My name is Andre Fenton.
I'm a professor of neuroscience at New York University.
I also co-Direct the Neural Systems and Behavior Course at the Marine Biological Laboratories
in Woods Hole.
I also founded Bio-Signal Group, which makes medical devices to help patients and physicians
handle and manage neurological emergencies.
This is the third part of a three-part lecture series wherein I describe some of the work
we've been doing in thinking about and discovering and realizing what the underpinnings are of
memory.
And in this third part, I'll talk a little bit about how we can use that understanding.
I want to remind you that this work... these are the people in my laboratory...
I want to remind you that this work has been done by a large number of people, not only
people in my laboratory, but people in other laboratories, and that this effort has extended
across a substantial amount of time, in fact, decades.
So, what I've talked about in Part 1 and Part 2, in particular, of this series is how we
can teach animals how to learn something, how we can look in particular parts of their
brains to dissect the neural circuits that are crucial for learning and forming memories,
and what molecular mechanisms, in particular, this molecule protein kinase Mζ that is crucial
for the maintenance or the storage, long-term, of this information that's collected from
experience.
What I want to talk about today is that, while we focused on memory, memory really is not
everything.
It's a lot about how you use memory, how you use the information that you've stored in
your brain.
So, let's talk about that.
You can think about what I'm going to describe, now, as cognitive control.
It's also commonly called executive function.
And this... there are various descriptions of it, but think about it as the ability to
coordinate and use information from multiple sources.
You typically want to do this so that you can optimize your actions or choices in the
world.
And what's important about cognitive control is that it's impaired in most forms of mental
illness, in one way or another.
And so it becomes something important, in fact, it's one of the goals of modern psychiatry,
how to improve cognitive control and related brain functions, because that's actually the
best predictor of a neuropsychiatric outcome clinically, and we want to optimize this sort
of behavior.
And so, to give you an intuition about cognitive control, we can use a test that's well known
to psychologists called the Stroup test, and the Stroup test is very simple.
You present a word, for example, the word red, here.
And you can present it in one color or another, and in this case red is written with red font,
if you will, and so it's a congruent case.
And so that's relatively easy.
You present that stimulus and your brain adopts the state amongst the activity in your neurons
that corresponds to red.
And there's no other compelling interpretation of that.
However, you could also present the word red in green.
And, in this case, if I'd asked you to say the color but ignore the meaning of the word,
you would actually have an intellectual challenge, a conflict, right?
Should you adopt the activity pattern in your brain that corresponds to the color -- green
-- or should you adopt the activity pattern in your brain that corresponds to the meaning
-- red?
And that challenge of selecting between multiple alternatives, in this case, just two, but
in the real world there can be many more than two alternatives, is what we mean by cognitive
control.
How you control your ability to use information and knowledge, typically for judicious purposes.
So, can we test cognitive control and measure it in rodents, because if we can then we can
study the neural underpinnings of cognitive control and we can do experiments designed
to teach us what kind of impact this kind of experience can have in the brain.
And so what I'm going to describe for you is the form of the active place-avoidance
task that we call the two-frame place-avoidance, in which, in this case, a rat but it can also
be a mouse, is on a rotating arena.
This arena is rotating about 5x faster than live because otherwise it would be boring
to watch, and you can see a red area and a blue area.
These areas are not marked red and blue for the rat; they're just marked red and blue
for us so that we can delineate parts of the space that the computer is tracking where
the animal goes.
And if the computer detects the rat in the red area, it electrifies the floor.
Okay?
It's not a very strong shock, so the rat simply wants to avoid being there and it's walking
around -- in this case, it's collecting small food pellets that are being dropped randomly.
If the computer detects the rat in the blue area, which is defined by the actual substrate
of the arena and the cues that the rat can use are things like scent marks that it lays
down -- urine, feces, that sort of thing -- and it can recognize clearly where it is on the
rotating arena, also.
So, if you think about this, whenever the animal gets shocked, as shown over here, if
it's shocked for being in a part of the room, shown by the red circles, then those red circles,
while they're in a particular part of the room, they are dispersed in the arena.
