Imagine a biological neural network whose physical size, if all its tissues were put together, wouldn't exceed the size of a regular strawberry.
🟢 How our brain processes speech?
By MIT Neuroscientist Ev Fedorenko
Her conclusions will sound very familiar to engineers and data scientists: there's a system operating inside the human head that behaves suspiciously similar to modern large language models. It's a kind of "mindless" language processor that maps words and meanings, but itself is completely incapable of thinking.
This ASSERTION IS BASED on a significant BODY OF DATA.
Fedorenko's lab conducted fMRI scans of 1,400 people to build a detailed probabilistic map of brain activity.
The architecture of this "language network" turned out to be surprisingly stable and reproducible: in most adults, it's localized in 3 specific areas of the left frontal lobe and along a long stretch of the middle temporal gyrus.
Fedorenko calls this structure a functional block, comparable to an organ like the digestive system or the face recognition zone.
The most interesting part begins when you look at its functionality. Fedorenko describes this network as a parser or a set of pointers. Its task is purely utilitarian - to act as an interface between input signals (sound, text, gestures) and abstract representations of meaning stored in completely different parts of the brain.
The language network itself has no episodic memory, social intelligence, or the ability to reason. The entire process of reflection takes place outside its boundaries.
This explains the phenomenon of aphasia: when this "interface" is damaged, a person retains complex cognitive thinking but is locked inside themselves, having lost access to the vocabulary and grammatical rules.
The similarity to LLMs becomes even more obvious when you look at the system's limitations.
Research shows that the human language network has an extremely narrow contextual window: it can effectively process chunks of up to 8-10 words in length.
In essence, this is a rather superficial system. It reacts to Noam Chomsky's grammatically correct nonsense "Colorless green ideas sleep furiously" just as actively as it does to meaningful sentences. What matters to it is the structure and statistical probability of word pairings, not the truth or deep meaning of the statement.
This makes it akin to early language models: the network simply learned the rules by which words are assembled into chains.
Fedorenko's data force us to reconsider classic anatomical concepts, as many textbooks still refer to outdated concepts.
For example, Broca's area, which for decades was considered the center of speech, turned out to be an area of motor planning. It merely prepares the mouth muscles for articulation and is activated even when uttering complete nonsense, acting as a controlled region for receiving commands.
The real language network of the brain is a separate, specialized computing cluster that, like ChatGPT, brilliantly mimics the coherence of speech, even if there's no real thought behind it.
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