How Does Memory Work? (Featuring Dr. Michael Yassa)

Kelly talks to Dr. Michael Yassa about how memories are formed, comparing brains to computers, brain-computer interfaces, and more! 

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Episode Transcript

Speaker 1 (00:05):
The analogy that I like to use for this is
imagine you are at a club and there's lots and
lots of noise going on, lots of things going on,
lots of people talking to each other, there's loud music
and so on, and you're trying to communicate something to
somebody who's dancing alongside gm, and it's very, very difficult
because of all of that noise. But now you get
real close to them and you kind of, you know,

(00:26):
hold your hand to their ears and you start to
talk directly into their ears. Now they're going to receive
that communication with much higher fidelity, be able to tune
out noise and selectively attend to that communication. You've enhanced
the communication between that person and the person they're talking to.
That's what happens at synapses. There's lots and lots of
synoptic firing, lots and lots of communication happening. But when

(00:48):
cells start to attach to each other, they communicate much
more preferentially. They can transmit signals that express that form
of learning. In other words, if there's an experience that
happens that is learned by the brain, the brain can
express a form of plasticity or a form of memory
in the strength of the connections. So if the connections

(01:09):
grow stronger, that's a signal that this memory has been learned.
And most of the information that we have about this
comes from animal models, comes from slice recordings where we
can see evidence for enhancements in the connectivity, enhancement of
the communication between cells as a result of a learning experience.

Speaker 2 (01:26):
You've reminded me why I hate clubs. I'm sorry, no
one invites me to them anymore.

Speaker 1 (01:31):
I share that with you. Hi, I'm Daniel.

Speaker 3 (01:46):
I'm a particle physicist, and every day I rely more
on my computer's memory instead.

Speaker 1 (01:50):
Of my own.

Speaker 2 (01:53):
Yeah, I am Kelly Leader Smith. I'm a biologist, and
I'm having a lot more of those moments where you
walk into a room and think why am I in here?

Speaker 3 (02:04):
I walk around campus here at you see Irvine and
a lot of folks go hey, Professor Whitson, and I
go hey, and I think I have no idea who you.

Speaker 1 (02:10):
Are and why we know each other.

Speaker 3 (02:13):
And sometimes it's just because they were in a class
I taught with four hundred people, and the relationship is
a little axometrical. And sometimes it's just because my memory
is terrible, and maybe we hit coffee and I've forgotten,
So I apologize to folks out there who I'm pretending
to recognize.

Speaker 2 (02:28):
Yeah, yeah, no, I'm there also, And every once in
a while be standing in the grocery store and I'll
stand in front of the aisle for a little too
long and my daughter will go, you forgot, didn't you. Yeah,
I have no idea what I'm looking for right now.
And hopefully this doesn't give us too much anxiety thinking
about what the root cause of our memory problems are.

Speaker 3 (02:47):
I have that as well. Is that a memory issue
or is that a distraction issue? Like where you're looking
for capers, but then you see a jar pickles and
it makes you think about that last time you had
a pickle, and then you're like, m I wonder if
you can pickle at home. And then five minutes later
you're dreaming about a whole pickling building in your backyard,
and you've forgotten that you were looking for capers.

Speaker 2 (03:06):
So I don't like pickles. So no, that's not my scenario.
But sometimes it'll be like, you know, I see my
reflection in a bottle, and I'll be like, oh, is
that spot skin cancer? When am I gonna die.

Speaker 1 (03:15):
There we go?

Speaker 3 (03:16):
Yeah, exactly, but.

Speaker 2 (03:18):
It is often distraction instead of forgetfulness. But yeah, sometimes
it's hard to disentangle those things.

Speaker 3 (03:24):
Well, I just learned something deeply troubling about you that
you don't like pickles.

Speaker 2 (03:28):
What you know, Daniel, You've made a really great point
about your memory, because we have definitely talked to about
and I think even on the show, we've talked about this.

Speaker 3 (03:39):
That's embarrassing, but not as embarrassing as being closed minded
to the wonderful world of pickles. I'm with you, like
the big deal pickle, okay with the sandwich, but I'm
not munching on one in general. But have you ever
done home pickling, you know, like you can pickle cauliflower
or carrots.

Speaker 1 (03:54):
It's really wonderful.

Speaker 2 (03:55):
The only pickled item I've ever enjoyed is Cowboy candy,
which which is when you slice of really hot halopanos
and put them in like a sugar pickle. Oh so good.
That I love on sandwiches. Other than that, I have
not met a pickle that I like.

Speaker 3 (04:09):
I'm sorry, I have to work on that, all right.

Speaker 2 (04:11):
Okay, all right, well, I'll keep my mind open. But
today we got a wonderful question from our listener, Simon,
who is interested in memory, and so let's go ahead
and listen to Simon's question.

Speaker 4 (04:22):
Now, Hi, Daniel and Kelly. This is Simon from New York.
I was a huge fan of Daniel and joege Explain
the Universe. However, I am loving the new show with
Kelly and never missed an episode. Here's my question, I
think mainly for Kelly. I am now into my seventies
and not surprisingly find myself reflecting a lot on my

(04:46):
life and the thousands, perhaps millions of memories that go
into a lifetime. I have often wondered exactly how the
human brain, using biological substances, chemicals, and electricity, actually doors memories.
I have tried to read about this, but have not
found anything to satisfy my curiosity or wonder Perhaps this

(05:09):
blurs too much into the question of what is consciousness
and sentience and it's not something you want to delve into.
But if you would like to tackle it, I would
love to hear about what insights biology and physics have
to offer. I have very recently been reading a lot
about computers, trying to understand how they really work and

(05:30):
that seems somewhat related, but only somewhat anyway, Thanks to
both of you for all you do. My weeks would
not be complete without listening to your podcast episodes.

Speaker 2 (05:42):
All right, Simon, we love your accent.

Speaker 1 (05:44):
We do.

Speaker 2 (05:45):
I grew up in New Jersey and I miss hearing
that accent more often, so that was awesome, And thank
you for this fantastic question. And we got really lucky.
So folks, remember we talked in the past about whether
or not tripped a fan from Turn he actually makes
you sleepy on Thanksgiving and we interviewed Mark Mapstone for
that and he suggested that if we were interested in memory,

(06:07):
we should talk to his colleague, and his colleague was
willing to come on the show. So on today's show
we have doctor Michael Yassa. He's a professor at the
University of California, Irvine, where he's also the director of
the Center for the Neurobiology of Learning and Memory and
is the director of the UCI Brain Initiative. So like

(06:27):
clearly the perfect person for this topic.

Speaker 3 (06:29):
Yes, amazing, and also it's one more notch on my
personal goal to have my entire neighborhood on the podcast.
For those of you who don't know people that you
see Irvine. Many of us live in this faculty neighborhood
right next to campus, so we're all friends and neighbors
and we know each other. And by now we've had
a significant fraction of that neighborhood on the podcast. Because
I want to know, like, hey, who's an expert flight

(06:51):
I'm like, oh, I know that guy who's on the
next street. And so it's a fantastic resource.