And if the animal gets shocked or being in the blue part, the rotating part of the arena,
although the shocks are collected there, they are actually dispersed in the room.
So, the animals has, very much like we did when looking at the Stroup test, to decide,
given the particular shock stimulus, will it interpret it as being a shock delivered
for being in a part of the room or will it interpret that very same stimulus in an alternative
way, for being in a part of the arena?
And that's the challenge that we're going to give our rats and look to see what kinds
of consequences that might have in the brain.
We're going to use a simpler form of this test, what I call the active place-avoidance
task, and we're going to use it in a memory configuration.
So, in this case, the animal can look out into the world -- we're going to use mice
-- and it can decide to avoid a particular part of the room, but there's no particular
part of the arena floor that is useful to avoid.
We haven't designed a shock zone on the arena floor.
Nonetheless, when the animal actually gets shocked, it was shocked for being in a particular
part of the room, but it's also experienced as being a shock on a particular part of the
floor.
The distinction here is that where it's shocked on the floor is actually irrelevant, and in
some sense knowing where it is on the floor is a distraction that the animal has to ignore
in order to behave efficiently, in this case.
That will become important.
So, we can ask this question: How does this cognitive training, to use on class of useful
information and ignore what is another class of currently not useful information, how does
this change the synaptic network function in the brain?
And we're going to use the hippocampus, which we know to be crucial for learning and memory
in this test, and we're going to study a particular subregion of the hippocampus called the CA1
region, and what's shown here is a neuron, a single CA1 neuron, which you can see, as
shown with the red and blue arrows, has two different what I will call compartments, where
inputs from other neurons arise.
And the inputs are segregated anatomically, as shown here, and they actually come from
different areas.
So, another portion of the hippocampus, the CA3 region of the hippocampus, actually projects
to the proximal dendritic region, which is shown here in red, and the entorhinal cortex,
a different part of the brain, projects to the distal dendrites of the CA1 region.
And what we can do is, after training the animals and testing their memories, what we
can do is sacrifice them, make slices through the hippocampus, and study the synaptic electrophysiological
properties of how one presynaptic input is about to influence the postsynaptic output
in CA1.
And we can stimulate one pathway or another.
I'm going to focus on the pathway indicated in red, because that's actually in the strengthened
pathway.
And what we'll be able to measure, as shown here, is a synaptic response, this initial
upswing, if you will, the synaptic response.
The slope of that is a measure of how strong the synapse is, and we'll be using that as
an estimate of how this cognitive training has changed the synaptic response, which,
remember, is the connection between one set of neurons and another within this network.
I want to remind you, as we talked about in Part 2 of this three-part lecture series,
that, as shown in this image, if you train animals and wait one month, you can find that
there are increases in the amount and distribution of PKMζ, a molecule that is crucial for storing
and persistently storing this kind of memory, as well as other memories.
And so we can ask the question, what happens to the function of this neural circuit when
long-term memory is stored, whereas previously we were just interested in understanding what
components, what molecular components are crucial for the memory storage.
Now, let's ask, what is that impact on the actual function of this circuit.
So, what we can do is repeat an experiment, which is to train the animals, in this case,
we train them for 3 trials each day for 4 days, to establish a long-lasting place-avoidance
memory, and we'll test that memory 30 days after the end of training.
And you can see here, in the control case, the animals are on the arena for exactly the
same amount of time as in the training case, the shock is however never turned on and they
can walk everywhere and they choose to do so.
However, the trained animals, as you can see in the bottom set of these tracks, when the
shock is turned on they learn to stay away from the shock zone and they persist in staying
away from the shock zone, as least some of them do, 30 days later.
Now, I want to point out that 30 days later, we're going to test memory, but in both groups
of animals they've had the identical current experience.
In fact, the last 30 days of their lives have been identical or at least indistinguishable.
We're not going to turn the shock on; we're just going to see where they go.
And what you can see is, in the bottom, there, is if we measure, how long does it take the
animals to enter this former shock zone after the memory retention on day 34?
