Latest / Daniel and Kelly’s Extraordinary Universe / How Does Memory Work? (Featuring Dr. Michael Yassa)

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How Does Memory Work? (Featuring Dr. Michael Yassa) · Daniel and Kelly’s Extraordinary Universe

0:05
Speaker 1: The analogy that I like to use for this is
0:08
Speaker 1: imagine you are at a club and there's lots and
0:11
Speaker 1: lots of noise going on, lots of things going on,
0:13
Speaker 1: lots of people talking to each other, there's loud music
0:16
Speaker 1: and so on, and you're trying to communicate something to
0:19
Speaker 1: somebody who's dancing alongside gm, and it's very, very difficult
0:22
Speaker 1: because of all of that noise. But now you get
0:25
Speaker 1: real close to them and you kind of, you know,
0:26
Speaker 1: hold your hand to their ears and you start to
0:28
Speaker 1: talk directly into their ears. Now they're going to receive
0:32
Speaker 1: that communication with much higher fidelity, be able to tune
0:34
Speaker 1: out noise and selectively attend to that communication. You've enhanced
0:38
Speaker 1: the communication between that person and the person they're talking to.
0:42
Speaker 1: That's what happens at synapses. There's lots and lots of
0:45
Speaker 1: synoptic firing, lots and lots of communication happening. But when
0:48
Speaker 1: cells start to attach to each other, they communicate much
0:51
Speaker 1: more preferentially. They can transmit signals that express that form
0:55
Speaker 1: of learning. In other words, if there's an experience that
0:59
Speaker 1: happens that is learned by the brain, the brain can
1:02
Speaker 1: express a form of plasticity or a form of memory
1:06
Speaker 1: in the strength of the connections. So if the connections
1:09
Speaker 1: grow stronger, that's a signal that this memory has been learned.
1:12
Speaker 1: And most of the information that we have about this
1:15
Speaker 1: comes from animal models, comes from slice recordings where we
1:18
Speaker 1: can see evidence for enhancements in the connectivity, enhancement of
1:22
Speaker 1: the communication between cells as a result of a learning experience.
1:26
Speaker 2: You've reminded me why I hate clubs. I'm sorry, no
1:29
Speaker 2: one invites me to them anymore.
1:31
Speaker 1: I share that with you. Hi, I'm Daniel.
1:46
Speaker 3: I'm a particle physicist, and every day I rely more
1:49
Speaker 3: on my computer's memory instead.
1:50
Speaker 1: Of my own.
1:53
Speaker 2: Yeah, I am Kelly Leader Smith. I'm a biologist, and
1:55
Speaker 2: I'm having a lot more of those moments where you
1:57
Speaker 2: walk into a room and think why am I in here?
2:04
Speaker 3: I walk around campus here at you see Irvine and
2:05
Speaker 3: a lot of folks go hey, Professor Whitson, and I
2:08
Speaker 3: go hey, and I think I have no idea who you.
2:10
Speaker 1: Are and why we know each other.
2:13
Speaker 3: And sometimes it's just because they were in a class
2:15
Speaker 3: I taught with four hundred people, and the relationship is
2:17
Speaker 3: a little axometrical. And sometimes it's just because my memory
2:20
Speaker 3: is terrible, and maybe we hit coffee and I've forgotten,
2:23
Speaker 3: So I apologize to folks out there who I'm pretending
2:27
Speaker 3: to recognize.
2:28
Speaker 2: Yeah, yeah, no, I'm there also, And every once in
2:30
Speaker 2: a while be standing in the grocery store and I'll
2:32
Speaker 2: stand in front of the aisle for a little too
2:33
Speaker 2: long and my daughter will go, you forgot, didn't you. Yeah,
2:38
Speaker 2: I have no idea what I'm looking for right now.
2:40
Speaker 2: And hopefully this doesn't give us too much anxiety thinking
2:44
Speaker 2: about what the root cause of our memory problems are.
2:47
Speaker 3: I have that as well. Is that a memory issue
2:50
Speaker 3: or is that a distraction issue? Like where you're looking
2:52
Speaker 3: for capers, but then you see a jar pickles and
2:55
Speaker 3: it makes you think about that last time you had
2:56
Speaker 3: a pickle, and then you're like, m I wonder if
2:58
Speaker 3: you can pickle at home. And then five minutes later
3:00
Speaker 3: you're dreaming about a whole pickling building in your backyard,
3:03
Speaker 3: and you've forgotten that you were looking for capers.
3:06
Speaker 2: So I don't like pickles. So no, that's not my scenario.
3:09
Speaker 2: But sometimes it'll be like, you know, I see my
3:11
Speaker 2: reflection in a bottle, and I'll be like, oh, is
3:13
Speaker 2: that spot skin cancer? When am I gonna die.
3:15
Speaker 1: There we go?
3:16
Speaker 3: Yeah, exactly, but.
3:18
Speaker 2: It is often distraction instead of forgetfulness. But yeah, sometimes
3:22
Speaker 2: it's hard to disentangle those things.
3:24
Speaker 3: Well, I just learned something deeply troubling about you that
3:26
Speaker 3: you don't like pickles.
3:28
Speaker 2: What you know, Daniel, You've made a really great point
3:31
Speaker 2: about your memory, because we have definitely talked to about
3:36
Speaker 2: and I think even on the show, we've talked about this.
3:39
Speaker 3: That's embarrassing, but not as embarrassing as being closed minded
3:43
Speaker 3: to the wonderful world of pickles. I'm with you, like
3:46
Speaker 3: the big deal pickle, okay with the sandwich, but I'm
3:48
Speaker 3: not munching on one in general. But have you ever
3:50
Speaker 3: done home pickling, you know, like you can pickle cauliflower
3:53
Speaker 3: or carrots.
3:54
Speaker 1: It's really wonderful.
3:55
Speaker 2: The only pickled item I've ever enjoyed is Cowboy candy,
3:59
Speaker 2: which which is when you slice of really hot halopanos
4:02
Speaker 2: and put them in like a sugar pickle. Oh so good.
4:06
Speaker 2: That I love on sandwiches. Other than that, I have
4:08
Speaker 2: not met a pickle that I like.
4:09
Speaker 3: I'm sorry, I have to work on that, all right.
4:11
Speaker 2: Okay, all right, well, I'll keep my mind open. But
4:14
Speaker 2: today we got a wonderful question from our listener, Simon,
4:18
Speaker 2: who is interested in memory, and so let's go ahead
4:21
Speaker 2: and listen to Simon's question.
4:22
Speaker 4: Now, Hi, Daniel and Kelly. This is Simon from New York.
4:28
Speaker 4: I was a huge fan of Daniel and joege Explain
4:30
Speaker 4: the Universe. However, I am loving the new show with
4:33
Speaker 4: Kelly and never missed an episode. Here's my question, I
4:37
Speaker 4: think mainly for Kelly. I am now into my seventies
4:42
Speaker 4: and not surprisingly find myself reflecting a lot on my
4:46
Speaker 4: life and the thousands, perhaps millions of memories that go
4:50
Speaker 4: into a lifetime. I have often wondered exactly how the
4:54
Speaker 4: human brain, using biological substances, chemicals, and electricity, actually doors memories.
5:01
Speaker 4: I have tried to read about this, but have not
5:04
Speaker 4: found anything to satisfy my curiosity or wonder Perhaps this
5:09
Speaker 4: blurs too much into the question of what is consciousness
5:12
Speaker 4: and sentience and it's not something you want to delve into.
5:16
Speaker 4: But if you would like to tackle it, I would
5:18
Speaker 4: love to hear about what insights biology and physics have
5:22
Speaker 4: to offer. I have very recently been reading a lot
5:26
Speaker 4: about computers, trying to understand how they really work and
5:30
Speaker 4: that seems somewhat related, but only somewhat anyway, Thanks to
5:35
Speaker 4: both of you for all you do. My weeks would
5:38
Speaker 4: not be complete without listening to your podcast episodes.
5:42
Speaker 2: All right, Simon, we love your accent.
5:44
Speaker 1: We do.
5:45
Speaker 2: I grew up in New Jersey and I miss hearing
5:48
Speaker 2: that accent more often, so that was awesome, And thank
5:51
Speaker 2: you for this fantastic question. And we got really lucky.
5:54
Speaker 2: So folks, remember we talked in the past about whether
5:58
Speaker 2: or not tripped a fan from Turn he actually makes
6:00
Speaker 2: you sleepy on Thanksgiving and we interviewed Mark Mapstone for
6:04
Speaker 2: that and he suggested that if we were interested in memory,
6:07
Speaker 2: we should talk to his colleague, and his colleague was
6:09
Speaker 2: willing to come on the show. So on today's show
6:12
Speaker 2: we have doctor Michael Yassa. He's a professor at the
6:15
Speaker 2: University of California, Irvine, where he's also the director of
6:19
Speaker 2: the Center for the Neurobiology of Learning and Memory and
6:23
Speaker 2: is the director of the UCI Brain Initiative. So like
6:27
Speaker 2: clearly the perfect person for this topic.
6:29
Speaker 3: Yes, amazing, and also it's one more notch on my
6:32
Speaker 3: personal goal to have my entire neighborhood on the podcast.
6:36
Speaker 3: For those of you who don't know people that you
6:38
Speaker 3: see Irvine. Many of us live in this faculty neighborhood
6:41
Speaker 3: right next to campus, so we're all friends and neighbors
6:43
Speaker 3: and we know each other. And by now we've had
6:45
Speaker 3: a significant fraction of that neighborhood on the podcast. Because
6:49
Speaker 3: I want to know, like, hey, who's an expert flight
6:51
Speaker 3: I'm like, oh, I know that guy who's on the
6:53
Speaker 3: next street. And so it's a fantastic resource.
6:56
Speaker 2: That is pretty great. So let's go ahead and bring
6:58
Speaker 2: Mike on the show. But we should mention you were
7:00
Speaker 2: off telling people about your amazing research ideas, so you
7:03
Speaker 2: were not able to join us for this interview. So
7:06
Speaker 2: I flew solo with Mike.
7:07
Speaker 3: Thanks very much for handling this while I was goofing
7:09
Speaker 3: around in the area my pleasure.