Speaker 2 (06:56):
That is pretty great. So let's go ahead and bring
Mike on the show. But we should mention you were
off telling people about your amazing research ideas, so you
were not able to join us for this interview. So
I flew solo with Mike.

Speaker 3 (07:07):
Thanks very much for handling this while I was goofing
around in the area my pleasure.

Speaker 2 (07:12):
I had a blast. All right, Welcome to the show, Mike,
Thanks for being with us today.

Speaker 1 (07:18):
Thanks for having me.

Speaker 2 (07:20):
So what got you interested in studying memory? Let's start
by getting to know you of it?

Speaker 1 (07:24):
Sure, So, I don't think that I really knew much
about memory when I was an undergraduate. I was fascinated
by the brain just by virtue of taking a couple
of classes that kind of inspired that passion, that love
for everything brain related. And one of the things that
was really fascinating about it is that I felt, even
at the time, this was in the late nineties, that
we knew next to nothing. Unlike other classes that I took,

(07:47):
where there was sort of a big body of knowledge,
it felt like with the brain, there's just so much
more that we really didn't understand. So that became really fascinating.
As I started to dive a little bit more deeply
into different aspects of how the brain functions, memory came
about as one that was front and the foremost, particularly
because we started to see or I started to see
that memory loss is just very devastating, unlike any other

(08:11):
cognitive domain that if you know, if you have attentional
deficit or if you have a deficit with executive function,
you know, that can be somewhat circumscribed. It's a contained
kind of deficit, not memory loss, which just utterly devastating,
you know, seeing patients with Alzheimer's disease, seeing patients with
various forms of memory loss, that was really compelling, and

(08:33):
I started to understand a bit more that memory is
what makes us who we are. It's so fundamental to
our core. It's the essence of our consciousness. Everything that
we do we do because of some experience that we've
had that we've been able to store, and it just
became not just fascinating, but like entirely all consuming. So
I focused on memory from all of its aspects. One

(08:54):
is trying to understand it's fundamental inner workings, and too
trying to understand how it breaks down in a variety
of differ and conditions. And if we can do that,
maybe we can help people. Yeah.

Speaker 2 (09:03):
I've got a neighbor with Alzheimer's and it's been totally
devastating for the two of them. So yeah, So this
interview was inspired by a question that we got from
the listener and one of the things that they asked
about is does the concept of memory blur the line
with consciousness and sentience? How do you view these concepts?

Speaker 1 (09:22):
Yeah, you know, it's interesting. There's a somewhat related question,
which is, you know you can have a computer have memory.
When we talked about memory and a computing platform in
a robot or a botic application, certainly when you think
about chat GPT, well that can hold on to memory
for some period of time and use that to guide
how it responds to the us there and so on.
So memory in and of itself may not be the

(09:45):
thing that I would say as associated with sentiens. I
think that it's the way that our memory works, not
just as humans, but as sort of you know, live organisms.
It's not like the way that you would do it
in a computer. So let me elaborate. Memory is stored
in a computer is very much one to one. Everything
that you see and learn, your storing with incredibly high fidelity.

(10:09):
You try to retrieve it twenty years from now, thirty
years from now. It's exactly to say there's no degradation.
But that creates a problem for a memory system, and
that it's more difficult to extract generalities. It's more difficult
to generate knowledge based on memory. But say as a
human and you're encoding memories all the time. These memories
are stored, but we know that there's blurriness of memories,

(10:30):
there's forgetting of memories. There's all sorts of things that
we tend to think of as memory problems, but in
fact one could argue they're not bugs, they're features of
the system. Because memory is not intended to be a
super high fidelity kind of system. It's intended to get
enough information in so that you can generalize knowledge, so
you can learn from experience and be able to guide

(10:51):
your future decision making. So, while a computer's memory is
really about storage, with high fidelity, you don't want to
write a filin word and then store and then later
on have an abstract version of it rather than what
you actually wrote. You want to have an accurate record
of what you actually wrote. But for the brain, what
you might want to get later on is that abstract version.
It's just enough knowledge to be able to guide your

(11:12):
future decision making. And that's the reality of how memory
evolved in live organisms. And maybe the thing that makes
it very different from nonsensient beings is that it never
really evolved to think too much about the past. It
evolved almost entirely to think about the future. So the
reason why you might store something is because you want

(11:33):
to use that knowledge to guide future decision making, to
make sure that you do things that are adaptive to
promote your survival. You're not going back to the same
poison as berry bush. You know, to run from a
bear out in the wild, as supposed to go up
and say Hello, those kinds of things are based on memory,
equipping us to make better predictions for the future.

Speaker 2 (11:50):
So can we dig in a little bit more to
this trade off? So why can't you remember everything perfectly
and generalize when the time is right.

Speaker 1 (12:00):
Yeah. So it turns out that you can mathematically and
computationally model this and it gives you a pretty straightforward answer.
And the way that it works is that if you
were to encode every single experience that you have in
a very high resolution and high fidelity kind of approach,
then it becomes very difficult to generalize that to new situations.

(12:22):
The representations in the brain become almost hyper specific. They're
very very specific to those instances in which they were encoded.
So being able to extract the generalities or the knowledge
that you can apply to new things requires that there's
enough blur, enough fuzziness across the different instances so you
can generalize that knowledge. I'll give you an example. If

(12:43):
I were to ask you what is the capital of
the United States, you'd have a very very quick answer
for me, which is Washington, d Z Exactly. Now, if
I ask you, when did you first learn that?

Speaker 2 (12:54):
Now don't know.

Speaker 1 (12:56):
So now if I had asked you the day right
after you first learned that, be in class or maybe
from parents, you would have a pretty good memory for it.
That's a pretty exciting thing that you just learned. But
the reality is you've learned it so many times over
so many different exposures. You've heard in a million times
in many different settings. And what's most important is not
so much the first time you heard it or the
last time you heard it, but the fact that you

(13:19):
extracted that piece of knowledge, that core piece of knowledge
out and now that's part of your body of knowledge.
So the specifics around how and when and where we
encoded specific things may not be all that important from
an evolutionary standpoint to hold on to as the memory
for the actual knowledge is important. That's what's going to

(13:39):
guide your future action. That's what's important to generalize the
new situations. So in some ways there's no evolutionary pressure
to hold on to the specifics over time. But it
is an interesting point like why can't we have both? Well,
you can think about it from an energetic standpoint. If
you have a limited resource system, why would you invest
your energy into storing the specifics when you know you're

(14:01):
not going to use them down the line.

Speaker 2 (14:02):
Yeah, no, fair enough. So you mentioned the analogy of
the brain as a computer. Is there any analogy over
history comparing a brain to something else that you think
is a helpful analogy or the brain is just so
different it doesn't make sense to try to compare it
to anything we have experience with.

