of decisions I know not now,
  • 58:16but perhaps in the future,
  • 58:18and I will recruit John to
  • 58:20help back you up on this one.
  • 58:23Yeah, it's John.
  • 58:24Do you want to start her?
  • 58:26I
  • 58:26have go ahead, go ahead once you start.
  • 58:29I mean it's so some of this work.
  • 58:32I'm actually referring to colleagues work so.
  • 58:35I'm thinking of Amy Atkin, for example.
  • 58:37We've had a lot of interesting conversy
  • 58:40thinking about different types of anxiety,
  • 58:42different types of you know psychiatric
  • 58:45conditions where you're you're put into
  • 58:47buckets with some symptoms, but that's not.
  • 58:53Basically, with the biological perturbations,
  • 58:55so using resting state,
  • 58:57fMRI is is something that a meeting has
  • 59:00been able to do to sort of predict,
  • 59:02you know what treatment strategy
  • 59:04would be most successful with
  • 59:05this particular individual.
  • 59:07I'm a big proponent of individual
  • 59:09individualized medicine.
  • 59:10I understand us residency.
  • 59:11fMRI might not be, you know.
  • 59:13We need something that
  • 59:15could be more affordable,
  • 59:16more easily applicable to a broader
  • 59:18population that can be rapidly used,
  • 59:19so I understand that's sort of,
  • 59:21you know, a proof of principle,
  • 59:23maybe not the immediate thing that
  • 59:24we would put right into practice,
  • 59:26but that's sort of what I would
  • 59:28love to see happen in the future
  • 59:30of mental health treatment.
  • 59:31Go ahead, John.
  • 59:33Well first K, What an amazing awesome,
  • 59:37fantastic, wonderful, stupendous,
  • 59:38exceptional presentation.
  • 59:39It was just so enlightening.
  • 59:42And and and such a great example
  • 59:45of the way you approach this work.
  • 59:50And and because it was so fantastic,
  • 59:52it's about 10 years of head of
  • 59:55anything that we're able to to do
  • 59:57in the clinic while you were away.
  • 60:00The thought of we,
  • 01:00:01we got into a little discussion about how,
  • 01:00:04how could we even think about
  • 01:00:06developing biomarkers of new retention
  • 01:00:07signaling in the human brain,
  • 01:00:09and which would be kind of the
  • 01:00:11first step in guiding a precision
  • 01:00:13medicine approach.
  • 01:00:14But we're all in with you on
  • 01:00:17on the idea that.
  • 01:00:19That if we we treat illnesses,
  • 01:00:22we treat pathology in other areas
  • 01:00:25of medicine and we treat people in
  • 01:00:28in psychiatry and we need to be able
  • 01:00:32to incorporate an understanding of
  • 01:00:34the pathology that people actually
  • 01:00:36have if we want to get better
  • 01:00:39and more specific treatments.
  • 01:00:41So that's that's clearly a
  • 01:00:43critical step in the pathway.
  • 01:00:45So what a wonderful lecture
  • 01:00:47really appreciate it.
  • 01:00:49Thank you.
  • 01:00:49Yeah,
  • 01:00:50I mean I this also didn't make it
  • 01:00:52into the seminar because it's still.
  • 01:00:59Have collected so recently but we are.
  • 01:01:01We've now started using the
  • 01:01:02tensor from you lonely.
  • 01:01:04You along these lab created.
  • 01:01:05You know all of his tools work so well
  • 01:01:08and he created a new retention sensor
  • 01:01:10and so obviously you know I'm not
  • 01:01:13necessarily a proponent of, you know.
  • 01:01:15I think there's a lot of safety
  • 01:01:17testing that needs to be put in place.
  • 01:01:20You know long term effects of of using
  • 01:01:22viral or genetic tools in humans,
  • 01:01:24even though there's systemic administration
  • 01:01:26potentially possible long term effects.
  • 01:01:28I'm just having a transgene and creating
  • 01:01:30proteins needs to be something that is
  • 01:01:32dealt with a great amount of caution,
  • 01:01:35so I will make that big disclaimer.
  • 01:01:37Circle it underline highlight.
  • 01:01:38However, you know,
  • 01:01:39potentially you could see you know
  • 01:01:42this isn't this is one way that you
  • 01:01:45could be able to to sort of say what
  • 01:01:47is going on in terms of the dynamics
  • 01:01:50and so it offers some some window into
  • 01:01:52potentially using neurotransmitters.
  • 01:01:54Biomarker even this really needs
  • 01:01:55to be stressed out and approved.
  • 01:02:01Away from that, but that's sort of my long
  • 01:02:04term forward looking view. Thanks John.
  • 01:02:07I want to apologize that I haven't been
  • 01:02:09reading out the names of the questioners,
  • 01:02:11so I will try to start reading out the names
  • 01:02:14of the questioners as I asked the questions.