7:12
Speaker 2: I had a blast. All right, Welcome to the show, Mike,
7:17
Speaker 2: Thanks for being with us today.
7:18
Speaker 1: Thanks for having me.
7:20
Speaker 2: So what got you interested in studying memory? Let's start
7:22
Speaker 2: by getting to know you of it?
7:24
Speaker 1: Sure, So, I don't think that I really knew much
7:28
Speaker 1: about memory when I was an undergraduate. I was fascinated
7:31
Speaker 1: by the brain just by virtue of taking a couple
7:33
Speaker 1: of classes that kind of inspired that passion, that love
7:36
Speaker 1: for everything brain related. And one of the things that
7:40
Speaker 1: was really fascinating about it is that I felt, even
7:42
Speaker 1: at the time, this was in the late nineties, that
7:44
Speaker 1: we knew next to nothing. Unlike other classes that I took,
7:47
Speaker 1: where there was sort of a big body of knowledge,
7:49
Speaker 1: it felt like with the brain, there's just so much
7:52
Speaker 1: more that we really didn't understand. So that became really fascinating.
7:56
Speaker 1: As I started to dive a little bit more deeply
7:57
Speaker 1: into different aspects of how the brain functions, memory came
8:01
Speaker 1: about as one that was front and the foremost, particularly
8:04
Speaker 1: because we started to see or I started to see
8:07
Speaker 1: that memory loss is just very devastating, unlike any other
8:11
Speaker 1: cognitive domain that if you know, if you have attentional
8:15
Speaker 1: deficit or if you have a deficit with executive function,
8:19
Speaker 1: you know, that can be somewhat circumscribed. It's a contained
8:22
Speaker 1: kind of deficit, not memory loss, which just utterly devastating,
8:26
Speaker 1: you know, seeing patients with Alzheimer's disease, seeing patients with
8:30
Speaker 1: various forms of memory loss, that was really compelling, and
8:33
Speaker 1: I started to understand a bit more that memory is
8:36
Speaker 1: what makes us who we are. It's so fundamental to
8:38
Speaker 1: our core. It's the essence of our consciousness. Everything that
8:41
Speaker 1: we do we do because of some experience that we've
8:43
Speaker 1: had that we've been able to store, and it just
8:46
Speaker 1: became not just fascinating, but like entirely all consuming. So
8:50
Speaker 1: I focused on memory from all of its aspects. One
8:54
Speaker 1: is trying to understand it's fundamental inner workings, and too
8:57
Speaker 1: trying to understand how it breaks down in a variety
8:59
Speaker 1: of differ and conditions. And if we can do that,
9:01
Speaker 1: maybe we can help people. Yeah.
9:03
Speaker 2: I've got a neighbor with Alzheimer's and it's been totally
9:06
Speaker 2: devastating for the two of them. So yeah, So this
9:09
Speaker 2: interview was inspired by a question that we got from
9:11
Speaker 2: the listener and one of the things that they asked
9:14
Speaker 2: about is does the concept of memory blur the line
9:17
Speaker 2: with consciousness and sentience? How do you view these concepts?
9:22
Speaker 1: Yeah, you know, it's interesting. There's a somewhat related question,
9:25
Speaker 1: which is, you know you can have a computer have memory.
9:28
Speaker 1: When we talked about memory and a computing platform in
9:31
Speaker 1: a robot or a botic application, certainly when you think
9:34
Speaker 1: about chat GPT, well that can hold on to memory
9:36
Speaker 1: for some period of time and use that to guide
9:39
Speaker 1: how it responds to the us there and so on.
9:42
Speaker 1: So memory in and of itself may not be the
9:45
Speaker 1: thing that I would say as associated with sentiens. I
9:49
Speaker 1: think that it's the way that our memory works, not
9:52
Speaker 1: just as humans, but as sort of you know, live organisms.
9:55
Speaker 1: It's not like the way that you would do it
9:57
Speaker 1: in a computer. So let me elaborate. Memory is stored
10:01
Speaker 1: in a computer is very much one to one. Everything
10:05
Speaker 1: that you see and learn, your storing with incredibly high fidelity.
10:09
Speaker 1: You try to retrieve it twenty years from now, thirty
10:11
Speaker 1: years from now. It's exactly to say there's no degradation.
10:14
Speaker 1: But that creates a problem for a memory system, and
10:17
Speaker 1: that it's more difficult to extract generalities. It's more difficult
10:20
Speaker 1: to generate knowledge based on memory. But say as a
10:24
Speaker 1: human and you're encoding memories all the time. These memories
10:27
Speaker 1: are stored, but we know that there's blurriness of memories,
10:30
Speaker 1: there's forgetting of memories. There's all sorts of things that
10:32
Speaker 1: we tend to think of as memory problems, but in
10:36
Speaker 1: fact one could argue they're not bugs, they're features of
10:39
Speaker 1: the system. Because memory is not intended to be a
10:42
Speaker 1: super high fidelity kind of system. It's intended to get
10:45
Speaker 1: enough information in so that you can generalize knowledge, so
10:49
Speaker 1: you can learn from experience and be able to guide
10:51
Speaker 1: your future decision making. So, while a computer's memory is
10:55
Speaker 1: really about storage, with high fidelity, you don't want to
10:58
Speaker 1: write a filin word and then store and then later
11:00
Speaker 1: on have an abstract version of it rather than what
11:02
Speaker 1: you actually wrote. You want to have an accurate record
11:04
Speaker 1: of what you actually wrote. But for the brain, what
11:07
Speaker 1: you might want to get later on is that abstract version.
11:10
Speaker 1: It's just enough knowledge to be able to guide your
11:12
Speaker 1: future decision making. And that's the reality of how memory
11:16
Speaker 1: evolved in live organisms. And maybe the thing that makes
11:19
Speaker 1: it very different from nonsensient beings is that it never
11:23
Speaker 1: really evolved to think too much about the past. It
11:27
Speaker 1: evolved almost entirely to think about the future. So the
11:30
Speaker 1: reason why you might store something is because you want
11:33
Speaker 1: to use that knowledge to guide future decision making, to
11:36
Speaker 1: make sure that you do things that are adaptive to
11:38
Speaker 1: promote your survival. You're not going back to the same
11:40
Speaker 1: poison as berry bush. You know, to run from a
11:42
Speaker 1: bear out in the wild, as supposed to go up
11:44
Speaker 1: and say Hello, those kinds of things are based on memory,
11:47
Speaker 1: equipping us to make better predictions for the future.
11:50
Speaker 2: So can we dig in a little bit more to
11:52
Speaker 2: this trade off? So why can't you remember everything perfectly
11:57
Speaker 2: and generalize when the time is right.
12:00
Speaker 1: Yeah. So it turns out that you can mathematically and
12:03
Speaker 1: computationally model this and it gives you a pretty straightforward answer.
12:07
Speaker 1: And the way that it works is that if you
12:09
Speaker 1: were to encode every single experience that you have in
12:12
Speaker 1: a very high resolution and high fidelity kind of approach,
12:17
Speaker 1: then it becomes very difficult to generalize that to new situations.
12:22
Speaker 1: The representations in the brain become almost hyper specific. They're
12:26
Speaker 1: very very specific to those instances in which they were encoded.
12:29
Speaker 1: So being able to extract the generalities or the knowledge
12:33
Speaker 1: that you can apply to new things requires that there's
12:36
Speaker 1: enough blur, enough fuzziness across the different instances so you
12:40
Speaker 1: can generalize that knowledge. I'll give you an example. If
12:43
Speaker 1: I were to ask you what is the capital of
12:44
Speaker 1: the United States, you'd have a very very quick answer
12:46
Speaker 1: for me, which is Washington, d Z Exactly. Now, if
12:50
Speaker 1: I ask you, when did you first learn that?
12:54
Speaker 2: Now don't know.
12:56
Speaker 1: So now if I had asked you the day right
12:58
Speaker 1: after you first learned that, be in class or maybe
13:01
Speaker 1: from parents, you would have a pretty good memory for it.
13:03
Speaker 1: That's a pretty exciting thing that you just learned. But
13:05
Speaker 1: the reality is you've learned it so many times over
13:08
Speaker 1: so many different exposures. You've heard in a million times
13:11
Speaker 1: in many different settings. And what's most important is not
13:14
Speaker 1: so much the first time you heard it or the
13:16
Speaker 1: last time you heard it, but the fact that you
13:19
Speaker 1: extracted that piece of knowledge, that core piece of knowledge
13:22
Speaker 1: out and now that's part of your body of knowledge.
13:25
Speaker 1: So the specifics around how and when and where we
13:28
Speaker 1: encoded specific things may not be all that important from
13:32
Speaker 1: an evolutionary standpoint to hold on to as the memory
13:36
Speaker 1: for the actual knowledge is important. That's what's going to
13:39
Speaker 1: guide your future action. That's what's important to generalize the
13:43
Speaker 1: new situations. So in some ways there's no evolutionary pressure
13:47
Speaker 1: to hold on to the specifics over time. But it
13:50
Speaker 1: is an interesting point like why can't we have both? Well,
13:53
Speaker 1: you can think about it from an energetic standpoint. If
13:55
Speaker 1: you have a limited resource system, why would you invest
13:58
Speaker 1: your energy into storing the specifics when you know you're
14:01
Speaker 1: not going to use them down the line.
14:02
Speaker 2: Yeah, no, fair enough. So you mentioned the analogy of
14:06
Speaker 2: the brain as a computer. Is there any analogy over
14:10
Speaker 2: history comparing a brain to something else that you think
14:13
Speaker 2: is a helpful analogy or the brain is just so
14:15
Speaker 2: different it doesn't make sense to try to compare it
14:17
Speaker 2: to anything we have experience with.
14:19
Speaker 1: So that is a really interesting question. And I have
14:21
Speaker 1: thought about this before, and I keep coming back to
14:24
Speaker 1: the computer as the closest thing, and I always tell
14:27
Speaker 1: people I think it is possible that we will get
14:30
Speaker 1: to a point, perhaps with quantum computing and other types
14:32
Speaker 1: of things, where we might be able to approximate a
14:36
Speaker 1: human brain like functionality in a computer. To this day,
14:40
Speaker 1: we don't have that, even with the incredible advent of
14:44
Speaker 1: AI in large language models and all of those things.
