Mind Brain Lecture 2016: with Alan Alda, Eric Kandel and Jim Simons

hi everybody as always I am really delighted to welcome you all on behalf of the Department of neurobiology and behavior to the annual Sports mind brain

lecture Series this year I'm really thrilled to bring us all together for a special celebration for the 20th year of the warts mindbrain lecture and today we

get to host a a trio of experts in their fields for a Roundtable discussion on the broad subject of melding the mind

and math brain science past and future for those of you who don't regularly come to this event although you should let me remind you what we are

celebrating here so for 20 years the sworts foundation has sponsored the mind brain lecture series it's a public lecture series that is intended for a

general audience and to bring together the Stony Brook University Community with some of the leaders in the field of Neuroscience to keep us all up to dat

with studies of how the brain works in order to produce the full repertoire of our behaviors the tradition of this Gathering was begun in 1997 by Jerry

Schwartz the founder of symbol Technologies and inventor of the barcode reader and it's brought a distinguished array of systems and computational

neuroscientists to come visit with all of us here at Stony Brook it's been a spectacular 20 years and this year to celebrate the foundation's generosity we have a

special treat and it's a different Forum from the past years we have three individuals ex each experts in their field and each so famous that they actually don't need um an introduction

uh and they're going to respond to the questions that many of you have already submitted uh VI via Twitter and the web and we thank you for those on the subject of how brain science and math

have been are and and will be converging to give us new insights into how the brain works our super Trio includes Eric candell who is winner of the Nobel Prize

in physiology or medicine for His Brilliant work in the so Neuroscience of memory and Jim Simons an astonishing mathematician the previous chair of

mathematics here at Stony Brook and a major philanthropist and third really the moderator of the discussion is Alan Alder who many of you know is a renowned

actor including all 251 episodes of mash also in West Wing most recently in Blacklist and movies including The Aviator everybody says I love you my

personal favorite and most recently Bridge of spies from this list of credits and more you may ask why Allan to keep these scientists on track

there's a really important reason that Allan has been engaged actually in putting together today's event right from the get-go while Allan has continued his career in performance as

an actor a writer and a director I don't know how he does it all he has also dedicated himself for the last decade or so um to working with Scientists in

particular with neuroscientists to get us to do a better job at Comm communicating the excitement of scientific discovery to all of you he's a professor here at Stony Brook we're

all very lucky leading the AL the center for communicating science and he's also the recent recipient of the National Academy of Sciences 2016 Public Welfare

medal for his contributions to communicating science a warm welcome please for Eric tandel Alan Alo Jim Simon

thank [Applause] you thank you it's so great to be in the same room and on the same stage with the

great Eric Handel and the great Jim Simons it's is going to be a real pleasure I notice on the back wall here it says melding the mind and math brain

science past and future I I wonder Eric if if you would just give us a little overview of what

brain science started as or where it where it was let's say 50 years or so ago and how we got to where we are

now uh well when I started in brain science which was

1957 before many of you were born um we had a very good understanding how of how individual nerve cells work and

how they communicate with one another uh we had an idea how um certain behavioral functions occurred in the brain because

of lesions that neurologists had detected um and that was really the basis of our understanding our approach

to complex Behavior was very primitive um brain scientists were not comfortable studying behavior and Bon Lodge did very

little of it but soon thereafter cognitive psychology people who were studying behavior in rather sophisticated ways sort of elaborating what Freud had

done but in much more empirical uh ways uh became interested in brain science

and in about 1965 a merger occurred between cognitive psychology and brain science which really gave R to a new science of mind and that received a

tremendous impetus a tremendous spur from molecular biology which is coming along because before that most biologists were not interested in the brain why is that because the anatomy

was boring and understanding current flow was beyond most biologists you had to know MMS law and stuff like that people like Jim science do that stuff but most of the other people didn't know

that uh but once molecular biology came along and you realize that certain molecules were not only found in the brain but also found in the liver you saw the

universality of biological processes and that brought them into the game and that has had a tremendous impact and with that also with time came Imaging so that in experimental animals and even more

important in people you could begin to see what happens when we have a conversation when you think about something when you do something so it's brought brain science a long way I mean we're very far from understanding the

brain I would say we're maybe 20% there in an optimistic moment uh but we have a very good start and we're moving at a reasonable

clip you've reached the point I take it now just from my general reading I get the impression that you've gone from an

examination of individual cells to considering cell cells as they interact by the hundreds or