In the trained animals as a group, they have an elevated... they're at about 5 or so minutes
before they enter the shock zone for the first time, whereas the control animals enter in
a few seconds.
But if you look, now, in the middle panel, there, if you look at the trained animals
and the control animals and make a histogram of how long it took the animals to avoid the
shock zone to first enter, you can see that the black bar, 100% of the animals enter the
shock zone within the first, say, 15 seconds if they're in the control group, but a substantial
number, about 1/3 or so, of the trained animals also enter the shock zone within the same
15 or so seconds, and you can say they have a poor memory assessed in this way, whereas
the others have a much better or strong memory.
And so you can divide the animals who were trained, who had the same training experience,
into those who have poor as well as those who have good memory.
That's going to be important because now we can look and see how the synapses change.
And what's shown here in the upper-left, you can see those animals that performed and showed
a good memory, that curve, the red curve, is shifter to the left compared to those animals
in black that didn't form a memory that we called place-avoidance, and, similar, the
animals that showed poor memory are no different than the controls.
And so, on that plot, what's shown on the x axis is the strength of our test stimulation
and what's shown on the y axis is the slope of the synaptic response -- the steeper the
response or the higher that value, the stronger the synapse.
So, what this shows is that, after a month, if the animals show a strong (good) memory
recall, then their synapses become strengthened.
And that is summarized in the plot on the right, as you can see, and we can do another
test in this system and that is shown on the bottom plot.
What we can do is deliver a 100-Hz, high-frequency stimulation, that's what HSF stands for, and
when we do that we can strengthened, artificially, these synapses and we can watch how that long-term
potentiation persists and, again, what you can see is there's a difference between the
trained and the control animals, and in particular the trained animals that remembered well,
they have a weaker potentiation -- they have LTP but it's not as strong, the magnitude
is less, than the animals that also had training but had a poor memory.
And the animals that had a poor memory are no different than the control animals that
didn't have any memory, and that's shown by the bar graphs on the right in summary form.
So, that's quite remarkable.
We can demonstrate that the animals formed a memory, it persisted for up to a month,
and if and only if it did you can measure a detectable change in the synaptic strength
and synaptic ability to change in this part of the brain.
There are very few changes that have ever been described like that.
In fact, there are other changes that you can detect at this synapse.
What's shown here on the x axis is the strength of the synaptic response and what's shown
on the y axis is the likelihood that that response is associated with the generation
of an action potential, what we call a spike.
And so, because the red trace is shifted to the left, what that shows is that, for a particular
stimulation or a response to a simulation you get a bigger or more likely generation
of an action potential.
So, this circuit has become more responsive, if you will, as a function of this training.
You can see in the upper trace, here, that this is repeat of what I showed you before.
The high-frequency stimulation causes long-term potentiation, but it's of a lower magnitude
in the trained animals than the untrained animals.
The animals are harder to change after the training.
In fact, that's not quite true.
They, if you look at the lower trace, this is a different kind of stimulation, this 1
Hz, 1 time for 15 minutes stimulation, this causes a depression of the synapse, a weakening
of the synapse, and the trained animals, instead of having a weaker depression, have an enhanced
depression.
So, this synapse changes its plastic properties: it's harder to strengthen, easier to depress,
easier to weaken.
And this, again, is after just a few minutes of training across a few days.
You might think, oh, so has the brain saturated in its ability to change its synapses and
therefore store memory?
Well, this trace shows you that's not the case.
If we repeat the high-frequency stimulation after, say, 15 minutes, we can see that the
trained animals potentiate, eventually, just as much as the untrained animals, so it's
not like the brain has filled up, if you will, in its ability to make plastic changes; it's
just now different.
And, again, this is different not because of a drug, not because of any electrical stimulation,
just because of the animals' cognitive experience, which in these cases corresponds to about
30 minutes of experience during the training.
Somewhere between 30 minutes and 120 minutes -- 2 hours -- we see approximately the same
thing.
So, we can look in some detail, okay, at the neural circuit, here, of the hippocampus.
What you can see is that the hippocampus is a structure that's made up of different cells
with different inputs, and we've been focusing on the CA1 cell.