14:46
Speaker 1: Still there are certain things that human brains can do,
14:49
Speaker 1: and mammalian brains in general can do that computers just
14:52
Speaker 1: are not capable of. But there is not another device
14:55
Speaker 1: out there that is capable of this level of processing
14:59
Speaker 1: that I can think think of to associate with that analogy. Particularly.
15:03
Speaker 1: I mean, I think one of the things that the
15:04
Speaker 1: brain does, don't get me wrong, like the computational kinds
15:08
Speaker 1: of things that have been built are incredible, and the
15:11
Speaker 1: amount of the minuscule amount of time that it takes
15:13
Speaker 1: for them to be able to process and provide an
15:15
Speaker 1: answer is just wild beyond the imagination. But there are
15:20
Speaker 1: still some things that brains can do that the computer scans,
15:24
Speaker 1: and in particular it has to do with the ability
15:27
Speaker 1: to extract knowledge, the ability to error correct, the ability
15:31
Speaker 1: to do the kinds of decision making that we do
15:34
Speaker 1: as humans that are very difficult to encapsuling in the computer.
15:37
Speaker 1: The ability to have emotion emotional reactions. Those things are
15:40
Speaker 1: still very difficult to model. While you can tell the
15:42
Speaker 1: computer all you want about what we think the human
15:44
Speaker 1: experience is, we still don't understand that well enough to
15:47
Speaker 1: be able to model it computer.
15:49
Speaker 2: Yeah, fair enough, all right, So let's pull back to
15:51
Speaker 2: memory a little bit. So we've talked about how memory
15:54
Speaker 2: differs from sentience. Are there different kinds of memory and
15:58
Speaker 2: do our brains store different kinds of manator differently?
16:01
Speaker 1: Yes, And oftentimes we just say memory as like one
16:04
Speaker 1: big blanket umbrella kind of term, But it is important
16:08
Speaker 1: to know that there are different memory types, different memory
16:11
Speaker 1: systems in the brain, and they serve different functions. So
16:14
Speaker 1: let me give you a couple of examples. One type
16:16
Speaker 1: of memory, which I tend to like quite a bit,
16:18
Speaker 1: we studied quite often in my research laboratory, is what
16:21
Speaker 1: we call episodic memory, memory for episodes, memory for events
16:24
Speaker 1: that happened to us, And we tend to kind of
16:27
Speaker 1: operationally define it as remembering what happened, where it happened,
16:30
Speaker 1: and when it happens, and whenever you have kind of
16:32
Speaker 1: like the collection or the conjunction of those three, you
16:35
Speaker 1: can label that as an episode and you have a
16:36
Speaker 1: memory for a particular episode in your life. Typically you
16:39
Speaker 1: think about that as also the root of our autobiographical memory,
16:42
Speaker 1: our memory for autobiographical experiences, things that happen to us.
16:47
Speaker 1: But that's very different from membering how to tie your
16:49
Speaker 1: shoe races, or how to ride a bicycle, or how
16:52
Speaker 1: to do something like your tennis swing or your golf swing.
16:57
Speaker 1: You know, those kinds of things are trained in the
17:00
Speaker 1: brain very differently. They involve very different systems. A lot
17:03
Speaker 1: of times, they require more trial and error kind of learning,
17:07
Speaker 1: and they tend to be a bit less accessible to consciousness.
17:10
Speaker 1: So there will call sort of implicit kinds of learning
17:14
Speaker 1: so if you look at how the brain is organized,
17:16
Speaker 1: pretty much every patch of cortex is capable of some
17:20
Speaker 1: form of memory. Another term that we typically use in
17:23
Speaker 1: neuroscience is plasticity. The idea that the brain is plastic
17:26
Speaker 1: means it's capable of change. So whenever you have experience,
17:30
Speaker 1: cells that are responding to that experience are capable of change,
17:33
Speaker 1: and that change typically is thought of as a change
17:36
Speaker 1: in the connections and the way that cells communicate with
17:39
Speaker 1: each other, but some change that reflects a record of
17:42
Speaker 1: the experience that you had. Now, those changes happen throughout
17:46
Speaker 1: They can happen in our visual cortex, our visual system,
17:48
Speaker 1: our auditory system. They can happen in the episodic memory
17:52
Speaker 1: systems in the brain, or they can happen in these
17:54
Speaker 1: more implicit memory kinds of systems in the brain that
17:57
Speaker 1: typically support more unconscious function like knowing how to ride
18:01
Speaker 1: a bicycle, like knowing how to swing the golf club
18:03
Speaker 1: and those kinds of things. Those are stored separately. And
18:06
Speaker 1: we know this to be true because we see patients
18:09
Speaker 1: that have deficits in one type of memory and not another,
18:11
Speaker 1: because they have maybe a focal stroke or some damage
18:14
Speaker 1: or some deficit that impacted one system and not the other.
18:17
Speaker 1: So they struggle with that one type of memory that's
18:19
Speaker 1: affected in that system, but everything else seems to be intact.
18:22
Speaker 2: And by type of memory does that mean like category
18:24
Speaker 2: of memories like the tennis swing and the other sort
18:27
Speaker 2: of muscle memory things, or like I could forget high
18:30
Speaker 2: school if I had a stroke in the right place right.
18:33
Speaker 1: Although that's actually increasingly difficult. So typically, if there is
18:36
Speaker 1: a stroke that is focal, it might affect motor memory.
18:40
Speaker 1: It might affect memory that allows you to kind of
18:42
Speaker 1: move your hands in the right way and be able
18:44
Speaker 1: to support that kind of function. But episodic memory is
18:47
Speaker 1: this really weird thing. Initially, it does depend on key
18:51
Speaker 1: regions of the brain, one of them being the hippocampus.
18:53
Speaker 1: That's a really important region for episodic memory. But over
18:57
Speaker 1: time memories start to become somewhat independent of the hippi
19:00
Speaker 1: campus they start to become stored elsewhere, and that's one
19:03
Speaker 1: of the reasons why in Alzheimer's disease, where we know
19:06
Speaker 1: the hippocampus is one of the earliest regions to degenerate.
19:10
Speaker 1: As that starts to go away, you see a loss
19:14
Speaker 1: of recent memories things that were recently acquired, maybe weeks, months,
19:18
Speaker 1: or a couple of years before the decline started. But
19:22
Speaker 1: things from long ago, like high school are preserved. And
19:26
Speaker 1: the reason they're preserved is that they've now been consolidated
19:29
Speaker 1: that sort of a technical term for made strength and
19:32
Speaker 1: made resilience to loss. And that's because their stored sort
19:36
Speaker 1: of in parallel throughout the brain. So just the focal
19:39
Speaker 1: deficit there is likely not going to wipe out those
19:42
Speaker 1: particular memories, but it's much more likely to wipe out say, yeah,
19:45
Speaker 1: your ability to have the right swing or ride a
19:49
Speaker 1: bicycle or anything like that. Those are the kinds of
19:51
Speaker 1: things that are much more focally stored.
19:53
Speaker 2: Okay, and can we dig a little bit more into
19:56
Speaker 2: exactly how the brain stores memories. Is it like how
19:59
Speaker 2: do neurons connect with each other? Yeah, let's dig in.
20:02
Speaker 1: Yeah. So brain cells are very very unique compared to
20:06
Speaker 1: other cells in the body. And provided this is again
20:09
Speaker 1: I always tell my students, you know, this is true
20:11
Speaker 1: ninety five percent of the time according to our knowledge today.
20:14
Speaker 1: I sometimes things you know, several weeks from now, months, years,
20:18
Speaker 1: things can get revised. So this is just according to
20:20
Speaker 1: our current knowledge today, brain cells are able to communicate
20:24
Speaker 1: with one another in a way that other cells in
20:26
Speaker 1: the body are not able to. And the way that
20:29
Speaker 1: they communicate with each other is using a combination of
20:32
Speaker 1: electricity and chemistry. So the transmission of signals within a
20:37
Speaker 1: brain cell is entirely electrical, and we can talk about
20:40
Speaker 1: that in a second, but the transmission from one cell
20:44
Speaker 1: to the next most of the time is chemical. It
20:47
Speaker 1: involves the release of a neurochemical that goes from one cell,
20:50
Speaker 1: binds to the other, and then initiates another electrical signal
20:54
Speaker 1: from the next cell to the next cell. So it
20:57
Speaker 1: goes really fast electrical, somewhat slower chemical, really fast electrical,
21:01
Speaker 1: someone slower chemical, and so on, and you have this
21:03
Speaker 1: sort of progression of communication between cells. And that's really
21:08
Speaker 1: important because these cells need to bring in signals that
21:11
Speaker 1: essentially encode the outside world and bring that knowledge into
21:15
Speaker 1: the brain to create some sort of representation of it,
21:17
Speaker 1: and then act on them. Allow us to move, allow
21:20
Speaker 1: us to avoid a threat, allow us to seek reward,
21:22
Speaker 1: all of those kinds of things. So that's how the
21:24
Speaker 1: brain typically communicates. But your question is how does memory happen?
21:28
Speaker 1: And there was sort of lots of answers over the years.
21:32
Speaker 1: We used to think, well, maybe it's encoded in the
21:34
Speaker 1: DNA and cells. Maybe it's encoded in the cell size,
21:39
Speaker 1: maybe it's encoded in the whatever else is happening to
21:41
Speaker 1: change cell shape. And the current answer is that it
21:46
Speaker 1: is much more likely to be encoded in the connections
21:49
Speaker 1: in the way that these cells communicate with one another.
21:51
Speaker 1: So let's say sell A is firing and cell B
21:55
Speaker 1: is receiving a signal from cell A. If I were
21:59
Speaker 1: to modify some how the frequency by which sell A communicates,
22:02
Speaker 1: would sell be by making it fire more, or increase
22:06
Speaker 1: the neurotransmitter release, or increase the number of receptors on
22:11
Speaker 1: the second cell that receives that neurotransmitter. I can make
22:14
Speaker 1: it so that the communication between those cells is enhanced.
