The research focus of the Simonyan Laboratory is two-fold: identification of the central mechanisms responsible for speech production and elucidation of the pathophysiology of neurological voice and speech disorders.
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Mass Eye and Ear researchers Dr. Kristina Simonyan and Dr. Davide Valeriani were awarded a grant from the Radcliffe Institute for Advanced Study at Harvard University to organize a virtual seminar on September 10-11, 2020, which explored Brain-Computer Interfaces (BCIs) for transforming the treatment of dystonia. The seminar (by invitation only) brought together a diverse, interdisciplinary group of researchers from the fields of brain imaging, BCIs, computer science, and biotechnology, and clinicians from the fields of neurology, neurosurgery, otolaryngology, and speech-language pathology to explore a roadmap for transforming dystonia treatment. Read more here.
Harvard’s diverse neuroscience community — hundreds of basic researchers and physician-scientists, are engaged in the process of discovery across campuses and disciplines in Cambridge and the Greater Boston Area.
Dr. Simonyan was features as the Neuroscientist of the Week #60. Read more here.
The neuroscience community at Harvard is brimming with talented and interesting individuals, each with their own unique stories on how they got here, what motivates them, what passions and dreams they have, who inspires them and what they do for fun.
Read here about Arman Simonyan, who visited and worked in the lab this Summer.
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Tweets by @SimonyanLab
- Find out how Dr. Kristina Simonyan of @SimonyanLab, a neuroscientist and the head of the Dystonia & Speech Motor Control Laboratory at @MassEyeAndEar, created an AI-based deep learning platform that offers patients some peace of mind. #AmazonResearchAwards t.co/RISBq9l4PA
- Artificial Intelligence Is Leading the Way to Enhanced Diagnoses in Otolaryngology t.co/XAg8fsJ2ju
- Researchers at @SimonyanLab have developed a diagnostic tool that detects #dystonia from MRI, the first technology to provide objective diagnosis of the disorder. An AI-based deep learning platform called DystoniaNet diagnosed dystonia with 98.8% accuracy. t.co/cMjAyScvNO
- #Researchers were able to distinguish and identify isolated focal #dystonias with high-level of accuracy using a deep learning method of #artificialintelligence. #neurology @PNASNews @SimonyanLab @DavideValeriani @MarkHallett007 t.co/HYgQCotcSv t.co/RpQAABpD1r