An NYU team uses machine learning to analyze neural activity data and uncover how speech is produced. In a recent paper published in Nature Communications Psychology, a research team at NYU, led by Associate Professor Adeen Flinker and Postdoctoral Researcher Adam Morgan, explored how the brain constructs sentences from individual words. Using high-resolution electrocorticography (ECoG), […]



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An NYU team led by Adeen Flinker and Adam Morgan used machine learning to analyze neural activity data obtained through electrocorticography (ECoG). Their research, published in Nature Communications Psychology, aimed to understand how the brain forms sentences from individual words. By analyzing high-resolution ECoG data, the team sought to identify the neural mechanisms underlying sentence construction. Their findings shed light on the brain’s complex processes involved in speech production, providing valuable insights into the cognitive functions that enable us to communicate through language. The study contributes to a better understanding of the neural basis of language.

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