{"slug": "we-may-have-finally-identified-the-brains-language-network", "title": "We May Have Finally Identified the Brain’s Language Network", "summary": "Neuroscientists at Stanford University and the Massachusetts Institute of Technology have identified the brain's language network, publishing their findings in Nature Communications. The study, led by Cory Shain of Stanford and Evelina Fedorenko of MIT, analyzed fMRI scans of nearly 1,200 people and found a stable network across the left hemisphere and frontal temporal regions, detectable even during non-language tasks. The network's shape varies between individuals but remains consistent within each person regardless of task.", "body_md": "The quest to map the “language center” of the brain has been going on for decades. Early research relied on brain injuries and the corresponding disorders to pin down relevant areas of the brain. While technological advancements in neural imaging have led to the identification of the regions involved, the results have been more piecemeal than comprehensive. After all, what we call “language” is incredibly complicated. It involves hearing, auditory processing, memory retrieval, muscle control—the list goes on. But now, neuroscientists may have finally mapped the language network, detailing the process in a paper [published](http://dx.doi.org/10.1038/s41467-026-75745-8) in *Nature Communications* today.\n\n“Language is a very complex thing,” study author Cory Shain of Stanford University said in a [statement](https://www.eurekalert.org/news-releases/1139675). “It’s like a spider web that ties together almost everything about us. It’s hard to reach agreement on a definition of language, or even whether language is a unified ‘thing’ at all. With this study, we tried to set aside our preconceptions about what language is and ask what the brain itself is telling us about how language might be implemented.”\n\nFor their study, Shain and his colleague Evelina Fedorenko of the Massachusetts Institute of Technology sent nearly 1,200 people into an fMRI machine to observe the blood flow in their brains while they performed certain tasks. Some of the tasks, like reading aloud, focused on language, while others, like matching colored squares, did not. During all the tasks, the fMRI machine hummed away recording video of how their blood flow changed.\n\n**Read more: “ Language Is the Scaffold of the Mind”**\n\nTo identify the language network, the researchers took an interesting approach. Instead of just averaging brain scans to identify key regions that light up—which can distort or mask functional differences—they were able to closely examine individuals’ brains. Additionally, rather than looking at blood flow based on the tasks performed, they looked at how activity changed over time in different regions of the brain. This let them isolate a range of “functional connectomes” (or areas of the brain where activity covaried) that represented different possible networks, including the one for language.\n\nRemarkably, they were able to detect the language network even when looking only at scans taken during the non-language tasks.\n\n“The human brain appears to have a network that’s selective and necessary for language, and we can find that network from the activity in the brain alone,” Shain explained. “The simple fact that a person’s brain activity is always going up and down lets us detect where this network is with high fidelity. It’s such an important and stable structure that we can find it no matter what someone is doing.”\n\nSo where is it exactly?\n\nAccording to the team, this network spreads across the left hemisphere and frontal temporal regions of the brain, places where regions associated with language have previously been detected. Its shape, however, depends on the brain. The researchers found that the network can vary from person to person. Still, each person’s individual network structure stayed the same, regardless of the task they were performing.\n\nJust like us, language is complicated. Now, we know the network responsible for it is, too.\n\n*Enjoying *[Nautilus](https://nautil.us/)*? Subscribe to our free *[ newsletter](https://nautil.us/newsletter/?_sp=c43011db-6fcf-42f2-a38c-e033b87a4a1d.1759265717430).\n\n*Lead image: Vitalii Vodolazskyi / Adobe Stock*", "url": "https://wpnews.pro/news/we-may-have-finally-identified-the-brains-language-network", "canonical_source": "https://nautil.us/we-may-have-finally-identified-the-brains-language-network-1283730/", "published_at": "2026-08-13 16:00:00+00:00", "updated_at": "2026-08-13 16:23:05.189217+00:00", "lang": "en", "topics": ["neural-networks", "artificial-intelligence"], "entities": ["Stanford University", "Massachusetts Institute of Technology", "Cory Shain", "Evelina Fedorenko", "Nature Communications"], "alternates": {"html": "https://wpnews.pro/news/we-may-have-finally-identified-the-brains-language-network", "markdown": "https://wpnews.pro/news/we-may-have-finally-identified-the-brains-language-network.md", "text": "https://wpnews.pro/news/we-may-have-finally-identified-the-brains-language-network.txt", "jsonld": "https://wpnews.pro/news/we-may-have-finally-identified-the-brains-language-network.jsonld"}}