thousands is that the point where when you when brain science started to explore that is that the point where you needed you must have computational

analysis you must have a more sophisticated kind of math yes uh you actually need math even

for understanding how single cells work why would that be uh well in 1952 two British scientists by the name

of hodkin and Huxley uh developed what is called theic hypothesis they explain how the action potential is generated and how the

resting potential is generated okay now I have to stop you right there so I can understand what you say after this okay so they studied how the action potential is generated somebody's nodding her head

thank God somebody else needs it besides I'm sorry for forgive me okay no mo many many people here know exactly what Eric said but some people are at my stage and

we want to we're curious we want to know so the action potential is what a current down a a neuron it's electrical current it's an electrical signal that

is propagated down the neuron so let me begin a nerve cell has really several elements to it it has what are called D rites which are processes to come off

the main element called the cell body that has a nucleus has dendrites and that's where other cells connect to it the cell body then gives rise to a long

structure called the axon that ends in terminals they contact the neighboring cell um so the way information propagates from the cell body to the

terminals is by means of a signal called the action potential right and that's an electrical signal that's self-propagating and the mechanism of that propagation

was worked out by two major sign scientists called hotchkin and Huxley and Huxley was a mathematician and the last of their four papers is essentially a mathematical

exploration explaining the nature of the action potential that was really the first important mathematical contribution to neuroscience and it was of extraordinary importance so even

though it was only one cell that we're talking about as I understand it is this correct the the way the current get goes down the Axon

is because of a whole lot of things happening in the membrane atoms going out through Gates and other atoms coming in through Gates

go down okay so at rest the axon has what is called a resting potential it's minus 60

molts uh and that's due to the flow of pottassium ions and it used to be thoughts that what happens with the action potential is that the resting potential is

erased and one thing that hinx able to show by directly recording the action potential is it not only wipes out the resting potential but it overshoots and that's

because another class of ions sodium ions move from outside to in and they worked all that out and then hotchkin

uh sort of stepped to the side and Huxley worked out mathematical equations that explain explained the resting potential due to potassium sodium coming

in generating the action potential and repolarization how are you doing no it's too difficult to follow there are electrical signals in the

nervous system and we know how they work there you go thank you now you're talking my language okay so so Jim take our word for

it in the ner system that's the least of our problems I should say one other thing oh sure um what also was was worked out at that time and it was really a

controversy is nerve cells communicate with other nerve cells through a juncture called synapses and that works through the release of a chemical substance called

chemical transmitters that also was worked out and various chemical transmitters in the nervous system like aetl choline glutamate Gaba they were begin begin to be characterized in that

period now we have an excellent understanding of how nerve cells function how they communicate with one another always little subtleties of the answer but by and large we understand that we want to understand more complex

functions and that's of course where mathematical treatments come in Jim what what kind of assistance can a a

mathematician give to to uh an experiment in brain science it is it that there is so many things

going on that you need you need to be able to track them mathematically well there are a lot of things going on the brain has roughly uh

somewhere around 100 billion neurons that's about the same number of stars as there are in our galaxy and that's a lot of things to keep track of

you know 100 billion is not a small number and uh and they're connected by synapses and there's a lot more of those

because many nerves are connected to a lot of other nerves and SOA synapses are are hundreds of billions I don't know maybe a trillion trillion could that be

a trillion anyway so there's a lot of stuff to keep track of and going on at the same time not every neuron is

firing every second of course but uh this traffic that's that's that's going on all throughout the brain uh while while we're awake and to some extent

even while we're asleep so if you want to analyze traffic you you know it's it's kind of a mathematical problem problem right from right from the get-go

now there are certain uh helps that mathematics can bring to bear which is I would say

infrastructure assistance so for example uh I mentioned this to you the other day we were chatting uh we can

record neuronal activity uh by putting probes into let's say a mouse's brain electrical probes

which will which will signal when a when a neuron is is firing and a typical probe might have 10 sensors as it goes down this little teeny spine that goes

into the the brain and I don't even think it hurts the mouse actually so anyway I watched a brain operation and the doctor was putting his finger on the brain of the patient saying where do you

feel this in your body she didn't feel it in her brain apparently the brain doesn't well she' been draking at the time hadn't she no no she would say I oh I feel that in my big toe he said okay

you'll need that we won't cut that part out but so I was just confirming that the mouse probably doesn't feel anything yeah I think I think the mouse doesn't feel it but in any event whether he