22:18
Speaker 1: And the way that the analogy that I like to
22:20
Speaker 1: use for this is imagine you are at a club
22:24
Speaker 1: and there's lots and lots of noise going on, lots
22:26
Speaker 1: of things going on, lots of people talking to each other,
22:28
Speaker 1: there's loud music and so on, and you're trying to
22:31
Speaker 1: communicate something to somebody who's dancing alongside you, and it's very,
22:35
Speaker 1: very difficult because of all of that noise. But now
22:38
Speaker 1: you get real close to them and you kind of,
22:40
Speaker 1: you know, hold your hand to their ears and you
22:42
Speaker 1: start to talk directly into their ears. Now they're going
22:45
Speaker 1: to receive that communication with much higher fidelity, be able
22:47
Speaker 1: to tune out noise and selectively attend to that communication.
22:51
Speaker 1: You've enhanced the communication between that person and the person
22:54
Speaker 1: they're talking to. That's what happens at synapses. There's lots
22:58
Speaker 1: and lots of synaptic firing and lots of communication happening.
23:01
Speaker 1: But when cells start to attach to each other, they
23:04
Speaker 1: communicate much more preferentially. They can transmit signals that express
23:08
Speaker 1: that form of learning. In other words, if there's an
23:11
Speaker 1: experience that happens that is learned by the brain, the
23:15
Speaker 1: brain can express a form of plasticity or a form
23:18
Speaker 1: of memory in the strength of the connections. So if
23:22
Speaker 1: the connections grow stronger, that's a signal that this memory
23:25
Speaker 1: has been learned. And most of the information that we
23:28
Speaker 1: have about this comes from animal models, comes from slice recordings,
23:31
Speaker 1: where we can see evidence for enhancements in the connectivity,
23:35
Speaker 1: enhancement in the communication between cells as a result of
23:39
Speaker 1: a learning experience.
23:40
Speaker 2: One. You've reminded me why I hate clubs. That's sorry,
23:43
Speaker 2: no one invites me to them anymore.
23:45
Speaker 1: I share that what you do?
23:46
Speaker 2: Yeah yeah, Okay. So we've got these connections, they get strengthened,
23:49
Speaker 2: but then it feels like there's another step between having
23:52
Speaker 2: this connection and then having a like specific memory. So
23:54
Speaker 2: you know, like we're not at the point where we
23:56
Speaker 2: could even in mice and correct me if I'm wrong
23:58
Speaker 2: about this, where we could like see which neurons are
24:01
Speaker 2: firing together and know they're thinking about food. Yeah, yeah,
24:05
Speaker 2: So where do we go from there?
24:06
Speaker 1: So what you're talking about actually is a very very
24:09
Speaker 1: big problem that we deal with in neuroscience and in
24:12
Speaker 1: cognitive science, and it's the credit assignment problem. How do
24:17
Speaker 1: you know that a particular cell is assigned to a
24:19
Speaker 1: particular memory or a particular connection it's assigned to a
24:22
Speaker 1: particular memory. And it's a very challenging question and we
24:25
Speaker 1: don't know the answer yet, but we suspect There's been
24:28
Speaker 1: a lot of research on what's called mechanisms of allocation.
24:32
Speaker 1: In other words, how can you allocate particular synapses, brain
24:36
Speaker 1: cell connections and cells to a particular memory and not
24:40
Speaker 1: another right so how can we get the specificity that
24:43
Speaker 1: we need in the system. And there's been a flurry
24:46
Speaker 1: of work in recent years understanding there are certain proteins
24:49
Speaker 1: that are used to quote label synapses, label particular cells,
24:54
Speaker 1: and assign them to a one memory and not another.
24:58
Speaker 1: It's just really brilliant work by some colleagues in the
25:00
Speaker 1: field that is trying to really get at this specificity question.
25:03
Speaker 1: Now we're still early days. We don't have final answers yet,
25:06
Speaker 1: but I think we have some tentitive ideas that you
25:10
Speaker 1: can with specific proteins that are expressed in the synaps
25:13
Speaker 1: essentially label them or prime them to be the ones
25:16
Speaker 1: that are modified by this experience and maybe not another.
25:19
Speaker 2: Wow, and that's pretty cool, right.
25:20
Speaker 1: Yeah, because from the looment of the time, we thought, well,
25:22
Speaker 1: how can we ever have any specificity in our brains
25:25
Speaker 1: if memory just activates cells, how do you know which
25:27
Speaker 1: cells are the ones that are involved here? And this
25:29
Speaker 1: might actually re find us with some answers.
25:31
Speaker 2: Wow. I feel like I recently heard about the connectome project,
25:34
Speaker 2: which I think is trying to figure out all of
25:36
Speaker 2: the neurons. So does this suggest that once we have
25:39
Speaker 2: a connectome next we need to work on the proteome
25:42
Speaker 2: that connects to the connectome to really understand how all
25:45
Speaker 2: of this works, or how helpful is this connect dome
25:47
Speaker 2: project going to.
25:48
Speaker 1: Be very helpful? I think that every time we try
25:51
Speaker 1: it and map another home it is very helpful. At
25:54
Speaker 1: some point we all have an everything owned and you know,
25:57
Speaker 1: with that sort of large scale data effort, we're going
25:59
Speaker 1: to need also the AI, the machine learning, all of
26:02
Speaker 1: those tools people to pass through it and actually figure
26:05
Speaker 1: out what's going on. But it's interesting, you know, Kelly,
26:08
Speaker 1: When I was coming up as a student, there was
26:10
Speaker 1: always this question that was asked by faculty in my
26:13
Speaker 1: department and many other departments, And it's a theoretical question,
26:16
Speaker 1: and I want to pose that question to you, which is,
26:19
Speaker 1: if we were to map every single neuron in the
26:22
Speaker 1: brain and every single connection in the brain, would we
26:26
Speaker 1: have learned anything about how the brain actually functions? And
26:30
Speaker 1: whenever they asked that question, you know, some of us
26:33
Speaker 1: were attempted to say, well, yeah, of course you can
26:35
Speaker 1: have all the data, right, And the answer they wanted
26:37
Speaker 1: us to get to is no, you're no better off
26:39
Speaker 1: because you have a ton of data but no way
26:41
Speaker 1: to really test hypotheses and understand function. You have to
26:45
Speaker 1: have the right model, You have to have the right
26:47
Speaker 1: kind of strategy to go into that data and look
26:50
Speaker 1: for what's necessary. But I would argue that over the
26:53
Speaker 1: last twenty thirty years that thinking has evolved and now
26:57
Speaker 1: we can go in in a completely unsupervised without having
27:01
Speaker 1: a model, which means also we avoid some of the
27:03
Speaker 1: biases that might come from a model and ask what
27:06
Speaker 1: does the data tell us? Sure, there is an explosion
27:09
Speaker 1: of data, but there are patterns that are hidden in there,
27:12
Speaker 1: and if you train up AI enough, it can pick
27:14
Speaker 1: up on those patterns and maybe tell us that there's
27:17
Speaker 1: a new model. There's a different model. The way that
27:19
Speaker 1: we were thinking about the brain informing hypotheses may not
27:22
Speaker 1: have been right all along. So I go back to
27:25
Speaker 1: things like the connect home projects and trying to resolve
27:28
Speaker 1: the connect home, the proteome, the epigenome, all of those
27:32
Speaker 1: kinds of things as different layers of knowledge about the
27:36
Speaker 1: nervous system. And if we have all of that information,
27:39
Speaker 1: it stands to reason that we should be able to
27:41
Speaker 1: pick up on patterns, and patterns can maybe transform the
27:45
Speaker 1: way that we think about the brain. Maybe we're all
27:47
Speaker 1: along maybe the brain does quantum computing. Maybe all sorts
27:51
Speaker 1: of things that we just would have never imagined that
27:54
Speaker 1: are buried in that data.
27:56
Speaker 2: It sounds like an exciting time to be in the field.
27:58
Speaker 1: Oh. Absolutely, absolutely.
28:16
Speaker 2: I'm going to pull us back a little bit. In
28:17
Speaker 2: our conversation. You were talking about how you can strengthen
28:19
Speaker 2: connections between neurons. Does that happen because you're thinking of
28:23
Speaker 2: the same memory over and over again? And so how
28:25
Speaker 2: do memories get strengthened and how do we lose some
28:28
Speaker 2: of them?
28:28
Speaker 1: Yeah, So the strengthening of memory, or the idea of consolidation,
28:32
Speaker 1: which is exactly what it sounds like. It's making memories
28:34
Speaker 1: more solidified or more strengthened. It can happen because we
28:38
Speaker 1: are repeatedly rehearsing the memory, so we're thinking about it
28:41
Speaker 1: over and over. But the good news, Kelly, is that
28:44
Speaker 1: that happens completely incidentally, without you intentionally trying to do it.
28:48
Speaker 1: Your brain constantly brings up old memories and thinks about them,
28:51
Speaker 1: and even if you're not consciously aware of it, it happens
28:53
Speaker 1: while you sleep at night. Okay, so the brain is
28:56
Speaker 1: sort of on the back burner, constantly playing through these memories,
29:00
Speaker 1: replaying through these memories, and even when you go to sleep,
29:02
Speaker 1: it's replaying through these memories. So the strengthening act of
29:05
Speaker 1: memories doesn't have to be this intentional thing, which I
29:08
Speaker 1: think is a really powerful thing to tell students. Also,
29:11
Speaker 1: you don't have to sit here and like regurgitate and
29:13
Speaker 1: rehearse everything over and over and over. Just go through
29:15
Speaker 1: and understand and then get a good night's sleep, right,
29:18
Speaker 1: which is a lot of them really struggle to do.
29:20
Speaker 1: But during that period you might think, well, that's just rest.
29:24
Speaker 1: Actually the brain can be quite active during that period
29:27
Speaker 1: of time and can be playing through these memories and
29:29
Speaker 1: storing them and trying to make them morsistant to forgetting now.
29:33
Speaker 1: One thing to note also is that when you replay memories,
29:37
Speaker 1: when you bring back memories, you don't end up with
29:40
Speaker 1: the same thing being stored again. So memories are reconstructive
29:44
Speaker 1: in nature. If I were to bring back an experience,
29:47
Speaker 1: say that I have from a few weeks ago and
29:49
Speaker 1: talk about it with you, what I end up storing
29:51
Speaker 1: now and reinforcing is a somewhat altered version of that memory.