Speaker 1 (14:19):
So that is a really interesting question. And I have
thought about this before, and I keep coming back to
the computer as the closest thing, and I always tell
people I think it is possible that we will get
to a point, perhaps with quantum computing and other types
of things, where we might be able to approximate a
human brain like functionality in a computer. To this day,

(14:40):
we don't have that, even with the incredible advent of
AI in large language models and all of those things.
Still there are certain things that human brains can do,
and mammalian brains in general can do that computers just
are not capable of. But there is not another device
out there that is capable of this level of processing
that I can think think of to associate with that analogy. Particularly.

(15:03):
I mean, I think one of the things that the
brain does, don't get me wrong, like the computational kinds
of things that have been built are incredible, and the
amount of the minuscule amount of time that it takes
for them to be able to process and provide an
answer is just wild beyond the imagination. But there are
still some things that brains can do that the computer scans,

(15:24):
and in particular it has to do with the ability
to extract knowledge, the ability to error correct, the ability
to do the kinds of decision making that we do
as humans that are very difficult to encapsuling in the computer.
The ability to have emotion emotional reactions. Those things are
still very difficult to model. While you can tell the
computer all you want about what we think the human

(15:44):
experience is, we still don't understand that well enough to
be able to model it computer.

Speaker 2 (15:49):
Yeah, fair enough, all right, So let's pull back to
memory a little bit. So we've talked about how memory
differs from sentience. Are there different kinds of memory and
do our brains store different kinds of manator differently?

Speaker 1 (16:01):
Yes, And oftentimes we just say memory as like one
big blanket umbrella kind of term, But it is important
to know that there are different memory types, different memory
systems in the brain, and they serve different functions. So
let me give you a couple of examples. One type
of memory, which I tend to like quite a bit,
we studied quite often in my research laboratory, is what
we call episodic memory, memory for episodes, memory for events

(16:24):
that happened to us, And we tend to kind of
operationally define it as remembering what happened, where it happened,
and when it happens, and whenever you have kind of
like the collection or the conjunction of those three, you
can label that as an episode and you have a
memory for a particular episode in your life. Typically you
think about that as also the root of our autobiographical memory,
our memory for autobiographical experiences, things that happen to us.

(16:47):
But that's very different from membering how to tie your
shoe races, or how to ride a bicycle, or how
to do something like your tennis swing or your golf swing.
You know, those kinds of things are trained in the
brain very differently. They involve very different systems. A lot
of times, they require more trial and error kind of learning,
and they tend to be a bit less accessible to consciousness.

(17:10):
So there will call sort of implicit kinds of learning
so if you look at how the brain is organized,
pretty much every patch of cortex is capable of some
form of memory. Another term that we typically use in
neuroscience is plasticity. The idea that the brain is plastic
means it's capable of change. So whenever you have experience,
cells that are responding to that experience are capable of change,

(17:33):
and that change typically is thought of as a change
in the connections and the way that cells communicate with
each other, but some change that reflects a record of
the experience that you had. Now, those changes happen throughout
They can happen in our visual cortex, our visual system,
our auditory system. They can happen in the episodic memory
systems in the brain, or they can happen in these

(17:54):
more implicit memory kinds of systems in the brain that
typically support more unconscious function like knowing how to ride
a bicycle, like knowing how to swing the golf club
and those kinds of things. Those are stored separately. And
we know this to be true because we see patients
that have deficits in one type of memory and not another,
because they have maybe a focal stroke or some damage

(18:14):
or some deficit that impacted one system and not the other.
So they struggle with that one type of memory that's
affected in that system, but everything else seems to be intact.

Speaker 2 (18:22):
And by type of memory does that mean like category
of memories like the tennis swing and the other sort
of muscle memory things, or like I could forget high
school if I had a stroke in the right place right.

Speaker 1 (18:33):
Although that's actually increasingly difficult. So typically, if there is
a stroke that is focal, it might affect motor memory.
It might affect memory that allows you to kind of
move your hands in the right way and be able
to support that kind of function. But episodic memory is
this really weird thing. Initially, it does depend on key
regions of the brain, one of them being the hippocampus.

(18:53):
That's a really important region for episodic memory. But over
time memories start to become somewhat independent of the hippi
campus they start to become stored elsewhere, and that's one
of the reasons why in Alzheimer's disease, where we know
the hippocampus is one of the earliest regions to degenerate.
As that starts to go away, you see a loss

(19:14):
of recent memories things that were recently acquired, maybe weeks, months,
or a couple of years before the decline started. But
things from long ago, like high school are preserved. And
the reason they're preserved is that they've now been consolidated
that sort of a technical term for made strength and
made resilience to loss. And that's because their stored sort

(19:36):
of in parallel throughout the brain. So just the focal
deficit there is likely not going to wipe out those
particular memories, but it's much more likely to wipe out say, yeah,
your ability to have the right swing or ride a
bicycle or anything like that. Those are the kinds of
things that are much more focally stored.

Speaker 2 (19:53):
Okay, and can we dig a little bit more into
exactly how the brain stores memories. Is it like how
do neurons connect with each other? Yeah, let's dig in.

Speaker 1 (20:02):
Yeah. So brain cells are very very unique compared to
other cells in the body. And provided this is again
I always tell my students, you know, this is true
ninety five percent of the time according to our knowledge today.
I sometimes things you know, several weeks from now, months, years,
things can get revised. So this is just according to
our current knowledge today, brain cells are able to communicate

(20:24):
with one another in a way that other cells in
the body are not able to. And the way that
they communicate with each other is using a combination of
electricity and chemistry. So the transmission of signals within a
brain cell is entirely electrical, and we can talk about
that in a second, but the transmission from one cell
to the next most of the time is chemical. It

(20:47):
involves the release of a neurochemical that goes from one cell,
binds to the other, and then initiates another electrical signal
from the next cell to the next cell. So it
goes really fast electrical, somewhat slower chemical, really fast electrical,
someone slower chemical, and so on, and you have this
sort of progression of communication between cells. And that's really

(21:08):
important because these cells need to bring in signals that
essentially encode the outside world and bring that knowledge into
the brain to create some sort of representation of it,
and then act on them. Allow us to move, allow
us to avoid a threat, allow us to seek reward,
all of those kinds of things. So that's how the
brain typically communicates. But your question is how does memory happen?