feels it or he doesn't feel it or she whatever the sex of the mouse might be uh they put on put down you want to

understand neuron firing in in uh in a multiplicity of places so you put down maybe 20 of these things spines and each

one will has 10 detectors that's let's say 200 things that you're going to be measuring so you start recording all

this activity and well signals from here and signals from there but they're very difficult to tease apart two neurons might be right next to each other am I

listening recording this one or am I recording that one it is this the same neuron firing twice in a row or is it one a little bit nearer that that

creates a a statistical and mathematical problem is there a good algorithm for separating it's called Uh Spike sorting

and a spike being a signal yeah Spike on the traction potential every action potential gives a spike uh as the electrical signal signal is generated so

there's it's a very difficult problem to sort these spikes and uh mathematicians have come along and come up with uh

better and better algorithms for doing Spike sorting I think we're sorting some people in our foundation who I think now have the very best algorithm for Spike

sorting and uh I suppose better ones will come along so that's a way that mathematics is not going to learn it's not going to teach you biology but it's

not even going to model biology but it's going to allow biologists neuroscientists to see what's going on much better than they could have seen without mathematics do they have a

trouble communicating with each other does the mathematician readily understand what the brain scientist understands and vice versa does the brain scientist understand how best to

use the mathematical modeling for instance well in this case the brain scientist wants to see the spikes sorted and then he or she is going to do their

their own work but typical people who do this are the guys in our group know a fair amount of Neuroscience so so they they can have an intelligent conversation with the experimentalists

with whom they're working to develop this uh this algorithm but it it's uh this is this is U as I said infastructure stuff on the other hand if

you want to do Dynamic modeling of uh uh neurons in a in a in a different way uh mathematical models are

going to have to be developed to uh try to explain and interpret uh how how information

is being processed in the brain for example Eric learned a lot about memory I think that's perhaps what you won your your prize for uh so memories are

encoded some in a part of the brain which is the hippocampus I believe but how is it encoded what what what what is the

what's going on there H how how are different memories encoded and how do we retrieve them very fast we re we retrieve a memory very fast and uh so it

has to be compressed somehow and encoded and what that mechanism is and what the mathematics is of the of the compression is uh is not understood but it is going

to take some mathematics I think toh dope that out do you agree with that I completely agree with it in the last several weeks we've made a enormous

progress let me uh talk to that but before I I begin on memory let me make a general appointment which continues the theme that Jim is developing uh with the

exception of Hod and Huxley who collaborated very effectively you know both of them were biologists but one was also mathematician and developed this powerful model uh model building in the

1950s and 1960s uh was not very useful to brain scientists because the models were built out of speculation

not because there really was a lot of biological data available and the models didn't attempt to make predictions that would allow the

model to be falsified that is a new era that emerged really in the last 15 20 years in which very much as Jim told you biologists and mathematicians work

together understand each other's Mission and influence one another and the purpose of the model is to explain how things work and make predictions is about future events or

future kinds of things you should look for and in searching for that you can either strengthen the model or you can falsify let me say about progress in memory

storage uh we've learned within the last year what first of all a major class of memories what you think of memory a memory for people places and objects is

stored in the region of the brain called the hippocampus if you remember this patient hm who uh didn't remember from one day to another what was happening to him it's

because he had lesions in the hippocampus in both sides uh we now know and we can label in the brain that when you learn something

for example you learn a particular position in space um a group of cells in the campus becomes active and we can label those cells and then we can ask

the question if those cells are active when you learn learn something what happens when you recall that memory later on is it the same population of cells

that active and we have labels we can put on those cells and we can see it's exactly the same population that is active when you

recall it you can now do something very interesting you can label those cells with something called Channel Rod opsin

which is a an iron Channel a mar that allows you to activate those cells by simply Shining Light onto that region so you can activate the cells

involved in memory storage and produce a false memory when you say a false memory you mean something that never happened or it just makes you remember something that happened no something that never

happens so I learned something in this particular space yeah okay and those cells are active now if I move to that next space those cells are not active active but if I

artificially activate those cells that animals thinks it had been in the space before and remembers it so you can create false memories so we're now beginning to understand manipulations which are both beneficial for our

understanding but also could be potentially dangers of misused that really quite profound of how memory works and how we can move it around and all of these things become quite

sophisticated we remember will require more model building and so the interaction between you know computational neurosciences and brain science is

