ROSE: A neurocomputational architecture for syntax

Hello and welcome. This is active guest stream 64.1. It's November 29th, 2023. We're here with Elliot Murphy, returning guest, and we'll be talking about this paper, Rose, a neurocomputational architecture for syntax. So for introduction and describing how today's stream is going to go, Elliot, thank you for joining. All right. Thanks so much, Daniel. Yeah, I work at the UT Health in Houston in Texas in the epilepsy monitoring unit where we use intracranial recordings to map language in patients with epilepsy. But today I want to present something a little bit more theoretical, a little bit more kind of philosophical almost. This is a new paper that's just come out in the Journal of Neurolinguistics, and I thought it'd be good for me just to kind of walk through the paper step by step, give some motivation, give some description, give some kind of outline of the general kind of framing for the paper. So the framework for this paper is trying to propose a general model for how to research language using intracranial recordings. It's basically trying to move beyond research that comes from other kinds of extracranial imaging methods, and it's trying to really figure out what is the most appropriate level of description in terms of neural complexity for specific aspects of language. So there's many different parts of language, as we know. Language has words, it has sounds, you know, it has, you can read language, you can sign it, you can construct meaning, you can do all sorts of things. But the real kind of question for me is, at what level of neural complexity, and therefore at what level of appropriate recording resolution, based on what tools you have available, is going to be providing you with the most reliable signatures of particular levels of structure. So in this model, the Rose model, I invoke representations, operations, structures, and encoding, and I'll introduce them step by step. And so for the purposes of this kind of introduction, I'm just going to kind of outline what those general kind of frameworks are. But to begin, the most kind of basic assumption that we have about language, in terms of like the findings from linguistics, so the study of language, like the scientific study of language, one of the really basic introductions that you find in every introductory textbook, is that linguists have kind of arrived at the conclusion that the human mind brain applies a set of rules to recursively combine linguistic units into larger objects, which derives an unbounded array of hierarchically structured expressions, with humans in varying sentence meaning based on syntactic configuration. Now that's a lot of jargon. But essentially, what that means is, when you hear a linear sequence of words, like, you know, we watched a movie with Jim Carrey, you can pass that not simply as like beads on a string, you can pass it in two ways, depending on how you chunk the individual phrases together, and how you establish relations between different elements. So for example, you know, we watched a movie with Jim Carrey can mean that you watched, you know, Eternal Sunshine of Spotless Mind, or it can mean that you're sat there next to Jim Carrey watching, you know, the new Napoleon film, for example. So there's this kind of ambiguity there, but the ambiguity arises due to structural configurations. So that's kind of how you rearrange the sentences kind of in your head internally. And that is obviously a process that's independent immediately from sensory motor, you know, transformations or experience or speech or sound or orthography. So these are very abstract processes. And they're clearly mental processes. They're not processes of the visual system. They're not processes of the auditory system. They're clearly high order mental computations. So what that phrase, unbounded array of hierarchically structured expressions means, is it just means that humans have this generative capacity. And people like Carl Christen and Chomsky…