How the Brain Parses Language

Dyslexia seems to be more of an issue in English than other languages right?

But also, maybe the difficulty of parsing recruits other/executive function and is beneficial in other ways?

The per phoneme density/efficiency of English is supposed to be quite high as an emergent trade language.

Perhapse speaking a certain language would promote slower more intentional parsing, humility through syntax uncertainty, maybe not, all I know is that from a global network resilience perspective it's good that dumb memes have difficulty propagating across cultures/languages.

And we have those French/English text corpora in the form of Canadian law. All laws in Canada at the federal level are written in English and French.

This was used to build the first modern language translation systems, testing them going from English->french->english. And in reverse.

You could do similar here , understanding that your language is quite stilted legalese.

Edit: there might be other countries with similar rules in place that you could source test data from as well.

There are more differences between English and French than you just described, and they can affect your measurement. Even the corpora you use cannot be the same. There isn't "ceteris paribus" (holding everything else constant). The outcome of the experiment doesn't say anything about the hypothesis.

You're also going to use an artificial neural network to make claims about the human brain? That distance is too large to bridge with a few assumptions.

BTW, nobody believes our language faculties are doing the thinking. There are however, obviously, connections to thought: not only the concepts/meaning, but possibly sharing neural structures, such as the feedback mechanism that allows us to monitor ourselves.

I have a slightly better proposal: if you want to see the effect of gender, genderize English or neutralize French, and compare both versions of the same language. Careful with tokenization, though.

That presumes that languages with little morphology do not have equivalent structures at work elsewhere doing the same kind of heavy lifting.

One classic finding in linguistics is that languages with lots of morphology tend to have freer word order. Latin has lots of morphology and you can move the verb or subject anywhere in the sentence and it's still grammatical. In a language like English syntax and word order and word choice take on the same role as morphology.

Inflected languages may indeed have more information encoded in each token. But the relative position of the tokens to each other also encodes information. And inflected languages appear to do this less.

Languages with richer morphology may also have smaller vocabularies. To be fair, this is a contested conjecture too. (It depends a lot on how you define a morpheme.) But the theory is that languages like Ojibwe or Sansrkit with rich derivational morphologies and grammatical inflections simply don't need a dozen words for different types of snow, or to describe thinking. A single morpheme with an almost infinite number of inflected forms can carry all the shades of meaning, where different morphemes might be used to make the same distinctions, in a less inflected language.

I suspect you're more right than wrong. I'm a strong believer in this sort of thing -- that humans are best understood as a cyborg of a biological and semiotic organism, but mostly a "language symbiont inside a host". We should perhaps understand this as the strange creature of language jumping between hosts. But I suspect we're looking at a mule of sorts: it can't reproduce properly. But this mule could destroy us if we put it to work doing the wrong things, with too much agency when it doesn't have the features that give us the right to trust our own agency as evolved creatures.

You might be interested to look into the Leiden Theory of Language[1][2]. It's been my absolutely favourite fringe theory of mind since I stumbled across the rough premise in 2018, and went looking for other angles on it.

[1] https://www.kortlandt.nl/publications/art067e.pdf

[2]: https://en.wikipedia.org/wiki/Symbiosism

> Language is a mutualist symbiont and enters into a mutually beneficial relationship with its hominid host. Humans propagate language, whilst language furnishes the conceptual universe that guides and shapes the thinking of the hominid host. Language enhances the Darwinian fitness of the human species. Yet individual grammatical and lexical meanings and configurations of memes mediated by language may be either beneficial or deleterious to the biological host.

EDIT: almost forgot the best link!

Language as Organism: A Brief Introduction to the Leiden Theory of Language Evolution https://www.isw.unibe.ch/e41142/e41180/e523709/e546679/2004f...

Written French does have all that inflectional morphology you talk about, but spoken French has much less--a lot of the inflectional suffixes are just not pronounced on most verbs (with the exception of a few, like être and aller--but at least 'be' in English is inflected in ways that other verbs are not). So there's not that much redundancy.

As for gender marking on adjectives--or nouns--it does almost no semantic work in French, except where you're talking about professional titles (doctor, professor...) that can be performed by men or by women.

If you want a heavily inflected language, you should look at something like Turkish, Finnish, Swahili, Quechua, Nahuatl, Inuit... Even Spanish (spoken or written) has more verbal inflection than spoken French.

What do you make of this article? They used an auto-regressive genomic model to perform in-context learning experiments compared to language models. This showed that ICL behavior is not exclusive to language models. https://arxiv.org/html/2511.12797v1

I speak several languages too, though definitely not as many as you do. I'm also in the process of learning a completely new one, at an advanced age relative to when I last learned a new one (I was in my thirties then). To me, my brain most definitely doesn't process human language the way it handles computer language. It's about as different as it can get. The latter is "learning", the former is "burn patterns into the brain", and learning a language can take years, at least at this age. Computer languages? Those can be picked up in as little as a weekend, and getting proficient isn't a multi-year or decade long process. It feels totally different for me (I've been learning new computer languages at the same time as I've been trying to get up to speed with a new human language).

I completely understand! I'm also Polish American. I have to say it helps when mother's side of family is Gdańsk+west and father's Lublin+east. My wife's family is all from Warsaw area and I had to translate for my father-in-law during a holiday to Władysławowo-Hel (probably helps my aunt's father's side is Kashubian too, mmm... dessert first).

I was blown-away on holiday to Croatia. It was so unexpectedly relatively easily understandable after Czechia, Austria, and Slovenia. I was all, "What just happened!? Shouldn't this be something more like Italian?"

It took only a month for me to be able to communicate in Ukrainian with my ESL students, you're totally right about Cyrillic. And I too think in concepts but switch my brain to express them externally via language, whatever that language may be at the moment. I am terrible at translating OTOH, so unnatural!