(21:28):
And there was sort of lots of answers over the years.
We used to think, well, maybe it's encoded in the
DNA and cells. Maybe it's encoded in the cell size,
maybe it's encoded in the whatever else is happening to
change cell shape. And the current answer is that it
is much more likely to be encoded in the connections

(21:49):
in the way that these cells communicate with one another.
So let's say sell A is firing and cell B
is receiving a signal from cell A. If I were
to modify some how the frequency by which sell A communicates,
would sell be by making it fire more, or increase
the neurotransmitter release, or increase the number of receptors on

(22:11):
the second cell that receives that neurotransmitter. I can make
it so that the communication between those cells is enhanced.
And the way that the analogy that I like to
use for this is imagine you are at a club
and there's lots and lots of noise going on, lots
of things going on, lots of people talking to each other,
there's loud music and so on, and you're trying to

(22:31):
communicate something to somebody who's dancing alongside you, and it's very,
very difficult because of all of that noise. But now
you get real close to them and you kind of,
you know, hold your hand to their ears and you
start to talk directly into their ears. Now they're going
to receive that communication with much higher fidelity, be able
to tune out noise and selectively attend to that communication.
You've enhanced the communication between that person and the person

(22:54):
they're talking to. That's what happens at synapses. There's lots
and lots of synaptic firing and lots of communication happening.
But when cells start to attach to each other, they
communicate much more preferentially. They can transmit signals that express
that form of learning. In other words, if there's an
experience that happens that is learned by the brain, the

(23:15):
brain can express a form of plasticity or a form
of memory in the strength of the connections. So if
the connections grow stronger, that's a signal that this memory
has been learned. And most of the information that we
have about this comes from animal models, comes from slice recordings,
where we can see evidence for enhancements in the connectivity,

(23:35):
enhancement in the communication between cells as a result of
a learning experience.

Speaker 2 (23:40):
One. You've reminded me why I hate clubs. That's sorry,
no one invites me to them anymore.

Speaker 1 (23:45):
I share that what you do?

Speaker 2 (23:46):
Yeah yeah, Okay. So we've got these connections, they get strengthened,
but then it feels like there's another step between having
this connection and then having a like specific memory. So
you know, like we're not at the point where we
could even in mice and correct me if I'm wrong
about this, where we could like see which neurons are
firing together and know they're thinking about food. Yeah, yeah,
So where do we go from there?

Speaker 1 (24:06):
So what you're talking about actually is a very very
big problem that we deal with in neuroscience and in
cognitive science, and it's the credit assignment problem. How do
you know that a particular cell is assigned to a
particular memory or a particular connection it's assigned to a
particular memory. And it's a very challenging question and we
don't know the answer yet, but we suspect There's been

(24:28):
a lot of research on what's called mechanisms of allocation.
In other words, how can you allocate particular synapses, brain
cell connections and cells to a particular memory and not
another right so how can we get the specificity that
we need in the system. And there's been a flurry
of work in recent years understanding there are certain proteins

(24:49):
that are used to quote label synapses, label particular cells,
and assign them to a one memory and not another.
It's just really brilliant work by some colleagues in the
field that is trying to really get at this specificity question.
Now we're still early days. We don't have final answers yet,
but I think we have some tentitive ideas that you

(25:10):
can with specific proteins that are expressed in the synaps
essentially label them or prime them to be the ones
that are modified by this experience and maybe not another.

Speaker 2 (25:19):
Wow, and that's pretty cool, right.

Speaker 1 (25:20):
Yeah, because from the looment of the time, we thought, well,
how can we ever have any specificity in our brains
if memory just activates cells, how do you know which
cells are the ones that are involved here? And this
might actually re find us with some answers.

Speaker 2 (25:31):
Wow. I feel like I recently heard about the connectome project,
which I think is trying to figure out all of
the neurons. So does this suggest that once we have
a connectome next we need to work on the proteome
that connects to the connectome to really understand how all
of this works, or how helpful is this connect dome
project going to.

Speaker 1 (25:48):
Be very helpful? I think that every time we try
it and map another home it is very helpful. At
some point we all have an everything owned and you know,
with that sort of large scale data effort, we're going
to need also the AI, the machine learning, all of
those tools people to pass through it and actually figure
out what's going on. But it's interesting, you know, Kelly,
When I was coming up as a student, there was

(26:10):
always this question that was asked by faculty in my
department and many other departments, And it's a theoretical question,
and I want to pose that question to you, which is,
if we were to map every single neuron in the
brain and every single connection in the brain, would we
have learned anything about how the brain actually functions? And

(26:30):
whenever they asked that question, you know, some of us
were attempted to say, well, yeah, of course you can
have all the data, right, And the answer they wanted
us to get to is no, you're no better off
because you have a ton of data but no way
to really test hypotheses and understand function. You have to
have the right model, You have to have the right
kind of strategy to go into that data and look
for what's necessary. But I would argue that over the

(26:53):
last twenty thirty years that thinking has evolved and now
we can go in in a completely unsupervised without having
a model, which means also we avoid some of the
biases that might come from a model and ask what
does the data tell us? Sure, there is an explosion
of data, but there are patterns that are hidden in there,
and if you train up AI enough, it can pick

(27:14):
up on those patterns and maybe tell us that there's
a new model. There's a different model. The way that
we were thinking about the brain informing hypotheses may not
have been right all along. So I go back to
things like the connect home projects and trying to resolve
the connect home, the proteome, the epigenome, all of those
kinds of things as different layers of knowledge about the

(27:36):
nervous system. And if we have all of that information,
it stands to reason that we should be able to
pick up on patterns, and patterns can maybe transform the
way that we think about the brain. Maybe we're all
along maybe the brain does quantum computing. Maybe all sorts
of things that we just would have never imagined that
are buried in that data.

Speaker 2 (27:56):
It sounds like an exciting time to be in the field.

Speaker 1 (27:58):
Oh. Absolutely, absolutely.

Speaker 2 (28:16):
I'm going to pull us back a little bit. In
our conversation. You were talking about how you can strengthen
connections between neurons. Does that happen because you're thinking of
the same memory over and over again? And so how
do memories get strengthened and how do we lose some
of them?

Speaker 1 (28:28):
Yeah, So the strengthening of memory, or the idea of consolidation,
which is exactly what it sounds like. It's making memories
more solidified or more strengthened. It can happen because we
are repeatedly rehearsing the memory, so we're thinking about it
over and over. But the good news, Kelly, is that
that happens completely incidentally, without you intentionally trying to do it.