  • 01:02:17I also want to sort of echo Johns
  • 01:02:19phenomenal work. Phenomenal talk.
  • 01:02:20Thank you so much for being with us.
  • 01:02:23Kay Ann. I want to introduce you again
  • 01:02:25to Doctor Flynn's daughter, Sarah Flynn,
  • 01:02:27who's been able to join us today,
  • 01:02:29and it's really been a pleasure to have
  • 01:02:32a representative of the Flynn family.
  • 01:02:34Hi Sarah. Icera it's an honor.
  • 01:02:38So the next question is from Doctor Tech,
  • 01:02:41both the function and structure
  • 01:02:43of amygdala seem to be impaired
  • 01:02:45in subjects with schizophrenia.
  • 01:02:47Have you ever used,
  • 01:02:48or do you plan to use any models
  • 01:02:51of schizophrenia,
  • 01:02:53and in this preclinical work such
  • 01:02:55as phencyclidine administration
  • 01:02:56or some other way of getting it,
  • 01:02:59that that link?
  • 01:03:02I have not. I guess the short answer is no.
  • 01:03:05I have not done that,
  • 01:03:07but I think when I think about schizophrenia
  • 01:03:09and what what is really happening,
  • 01:03:11I guess the the way that I've
  • 01:03:14thought about the most is sort of a
  • 01:03:16computational framework, you know,
  • 01:03:18kind of drawing from like roles
  • 01:03:20and and oppression.
  • 01:03:22With Patricia Coleman,
  • 01:03:23rookies excuse me and thinking about just
  • 01:03:26how do you modulate signal to noise?
  • 01:03:28How do neuromodulators are near peptides?
  • 01:03:31Influence.
  • 01:03:32You know where you draw the
  • 01:03:34line for spike threshold,
  • 01:03:35so you know there's always going
  • 01:03:37to be some noise of inputs.
  • 01:03:38There's going to be some signal,
  • 01:03:40and one way that I think about this is.
  • 01:03:42Pattern completion there's
  • 01:03:43always going to be some noise,
  • 01:03:45and when there's more noise and.
  • 01:03:50No. You know membrane potentials are closer,
  • 01:03:53despite thresholds.
  • 01:03:54Then you might just get spiking
  • 01:03:56and therefore pattern completion,
  • 01:03:57and that's what the brain's
  • 01:03:58really good at doing.
  • 01:04:00This is not just limited Nicola.
  • 01:04:01I'm thinking of amygdala, hippocampus,
  • 01:04:03prefrontal cortex as a connected circuit,
  • 01:04:05but this is something this is sort
  • 01:04:06of the way I've been thinking about
  • 01:04:08how schizophrenia can can come
  • 01:04:10to be in the context of dopamine
  • 01:04:12and other neuropeptides as well.
  • 01:04:14But the signal to noise concept is really.
  • 01:04:17Gotten into the infected,
  • 01:04:18my brain and an I've been thinking
  • 01:04:20about a lot in that terms.
  • 01:04:22It makes a lot of intuitive sense
  • 01:04:24to me how you could get there.
  • 01:04:26So just just how hallucination is
  • 01:04:28constructed is fascinating to me,
  • 01:04:30but we haven't done those experiments.
  • 01:04:33Yeah, that that's an active area of
  • 01:04:36investigation in the in the department.
  • 01:04:39Jane Taylor and Phil Corlette are working
  • 01:04:42on models that really do sort of address
  • 01:04:46some of those behavioral aspects of.
  • 01:04:49Not necessarily pattern completion,
  • 01:04:50but I I like that idea of
  • 01:04:53signal to noise a lot.
  • 01:04:55So John Crystal asks in humans
  • 01:04:57emotions are quite differentiated.
  • 01:04:59So for example fear is
  • 01:05:01different from discussed,
  • 01:05:02which of course we do have discussed
  • 01:05:04circuits in the brain stem of mice that
  • 01:05:08are differentiated from fear circuits.
  • 01:05:10There different from frustration,
  • 01:05:11which of course we can distinguish
  • 01:05:14behaviourally in humans.
  • 01:05:15This higher level differentiation of
  • 01:05:17emotional states seems to involve insula.
  • 01:05:19And have you thought about how
  • 01:05:21the insula might fit in with
  • 01:05:22the story that you told today?
  • 01:05:25That's an excellent question.
  • 01:05:26I am not presently working on the insulin,
  • 01:05:28but my first postdoc from the lab on a
  • 01:05:31Baylor who now has her own lab in Bordeaux,
  • 01:05:34has focused a lot on the
  • 01:05:36insula and amygdala circuitry,
  • 01:05:37so I guess I would encourage you to
  • 01:05:40check out her work, but absolutely,
  • 01:05:42it's in its intricately involved in
  • 01:05:44reciprocally connected with a lot
  • 01:05:46of the different sort of, you know,
  • 01:05:47the emotional triad circuitry, I think.