We'll talk in a moment about the inputs at the dentate gyrus as well as the different
compartments of the CA1 neuron.
So, let's talk about the CA1 neuron, which is shown here in red, with the VHC... is the
ventral hippocampal commissure.
It's an input from another portion of the hippocampus on the other side, the CA3 region
of the hippocampus, and is an input to CA1.
And it arrives at this proximal part of the dendritic tree.
PP stands for perforant path and that's an anatomical term for the input from the neocortex,
from the entorhinal cortex, that can arrive both in the dentate gyrus as well as in the
distal dendrites of CA1, called the lacunosum moleculare, and I'll encode that as blue.
And so we're going to look at the response to perforant path input in CA1 as well as
the response to the ventral hippocampal input in the proximal dendrites of CA1 and how cognitive
training changes that.
And so, in order to do this in an awake animal, or at least an intact animal, because these
data that I'll show you are from an animal that's been trained and, after training, anesthetized
so we can be sure about where the electrodes are, what we're going to do is put 16 electrodes
along the somatodendritic axis of the brain in order to be sure about where it is that
we're recording from one animal to the next, and we're going to, in this way, triangulate
and focus our attention on the particular electrodes that are in the particular compartment
that we want to study.
And so, when we do that, we can calculate many things.
What I'm showing you here is something we call current source density.
Current source density is a way of describing the electrical response, or an electrical
signal, in neural tissue, so that you can recognize which, what we call, sources correspond
to a current that is leaving the neurons and going into the extracellular space -- that's
why it's a source -- and that's associated with inhibition, the suppression of activity,
or at least an outward current.
And we can look at, what will be shown here in blue, sinks, which is current leaving the
extracellular space and going inside of neurons, which is associated with excitation.
And so if we look at the ventral hippocampal responses in the untrained and the trained
animals, just looking at the colors there you can see that there's a difference.
The trained animals have a difference in their sources and sinks.
They appear in the same places anatomically, just their intensity is substantially different.
And if you look in the perforant path, the trained animals... right, these are the same
sets of neurons, the same electrodes, but a different input, and you can see that in
the trained animals, while the locations of the sources and sinks are approximately the
same, the intensity is actually not increased, it's decreased.
So, this is rather remarkable.
It's subregion specific alterations in the synaptic responses, both in excitation and
inhibition, within this narrow region of the brain.
And those data are summarized, shown below, while the upper case is an individual.
What I can show you is quantifying that... in the lower bar graphs, there, you can see
that the trained animals have a much bigger source, a bigger inhibition, as well as excitation
with the sink in the ventral hippocampal case, which is the CA3 region of the hippocampus
projecting to the red area, the area that's indicating red in the cartoon, which is the
proximal part of CA1, and the area indicated in blue, the perforant path input, you get
rather the opposite change.
Again, that's quite remarkable.
Remember, this is training and in this case the training was actually just, again, across
a single day for 10 minutes a trial and 3 trials.
So, 30 minutes of activity was sufficient to change the functional characteristics of
this part of the memory circuit that we looked in.
So, what I've shown you so far is that experience can persistently change neural circuit function.
The changes that I showed you before were measured at least 24 hours after the training,
and they persist in other experiments that we've done for at least 50 days.
And so that begs the question, you know, could we actually use cognitive training directed
in one way or another to tune the neural circuitry function so that we can preemptive... be preemptive
in preventing cognitive dysfunctions that will arise later in life.
So, we decided to ask this question some years ago.
Could preemptive cognitive training prevent future cognitive impairments?
So, we had to arrange to have future cognitive impairments.
And what we did was we used a neurodevelopmental model of a mental illness, like potentially
schizophrenia, and to do that, because we wanted it under our experimental control,
what we did was we took neonatal rats, when they were 7 days old, this corresponds to
a time in brain development that's approximately like the third trimester of a human pregnancy,
and what we did was we damaged a part of the brain called the ventral hippocampus, okay?
This is a portion of the brain that, as it develops right around this time, is developing
its connections to the frontal cortex and it changes a number of things in the brain
that have at least superficial resemblance to the kinds of changes that we believe happen
in schizophrenia.