(28:48):
Your brain constantly brings up old memories and thinks about them,
and even if you're not consciously aware of it, it happens
while you sleep at night. Okay, so the brain is
sort of on the back burner, constantly playing through these memories,
replaying through these memories, and even when you go to sleep,
it's replaying through these memories. So the strengthening act of
memories doesn't have to be this intentional thing, which I

(29:08):
think is a really powerful thing to tell students. Also,
you don't have to sit here and like regurgitate and
rehearse everything over and over and over. Just go through
and understand and then get a good night's sleep, right,
which is a lot of them really struggle to do.
But during that period you might think, well, that's just rest.
Actually the brain can be quite active during that period
of time and can be playing through these memories and

(29:29):
storing them and trying to make them morsistant to forgetting now.
One thing to note also is that when you replay memories,
when you bring back memories, you don't end up with
the same thing being stored again. So memories are reconstructive
in nature. If I were to bring back an experience,
say that I have from a few weeks ago and
talk about it with you, what I end up storing

(29:51):
now and reinforcing is a somewhat altered version of that memory.
It's not the same thing, because memory is reconstructed on
piecing together the pieces. Other pieces just get incorporated because
we're having a conversation about it. And then later on
what I remember is some amalgamation of all of those
experiences when I brought it back and changed it ever
so slightly. My colleague here at you see, Aravin Beth

(30:12):
Loftus built her career on studying false memories and how
they arise, and they are very, very frequent. They arise
all the time. We generate the more as we get older,
and they happen just by virtue of our memory being
a reconstructive system rather than a high fidelity video camera
or a picture of reality. It's just a sort of

(30:33):
a Hodgepodg construction of what that reality might have been.
And again we say, why is this happening? Why can't
we have a high fidelity version of things? And it's
possible that we just don't need to. So even with
these false memories arising, they're very artifactual, like you really
need to remember exactly what happened and where it happened,
that when it happened, Ergie, you just need to remember
the core knowledge. So if we focus on, hey, the

(30:55):
corenology is being remembered accurately. That's all that matters. Everything
else and go to crap, and nobody's going to be
less able to survive. So from a survival standpoint, it
certainly doesn't matter that you have this strengthening, be a
very high fidelity strengthening. It just matters that the core
component knowledge is the thing that strengthened, Like the capital
of the United States, Washington, everything else. Who cares.

Speaker 2 (31:16):
But if the lawyer is you priding you for details
in a court case, that's when you're in some trouble.

Speaker 1 (31:22):
Absolutely, and you know the good news is, well, the
somewhare good news is some lawyers, some federal judges, some
jury get the lecture about false memories and understand that
when you call witnesses to to stand and you're asking
very very specific questions, that their right collection is going
to be some combination of what actually happens, what the

(31:42):
brain sort of reconstructed it to be, what kinds of
questions are being asked, the pressure, any interrogation that happened earlier,
All of those things sort of weave their way into
that memory. You're never going to be able to get
this beautiful, accurate, one hundred percent depiction of what happens,
you're going to get some very of it that could
be quite a bit more corrupted.

Speaker 2 (32:03):
Gosh, there could be a whole podcast on that topic.
So my co host wanted me to dig into how
we learn about this kind of stuff. So you mentioned
that there are animal models, but just focusing on people
right now, how good are our techniques for watching how
the brain works in living humans to sort of try
to get a handle on some of this stuff.

Speaker 1 (32:23):
Yeah, So when we started out, the discipline of neuropsychology
had very, very poor tools available to it. So you
have to develop cognitive assessments, which have come a long way.
You can have the right kinds of cognitive assessments and
so on, but you really have to work with patients
and the clinic who come in presenting with memory problems,
with a variety of different conditions, and essentially it's akin

(32:45):
to leision studies. You're working with patients who might have
circumscribed focal deficit in the brain. You can see that
on structural MRI for example, and say this part of
the brain is damaged or missing. Therefore they have this
kind of function, So you might be able to say
something about the function of this part of the brain
in a healthy person. But our tools have evolved significantly since,

(33:06):
so two major advances that I can tell you are
still today. The chief ways by which we study this.
One is functional MRI, and we tend to do a
heck of a lot of that in my lab. So
functional MRI operates on the principle that you can put
somebody in the scanner totally intact brain and give them
a game to play, or a memory task, or any
sort of challenge that would engage the memory bits of

(33:29):
their brain, for example. And what you're imaging with functional
MRI is not neural activity directly. What you're imaging is
blood flow. The idea being that if there's a patch
of cortex patchup brain that is more active, that is
engaged in this challenge, it's going to require oxygen and
glucose and it's going to try to extract that out

(33:51):
of the blood flow. So by mapping how much oxygenated
blood and deoxygenated blood are going to different areas in
the brain, you can generate a contrast because it turns
out that the degree of oxygenation has a different magnetic signal.
So that's sort of a little hack that we pull
in MRI because we're changing ragnetic fields. So by measuring

(34:11):
that contrast, we can get an indirect proxy to where
neural activity might be by virtue of that blood flow change.
So that's been a really, really helpful technique since the
late nineties early two thousands. In the early days of
functional MRI, people did a bunch of like really just
awful studies because the technology was new and we didn't
know what to do with it, and folks didn't really

(34:34):
think beyond you know, the X marks the spot kind
of approach, Right, I want to know what the fill
in the blank part of the brain is. It even
got as absurd as I want to know what the
god part of the brain is. Right, So people start
to do those kinds of studies, try to go in
and say, X marks the spot, where's the stuff happening?

Speaker 2 (34:51):
Is this the same system where they had that dead trout? Oh?

Speaker 1 (34:55):
Yeah, you know that that trout study. Of course. So
at the end of the day, it is a statistic
approach to comparing activation, and yeah, that study is really
compelling because you could show that you see activation essentially
in something that is dead, and people every now and
then will kind of make fun of this, and remember
the old days of fMRI, when folks didn't really know

(35:15):
what they were doing, and you could get something like
this right, and in some cases you can even get
it to be published, which is crazy when you think
about it. But we've come a long way since. So
the beauty of functional MRI now is that one we
understand how to do the X marks the spot much
much better. We now have much better handle on this
historical challenges, the way to build the right contrasts, the

(35:35):
way to correct for multiple comparisons, all the things that
you tend to think of when you're doing large scale statistics.
That discipline had to kind of come to functional imaging
and inform it and that has happened, which is great.
But the second part is I told you before that
memory is all about the connections, and functional MRI initially
was all about blobbology, right, try to find little hotspots

(35:56):
in the brain. You pretty pictures the cover of science
and all that with little hotspots in the brain, and
that was the approach. But we know that memory is
not in the hotspots, memories and the connections, so we've
started to move much more towards connectivity analysis and asking
about how are the different parts of the brain communicating
dynamically and essentially coactivating with each other to support solving

(36:19):
this challenge or doing this memory test or memory game
while you're in the scanner. So that was the advent
of functional connectivity kinds of approaches which are I think
far more compelling, far more robust against some of the
initial critiques of a functional MRI, and they reflect the
true nature of how the brain works. The brain is
one big dynamical system. It's not just regions working in isolation.