absolutely standard you know your department here every good department has in its uh faculty a significant group of

people that does computational NE signs you know in the um in the Renaissance a common dinner dinner table

uh game was to see how many things someone could remember and they would use what they called memory Mansions they rooms they would have a an

imaginary house or maybe a real house and they put the if they had to remember a 100 objects they put them in different parts of the house and then as they walk through the house they'd remember a

hundred things which they wouldn't be able to do without an aid like that are were they using memory cells I mean the play cells that that just uh we're just hearing so much about uh they may be

using play cells to help them do this by spacing it in different locations activating different play cells when you were thinking about the fact that my grandmother is in this room and my

mother-in-law is in that room their names right yes so one of the the the points that Allan is making uh one of

the interesting discoveries that emerged which we don't fully understand yet is that um the cells of theic campus in

code space may I Get Up Stand Up yes if you can so if you were look at my hippocampus right now you'd see that the

group of cells that fire when I'm here like that another group that fire when they when I'm here like that another group that fires when I'm here like that

and every time I come back to the same place those same cells would fire so this is really quite amazing and you can see if you can now control those cells artificially how you

could fool the animal into thinking that it's one space or another but it also raises a more profound question which theoretical people and empirical people are um

examining if in fact this is a major structure for memory storage how come representation of space

is so important to it why do you think anybody have an idea we have to be able to move around that's one reason but another thing he said you could be

able to move around with this space spatial understand is an argument that almost everything that you

remember consciously is in a context so we're going to remember this discussion among the three of us in the context of this Auditorium and you're going to remember

it if you remember anything about it and we don't urge this on you does anybody remember anything so far so I mean that's an interesting problem again this is a problem that

theoreticians and experimentalists so now let me ask you a question based on what you just said when I was talking to Jim mcau the memory researcher outstanding he he made a big point out

of the fact that you your chances of remembering something are greatly enhanced if there's an emotional context to the

event that you're going to remember any emotion doesn't have to be fear could be Joy exaltation disgust so the question is what does

that have to do with place um emotion is mediated by a structure called the amydala amydala mediates both positive and

negative emotion and has extensive connections with the hippocampus so that's that's that gives us this is another thing that people have

been able to do just recently by manipulating cells so you can an animal can learn something which is very painful and activates the part of the

amigdala which mediates unpleasant emotion and then you can trick the Animal by activating part of the amydala which is pleasant and have it respond

with pleasure to something that previously scared the hell out of it so in principle this might might be useful someday for treating post-traumatic stress disorder helping you overcome the

painful thing so it sounds like maybe you get help from both the place and and the emotion and the emotion yes well many things converge with powerful memories which is maybe why we all

remember exactly where we were when we had that strong emotion when Kennedy was shot or other giant events I I associate

that event for instance with getting out of the car and seeing the fall leaves on the ground because 15 seconds later my neighbor

told me about the assassination and probably often when you do see fall leaves underground you're brought back to that to that memory so there's a lot

of entry points there's a lot of entry points into memory any little collection of which can trig can trigger that memory and probably the more profound

and important the memory is the more entry points there are to it so uh you can recall it quickly I'm wondering about but I want to say something about these Place cells because I heard of an

experiment you know David tank at at Princeton so he told me he's a well-known neuroscientist and so Eric told you about play cells and how they

fire when you're in different places in the room or in your environment and they this was very recently discovered a

Nobel Prize was was given for this a year ago or two years ago um so what this fellow David tank did he said

okay I'm going to uh so what's a what's a place let's say it's a two-dimensional array of and it tells you where you are on the XY AIS in the room more or less

so he came up with a different two-dimensional domain altogether and it had to do with sound

frequency one dimension was the frequency was it a low frequency or a high frequency that's a one parameter family of things and the other was I

think the intensity of the sound was it loud or was it soft so okay it was a a loud C or was a soft uh B flat or

whatever it was so that's a two-dimensional array then he gave rats I think or mice

uh a way to uh put pressure on a like a joy stick or something and travel through this array if you pushed it here

and there You' get a loud a or or whatever it was different positions of this or different forces on this stick

would produce sounds in in the two this two dimensional array and it turned out that the same place cells were firing the same play cells that told you where

you were in a floor were telling you where you were in this two-dimensional array that was quite astounding it seemed to me I I think I got it pretty

right uh so the pl cells are used for more things than finding your way in the maze in this particular example yes yes so maybe they well whatever it is those

