The role of feedback in speech in autism: The missing perceptuomotor link

  • Awarded: 2021
  • Award Type: Human Cognitive and Behavioral Science Award
  • Award #: 877751

Over the past few decades, there have been significant gains made in modern communication technology, yet there exists a huge gap in the application of these technologies to help individuals who are minimally verbal with autism spectrum disorder (mv-ASD) speak or communicate. In the current project, Christopher McDougle, Pattie Maes and Thomas Quatieri plan to draw on advanced signal sensing and analysis technologies using on-body and off-body devices to characterize both vocal and behavioral means of expression and to uncover the nature of the verbal deficit with a goal of promoting the generation of speech.

The project brings together multidisciplinary research groups that have expertise in ASD and the neurophysiology of communication: (1) the Massachusetts General Hospital (MGH) Lurie Center for Autism/Martinos Center for Biomedical Imaging with expertise in recruiting and characterizing a large ASD population, and in ASD speech protocol design and brain imaging, (2) the Massachusetts Institute of Technology (MIT) Media Lab with its innovative real-time on-body sensing and interpreting of human neurophysiology, and (3) the MIT Lincoln Laboratory with its advanced speech and neuro-computational modeling and analysis methods and mobile off-body multi-modal platforms.

The main aim of this multisite collaboration is to characterize and describe the locus of communication differences in individuals with mv-ASD, focusing on analysis of speech production as well as measures of attention and engagement when using the same stimuli. The study will involve characterizing and analyzing the communication abilities of 30 individuals with mv-ASD and age and sex-matched neurotypical individuals (ages 16–40 years).

The insights gained from the proposed project will help develop a set of tools for use by clinicians to augment the existing perceptuomotor system through tailored feedback, which may lead to a richer repertoire of vocalizations and improved intelligibility and the development of personalized treatments.

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