Hence, we'll call it a schizophrenia model.
And so what we did was we damaged this part of the brain and what we could test is the
animal's ability to do this cognitive task when it was an adult at about 60 days old,
and 60 days corresponds to young adulthood -- you can imagine that as 18, 19, 20-ish
in human terms.
And so when we asked the animals to do this kind of a task -- I'm showing you in this
case the same place-avoidance task that we used before -- from this perspective it should
be apparent that the place to avoid, that the rat is doing a good job of avoiding, right,
is fixed in the room using the stationary cues, but you can see the feces on the arena...
they are rotating and they rotate through the shock zone sometimes, and sometimes they're
away from the shock zone.
That should give you the impression or the indication that using local cues on the rotating
surface are not useful for identifying the location of shock.
And when animals are trained in this particular task, if they are the schizophrenia-treated
or schizophrenia model, so they've had the neonatal lesion, they're impaired.
The make many more errors than the control animals, who simply had the injections made
of the vehicle... the vehicle solution rather than the toxin that we injected.
Okay, so now we have a cognitive output or assay for the debilitating consequences of
this in an early lesion.
What we found that was interesting is this debilitating response only occurs in the presence
of the distraction and what we've done here is we've used the identical task, but instead
we've put a 2-cm layer of water on the arena, and what that does it is dissolves and dissipates
all of the local olfactory cues that the rat was using that it had to actively ignore because
they were irrelevant for localization where the shock was in the red shock zone, here.
And when we do that and we test the animals as adults, okay, despite having this lesion
they clearly are okay.
So, their memory is alright; they don't have a memory deficit.
What they have is a deficit when they are challenged to use one kind of information
and ignore another kind of information.
And that's the kind of deficit that we see in mental illness like schizophrenia.
So, here's the interesting thing.
Early in the brain, in brain development and as you go through puberty and such, the brain
has a state that we say is hyperplastic -- it's more willing to change.
And so we took advantage of this knowledge and, during adolescence, when the rats were
35 days old, which corresponds to being something like 13 in human terms in terms of brain development,
what we decided to do was give them this cognitive training, to use one kind of information and
practice in ignoring the distraction, as I showed you before.
And the control animals simply were put on the arena, but the shock was never turned
on, so they had the same physical experience of the arena, they just didn't have the few
seconds when the shock was turned on.
And, by the way, the shock is only turned on for half a second, and if an animal received
10-ish shocks during a trial, the trial is 10 minutes, but the shock is only on for about
5 seconds.
So, otherwise, the environment is really identical and the experience is identical between these
two groups of animals.
And so what you can see is, not surprisingly, we understood this during adolescence, the
schizophrenia model animals are just as good as the control animals in learning this task,
and here's the surprising thing.
What we wanted to do is we controlled for the animals who had the noncognitive training,
just walking around the task, and you can see that when they become adults they show
the typical impairment we showed before, right?
The animals that had the neonatal lesion make many more errors than the normal animals.
But here's the surprising thing: the animals that had the cognitive training, they no longer
expressed the cognitive deficit in adulthood.
In this work that we've published, you can look at the paper, we went on to test whether
this deficit was specific to this task or general to other tasks, and what I can tell
you and what the paper shows is that the animals, by having this early training, actually developed
abilities so that they were no longer impaired on this task, completely independent other
tasks, and even in tasks that were the opposite of this current task, where the knowledge
of this task would have been debilitating.
And so, what we were quite surprised at is that this kind of training that I showed you
before is able to alter neural circuit function doesn't only alter neural circuit function
in an abstract sense, the kind of thing that a neuroscientist or a neurobiologist would
be interested in, but it also changes brain function, it would appear, so that behavior
is also materially changed.
And we decided to examine what it is that was responsible for that.
And so that first and obvious thing to do is to look at the brain, and so what's shown
here is the brain at two different levels in the control animals, and you can see the
hippocampus in the dorsal as well as the ventral aspect -- upper and lower -- and in the schizophrenia
animal, here are two brains, and you can see they look pretty beat up and ugly, they have
big holes, they're shrunken, the ventricles are larger... what's interesting about both
of these brains is it's very hard to tell them apart from their damage.
