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