29:55
Speaker 1: It's not the same thing, because memory is reconstructed on
29:58
Speaker 1: piecing together the pieces. Other pieces just get incorporated because
30:01
Speaker 1: we're having a conversation about it. And then later on
30:04
Speaker 1: what I remember is some amalgamation of all of those
30:07
Speaker 1: experiences when I brought it back and changed it ever
30:09
Speaker 1: so slightly. My colleague here at you see, Aravin Beth
30:12
Speaker 1: Loftus built her career on studying false memories and how
30:16
Speaker 1: they arise, and they are very, very frequent. They arise
30:19
Speaker 1: all the time. We generate the more as we get older,
30:22
Speaker 1: and they happen just by virtue of our memory being
30:24
Speaker 1: a reconstructive system rather than a high fidelity video camera
30:30
Speaker 1: or a picture of reality. It's just a sort of
30:33
Speaker 1: a Hodgepodg construction of what that reality might have been.
30:36
Speaker 1: And again we say, why is this happening? Why can't
30:39
Speaker 1: we have a high fidelity version of things? And it's
30:42
Speaker 1: possible that we just don't need to. So even with
30:45
Speaker 1: these false memories arising, they're very artifactual, like you really
30:48
Speaker 1: need to remember exactly what happened and where it happened,
30:50
Speaker 1: that when it happened, Ergie, you just need to remember
30:52
Speaker 1: the core knowledge. So if we focus on, hey, the
30:55
Speaker 1: corenology is being remembered accurately. That's all that matters. Everything
30:59
Speaker 1: else and go to crap, and nobody's going to be
31:01
Speaker 1: less able to survive. So from a survival standpoint, it
31:04
Speaker 1: certainly doesn't matter that you have this strengthening, be a
31:07
Speaker 1: very high fidelity strengthening. It just matters that the core
31:10
Speaker 1: component knowledge is the thing that strengthened, Like the capital
31:13
Speaker 1: of the United States, Washington, everything else. Who cares.
31:16
Speaker 2: But if the lawyer is you priding you for details
31:19
Speaker 2: in a court case, that's when you're in some trouble.
31:22
Speaker 1: Absolutely, and you know the good news is, well, the
31:26
Speaker 1: somewhare good news is some lawyers, some federal judges, some
31:29
Speaker 1: jury get the lecture about false memories and understand that
31:35
Speaker 1: when you call witnesses to to stand and you're asking
31:37
Speaker 1: very very specific questions, that their right collection is going
31:40
Speaker 1: to be some combination of what actually happens, what the
31:42
Speaker 1: brain sort of reconstructed it to be, what kinds of
31:45
Speaker 1: questions are being asked, the pressure, any interrogation that happened earlier,
31:49
Speaker 1: All of those things sort of weave their way into
31:52
Speaker 1: that memory. You're never going to be able to get
31:54
Speaker 1: this beautiful, accurate, one hundred percent depiction of what happens,
31:58
Speaker 1: you're going to get some very of it that could
32:01
Speaker 1: be quite a bit more corrupted.
32:03
Speaker 2: Gosh, there could be a whole podcast on that topic.
32:05
Speaker 2: So my co host wanted me to dig into how
32:10
Speaker 2: we learn about this kind of stuff. So you mentioned
32:12
Speaker 2: that there are animal models, but just focusing on people
32:15
Speaker 2: right now, how good are our techniques for watching how
32:19
Speaker 2: the brain works in living humans to sort of try
32:22
Speaker 2: to get a handle on some of this stuff.
32:23
Speaker 1: Yeah, So when we started out, the discipline of neuropsychology
32:28
Speaker 1: had very, very poor tools available to it. So you
32:31
Speaker 1: have to develop cognitive assessments, which have come a long way.
32:34
Speaker 1: You can have the right kinds of cognitive assessments and
32:36
Speaker 1: so on, but you really have to work with patients
32:38
Speaker 1: and the clinic who come in presenting with memory problems,
32:42
Speaker 1: with a variety of different conditions, and essentially it's akin
32:45
Speaker 1: to leision studies. You're working with patients who might have
32:49
Speaker 1: circumscribed focal deficit in the brain. You can see that
32:52
Speaker 1: on structural MRI for example, and say this part of
32:54
Speaker 1: the brain is damaged or missing. Therefore they have this
32:57
Speaker 1: kind of function, So you might be able to say
32:59
Speaker 1: something about the function of this part of the brain
33:01
Speaker 1: in a healthy person. But our tools have evolved significantly since,
33:06
Speaker 1: so two major advances that I can tell you are
33:09
Speaker 1: still today. The chief ways by which we study this.
33:12
Speaker 1: One is functional MRI, and we tend to do a
33:14
Speaker 1: heck of a lot of that in my lab. So
33:16
Speaker 1: functional MRI operates on the principle that you can put
33:19
Speaker 1: somebody in the scanner totally intact brain and give them
33:23
Speaker 1: a game to play, or a memory task, or any
33:25
Speaker 1: sort of challenge that would engage the memory bits of
33:29
Speaker 1: their brain, for example. And what you're imaging with functional
33:32
Speaker 1: MRI is not neural activity directly. What you're imaging is
33:35
Speaker 1: blood flow. The idea being that if there's a patch
33:39
Speaker 1: of cortex patchup brain that is more active, that is
33:44
Speaker 1: engaged in this challenge, it's going to require oxygen and
33:47
Speaker 1: glucose and it's going to try to extract that out
33:51
Speaker 1: of the blood flow. So by mapping how much oxygenated
33:55
Speaker 1: blood and deoxygenated blood are going to different areas in
33:59
Speaker 1: the brain, you can generate a contrast because it turns
34:03
Speaker 1: out that the degree of oxygenation has a different magnetic signal.
34:06
Speaker 1: So that's sort of a little hack that we pull
34:07
Speaker 1: in MRI because we're changing ragnetic fields. So by measuring
34:11
Speaker 1: that contrast, we can get an indirect proxy to where
34:15
Speaker 1: neural activity might be by virtue of that blood flow change.
34:19
Speaker 1: So that's been a really, really helpful technique since the
34:22
Speaker 1: late nineties early two thousands. In the early days of
34:25
Speaker 1: functional MRI, people did a bunch of like really just
34:28
Speaker 1: awful studies because the technology was new and we didn't
34:31
Speaker 1: know what to do with it, and folks didn't really
34:34
Speaker 1: think beyond you know, the X marks the spot kind
34:36
Speaker 1: of approach, Right, I want to know what the fill
34:39
Speaker 1: in the blank part of the brain is. It even
34:42
Speaker 1: got as absurd as I want to know what the
34:43
Speaker 1: god part of the brain is. Right, So people start
34:46
Speaker 1: to do those kinds of studies, try to go in
34:48
Speaker 1: and say, X marks the spot, where's the stuff happening?
34:51
Speaker 2: Is this the same system where they had that dead trout? Oh?
34:55
Speaker 1: Yeah, you know that that trout study. Of course. So
34:58
Speaker 1: at the end of the day, it is a statistic
35:00
Speaker 1: approach to comparing activation, and yeah, that study is really
35:04
Speaker 1: compelling because you could show that you see activation essentially
35:07
Speaker 1: in something that is dead, and people every now and
35:10
Speaker 1: then will kind of make fun of this, and remember
35:12
Speaker 1: the old days of fMRI, when folks didn't really know
35:15
Speaker 1: what they were doing, and you could get something like
35:16
Speaker 1: this right, and in some cases you can even get
35:19
Speaker 1: it to be published, which is crazy when you think
35:21
Speaker 1: about it. But we've come a long way since. So
35:25
Speaker 1: the beauty of functional MRI now is that one we
35:28
Speaker 1: understand how to do the X marks the spot much
35:30
Speaker 1: much better. We now have much better handle on this
35:32
Speaker 1: historical challenges, the way to build the right contrasts, the
35:35
Speaker 1: way to correct for multiple comparisons, all the things that
35:37
Speaker 1: you tend to think of when you're doing large scale statistics.
35:41
Speaker 1: That discipline had to kind of come to functional imaging
35:44
Speaker 1: and inform it and that has happened, which is great.
35:47
Speaker 1: But the second part is I told you before that
35:49
Speaker 1: memory is all about the connections, and functional MRI initially
35:53
Speaker 1: was all about blobbology, right, try to find little hotspots
35:56
Speaker 1: in the brain. You pretty pictures the cover of science
35:58
Speaker 1: and all that with little hotspots in the brain, and
36:02
Speaker 1: that was the approach. But we know that memory is
36:04
Speaker 1: not in the hotspots, memories and the connections, so we've
36:07
Speaker 1: started to move much more towards connectivity analysis and asking
36:11
Speaker 1: about how are the different parts of the brain communicating
36:14
Speaker 1: dynamically and essentially coactivating with each other to support solving
36:19
Speaker 1: this challenge or doing this memory test or memory game
36:22
Speaker 1: while you're in the scanner. So that was the advent
36:25
Speaker 1: of functional connectivity kinds of approaches which are I think
36:29
Speaker 1: far more compelling, far more robust against some of the
36:32
Speaker 1: initial critiques of a functional MRI, and they reflect the
36:36
Speaker 1: true nature of how the brain works. The brain is
36:38
Speaker 1: one big dynamical system. It's not just regions working in isolation.