(36:41):
Everything is connecting with each other, so we owe it
to ourselves to try to understand it from that much
more complex way. So functional MRI still remains a very
very powerful tool, but now the analysis that we can
do are just far more advanced. The other thing that
I think is just incredibly powerful, aside from anim models,
is the ability to directly record electrical activity from cells

(37:05):
or from what it's called local field potentials that the
areas around cells that have also electrical activity. It can
be measured directly in patients, and these are typically patients
that are going to undergo surgery for epileptic seizures. So
the surgery is done to remove the part of the
brain where the seizures are emanating from. And typically when

(37:26):
they come into a hospital, they're in a hospital for
about a week or so. They get implanted with electrodes
to record from the parts of the brain where the
clinician might suspect that epilepsy is happening, and they're taken
off of anti epileptic medication and essentially they're waiting to
induce a seizure, and once that seizure is induced, they
attract the location. That's how they decide on a way

(37:47):
to do the surgery. There's about a week or so
while they're in the hospital with electrodes penetrating deep into
their cortex and many of those electrodes directly into the
memory bits of the brain, like the hippocampus. And those
are just an incredible group of individuals because they also
most of them want to help science and they understand
the opportunity the scientists have while they're laying in a

(38:10):
hospital bed for about a week to understand something fundamental
about the brain. So every now and then they give
us the opportunity to give them a challenge, maybe on
an iPad or a computer while they're laying there and
they try to solve this challenge, try to play this
memory game or do this memory test while we're recording
direct electrical activity from their brain cells, which is incredible.

(38:31):
So it gives us almost the same degree of information
that you can get in an animal model. Now in
an animal model, in a road that you can stick
more electrones, you can get higher fidelity. And with patients
you have to do things that are only clinically warranted.
So there's an ethical obligation, of course to make sure
that nothing is being done that would ever put the
patient an increase risk. So that also poses some limitations

(38:53):
as to how you can record activity and get that data.
But it's just incredible access that we have to the
brain in partnership with these remarkable individuals, and we've learned
a heck of a lot about how the brain works
and how memory works from those direct electrical recordings.

Speaker 2 (39:07):
Wow. I previously wrote a chapter on brain computer interfaces
and I was reading about like, utah arrays. Is this
the same thing or is this a different kind of electrode.

Speaker 1 (39:17):
Yes, So, utah arrays are one way to do it.
Utah arrays are a little bit more invasive. They involve
several electrodes that are kind of going through the surface
of the cortex. At the same time, they're no longer
kind of the standard practice for most patients. They're still
used in some cases where they're clinically warranted, but in
many cases they're not because you suspect that what's happening

(39:39):
is deep into the brain, so you stick direct single
electrodes all the way down to where you suspect the
action might be, and you avoid some of the potential
damage that happens with UTAH rays. So they're used in
some clinical contexts, but in many others, we can stick
these much thinner, slimmer electrodes directly into the parts of
the brain that we suspect yet epilepsy is ennything from

(40:01):
so far less damage that way, and those patients typically
have better outcomes than patients implanted with guitar rays. Now,
your point about BCIs, and there's a number of companies
out there that are trying to develop brain computer interfaces
using these kinds of arrays. I think that's a particular
challenge for those enterprises is how do you create a
way to measure directly from the brain and to be

(40:23):
able to stimulate and influence the brain without causing too
much damage. Having electrones that are thin enough, that are
made from the right material so that you don't cause
a lot of tissue damage, because ideally, what you want
to do is create an interface that helps people, so
you don't want to inadvertently cause more damage.

Speaker 2 (40:40):
Now, when we were thinking about UTAH rays and damage,
you know, we thought about like a cup with jello
in it, and you stick some needles in there, and
as you move the jello around, if the needles are
kind of staying in place, that would sort of mess
up the brain. Is that a good way to think
about it? Does it all move together?

Speaker 1 (40:55):
Yeah? The brain certainly is as vulnerable maybe as a
cup of gello. But the key is also flexibility. So
you're right. When you have these electrodes, there's a bit
of a compromise. So want them to be flexible so
that they're moving with their brain. You're absolutely right, and
that'll cause less tissue damage. But at the same time,
flexibility you can come at a cost, which is what

(41:16):
they're targeting, might change. So you want to make them
flexible enough sort of they don't cause damage, but rigid
enough so that they can continue to target the same region,
so it is not an easy challenge at all. But
there's been some developments recently in doing these kinds of
arrays with animals, and we haven't yet pourted that over
to humans and done the FD approval and all of
those kinds of things. It's happening soon. There's already experiments

(41:39):
that try to test out one of the technologies like
neuropixel for example, or near epixels technologies. Those have been
incredibly powerful for animal models for reading from road insight
from non human primates and their small form factor. They're thinner,
but they have a ton of electrode contacts on there,
so it can really give you information from a lot
of different sounds simultaneou sleep. And pointing that over to

(42:02):
humans I think will be a really helpful thing to do.
But that's only been done in some limited experiments and
not widespread. You so hoping that some variants of those
kinds of technologies will make us way to primetime soon.

Speaker 2 (42:12):
I've watched some videos of people with brain computer interfaces
that were able to do incredible things, But one of
the things that sounded totally devastating to me was if
I understand this correctly, it's over time, the brain has
a response to those electrodes and like kind of walls
them off and the connection gets less good. I don't
know exactly what's happening. Do we have any progress in
that area.

Speaker 1 (42:32):
Well, so that's another thing that needs to be tackled. Also,
with some of these newer silicon probes, they're less likely
to have the inflammatory and the calcification kinds of responses
that happened around electrodes, because remember, this is a foreign
object entering the brain, and the brain's natural disposition towards
foreign objects is attack it, right. That's why we have
brains immune cells, we have microglia, we have a lot

(42:54):
of cells that are dedicated to detecting and eliminating foreign objects.
So you tend to see them of aggregate around electrodic
contact locations and things like that. But there are ways
with different substances to kind of maybe fool the brain
a little bit into thinking this is okay. You can
try to also reduce the brains immune response to some
extent when these things are coming in. So there's approaches

(43:16):
that are being developed to try to get better long
term outcomes, but yet we're still very early.

Speaker 2 (43:20):
In this game, And for listeners who are maybe not
es familiar with brain computer interfaces, what are some reasons
that people might get a brain computer interface.

Speaker 1 (43:28):
There's a variety of reasons. So, for example, for someone
who has lost the ability to control their limbs because
of a stroke or a focal deficit, being able to
have a brain computer interface shortcut signals so that they
can still control their limbs and their body is remarkable.
And patients who have had those kinds of approaches, it
is just life changing. They go from a paraplegic or

(43:49):
quadriplegic to being able to have use of their arms
or their legs again. So there's incredibly utility there. For
folks who might have epilepsy. For example, there is a
brain computer interface that is a stimulator that is implanted
in the brain that responds to the earliest science of
epileptic seizures and that is able to with electrical stimulation

(44:11):
essentially knock it out. So now instead of having to
have the person be going in for surgery and lomping
up parts of the brain or having them be devastated
by epileptic seizures, you can have an implanted BCI that
responds in a closed loop system, so it uses the
responses of the brain itself to tell the stimulator what
to do. And that's a completely closed loop, so it

(44:32):
doesn't require any user interventionally outside. That allows it to
do a much better job of helping the patients overcome
seizures or epilepsy. So there's a number of different uses.
I can imagine that for movement disorders, for a variety
of different conditions where you might want to implant something
that communicates with the brain and feeds at the right
signal at the right time, there's going to be a

(44:53):
huge use for a BCI. Then there's a whole other
class of uses that may not work vire implantation. Right,
So these external devices maybe devices that are communicating with
the brain and external fashion portable or multiple, and they
allow it to improve function for stroke rahabilitation, or improve

(45:15):
function in some other way. There's a lot of folks
also kind of you know, taking the transhumanist approach here
and trying to develop PCIs to just improve our function.
We just want to be better at something, right, So
what if I can control this robotic arm to do
some you know, whatever it is. So don't care too
much about those but certainly the utility for helping patients
is huge.

