Combining computational controls with natural text sheds new light on how the brain processes language

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Strategy. Credit: Nature Computational Science (2022). DOI: 10.1038/s43588-022-00354-6

People accomplish an outstanding quantity of duties by combining items of knowledge. We understand objects by combining edges, categorize scenes by combining objects, interpret occasions by combining actions, and perceive sentences by combining phrases.

However researchers do not but have a transparent understanding of how the brain varieties and maintains the that means of the entire—corresponding to a sentence—from its elements. Carnegie Mellon University researchers within the College of Pc Science’s (SCS) Machine Studying Division (MLD) have shed new gentle on the brain processes that help the emergent that means of mixed phrases.

Mariya Toneva, a former MLD Ph.D. pupil now college on the Max Planck Institute for Software program Programs, labored with Leila Wehbe, an assistant professor in MLD, and Tom Mitchell, the Founders University Professor in SCS, to review which areas of the mind processed the that means of mixed phrases and the way the mind maintained and up to date the that means of phrases.

This work might contribute to a extra full understanding of how the mind processes, maintains and updates the that means of phrases, and will redirect analysis focus to areas of the mind appropriate for future wearable neurotechnology, corresponding to units that may decode what an individual is making an attempt to say straight from brain activity. These units may help individuals with ailments like Parkinson’s or a number of sclerosis that restrict muscle management.

Toneva, Mitchell and Wehbe used neural networks to construct computational fashions that might predict the areas of the mind that course of the brand new that means of phrases when they’re mixed. They examined this mannequin by recording the mind exercise of eight individuals as they learn a chapter of “Harry Potter and the Sorcerer’s Stone.”

The outcomes recommend that some areas of the mind course of each the that means of particular person phrases and the that means of mixed phrases, whereas others course of solely the meanings of particular person phrases. Crucially, the authors additionally discovered that one of many neural exercise recording instruments they used, magnetoencephalography (MEG), didn’t seize a sign that mirrored the that means of mixed phrases.

Since future wearable neurotechnology units would possibly use recording instruments just like MEG, one potential limitation is their lack of ability to detect the that means of mixed phrases, which might have an effect on their capability to assist customers produce language.

The staff’s work builds on previous analysis from Wehbe and Mitchell that used functional magnetic resonance imaging to establish the elements of the mind engaged as individuals learn a chapter of the identical Potter ebook. The outcome was the primary built-in computational mannequin of studying, figuring out which elements of the mind are liable for such subprocesses as parsing sentences, figuring out the that means of phrases and understanding relationships between characters.

The findings are revealed within the journal Nature Computational Science.

Extra data:
Mariya Toneva et al, Combining computational controls with pure textual content reveals features of that means composition, Nature Computational Science (2022). DOI: 10.1038/s43588-022-00354-6

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Combining computational controls with pure textual content sheds new gentle on how the mind processes language (2022, November 29)
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