same play cells were were helping to guide the mouse or tell the mouse where he was in a different kind of two-dimensional all right so it's pretty

amazing you were you said something the other day that was so interesting it was related to all the things the changes the physical changes taking place in our

brains you talked about infants and how fast they're making how many synapses oh they're creating it seem like a

fantastically large here's a statistic that I learned few days ago a baby in the womb its brain is developing very rapidly it's highly developed it's not

completely developed it's highly developed when Bor already now I I told you how many neurons there are and how many synapses so at a certain point in

the baby's development synapses new synapses are being created at the rate of 40,000 per

second per second 40,000 per second and that is a true statistic told me by a woman who's an honest woman but then there's this thing where

they have to be pruned huh well there Eric knows more pruning go on pruning than I do how how when does pruning stop at a certain point uh there two points

before we get to pruning yes uh uh Jim made a very profound Point um I recently read up

on um competitive Sports in young people because it's really quite scary when you realize what happens in the National Football League to kids to

adults who play football they have brain concussions repeatedly and after a while they get severe brain injury and you realize that with kids this is also a

possibility that actually this occurs and until quite recently kids were encouraged to suck it up and go back and play some more even if they bunt their head very seriously so that can cause

really quite significant brain trauma which you want to avoid but similar if not more severe brain trauma can come from social deprivation so in this period when

you're forming all these synapses if you don't get affection from your parents if your parents pay no attention to you if worse if they abuse you

you have serious consequences for your brain in fact the hippocampus this area that's involved in brain damage is significantly smaller if you

come from a very financially impoverished home now one doesn't know whether this is lack of food or just the social pressure that a family is under but four

independent Studies have shown that if a child is brought up in a highly impoverished home its hippocampus is going to be substantially smaller

pruning you produce a lot of synapses because you want to make sure all cells appropriately interconnect with one another but at about puberty you begin

to have a peeling back a pruning of th synaptic connections and we were talking about this a very interesting Discovery

emerged just a week or two ago um it has been known that in schizophrenia uh and I think this is also thought to

be true for autism there is an excessive pruning of synaptic connections and one of the reasons schizophrenic people have difficulty particularly with their prefrontal cortex with certain cognitive

tasks is thought to be attributable to this excessive pruning one also knew that there are certain genes

that mutations in them are specifically correlated with schizophrenia and it turns out people have analyzed two of these very recently and see to see what

their function is and it turns out these genes are involved in pruning so the first time in schizophrenia that we've identified a gene with a specific function which is really significant

progress and it's interesting they turns out to be involved in pruning now what happens if instead of

um what if you what if you don't get enough pruning is there is there a disability asso assciated with that it could be autism autism some people think

there's not enough pruning that goes on at a certain stage then and then there's overload instead of underload and and that could cause uh that could cause you form inappropriate connections yes yeah

that's right so uh and and it's it's different I wonder if in the so-called idiot savant situation you have you have an excess of cells that can perform

certain functions but others that don't it's possible possible certainly possible which which which is my half-baked Theory and it it reminds me

that I wanted to ask you both i' I've heard of mathematicians working with brain scientists as uh theorists they're called often theorists what why does a

mathematician offer theory in what way does a mathematician offer theory that the brain scientist doesn't um they think more conceptual

terms the brand scientists do and they have you know a mathematical approach to explaining that uh so they bring a different set of

skills uh that biologists bi and lolog don't have now some biologists do have that but most biologists don't have that he's in a better way to explain that than I can

well well models of things are typically uh mathematical models uh my business for a while after I left pure mathematics was trying to model

financial markets uh and uh you develop ways of looking at the movement of stocks or Commodities or one thing or another and

you see mathematical patterns of one sort or another and you say okay well this is we can model the stock market uh with these

patterns uh and it sheds some light on what's what going on not not as much as I'd like to shed and what's going on but

uh but uh but it helps it it reduces the uncertainty of certain things so models are typically mathematical models and uh

you know uh Michael Faraday uh did most of the basic work in understanding of the interactions between electricity and

magnetism but he didn't know much math and it took the next guy

um ma Maxwell thank you now you can see what's happening to my head it took the next guy Maxwell James

Clark Maxwell to interpret what Faraday was doing with a real mathematical model namely an equation so so-called