Speaker 2 (45:34):
So getting a little more sci fi here, do you
think we'll ever be able to know what somebody is
thinking by having, you know, a cap on their head
or electrodes in their brain or is that just way
too far off?

Speaker 1 (45:46):
I think we already do so. I think we are
to some extent with an electrocapsule. Egen is really the
technology that you're talking about, or there's other ways to
do it also, various ultrasound technologies and so on. You
can detect and stimulate pretty easily, but the problem is
the kinds of things that you can get the system

(46:06):
to do are still fairly rudimentary. So I can tell,
for example, based on eg signal whether the person is
going to move their hand or make some overt kind
of gesture, and motor control is a somewhat simpler system
than like memory, executive decision, or emotion or having very
complex feelings like guilt, right or things like that are

(46:29):
much more difficult to capture in the simple signals that
we're capturing. The BCIs right now. So do I anticipate
that at one point we'll be able to do one percent?
There's no doubt the technologies there. It's just a matter
of are we recording from enough are we able to
build the sophisticated models to model this function, and we're
making rapid progress in that arena. So from a sci

(46:51):
fi perspective, I'm sure you've heard this before. The moving vehicle,
the car was sci fi at one point until someone
invented it, right, So the things that we think about
a sci fi are just science that's not here yet.

Speaker 2 (47:02):
All right, Yeah, the future is now. So let's talk
about losing memory a little bit as we wrap things up.

(47:24):
So we talked about how your brain is working overnight
to strengthen memories. How do we lose memories over time?

Speaker 1 (47:31):
So there's a number of different ways to do this.
Memory can be lost because of decay, so just the
passage of time a lot of times can make memories
just harder to remember, harder to access. And we've known
this since eighteen eighties. Herman Ebbinghouse was the first to
kind of do this using experiments with himself. You would
learn lists of nonsense syllables and then try to map

(47:54):
his own forgetting curve. So how much forgetting happens over
the first twenty four hours, next twenty four hours, next
twenty four hours. Yeah, I know, experiments on yourself very
very boring times in eighteen eighty so it didn't have
too much else to do, so I did this with himself,
but maps what's called the forgetting curve, which we still
to this day. We can look at any sort of
memory function or any memory task that we do in

(48:14):
the lot and we see a very clear forgetting curve.
A lot of forget the first twenty four hours. Then
things to kind of taper off. So there's that, And
the suspicion is that mostly it's decay, but sometimes it
happens because of interference, because similar memories get in there
and kind of interfere with one another, compete with one another,
sort of the memory that you have for them get
a little bit fuzzy. And again these are maybe features,

(48:36):
not bugs, right where maybe the system is not intending
to hold onto memories with high fidelity for long. So
interference and decay help us extract what's most important and
keep that over time, and then other things can kind
of go away. So those are natural things that happen
in every brain all the time, and there's nothing to
be concerned about decay, interference, nothing to be concerned about.
But as we get older, and by older I hate

(48:59):
to say this, you know, talking about like forties.

Speaker 2 (49:01):
And above that what I wanted to hear money, Well,
I'm going to.

Speaker 1 (49:06):
Say graduate in our fourth decade and then maybe a
little bit more precipitously, over time, memory does get more difficult.
So things do degrade, and we start to maybe lose
to some extent, our ability to make new memories, encode
new memories, our memories. For the old stuff is still
there's still resilience, even though every now and then we
might have a problem with access. So we get distracted,

(49:28):
we lose retrieval cues, but you know it's there because
if you get the right reminder, boom, it comes back. Right.
It's just a matter of like tip of a tongue,
you know, being able to remember exactly that the right
queue for retrieval. That becomes more difficult when we're just
more distracted. But as we get older, making new memories
becomes harder. And then for some folks who might go
down the trajectory to Alzheimer's disease, right then that becomes

(49:52):
exceptionally more difficult. And that's one of the first things
to go. And there's a very difficult line between what's
normal I hate to say that word, maybe more typical
age associated memory impairment, which you can expect in every brain,
and that's something that may be a bit more costs
for concern because it may be going down to about
the Alzheimer's disease. Dissociating those two, say in the sixties

(50:14):
and seventies, is actually very difficult. It's not very easy
because both can start out as a form of forgetfulness.
But with Alzheimer's disease or with dementia, it's very progressive,
so it does get worse and worse and worse over time.
That change in a healthy aging brain or a typical
aging brain is far less deep, so you don't see

(50:34):
too much changing over time. You don't see this degradation
to the point where it becomes very noticeable by family, friends, neighbors,
and so on. So those are the forms of memory
loss or memory change that happened. Some totally innocuous, no
cause for concern, they happen every day to everyone, to
the best of us. And then some that are a
bit more cause for concern.

Speaker 2 (50:54):
As we get older and mechanistically, is it just the
messages are not getting sent between those anymore, or this is.

Speaker 1 (51:01):
Something we've done quite a bit of work on. Actually mechanistically,
what seems to be the case is that first the
part of the brain that's really important for encoding these
episodic memories, the hippocampus, as I said, has a very
interesting change and it's dynamic. So this is a massive
information processing hub in the brain. Even though it's a
small structure, it carries a big information processing load, and

(51:24):
it kind of can shift its state from encoding new
information to remembering old information. And there are a few
changes that happen to the cells in that system as
we get older that bias the system towards remembering old
information and away from encoding new information. And there's lots
of sort of reasons why that is, we tend to
change the excitation inhibition balance, we tend to change neurotransmitter concentrations,

(51:49):
all of those kinds of things as we get older
that cause that change in the information processing balance. But
the other thing that happens more in the context of
Alzheimer's disease is you also start to deprive the hippocampus
of its main input coming in from the rest of
the brain. So there's a region that sits alongside the
hippo campus called the antorhinal cortex, and that region shrivels

(52:11):
up in Alzheimer's disease. It's one of the first regions
to deposit what's called tangle pathology or tau tangles, and
that's a marker of cell death. So there's massive cell
loss that's happening in that's around cortex early on, which
deprives the hippocampus of its principal inputs. So in computer
science we have this old adage called garbage in garbage out,

(52:33):
and that's essentially what's happening in the hippocampus. It's the
quality of the information that's coming in starts to become
much more degraded than the context of Alzheimer's c's, So
we can't possibly expect it to do a good job
encoding information and story with high fidelity if the information
coming in is in some ways quote garbage. So that
tends to be one of the things that is also

(52:54):
mechanistically associated with memory loss in the aging brain.

