Charan Ranganath

which is just fascinating, right? So you have this internal model, and that's a kind of a working memory product. It's something that you're keeping online that's allowing you to interpret this world around you. Now, to build that model, though, you need to pull out stuff from your general knowledge of the world, which is what we call semantic memory.

which is just fascinating, right? So you have this internal model, and that's a kind of a working memory product. It's something that you're keeping online that's allowing you to interpret this world around you. Now, to build that model, though, you need to pull out stuff from your general knowledge of the world, which is what we call semantic memory.

which is just fascinating, right? So you have this internal model, and that's a kind of a working memory product. It's something that you're keeping online that's allowing you to interpret this world around you. Now, to build that model, though, you need to pull out stuff from your general knowledge of the world, which is what we call semantic memory.

And then you'd want to be able to pull out memories for specific events that happened in the past, which we call episodic memory. So... In a way, they're all connected, even though it's different.

And then you'd want to be able to pull out memories for specific events that happened in the past, which we call episodic memory. So... In a way, they're all connected, even though it's different.

And then you'd want to be able to pull out memories for specific events that happened in the past, which we call episodic memory. So... In a way, they're all connected, even though it's different.

The things that we're focusing on and the way we organize information in the present, which is working memory, will play a big role in determining how we remember that information later, which people typically call long-term memory.

The things that we're focusing on and the way we organize information in the present, which is working memory, will play a big role in determining how we remember that information later, which people typically call long-term memory.

The things that we're focusing on and the way we organize information in the present, which is working memory, will play a big role in determining how we remember that information later, which people typically call long-term memory.

We're not at all the first to do this. Jeff Sachs was a big pioneer in this, and I've been working with many other people. Ken Norman, Leila Devachi at Columbia has done some interesting stuff with this.

We're not at all the first to do this. Jeff Sachs was a big pioneer in this, and I've been working with many other people. Ken Norman, Leila Devachi at Columbia has done some interesting stuff with this.

We're not at all the first to do this. Jeff Sachs was a big pioneer in this, and I've been working with many other people. Ken Norman, Leila Devachi at Columbia has done some interesting stuff with this.

There's this idea that we form these internal models at particular points of high prediction error or points of, I believe, also points of uncertainty, points of surprise or motivationally significant periods. And those points are when it's maximally optimal to encode an episodic memory. So I used to think, oh, well, we're just encoding episodic memories constantly, boom, boom, boom, boom, boom.

There's this idea that we form these internal models at particular points of high prediction error or points of, I believe, also points of uncertainty, points of surprise or motivationally significant periods. And those points are when it's maximally optimal to encode an episodic memory. So I used to think, oh, well, we're just encoding episodic memories constantly, boom, boom, boom, boom, boom.

There's this idea that we form these internal models at particular points of high prediction error or points of, I believe, also points of uncertainty, points of surprise or motivationally significant periods. And those points are when it's maximally optimal to encode an episodic memory. So I used to think, oh, well, we're just encoding episodic memories constantly, boom, boom, boom, boom, boom.

But think about how much redundancy there is in all that, right? It's just a lot of information that you don't need. But if you capture an episodic memory at the point of maximum uncertainty for the singular experience, it's only gonna happen once. But if you capture it at the point of maximum uncertainty or maximum surprise, you have the most useful point in your experience that you've grabbed.

But think about how much redundancy there is in all that, right? It's just a lot of information that you don't need. But if you capture an episodic memory at the point of maximum uncertainty for the singular experience, it's only gonna happen once. But if you capture it at the point of maximum uncertainty or maximum surprise, you have the most useful point in your experience that you've grabbed.

But think about how much redundancy there is in all that, right? It's just a lot of information that you don't need. But if you capture an episodic memory at the point of maximum uncertainty for the singular experience, it's only gonna happen once. But if you capture it at the point of maximum uncertainty or maximum surprise, you have the most useful point in your experience that you've grabbed.

And what we see is that the hippocampus and these other networks that are involved in generating these internal models of events, they show a heightened period of connectivity or correlated activity during those breaks between different events, which we call event boundaries. These are the points where you're surprised or you cross from one room to another and so forth.

And what we see is that the hippocampus and these other networks that are involved in generating these internal models of events, they show a heightened period of connectivity or correlated activity during those breaks between different events, which we call event boundaries. These are the points where you're surprised or you cross from one room to another and so forth.