  • 01:05:49Also Nadine Gogol's work in the insula is.
  • 01:05:56But I haven't done that, but there is
  • 01:05:59beautiful work being done by a number
  • 01:06:02of rising stars in the
  • 01:06:04field. And Mark Anderman also has
  • 01:06:06some market as well. Yes, absolutely.
  • 01:06:08So another question from the chat allcare
  • 01:06:11asks or says behavioral activation
  • 01:06:13is 1 therapeutic form of activation
  • 01:06:16of positive valence neurons using
  • 01:06:18psychotherapy which is used to treat
  • 01:06:20negative balance disorders like depression.
  • 01:06:22And he asks, you might,
  • 01:06:24if you think this might rely on
  • 01:06:27the competition between the BLA.
  • 01:06:29Nucleus incumbents in the BL.
  • 01:06:31A central amygdala circuits and I would add.
  • 01:06:33If so, how might you measure that in
  • 01:06:35a person who is undergoing therapy?
  • 01:06:38Oh, oh,
  • 01:06:38the second part of your question.
  • 01:06:40I'm going to come back to that that in a
  • 01:06:43moment I think this is a great question.
  • 01:06:46It it actually brings us back to Harkins
  • 01:06:48back to a few questions ago regarding
  • 01:06:50clinical treatment, and I think.
  • 01:06:53The reality is. That that.
  • 01:06:58I've been told that pharmacological
  • 01:07:00treatment, in my opinion not specific,
  • 01:07:02and so this is. It's not.
  • 01:07:03It's never going to be maximally
  • 01:07:05effective in my opinion on its own.
  • 01:07:07I think pharmacological treatments are
  • 01:07:09always going to be better in combination with
  • 01:07:11some form of cognitive behavioral therapy,
  • 01:07:13and I'm using that a very
  • 01:07:14very broad term and again,
  • 01:07:16of course I'm not a medical professional
  • 01:07:18and not qualified to give medical advice,
  • 01:07:20but my perception and my understanding
  • 01:07:22of the circuitry would suggest this dual
  • 01:07:24approach would be what is necessary.
  • 01:07:26I do think it's very likely that there's
  • 01:07:28going to be competition between circuits.
  • 01:07:30There's going to be interaction because both.
  • 01:07:33BLANECNBLICE central amygdala
  • 01:07:34neurons are not only rip,
  • 01:07:36typically connected model synaptically
  • 01:07:38with excitatory connections,
  • 01:07:40but also through feedforward connections
  • 01:07:42and that dual connectivity allows a
  • 01:07:45lot of opportunity for regulation of
  • 01:07:47the net strength of connections between
  • 01:07:50those two populations of neurons,
  • 01:07:52and so we do see a lot of plus.
  • 01:08:00I did not object into that study today,
  • 01:08:03but but we have seen that and simple
  • 01:08:06manipulations, food deprivation,
  • 01:08:07social isolation of these things
  • 01:08:09will change the balance of, you know,
  • 01:08:11the the plasticity between these two
  • 01:08:13populations of neurons in their ability to
  • 01:08:16affect each other in a very qualitative
  • 01:08:18way where you know it can become from a
  • 01:08:21suppression to a facilitation based on,
  • 01:08:23for example, food deprivation.
  • 01:08:25And so this is something this is.
  • 01:08:27Gwendolyn calhouns.
  • 01:08:29A study that's that's been
  • 01:08:30bar by archive for awhile.
  • 01:08:31But yeah, I think I think that's
  • 01:08:33kind of how I would imagine
  • 01:08:35this circuitry playing into it,
  • 01:08:36but it's going to be broader than that.
  • 01:08:38Of course, you know,
  • 01:08:39I don't think this is the end all and be
  • 01:08:42all of Dylan's processing by any means.
  • 01:08:44I don't mean to imply that.
  • 01:08:49And a representative of how the brain
  • 01:08:51will apply biological implementational
  • 01:08:52strategies to solve this problem.
  • 01:08:54And I think we'll see that motif
  • 01:08:56appear again and again in different in
  • 01:08:59different circuits as well as the glow.
  • 01:09:05Therefore.
  • 01:09:07That's all the questions from the chat,
  • 01:09:09except for some comments to
  • 01:09:11say brilliant presentation.
  • 01:09:12Does anyone else have any
  • 01:09:13questions they'd like to ask live?
  • 01:09:19Well, if not thank you so much Kay,
  • 01:09:22for being with us with a 3 hour
  • 01:09:25difference in time early early on
  • 01:09:27the West Coast it was a pleasure to
  • 01:09:30be able to hear about your work and
  • 01:09:33particularly to have our audience that
  • 01:09:36involves everything from a molecule
  • 01:09:38to a patient to to be able to stab.
  • 01:09:41Your synthesis has been really helpful,
  • 01:09:43so thanks so much everyone in
  • 01:09:45Marina for hosting and having me.
  • 01:09:50Wonderful God care.