Researchers from Massachusetts Institute of Technology (MIT) have conducted a study which demonstrates that sentences with complex grammar or unexpected meaning tend to stimulate the brain's key language processing centers significantly more than straightforward or nonsensical sentences. The study was led by Evelina Fedorenko, an Associate Professor of Neuroscience at MIT, and Greta Tuckute, a…
MIT neuroscientists have used an artificial language network to determine the type of sentences that most stimulate the brain's key language processing regions. Their study reveals that the brain reacts more to complex sentences with unusual grammar or unexpected meaning. Straightforward sentences or nonsensical sequences show little engagement. The researchers focused on language processing regions…
A team of neuroscientists from the Massachusetts Institute of Technology (MIT) have used an artificial language network to identify the type of sentences that activate the brain's critical language processing centres. The team learned that more complex sentences, which feature unusual grammar or unexpected meanings, generate strong responses from these centres, while straightforward sentences barely…
Using an artificial language network, neuroscientists from MIT have identified the type of sentences that most effectively activate the human brain's language processing centres. Their findings, published in Nature Human Behavior, show that the most stimulating sentences are those which are complex due to uncommon words or grammar, or unexpected meanings. Simplistic sentences or nonsensical…
A recent study from MIT has uncovered that the human brain's principal language processing centers are most activated while reading complex, unusual sentences. The artificial language network assisted study revealed that the more intricate a sentence was, either through unconventional grammar or unexpected meaning, the more these language processing centers were activated. In contrast, simple…
MIT researchers have used an artificial language network to decipher which types of sentences activate the brain's language processing centers most effectively. Their study reveals that sentences of higher complexity with unusual grammar or unexpected meanings engage these centers to a greater degree than straightforward sentences or nonsensical series of words. Their findings are based…
A new MIT study has found that computational models derived from machine learning that mimic the structure and function of the human auditory system could help improve the design of hearing aids, cochlear implants, and brain-machine interfaces. Its research explored deep neural networks trained to perform auditory tasks and showed that these models generate internal…
A recent study from MIT has shown that computational models that mimic the structure and function of the human auditory system could significantly aid research into more sophisticated hearing aids, cochlear implants, and brain-machine interfaces. Modern computational models that use machine learning have already made progress in this area.
The MIT team carried out the…
A new study from MIT reveals that modern computational models based on machine learning, which mimic the structure and function of the human auditory system, are coming closer to potentially aiding the design of improved hearing aids, cochlear implants, and brain-machine interfaces.
The MIT team’s research is the most extensive to date on deep neural networks,…