36:41
Speaker 1: Everything is connecting with each other, so we owe it
36:44
Speaker 1: to ourselves to try to understand it from that much
36:47
Speaker 1: more complex way. So functional MRI still remains a very
36:51
Speaker 1: very powerful tool, but now the analysis that we can
36:54
Speaker 1: do are just far more advanced. The other thing that
36:56
Speaker 1: I think is just incredibly powerful, aside from anim models,
37:00
Speaker 1: is the ability to directly record electrical activity from cells
37:05
Speaker 1: or from what it's called local field potentials that the
37:08
Speaker 1: areas around cells that have also electrical activity. It can
37:11
Speaker 1: be measured directly in patients, and these are typically patients
37:16
Speaker 1: that are going to undergo surgery for epileptic seizures. So
37:19
Speaker 1: the surgery is done to remove the part of the
37:22
Speaker 1: brain where the seizures are emanating from. And typically when
37:26
Speaker 1: they come into a hospital, they're in a hospital for
37:28
Speaker 1: about a week or so. They get implanted with electrodes
37:31
Speaker 1: to record from the parts of the brain where the
37:33
Speaker 1: clinician might suspect that epilepsy is happening, and they're taken
37:38
Speaker 1: off of anti epileptic medication and essentially they're waiting to
37:41
Speaker 1: induce a seizure, and once that seizure is induced, they
37:44
Speaker 1: attract the location. That's how they decide on a way
37:47
Speaker 1: to do the surgery. There's about a week or so
37:50
Speaker 1: while they're in the hospital with electrodes penetrating deep into
37:53
Speaker 1: their cortex and many of those electrodes directly into the
37:56
Speaker 1: memory bits of the brain, like the hippocampus. And those
38:00
Speaker 1: are just an incredible group of individuals because they also
38:04
Speaker 1: most of them want to help science and they understand
38:07
Speaker 1: the opportunity the scientists have while they're laying in a
38:10
Speaker 1: hospital bed for about a week to understand something fundamental
38:13
Speaker 1: about the brain. So every now and then they give
38:16
Speaker 1: us the opportunity to give them a challenge, maybe on
38:18
Speaker 1: an iPad or a computer while they're laying there and
38:21
Speaker 1: they try to solve this challenge, try to play this
38:24
Speaker 1: memory game or do this memory test while we're recording
38:27
Speaker 1: direct electrical activity from their brain cells, which is incredible.
38:31
Speaker 1: So it gives us almost the same degree of information
38:34
Speaker 1: that you can get in an animal model. Now in
38:36
Speaker 1: an animal model, in a road that you can stick
38:38
Speaker 1: more electrones, you can get higher fidelity. And with patients
38:41
Speaker 1: you have to do things that are only clinically warranted.
38:43
Speaker 1: So there's an ethical obligation, of course to make sure
38:46
Speaker 1: that nothing is being done that would ever put the
38:48
Speaker 1: patient an increase risk. So that also poses some limitations
38:53
Speaker 1: as to how you can record activity and get that data.
38:56
Speaker 1: But it's just incredible access that we have to the
38:58
Speaker 1: brain in partnership with these remarkable individuals, and we've learned
39:02
Speaker 1: a heck of a lot about how the brain works
39:04
Speaker 1: and how memory works from those direct electrical recordings.
39:07
Speaker 2: Wow. I previously wrote a chapter on brain computer interfaces
39:11
Speaker 2: and I was reading about like, utah arrays. Is this
39:14
Speaker 2: the same thing or is this a different kind of electrode.
39:17
Speaker 1: Yes, So, utah arrays are one way to do it.
39:20
Speaker 1: Utah arrays are a little bit more invasive. They involve
39:24
Speaker 1: several electrodes that are kind of going through the surface
39:27
Speaker 1: of the cortex. At the same time, they're no longer
39:30
Speaker 1: kind of the standard practice for most patients. They're still
39:33
Speaker 1: used in some cases where they're clinically warranted, but in
39:36
Speaker 1: many cases they're not because you suspect that what's happening
39:39
Speaker 1: is deep into the brain, so you stick direct single
39:42
Speaker 1: electrodes all the way down to where you suspect the
39:45
Speaker 1: action might be, and you avoid some of the potential
39:48
Speaker 1: damage that happens with UTAH rays. So they're used in
39:50
Speaker 1: some clinical contexts, but in many others, we can stick
39:54
Speaker 1: these much thinner, slimmer electrodes directly into the parts of
39:58
Speaker 1: the brain that we suspect yet epilepsy is ennything from
40:01
Speaker 1: so far less damage that way, and those patients typically
40:04
Speaker 1: have better outcomes than patients implanted with guitar rays. Now,
40:08
Speaker 1: your point about BCIs, and there's a number of companies
40:11
Speaker 1: out there that are trying to develop brain computer interfaces
40:14
Speaker 1: using these kinds of arrays. I think that's a particular
40:17
Speaker 1: challenge for those enterprises is how do you create a
40:20
Speaker 1: way to measure directly from the brain and to be
40:23
Speaker 1: able to stimulate and influence the brain without causing too
40:26
Speaker 1: much damage. Having electrones that are thin enough, that are
40:30
Speaker 1: made from the right material so that you don't cause
40:33
Speaker 1: a lot of tissue damage, because ideally, what you want
40:35
Speaker 1: to do is create an interface that helps people, so
40:37
Speaker 1: you don't want to inadvertently cause more damage.
40:40
Speaker 2: Now, when we were thinking about UTAH rays and damage,
40:43
Speaker 2: you know, we thought about like a cup with jello
40:45
Speaker 2: in it, and you stick some needles in there, and
40:48
Speaker 2: as you move the jello around, if the needles are
40:50
Speaker 2: kind of staying in place, that would sort of mess
40:52
Speaker 2: up the brain. Is that a good way to think
40:53
Speaker 2: about it? Does it all move together?
40:55
Speaker 1: Yeah? The brain certainly is as vulnerable maybe as a
40:59
Speaker 1: cup of gello. But the key is also flexibility. So
41:02
Speaker 1: you're right. When you have these electrodes, there's a bit
41:05
Speaker 1: of a compromise. So want them to be flexible so
41:08
Speaker 1: that they're moving with their brain. You're absolutely right, and
41:10
Speaker 1: that'll cause less tissue damage. But at the same time,
41:13
Speaker 1: flexibility you can come at a cost, which is what
41:16
Speaker 1: they're targeting, might change. So you want to make them
41:19
Speaker 1: flexible enough sort of they don't cause damage, but rigid
41:21
Speaker 1: enough so that they can continue to target the same region,
41:24
Speaker 1: so it is not an easy challenge at all. But
41:27
Speaker 1: there's been some developments recently in doing these kinds of
41:30
Speaker 1: arrays with animals, and we haven't yet pourted that over
41:33
Speaker 1: to humans and done the FD approval and all of
41:36
Speaker 1: those kinds of things. It's happening soon. There's already experiments
41:39
Speaker 1: that try to test out one of the technologies like
41:41
Speaker 1: neuropixel for example, or near epixels technologies. Those have been
41:46
Speaker 1: incredibly powerful for animal models for reading from road insight
41:49
Speaker 1: from non human primates and their small form factor. They're thinner,
41:53
Speaker 1: but they have a ton of electrode contacts on there,
41:56
Speaker 1: so it can really give you information from a lot
41:58
Speaker 1: of different sounds simultaneou sleep. And pointing that over to
42:02
Speaker 1: humans I think will be a really helpful thing to do.
42:05
Speaker 1: But that's only been done in some limited experiments and
42:07
Speaker 1: not widespread. You so hoping that some variants of those
42:10
Speaker 1: kinds of technologies will make us way to primetime soon.
42:12
Speaker 2: I've watched some videos of people with brain computer interfaces
42:16
Speaker 2: that were able to do incredible things, But one of
42:18
Speaker 2: the things that sounded totally devastating to me was if
42:20
Speaker 2: I understand this correctly, it's over time, the brain has
42:23
Speaker 2: a response to those electrodes and like kind of walls
42:26
Speaker 2: them off and the connection gets less good. I don't
42:28
Speaker 2: know exactly what's happening. Do we have any progress in
42:31
Speaker 2: that area.
42:32
Speaker 1: Well, so that's another thing that needs to be tackled. Also,
42:34
Speaker 1: with some of these newer silicon probes, they're less likely
42:37
Speaker 1: to have the inflammatory and the calcification kinds of responses
42:41
Speaker 1: that happened around electrodes, because remember, this is a foreign
42:44
Speaker 1: object entering the brain, and the brain's natural disposition towards
42:47
Speaker 1: foreign objects is attack it, right. That's why we have
42:51
Speaker 1: brains immune cells, we have microglia, we have a lot
42:54
Speaker 1: of cells that are dedicated to detecting and eliminating foreign objects.
42:58
Speaker 1: So you tend to see them of aggregate around electrodic
43:02
Speaker 1: contact locations and things like that. But there are ways
43:05
Speaker 1: with different substances to kind of maybe fool the brain
43:08
Speaker 1: a little bit into thinking this is okay. You can
43:10
Speaker 1: try to also reduce the brains immune response to some
43:13
Speaker 1: extent when these things are coming in. So there's approaches
43:16
Speaker 1: that are being developed to try to get better long
43:18
Speaker 1: term outcomes, but yet we're still very early.
43:20
Speaker 2: In this game, And for listeners who are maybe not
43:22
Speaker 2: es familiar with brain computer interfaces, what are some reasons
43:25
Speaker 2: that people might get a brain computer interface.
43:28
Speaker 1: There's a variety of reasons. So, for example, for someone
43:31
Speaker 1: who has lost the ability to control their limbs because
43:34
Speaker 1: of a stroke or a focal deficit, being able to
43:37
Speaker 1: have a brain computer interface shortcut signals so that they
43:40
Speaker 1: can still control their limbs and their body is remarkable.
43:44
Speaker 1: And patients who have had those kinds of approaches, it
43:46
Speaker 1: is just life changing. They go from a paraplegic or
43:49
Speaker 1: quadriplegic to being able to have use of their arms
43:52
Speaker 1: or their legs again. So there's incredibly utility there. For
43:56
Speaker 1: folks who might have epilepsy. For example, there is a
44:00
Speaker 1: brain computer interface that is a stimulator that is implanted
44:05
Speaker 1: in the brain that responds to the earliest science of
44:07
Speaker 1: epileptic seizures and that is able to with electrical stimulation
44:11
Speaker 1: essentially knock it out. So now instead of having to
44:14
Speaker 1: have the person be going in for surgery and lomping
44:17
Speaker 1: up parts of the brain or having them be devastated
44:19
Speaker 1: by epileptic seizures, you can have an implanted BCI that
44:23
Speaker 1: responds in a closed loop system, so it uses the
44:26
Speaker 1: responses of the brain itself to tell the stimulator what
44:29
Speaker 1: to do. And that's a completely closed loop, so it
44:32
Speaker 1: doesn't require any user interventionally outside. That allows it to
44:35
Speaker 1: do a much better job of helping the patients overcome
44:39
Speaker 1: seizures or epilepsy. So there's a number of different uses.
