We are happy to announce that our Programme Leader, Dr Alexandra Woolgar, and Dr Laura Gwilliams from Stanford University have been awarded a BRAIN Foundation Research Grant to embark on an exciting new project that will use brain imaging to advance understanding of receptive language ability in non-speaking/minimally speaking autistic adults.
This collaboration between University of Cambridge and Stanford University seeks to characterise receptive language processing based on brain activity gathered from EEG (electroencephalography) and MEG (magnetoencephalography) data. Building on previous work by Dr Woolgar and Dr Gwilliams, this study will use a novel advances in machine learning to track properties of language that are encoded in very subtle neural responses during naturalistic listening. We will investigate neural processing of a comprehensive suite of spoken language features (speech sounds, word structure, word properties, syntax, semantics) simultaneously to develop a personalised, receptive language "fingerprint" at the individual-subject level. Critically, this approach allows for evaluation of language comprehension without needing to rely on motor responses (such as speaking or pointing) and thus holds potential lead to a better understanding of language ability in non-speaking autistic individuals.
Other highlights of the study include:
Use of a portable EEG to accommodate participants’ sensory and kinesthetic needs.
Analysis and results inferred at the individual participant level (vs at the group level, as is the norm in neuroscience research) to enable a better understanding of individual differences and heterogeneity within autism.
This will be one of the largest neuroimaging studies with non-speaking autistic individuals and the first to use naturalistic listening and machine learning to track their neural coding of a large suite of language features.
We welcome postdoctoral scholars with excellent neuroimaging timeseries analysis skills to express an interest in joining this project here.
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