Maxwell's equations so you you can think of Faraday was the experimentalist fooling around with gee look look what happens here when I turn up the magnetic intensity I get more current flowing gee

there seems to be things are going around in circles what whatever it was that he was develop he was showing so he was the experimentalist but he wasn't the model

builder far uh uh Maxwell was the guy who really uh built built the models and and similarly probably now far far

Maxwell might have been wrong uh you he wrote down these equations and then they really had to be tested out in the laboratory so to speak and say is is he

really right and the same thing will go on in biology where experimentalist will have some data he'll show a mathematically inclined person oh I think I can I think I can make a model

of this and they'll write down some equations or whatever it is and uh something in graph Theory or whatever branch of mathematics is going to be convenient and then I'll say well here's

my model and experimentals say good let's try it out let's see if it actually predicts what happens if it does great sometimes it does and you've

made progress sometimes it doesn't and well it's back to the drawing board and and that's the interaction that will that will take place I think for years

in biology as as we begin to understand these processes better and can and model them they'll be mathematical type models could you go into just a little bit for

my benefit so I can understand a little better than I do now what a mathematical model is you have the brain you have some understanding of it you want more

understanding what the model sounds to me like you're matching up elements of the brain that you're aware of you're

tracking them with some kind of um system of getting signals from them and you're attaching D you're making them data points and you're doing

mathematical manipulations that give us more information well I don't quite get how the model works well I'll give you a simple example of a model that could apply to

neuronal activity so um you could uh you know what a matrix

is it's an array of outside of being a movie I don't know you don't who knows what a matrix is oh okay we got enough Matrix you got enough you can talk to there's enough

Matrix knowledge out there so well a matrix is a big array of numbers sometimes it's squared has the same number of rows as it has as it has

columns and uh and the Matrix I'm about to describe is a square Matrix so I say okay I have all these neurons

uh well uh gosh 80 billion okay and some pairs are connected and and the connection has a has a Direction so I

say okay I have 100 billion columns and 100 billion rows and I want to fill in now a number

at each place in this Matrix well there'll be a number only if neuron I is connected to neuron J

there'll be a number moreover I can say oh I fires and hits J so it's a positive number it's going in this direction and

there's a particular strength in the synapse so I'll just write down a number that corresponds to the strength of neuron I going to neuron J now you'll

get this gigantic array of numbers most of them will be be zero CU most neurons are not connected neuron is not connected to every one of the neurons in

the brain uh a relatively small set so it'll be mostly zeros but it's a great big Matrix okay so that's a model of the

connectivity of the brain now what is that what's going to be the Dynamics of that well you could then fire up a certain uh threshold in each Place uh

each guy if he's he's going to fire he's going to make uh the next the next guy's fire uh the numbers can be negative because a neuron can be a a u inhibitory

neuron so it could it could fire this direction and that'll dampen down so you can see these are the pieces of a model it's way too simple-minded to do much of

a job but on the other hand there it is it's a start it's a starting place for trying to analyze this big Network of neurons sounds once you have the model

it sounds like you're saying you could say if this happens between these two points on the model then if we do this

between these two points on the model this should happen and this would be involved in this activity so you can predict parts of the brain that might be involved that you wouldn't have known you can actually I mean he gave a

wonderful example so let's assume we have two structures two nuclei that are interconnected but we don't know which particular cells in one

connects to which particular cells let's say we have a driver population and a follower population um so what you can do is you know that the driver has to

precede the followup because it triggers the action potential so this action potential has to occur before that and you can also have some precise idea if you look at a lot of them if you see that this one consistently fires before

that one what is the separation between them so you can infer if you have that kind of Separation these cells are directly connected so you'll see that some cells are directly connected others

are not and you can ask the position what is the position in space of the cells that are connected to each other is it the extreme of one nucleus connecting to the scent of another or is

it matched in some other way and you can test these things first theoretically and then you can actually Trace those connections anatomically and see whether that model is correct so am I right in

thinking that the model gives you a place to look anatomically exactly which you where you'll find it exactly okay I'm a little okay so that's okay that

that pays my way here today that's no no no no this I learned something then I then I feel okay no no but I mean what what has really made it so powerful is

that the models number one allow you to pull together complex bodies of data that difficult to deal with intuitively

okay and two it allows you to make predictions that you can then test biologically to either falsify or verify

the model very powerful it sounds as though the the more deeply you study the brain the more you must rely on this kind of absolutely computational an

absolutely absolutely because knowing where things are in the brain when we were looking at one cell versus another cell yeah we didn't need it yeah but now when you're looking at how 100 cells

