• Posted January 22, 2026

Study Finds Human Language Processing Mirrors How AI Understands Words

The human brain may understand spoken language in a way that is surprisingly similar to how artificial intelligence (AI) processes words, a new study suggests.

By tracking brain activity as people listened to a spoken story, researchers found that the brain builds meaning step by step, very similar to the way large AI language models do.

The findings challenge older ideas that language understanding relies mainly on strict rules or fixed symbols.

The study, published recently in the journal Nature Communications, analyzed brain signals from people listening to a 30-minute podcast.

"What surprised us most was how closely the brain's temporal unfolding of meaning matches the sequence of transformations inside large language models," lead author Ariel Goldstein of Hebrew University of Jerusalem said in a news release.

"Even though these systems are built very differently, both seem to converge on a similar step-by-step buildup toward understanding," Goldstein added.

Language doesn’t “click” all at once in the brain. Instead, each word moves through a series of stages.

In early moments, the brain responds to basic features of speech. Later, it pulls in context.

The researchers found that this process closely matched how AI models handle language, where early layers focus on simple word details and deeper layers build meaning using context.

This match was strongest in higher-level language regions of the brain, including Broca’s area, which plays a key role in speech and language.

Activity in these areas appeared later in time and lined up with the deepest layers of AI models, researchers said.

For years, scientists thought language understanding depended mostly on fixed building blocks.

But in this study, those traditional features did not explain actual brain activity as well as the contextual patterns used by AI systems.

Instead, the findings suggest that meaning forms gradually and depends heavily on context, not rigid rules.

To help other scientists explore how the brain creates meaning, the research team released the full findings, which include detailed brain recordings and language features collected during the study.

The dataset offers a new way for researchers to test ideas about language, compare brain activity with AI models and build models that better reflect how humans understand speech.

More information

The Memory and Aging Center has more on speech and learning.

SOURCE: Hebrew University of Jerusalem, news release, Jan. 21, 2026