44:43
Speaker 1: I can imagine that for movement disorders, for a variety
44:46
Speaker 1: of different conditions where you might want to implant something
44:49
Speaker 1: that communicates with the brain and feeds at the right
44:51
Speaker 1: signal at the right time, there's going to be a
44:53
Speaker 1: huge use for a BCI. Then there's a whole other
44:57
Speaker 1: class of uses that may not work vire implantation. Right,
45:02
Speaker 1: So these external devices maybe devices that are communicating with
45:05
Speaker 1: the brain and external fashion portable or multiple, and they
45:10
Speaker 1: allow it to improve function for stroke rahabilitation, or improve
45:15
Speaker 1: function in some other way. There's a lot of folks
45:17
Speaker 1: also kind of you know, taking the transhumanist approach here
45:20
Speaker 1: and trying to develop PCIs to just improve our function.
45:22
Speaker 1: We just want to be better at something, right, So
45:25
Speaker 1: what if I can control this robotic arm to do
45:27
Speaker 1: some you know, whatever it is. So don't care too
45:30
Speaker 1: much about those but certainly the utility for helping patients
45:33
Speaker 1: is huge.
45:34
Speaker 2: So getting a little more sci fi here, do you
45:37
Speaker 2: think we'll ever be able to know what somebody is
45:40
Speaker 2: thinking by having, you know, a cap on their head
45:42
Speaker 2: or electrodes in their brain or is that just way
45:45
Speaker 2: too far off?
45:46
Speaker 1: I think we already do so. I think we are
45:49
Speaker 1: to some extent with an electrocapsule. Egen is really the
45:53
Speaker 1: technology that you're talking about, or there's other ways to
45:56
Speaker 1: do it also, various ultrasound technologies and so on. You
46:00
Speaker 1: can detect and stimulate pretty easily, but the problem is
46:04
Speaker 1: the kinds of things that you can get the system
46:06
Speaker 1: to do are still fairly rudimentary. So I can tell,
46:09
Speaker 1: for example, based on eg signal whether the person is
46:12
Speaker 1: going to move their hand or make some overt kind
46:16
Speaker 1: of gesture, and motor control is a somewhat simpler system
46:20
Speaker 1: than like memory, executive decision, or emotion or having very
46:25
Speaker 1: complex feelings like guilt, right or things like that are
46:29
Speaker 1: much more difficult to capture in the simple signals that
46:33
Speaker 1: we're capturing. The BCIs right now. So do I anticipate
46:36
Speaker 1: that at one point we'll be able to do one percent?
46:39
Speaker 1: There's no doubt the technologies there. It's just a matter
46:42
Speaker 1: of are we recording from enough are we able to
46:44
Speaker 1: build the sophisticated models to model this function, and we're
46:48
Speaker 1: making rapid progress in that arena. So from a sci
46:51
Speaker 1: fi perspective, I'm sure you've heard this before. The moving vehicle,
46:55
Speaker 1: the car was sci fi at one point until someone
46:57
Speaker 1: invented it, right, So the things that we think about
47:00
Speaker 1: a sci fi are just science that's not here yet.
47:02
Speaker 2: All right, Yeah, the future is now. So let's talk
47:21
Speaker 2: about losing memory a little bit as we wrap things up.
47:24
Speaker 2: So we talked about how your brain is working overnight
47:27
Speaker 2: to strengthen memories. How do we lose memories over time?
47:31
Speaker 1: So there's a number of different ways to do this.
47:33
Speaker 1: Memory can be lost because of decay, so just the
47:37
Speaker 1: passage of time a lot of times can make memories
47:40
Speaker 1: just harder to remember, harder to access. And we've known
47:43
Speaker 1: this since eighteen eighties. Herman Ebbinghouse was the first to
47:47
Speaker 1: kind of do this using experiments with himself. You would
47:50
Speaker 1: learn lists of nonsense syllables and then try to map
47:54
Speaker 1: his own forgetting curve. So how much forgetting happens over
47:57
Speaker 1: the first twenty four hours, next twenty four hours, next
47:59
Speaker 1: twenty four hours. Yeah, I know, experiments on yourself very
48:02
Speaker 1: very boring times in eighteen eighty so it didn't have
48:04
Speaker 1: too much else to do, so I did this with himself,
48:07
Speaker 1: but maps what's called the forgetting curve, which we still
48:09
Speaker 1: to this day. We can look at any sort of
48:11
Speaker 1: memory function or any memory task that we do in
48:14
Speaker 1: the lot and we see a very clear forgetting curve.
48:16
Speaker 1: A lot of forget the first twenty four hours. Then
48:18
Speaker 1: things to kind of taper off. So there's that, And
48:20
Speaker 1: the suspicion is that mostly it's decay, but sometimes it
48:24
Speaker 1: happens because of interference, because similar memories get in there
48:28
Speaker 1: and kind of interfere with one another, compete with one another,
48:30
Speaker 1: sort of the memory that you have for them get
48:32
Speaker 1: a little bit fuzzy. And again these are maybe features,
48:36
Speaker 1: not bugs, right where maybe the system is not intending
48:39
Speaker 1: to hold onto memories with high fidelity for long. So
48:42
Speaker 1: interference and decay help us extract what's most important and
48:46
Speaker 1: keep that over time, and then other things can kind
48:48
Speaker 1: of go away. So those are natural things that happen
48:50
Speaker 1: in every brain all the time, and there's nothing to
48:53
Speaker 1: be concerned about decay, interference, nothing to be concerned about.
48:56
Speaker 1: But as we get older, and by older I hate
48:59
Speaker 1: to say this, you know, talking about like forties.
49:01
Speaker 2: And above that what I wanted to hear money, Well,
49:06
Speaker 2: I'm going to.
49:06
Speaker 1: Say graduate in our fourth decade and then maybe a
49:09
Speaker 1: little bit more precipitously, over time, memory does get more difficult.
49:14
Speaker 1: So things do degrade, and we start to maybe lose
49:18
Speaker 1: to some extent, our ability to make new memories, encode
49:20
Speaker 1: new memories, our memories. For the old stuff is still
49:23
Speaker 1: there's still resilience, even though every now and then we
49:25
Speaker 1: might have a problem with access. So we get distracted,
49:28
Speaker 1: we lose retrieval cues, but you know it's there because
49:30
Speaker 1: if you get the right reminder, boom, it comes back. Right.
49:34
Speaker 1: It's just a matter of like tip of a tongue,
49:36
Speaker 1: you know, being able to remember exactly that the right
49:38
Speaker 1: queue for retrieval. That becomes more difficult when we're just
49:41
Speaker 1: more distracted. But as we get older, making new memories
49:44
Speaker 1: becomes harder. And then for some folks who might go
49:47
Speaker 1: down the trajectory to Alzheimer's disease, right then that becomes
49:52
Speaker 1: exceptionally more difficult. And that's one of the first things
49:54
Speaker 1: to go. And there's a very difficult line between what's
49:59
Speaker 1: normal I hate to say that word, maybe more typical
50:02
Speaker 1: age associated memory impairment, which you can expect in every brain,
50:06
Speaker 1: and that's something that may be a bit more costs
50:08
Speaker 1: for concern because it may be going down to about
50:10
Speaker 1: the Alzheimer's disease. Dissociating those two, say in the sixties
50:14
Speaker 1: and seventies, is actually very difficult. It's not very easy
50:17
Speaker 1: because both can start out as a form of forgetfulness.
50:20
Speaker 1: But with Alzheimer's disease or with dementia, it's very progressive,
50:24
Speaker 1: so it does get worse and worse and worse over time.
50:28
Speaker 1: That change in a healthy aging brain or a typical
50:30
Speaker 1: aging brain is far less deep, so you don't see
50:34
Speaker 1: too much changing over time. You don't see this degradation
50:37
Speaker 1: to the point where it becomes very noticeable by family, friends, neighbors,
50:41
Speaker 1: and so on. So those are the forms of memory
50:44
Speaker 1: loss or memory change that happened. Some totally innocuous, no
50:48
Speaker 1: cause for concern, they happen every day to everyone, to
50:50
Speaker 1: the best of us. And then some that are a
50:53
Speaker 1: bit more cause for concern.
50:54
Speaker 2: As we get older and mechanistically, is it just the
50:57
Speaker 2: messages are not getting sent between those anymore, or this is.
51:01
Speaker 1: Something we've done quite a bit of work on. Actually mechanistically,
51:04
Speaker 1: what seems to be the case is that first the
51:07
Speaker 1: part of the brain that's really important for encoding these
51:10
Speaker 1: episodic memories, the hippocampus, as I said, has a very
51:13
Speaker 1: interesting change and it's dynamic. So this is a massive
51:17
Speaker 1: information processing hub in the brain. Even though it's a
51:19
Speaker 1: small structure, it carries a big information processing load, and
51:24
Speaker 1: it kind of can shift its state from encoding new
51:27
Speaker 1: information to remembering old information. And there are a few
51:31
Speaker 1: changes that happen to the cells in that system as
51:34
Speaker 1: we get older that bias the system towards remembering old
51:37
Speaker 1: information and away from encoding new information. And there's lots
51:41
Speaker 1: of sort of reasons why that is, we tend to
51:44
Speaker 1: change the excitation inhibition balance, we tend to change neurotransmitter concentrations,
51:49
Speaker 1: all of those kinds of things as we get older
51:51
Speaker 1: that cause that change in the information processing balance. But
51:54
Speaker 1: the other thing that happens more in the context of
51:57
Speaker 1: Alzheimer's disease is you also start to deprive the hippocampus
52:01
Speaker 1: of its main input coming in from the rest of
52:03
Speaker 1: the brain. So there's a region that sits alongside the
52:07
Speaker 1: hippo campus called the antorhinal cortex, and that region shrivels
52:11
Speaker 1: up in Alzheimer's disease. It's one of the first regions
52:14
Speaker 1: to deposit what's called tangle pathology or tau tangles, and
52:18
Speaker 1: that's a marker of cell death. So there's massive cell
52:22
Speaker 1: loss that's happening in that's around cortex early on, which
52:25
Speaker 1: deprives the hippocampus of its principal inputs. So in computer
52:29
Speaker 1: science we have this old adage called garbage in garbage out,
52:33
Speaker 1: and that's essentially what's happening in the hippocampus. It's the
52:36
Speaker 1: quality of the information that's coming in starts to become
52:39
Speaker 1: much more degraded than the context of Alzheimer's c's, So
52:42
Speaker 1: we can't possibly expect it to do a good job
52:45
Speaker 1: encoding information and story with high fidelity if the information
52:49
Speaker 1: coming in is in some ways quote garbage. So that
52:52
Speaker 1: tends to be one of the things that is also
52:54
Speaker 1: mechanistically associated with memory loss in the aging brain.