One of them is from the schizophrenia model that had this early life training, the other
is from the control animal that had the experience of walking around on the arena, but never
had to... was never encouraged, if you will, to be trained in using one kind of information
and ignoring the distracting information.
And what's shown here in the plots is the learning curve or the training of these animals
in adulthood.
You can see that, although the trained and exposed animals have the same brain damage,
the trained animal is very similar to the control animal in its training across this
task, whereas the animal that had simply the exposure is impaired and it takes a long time
before it learns, and it doesn't really get all the way there, right?
The same brain damage, but very different functional outcome.
So, that led us to ask the question, did the early cognitive experience change brain function?
And so, one of the things we can look at is the synchrony between the electrical activity
in different hemispheres of the brain.
There are other changes in the brain and other signals that we could measure, but this is
a handy signal, if you will.
It's the kind of signal that you could actually measure from the human scalp EEG of patients.
And what you can measure is how synchronized the electrical activity is in the two hemispheres,
in this case, of the hippocampus, because this electrical activity represents the activity
levels of many thousands, tens of thousands of coherently organized, in space as well
as in time, synapses.
And so, when you look at how the left and the right neural activity, synaptic activity,
the local field potential, is in a normal animal, you can see it's rather well synchronized
here, when I overlay the left and the right traces.
But in the schizophrenia model -- this is done in adulthood -- if the schizophrenia
animals have only had this early, this non-cognitive training, the exposure, you don't see very
good synchrony... very poor synchrony, in fact.
What's surprising is if they've had the early cognitive training, despite the persistent
brain damage, their brains are functionally different, their brains are functionally synchronized,
in fact, indistinguishable from the normal animals, at least in this measure.
So, this training, again, somehow promotes normal brain function, even if the brain anatomically
has been damaged.
I used the analogy earlier of the internet in thinking about how a complex system like
a set of neurons, 100 billion or so or many millions of neurons, interacting across tens
of thousands each, trillions of synapses, how it can self-organize, using activity as
the driver for its organization, how the internet is a self-organizing system where usage is
what drives its architecture and the deployment of resources for growth and shrinkage, depending
on usage.
We use that concept, if you will, to try and understand how it is that this activity, through
the synaptic changes that I showed you emerge from training, cause a reorganization, functionally,
of this neural circuit, not only to store memory, okay, but also to store the actual
or to change what is stored as the functional architecture of this system.
And so, to summarize, there are really two, I think, salient points to make.
One is that cognitive experience itself seems sufficient to tune the synaptic communication
pathways, right?
And that not only is able to create, but it's also able to control how information flows
through the brain, right?
This is the stuff of memory, but it's also the stuff that determines future experience
and future ability.
And that cognitive control itself, the ability to judiciously process or use one class of
information while actively suppressing or ignoring irrelevant information, that itself
may be an opportunity, a therapeutic opportunity, for experience-drive adjustments of tuning
of cognitive networks.
To the extent that we understand what kinds of cognitive efforts one needs to use to activate
and adjust the functioning of specific neural circuits, we will be able to harness that
knowledge and that ability, in large part perhaps not only to repair but in some sense
to inoculate brains against the genetic predispositions and the unfortunate experiences that might
actually cause debilitating consequences.
And so that's a future direction and goal of this kind of work.
So, to sum up, it's been said that what we think, be become, which seemed preposterous
on first blush, but if you think about the neurobiology of memory and the adjustments
of synapses that rather simple experiences are able to imbue, if you will, and impose
on a neural system, it causes one to be thoughtful and judicious about what one does with one's
experience, and it doesn't seem all that crazy that there might be some truth to the idea
that what we actually think, we might before.
So, in closing, I'd like to thank the many people who have contributed to this research
in my laboratory, both currently as well as in the past, as well as my many collaborators
in other laboratories, and of course for the generous support from the various agencies
that have supported us across the decades.
