A team of CBU scientists are developing a neural test that may be able to detect language comprehension in autistic people with minimal spoken language.
The test uses EEG to measure children’s neural responses to spoken sentences. It relies on machine-learning algorithms to detect whether the brain responds differentially to sentences that are semantically correct or incorrect. With this approach, the team found that they could detect language processing from the brains of 9 out of 10 children, without requiring them to give any spoken answers. We also validated the use of a portable, inexpensive EEG system, which could be used to test children outside the lab, where they are more comfortable.
We are now testing whether our methods can be used with non-speaking autistic people, which could give important insight into the language abilities of this under-researched population.
The published paper is:
Petit, S. et al. (2020) Toward an Individualized Neural Assessment of Receptive Language in Children. JSLHR. https://doi.org/10.1044/2020_JSLHR-19-00313