interact with a couple of hundred cells you it's very difficult to make sense out of it intuitively you need mathematical models they become more and more

important what what do you both think given what we seem to know now what do we need to know next what

what's sort of on the horizon what's possible to know not necessarily Blue Sky stuff but maybe it'd be interesting to know what you think it's possible to know eventually but what what's soon to

be known what do you what do you need to know so for example um we know a lot about the early stages

of visual processing because of work by people like kuf juub and weasel I mean you don't know these people but they showed that at different points in the visual system cells respond to different

stimulant and the most interesting thing they found is in the cortex you begin to move from responding to Circular stimuli to

responding to linear ones so some cells respond to linear stimuli they go up and down others that have specific a of

orientation okay period end of paragraph further on in the visual system we have an amazing thing you have cells that respond to

faces there are six patches in the brain called face patches in which cells respond to faces but question is how do you

construct those faces out of these linear the cells that respond to linear stimul so the whole in between area needs to be worked out here's the

sensory system we understand best and there are major holes in our understanding of it in most cases we don't have a very good understanding of the cortical representation of the sense

modalities and how they work so that's a major problem um with memories I pointed out before we're just beginning to see

that memories in the hippocampus involve populations of cells and how they work and how they can be recruited that's a very important advance but this is just

a recent kind of thing we know nothing about the major mental illnesses or psychiatric illnesses schizophrenia depression manic depressive disorders we begin beginning to make as a result of

Simon Foundation a lot of progress on autism but still got a long way to go so in terms of major psychiatric illnesses even neurological illnesses we're very

very far I one time when we were in conversation you said that especially coming from psychoanalysis as you have that

cognitive psychology gives Neuroscience questions to be answered beautiful I give you an

example psychoanalysis um Freud was the first person to sort of people talked about it before but first person to emphasize that part of the mind is conscious and the large part is

unconscious and he actually spoke about different kinds of unconscious processes first he spoke primarily about instinctual processes aggression and

eroticism but then he had preconscious unconscious he had the super ego the fact that we uh unconsciously make decisions because we think they're

morally right um but we know very little about the details of them cognitive psychologists are beginning to study this for example there's evidence from

cognitive psychological studies that you can make decisions in two ways unconsciously and consciously uh if you have to choose between many

options five different apartments then making the decision unconsciously is better if you have to choose between two you know one partner or another

better to make a conscious decision that's really quite fascinating what's the what's the uh evidence for that how does that play out why what's the reason people have shown because

well the logic of unconscious processes allows itself for multivariate kinds of analysis like that uh but this is interesting stuff that just beginning to

emerge from cognitive psychology we can now begin to explore in biological terms reminds me of um what I think of as a

largely unconscious state that I think Neuroscience calls the default mode when you don't think you're yes certain areas of the brain get active under those you

feel like you're just Marcus Rael yes you're sitting there or sometimes taking a shower or driving you're not really thinking had a friend of Robert Lam who

wrote bestselling novels by deliberately putting himself into that state he'd go driving for two hours with a yellow pad next to him and suddenly ideas would occur to him but he wasn't I hope he

stopped I hope he sto no as a matter he's no longer with us so I don't no doubt I I'm not sure why but I I want to say something sure add to this what's in the

future because a great deal of Neuroscience rightly so has been devoted to analyzing the brain's response to

external stimuli whether it's how our eye works or how our ear works what happens when someone kicks you in the shin or taps

your knee or all this stuff that's coming in from outside physical stuff because we can control it so easily yes and we can do those experiments and and

and understand but an awful lot of what's going on in our brain is internal you sit there and you think right now some of you are actually paying

attention to what's being said up here now it's coming in through your ear but that's only uh incidental it's information that's coming into your

brain and it's going to cause maybe you'll remember it maybe you won't maybe it'll trigger a whole train of thought but what's all that about you can sit in

a chair have a very very active brain you could be thinking about a math problem or you could be thinking about a romance or you could be thinking about uh God knows

what all of that the Dynamics of the brain the stream of Consciousness a train of train of thought is not really

understood as far as I can tell and that's a a whole other area which is just now beginning to be approached that

sounds so much like what your background is in psychoanalysis the associa of bringing to the surface the associative process of bringing to the surface

what's happening under I agree and you know the tragedy is that psychoanalysis never became empirical yeah uh Freud was an