52:57
Speaker 2: Do we know why that region starts to degree in
53:00
Speaker 2: some people and not others.
53:01
Speaker 1: You know, there's hypotheses and I have my pet hypothesies.
53:05
Speaker 1: In the field has its pet hypotheses and so on,
53:07
Speaker 1: But there's a variety of contributors. We suspect that in
53:10
Speaker 1: the context of Alzheimer's disease, it's a combination of inflammatory changes,
53:15
Speaker 1: so that the mirror immune system is disregulated in Alzheimer's disease,
53:19
Speaker 1: where the inflammatory response that normally is very healthy starts
53:22
Speaker 1: to kind of take a turn and become very pathological.
53:25
Speaker 1: There is vascular damage that happens as we get older,
53:28
Speaker 1: and we suspect that some of those early vascular insults,
53:31
Speaker 1: so related to blood flows, deifenning of the arteries and
53:33
Speaker 1: so on, can also contribute to that. There's metabolic regulation
53:38
Speaker 1: that changes, so the metabolic demands of different regions also
53:42
Speaker 1: becomes disregulated as we get older. And then one thing
53:45
Speaker 1: that we've worked quite a bit on is excitation inhibition
53:48
Speaker 1: balance and the notion that normally the brain keeps this
53:51
Speaker 1: dynamic beautifully between stop signals and ghost signals, and as
53:56
Speaker 1: we get older there actually is an overabunton of the
54:00
Speaker 1: ghost signals which can drive the brain pathologically more towards
54:05
Speaker 1: memory loss and not enough of the stop signals, so
54:08
Speaker 1: that imbalance can also be a contributor. So it's a
54:11
Speaker 1: multifactorial issue. There's lots of contributors. This is not just
54:14
Speaker 1: one single pathology kind of model, as much as some
54:17
Speaker 1: of the field likes to believe that. It's a bit
54:19
Speaker 1: more complex.
54:20
Speaker 2: So as someone who just learned that they're in the
54:21
Speaker 2: old category, I.
54:24
Speaker 1: Would necessarily call it that. I would just say, we're
54:26
Speaker 1: maybe done developing and we're now just kind of hitting
54:30
Speaker 1: that hump of we're going to start the aging process.
54:32
Speaker 2: Got it, got it, I'll think of it that way.
54:34
Speaker 2: But I like that better. What kinds of science based
54:38
Speaker 2: things can we do to maintain our memory? So I
54:41
Speaker 2: see all these apps, pitch me, is there any science
54:43
Speaker 2: behind any of those things?
54:45
Speaker 1: Well, the app stuff probably not. I will tell you
54:48
Speaker 1: that the four big things that are really really important,
54:51
Speaker 1: and when I say really important, I mean they are
54:53
Speaker 1: supported both by epideological data and by clinical trials. So
54:57
Speaker 1: these things are really really helpful. The first one is
54:59
Speaker 1: physical activity. We know that physical activity maintains brain health
55:03
Speaker 1: well into older adulthood. We know that it can delay
55:06
Speaker 1: the onset of Alzheimer's disease. It can make the outcomes
55:09
Speaker 1: better for patients and as protective it really is knocking out.
55:13
Speaker 1: So sedentary lifestyle is a risk factor. We've done work
55:16
Speaker 1: also to show that even activity as brief as ten
55:19
Speaker 1: minutes of walking can be helpful to memory. So it
55:22
Speaker 1: doesn't take a lot, you know, I would say thirty
55:25
Speaker 1: minutes of you know, mild to moderate activity like walking,
55:28
Speaker 1: risk walking, that's sufficient to be able to give people
55:32
Speaker 1: a way to handle that risk factory. The second thing
55:34
Speaker 1: that's really important, and this kind of goes back to
55:36
Speaker 1: your idea about apps and kind of cognitive engagement. It
55:40
Speaker 1: turns out that apps and brain games on all of
55:42
Speaker 1: that efficacy is a little bit tendless, so there's conflicting reports.
55:46
Speaker 1: But we know that social engagement is really important. So
55:49
Speaker 1: in other words, if you remove social engagement, if folks
55:52
Speaker 1: become isolated the same past retirement, that's a risk factory
55:55
Speaker 1: for sure. But if they're able to continue to be
55:58
Speaker 1: social build archer social networks in person, you know, volunteering,
56:02
Speaker 1: community centers, churches, synagogues, whatever it is, or being around
56:06
Speaker 1: people in general, and that can also combine with physical activity.
56:10
Speaker 1: So let's say it's dance class now, it's physical activity
56:13
Speaker 1: and social contact. Right, those kinds of things, even in
56:16
Speaker 1: interventional studies, have been shown to have very positive results.
56:19
Speaker 1: Then the third piece is diet. A heart healthy diet
56:23
Speaker 1: is a brain healthy diet. And the one that has
56:25
Speaker 1: been tried and true in clinical trials is the Mediterranean diet.
56:28
Speaker 1: So the Mediterranean which has lots and lots of variants,
56:31
Speaker 1: but I think very colorful, leafy, green vegetables and so on,
56:35
Speaker 1: healthy fats, and reducing you know, things like red meat
56:39
Speaker 1: and some on. So that one also has been tried
56:41
Speaker 1: in clinical trials compared to other diets and seems to
56:44
Speaker 1: be able to stave off risk. And then the last piece,
56:47
Speaker 1: which I think is one of the most important, to sleep.
56:50
Speaker 1: We all need good quality and quantity of sleep every night.
56:54
Speaker 1: It turns out that actually during sleep we go through
56:57
Speaker 1: a process of glymphatic clearance and we clear out on
56:59
Speaker 1: the life lot of the pathologies that can lead down
57:02
Speaker 1: the path to Alzheimer's. These or at least be contributors
57:04
Speaker 1: to it. And studies have shown that if you have
57:08
Speaker 1: sleep loss folks for example, who sleep less than six
57:11
Speaker 1: hours a night versus those who sleep more than seven
57:13
Speaker 1: or eight hours there's differences in their amyloid uptakes, so
57:16
Speaker 1: that emiloid pathology is one of the chief pathology in
57:19
Speaker 1: Alzheimer's disease. You see a lot more of it in
57:21
Speaker 1: those who sleep those fewer hours, and a lot less
57:24
Speaker 1: of it and those who sleep longer. So sleep disruption,
57:27
Speaker 1: sleep loss, that's a risk factor. The good news is
57:31
Speaker 1: most sleep problems are treatable, whether it's because of obstructive
57:34
Speaker 1: sleep apnea, or insomnia or any other reason, restless slag,
57:38
Speaker 1: all of those things. There's good treatments out there that
57:40
Speaker 1: will help people sleep better. So those are the four
57:43
Speaker 1: sort of chief things. There's many other smaller things, but
57:45
Speaker 1: those are the four ones that I like to lead
57:47
Speaker 1: with because they have just excellent data in their favor.
57:50
Speaker 2: Well, I'm excited about the sleep thing. I like sleeping.
57:54
Speaker 2: Maybe it's time to get out and exercise a little
57:56
Speaker 2: more so. My co host is a physicist. He always
57:59
Speaker 2: ends on a aliens. So here we go. If an
58:03
Speaker 2: alien were to land on Earth today, do you think
58:05
Speaker 2: they would store memories in a similar way.
58:08
Speaker 1: You know, if you had asked me that question ten
58:09
Speaker 1: years ago, I would have said, yes, I think our
58:11
Speaker 1: memory system is exceptional. It's wonderful, it's brilliant. Why not
58:15
Speaker 1: they should be like a model to strive to achieve.
58:19
Speaker 1: But I will take the opportunity since we've got a
58:20
Speaker 1: couple more minutes, Kelly, and tell you about something that
58:23
Speaker 1: changes my answer to this question. And that is the
58:27
Speaker 1: discovery that was made first by James Magaw who is
58:30
Speaker 1: the founding director of my center here at uc Aervine,
58:33
Speaker 1: and we continue to do work with this group of
58:35
Speaker 1: remarkable individuals who have what's called highly superior autobiographical memory.
58:41
Speaker 1: We spent a lot of time during this conversation talking
58:43
Speaker 1: about how memory is fallible. There's forgetting, there's interference. It's
58:46
Speaker 1: not meant to store everything with high fidelity because that's
58:49
Speaker 1: going to compromise your knowledge generation and so on. Well,
58:52
Speaker 1: these folks would beg to differ. And it's incredible because
58:56
Speaker 1: they do store things with high fidelity. They can remember
58:59
Speaker 1: everything that happened in our lives since that they were
59:01
Speaker 1: teenagers and tell you exactly what happened on what day
59:04
Speaker 1: of the week, what month, and someone. And they don't
59:07
Speaker 1: have a problem extracting generalities and knowledge. Also, So sometimes
59:11
Speaker 1: I'll jup with them and say I think you're like
59:13
Speaker 1: the X men of our generation, X people of our generation.
59:17
Speaker 1: It's remarkable and we still don't understand how they do
59:19
Speaker 1: it and how their brains are wired differently. So if
59:22
Speaker 1: aliens sufficiently advanced to aliens, I think, if they're reaching
59:26
Speaker 1: Earth before we reach them, they're probably far more advanced
59:29
Speaker 1: than us. They're more likely to have figure it out
59:31
Speaker 1: a way to do that which sort of combines the
59:34
Speaker 1: best of what we have built into our computers and
59:37
Speaker 1: what we have built into our brains. Just no compromise,
59:40
Speaker 1: no sacrifice.
59:41
Speaker 2: Awesome. Well, I wish Daniel we're here to hear that,
59:44
Speaker 2: but I'm sure he'll enjoy hearing that explanation when he
59:46
Speaker 2: gets back. Thank you so much for your time, Mike.
59:48
Speaker 2: This was absolutely fascinating.
59:50
Speaker 1: They're very welcome. I very much enjoyed to Kelly. Thank you.
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