Relating sentence representations in deep neural networks with those encoded by the brain

In their investigation, the researchers considered several neural network architectures for word representation, including two recently proposed models called ELMo and BERT.

They compared how these networks process particular sentences with data collected from human subjects using magnetoencephalography (MEG), a functional neuroimaging technique for mapping brain activity, as they read the same sentences.

To begin with, they decided to use sentences with a simple syntax and basic semantics, such as "the bone was eaten by the dog."

Read more below: or watch this Github link:
https://lnkd.in/dvbiJAz
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