extremely good biologist uh and made several important discoveries in biology he was the first one that showed the nerve cells of simple animals is exactly like nerve

cells in your brain and mind so he showed the conservation of evolutionary processes applied to the brain as well and he only left biology because in those days in order to make a living in

basic science you had a private income and he wanted to get married um so it does all relate to sex it all relates to

sex and he in 1895 wrote a theoretical paper incomprehensible uh in which he tried to develop a neurobiological model of repression of unconscious processes and

he realized this is ridiculous our understanding of the brain is so primitive you can't possibly explain psycho analytic ideas but someday said biologists are going to be sufficiently sophisticated about the brain that they

will prove many of these ideas that I have wrong but the psychoanalytic Community was so successful for so many years many of you are too young but when I was a

house officer in Psychiatry you couldn't be chairman of the Department of Psychiatry unless you were a psychoanalyst they dominant mode only with time they realized that many of

these ideas were not tested empirically so are are now as you evoke memory as you suppress memory are you are you

getting close to to reproducing Freud's repressive repressed memories we we we we don't know I mean we need to explore now in a position to test some of these

ideas uh and to begin to explore unconscious mental processes and see how they work I mean he was the first one to point out that most of your life is unconscious and this is true you and I

the three of us are having a conversation yet when I talk I don't think ahead of myself you know this is the sentence grammatically correct I just spit it out I granted it's not cortically correct and it's probably

incoherent but I do so aming amazing how much of it is preconscious it's just astonishing how it is so what's known about that

relatively little but this is something we can get at certainly with imaging and I'll give you an example Stanis D has recently done a very beautiful set of

experiments uh he and this is the experiment per se is well known the result is not known uh if I show the two of you an image very briefly with a

masking stimulus uh you will not be able to recognize it a masking stimulus what do you mean another stimulus that interferes with your perception of this okay like the way the magician I I I show you the face and then I hold this

up okay or if I just show it very briefly let me not make it compliment yeah if I'm Imaging your brain at the same time

it shows that the occipital pole that is the back of your brain which first processes visual information in the CeX lights up so even though you're unaware of it

the cereal cortex already gets involved the highest processing region get recruited even though you're unconscious you now show you the same image for a longer period of time so you can really

perceive it you're now consciously aware of it you see that that information instead of being just localized to the back of the brain propagates forward and interacts with many areas and comes back

again and this is something people have predicted that Consciousness involves the propagation of information so can be used by a number of different areas by

the C cortex speech area action area etc etc etc so this is a beginning of getting a handle on some aspects of Consciousness which would be really fabulous to sort of understand in

Greater detail well I think we've covered brain research from the past to the

Future where where's many years in the future um L do do we do we want a where are you do we want a a question from let's take let's just try one question

from the folks out there do you have a favorite here well they like yeah you like well

here well this is a hard one him I was I I I this made me think though when I when I read it I thought what what what does the question even

mean what's the answer what's the relationship between the brain and the self is the self just a persistent illusion according to modern day

research or is it what is what's the difference or what's the connection the self is a perception that you have of

yourself in the brain every mental process from the most trivial you know hitting a backhand in ten it's not so trivial for me uh to thinking creative

ideas in mathematics all comes from the brain and the self is a perception you have of yourself is a Unity that's built into the brain and yet there are times

when you don't know who you are I mean there there's there there are times for some people only after a lot of wine or something like that most of the time I know all too

well who I am it's I want to chime in and that because that's a you know it's really a

profound question it seems to me you know we talk about my hand my

foot my brain who is this my who who is what is this thing and uh and it's obviously something that is emerged from

the structure of our brain this concept of self I don't know if a dog certainly a bacteria does not does not have a

sense of self I mean I can't imagine a bacteria a dog has a sense of self it might okay maybe that high up in contradiction to to another animal for

example or yeah it it uh my bone that's my bone that's my bone okay that's my bone uh so somewhere in the in this in

this evolutionary uh process the notion of self has has arisen and uh it's a

very profound notion and uh I think the the physiology will clarify this at some point we'll understand what what

networks are really what we call ourselves it's a very deep question in terms of figuring this out it's a profound question it's part of self-consciousness yeah

yeah I think maybe we've we've reached the the the end of the hour it's has anything occurred to either of you during this time that you said I really

want to squeeze this in not immediately is there anything you're glad I didn't ask you yes I want to thank you all for being

here and thank you to my two friends thanks so [Applause] much