Speaker 2 (52:57):
Do we know why that region starts to degree in
some people and not others.

Speaker 1 (53:01):
You know, there's hypotheses and I have my pet hypothesies.
In the field has its pet hypotheses and so on,
But there's a variety of contributors. We suspect that in
the context of Alzheimer's disease, it's a combination of inflammatory changes,
so that the mirror immune system is disregulated in Alzheimer's disease,
where the inflammatory response that normally is very healthy starts

(53:22):
to kind of take a turn and become very pathological.
There is vascular damage that happens as we get older,
and we suspect that some of those early vascular insults,
so related to blood flows, deifenning of the arteries and
so on, can also contribute to that. There's metabolic regulation
that changes, so the metabolic demands of different regions also
becomes disregulated as we get older. And then one thing

(53:45):
that we've worked quite a bit on is excitation inhibition
balance and the notion that normally the brain keeps this
dynamic beautifully between stop signals and ghost signals, and as
we get older there actually is an overabunton of the
ghost signals which can drive the brain pathologically more towards
memory loss and not enough of the stop signals, so

(54:08):
that imbalance can also be a contributor. So it's a
multifactorial issue. There's lots of contributors. This is not just
one single pathology kind of model, as much as some
of the field likes to believe that. It's a bit
more complex.

Speaker 2 (54:20):
So as someone who just learned that they're in the
old category, I.

Speaker 1 (54:24):
Would necessarily call it that. I would just say, we're
maybe done developing and we're now just kind of hitting
that hump of we're going to start the aging process.

Speaker 2 (54:32):
Got it, got it, I'll think of it that way.
But I like that better. What kinds of science based
things can we do to maintain our memory? So I
see all these apps, pitch me, is there any science
behind any of those things?

Speaker 1 (54:45):
Well, the app stuff probably not. I will tell you
that the four big things that are really really important,
and when I say really important, I mean they are
supported both by epideological data and by clinical trials. So
these things are really really helpful. The first one is
physical activity. We know that physical activity maintains brain health
well into older adulthood. We know that it can delay

(55:06):
the onset of Alzheimer's disease. It can make the outcomes
better for patients and as protective it really is knocking out.
So sedentary lifestyle is a risk factor. We've done work
also to show that even activity as brief as ten
minutes of walking can be helpful to memory. So it
doesn't take a lot, you know, I would say thirty
minutes of you know, mild to moderate activity like walking,

(55:28):
risk walking, that's sufficient to be able to give people
a way to handle that risk factory. The second thing
that's really important, and this kind of goes back to
your idea about apps and kind of cognitive engagement. It
turns out that apps and brain games on all of
that efficacy is a little bit tendless, so there's conflicting reports.
But we know that social engagement is really important. So

(55:49):
in other words, if you remove social engagement, if folks
become isolated the same past retirement, that's a risk factory
for sure. But if they're able to continue to be
social build archer social networks in person, you know, volunteering,
community centers, churches, synagogues, whatever it is, or being around
people in general, and that can also combine with physical activity.

(56:10):
So let's say it's dance class now, it's physical activity
and social contact. Right, those kinds of things, even in
interventional studies, have been shown to have very positive results.
Then the third piece is diet. A heart healthy diet
is a brain healthy diet. And the one that has
been tried and true in clinical trials is the Mediterranean diet.
So the Mediterranean which has lots and lots of variants,

(56:31):
but I think very colorful, leafy, green vegetables and so on,
healthy fats, and reducing you know, things like red meat
and some on. So that one also has been tried
in clinical trials compared to other diets and seems to
be able to stave off risk. And then the last piece,
which I think is one of the most important, to sleep.
We all need good quality and quantity of sleep every night.

(56:54):
It turns out that actually during sleep we go through
a process of glymphatic clearance and we clear out on
the life lot of the pathologies that can lead down
the path to Alzheimer's. These or at least be contributors
to it. And studies have shown that if you have
sleep loss folks for example, who sleep less than six
hours a night versus those who sleep more than seven
or eight hours there's differences in their amyloid uptakes, so

(57:16):
that emiloid pathology is one of the chief pathology in
Alzheimer's disease. You see a lot more of it in
those who sleep those fewer hours, and a lot less
of it and those who sleep longer. So sleep disruption,
sleep loss, that's a risk factor. The good news is
most sleep problems are treatable, whether it's because of obstructive
sleep apnea, or insomnia or any other reason, restless slag,

(57:38):
all of those things. There's good treatments out there that
will help people sleep better. So those are the four
sort of chief things. There's many other smaller things, but
those are the four ones that I like to lead
with because they have just excellent data in their favor.

Speaker 2 (57:50):
Well, I'm excited about the sleep thing. I like sleeping.
Maybe it's time to get out and exercise a little
more so. My co host is a physicist. He always
ends on a aliens. So here we go. If an
alien were to land on Earth today, do you think
they would store memories in a similar way.

Speaker 1 (58:08):
You know, if you had asked me that question ten
years ago, I would have said, yes, I think our
memory system is exceptional. It's wonderful, it's brilliant. Why not
they should be like a model to strive to achieve.
But I will take the opportunity since we've got a
couple more minutes, Kelly, and tell you about something that
changes my answer to this question. And that is the
discovery that was made first by James Magaw who is

(58:30):
the founding director of my center here at uc Aervine,
and we continue to do work with this group of
remarkable individuals who have what's called highly superior autobiographical memory.
We spent a lot of time during this conversation talking
about how memory is fallible. There's forgetting, there's interference. It's
not meant to store everything with high fidelity because that's
going to compromise your knowledge generation and so on. Well,

(58:52):
these folks would beg to differ. And it's incredible because
they do store things with high fidelity. They can remember
everything that happened in our lives since that they were
teenagers and tell you exactly what happened on what day
of the week, what month, and someone. And they don't
have a problem extracting generalities and knowledge. Also, So sometimes
I'll jup with them and say I think you're like

(59:13):
the X men of our generation, X people of our generation.
It's remarkable and we still don't understand how they do
it and how their brains are wired differently. So if
aliens sufficiently advanced to aliens, I think, if they're reaching
Earth before we reach them, they're probably far more advanced
than us. They're more likely to have figure it out
a way to do that which sort of combines the

(59:34):
best of what we have built into our computers and
what we have built into our brains. Just no compromise,
no sacrifice.

Speaker 2 (59:41):
Awesome. Well, I wish Daniel we're here to hear that,
but I'm sure he'll enjoy hearing that explanation when he
gets back. Thank you so much for your time, Mike.
This was absolutely fascinating.

Speaker 1 (59:50):
They're very welcome. I very much enjoyed to Kelly. Thank you.

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