But it has it's limits, I got to a point after German and Norwegian that I thought I harbored a super-power. Then I went to school in Hungary ;) I also had an ESL student from Lithuania, yep incomprehensible.

I think this quote may speak to the question:

> The brain’s general object-recognition machinery is at the same level of abstractness as the language network. It’s not so different from some higher-level visual areas such as the inferotemporal cortex (opens a new tab) storing bits of object shapes, or the fusiform face area storing a basic face template.

In other words, it sounds like the brain may start with the same basic methods of pattern matching for many different contexts, but then different areas of the brain specialize in looking for patterns in specific contexts such as vision or language.

This seems to align with the research of Jenny Saffran, for example, who has studied how babies recognize language, arguing that this is largely statistical pattern matching.

Me too! Babies and toddlers brains are like sponges. We started teaching my baby 3 languages since birth (essentially I always spoken with her in my native language, my wife in hers and gets English from living in the US). She’s not even 4 yet an fully fluent in all three and seemlessly jumps back and forth between them. (To my surprise, she doesn’t mix words from the different languages in the same sentence)

One part of the story I found fascinating is the overlap in infants' brains of the areas involved in tool use and hierarchical syntax. These diverge and specialize in adults. The homologous brain region in primates is involved in motor planning.

It's an interesting hint at the deeper evolutionary origins of language in the ability to plan complex actions, providing a neural basis for the observation that language and action planning have this common structure of an overall goal that can be decomposed into a structure of subgoals, which we see formalized in computer programs too.

This is an older reference (1991) where I first heard about it. there are more recent studies reinforcing various aspects of it but I didn't find one that was as comprehensive

https://doi.org/10.1017/S0140525X00071235

It's an interesting area of research, there is even some evidence that language experienced in utero affects speech perception: https://doi.org/10.1111/apa.12098.

I'd like one stage further - what are the genetics of this area? How does a dedicated brain area like this get encoded - (Hopefully the Allen Institute might dig on this one?); but if we can find how the areas are encoded in the DNA we could presumably see how they evolved, but then perhaps also spot other areas?

At that age, I always figured "Why parse?"

It isn’t clear though. Neural networks were inspired by the brain, but transformers? It is totally plausible but do we really think just in words?

We've been making the same metaphor ("that's how the brain works") with each new major technology we come up with...

Yes, but at least now we're comparing artificial to real neural networks, so the way it works at least has a chance of being similar.

I do think that a transformer, a somewhat generic hierarchical/parallel predictive architecture, learning from prediction failure, has to be at least somewhat similar to how we learn language, as opposed to a specialized Chompyskan "language organ".

The main difference is perhaps that the LLM is only predicting based on the preceding sequence, while our brain is driving language generation by a combination of sequence prediction and the thoughts being expressed. You can think of the thoughts being a bias to the language generation process, a bit like language being a bias to a diffusion based image generator.

What would be cool would be if we could to some "mechanistic interpretability" work on the brain's language generation circuits, and perhaps discover something similar to induction heads.

All of those analogies were useful in some ways, and LLMs are too.

There's also a progression in your sequence. There were rudimentary mechanical calculating devices, then electrical devices begat electrical computers, and LLMs are a particular program running on a computer. So in a way the analogies are becoming more refined as we develop systems more and more capable of mimicking human capabilities.

I think it's obvious that she means that it's something _like_ LLMs in some aspects. You are correct in that rhythm and intonation are very important in parsing language. (And also an important cue when learning how to parse language!) It's clear that the human language network is not like LLM in that sense. However, it _is_ a bit like an _early_ LLM (remember GPT2?) in the sense that it can produce and parse language, not that it makes much deeper sense in it.

>Yet, completely glosses over the role of rhythm in parsing language.

If you're talking about speech cadence/rhythm, then we also parse written language which doesn't have that. And we're quite capable of parsing a monotone robotic voice speaking with a monotonous mechanical rhythm too.

Ev Fedorenko is a highly recognized cognitive scientist that has been studying how humans parse language for years.

Of course this doesn't mean one shouldn't question what she says (that would be an obvious authority fallacy), but I do think it's fair to say that if you want to question it, the argument should be more elaborate that "this sounds like she has no idea of the topic".

That's a really good question. I don't have an answer, or even the beginning of an answer, but I would hazard a guess that there is a feedback loop. So listening to yourself talk (or even better, putting your thoughts down in print) is sort of like listening to someone else talk, which puts new ideas into your mind, or causes you to better organize the ones you already have.

Doing mathematical proofs might be an extreme example of that: a mathematician has (I am told) an intuition--a thought--but has to work it out rigorously. Once they've done that, the intuition becomes much clearer. I guess.

Yes, but animal/human brains (cortex) appear to have evolved to be prediction machines, originally mostly predicting evolving sensory inputs (how external objects behave), and predicting real-world responses to the animal's actions.

Language seems to be taking advantage of this pre-existing predictive architecture, and would have again learnt by predicting sensory inputs (heard language), which as we have seen is enough to induce ability to generate it too.

The disanalogy you quote might actually be the key insight. What if language operates at two levels, like Kahneman's System 1/2?

Level 1: Nearly autonomic — pattern-matched language that acts directly on the nervous system. Evidence: how insults land before you "process" them, how fluent speakers produce speech faster than conscious deliberation allows, and the entire body of work on hypnotic suggestion, which relies on language bypassing conscious evaluation entirely.

Level 2: The conscious formulation you describe — the translator between perception and meaning.

LLMs might be decent models of Level 1 but have nothing corresponding to Level 2. Fedorenko's "glorified parser" could be the Level 1 system.