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Deterioration of bulbar function in ALS

Bulbar functionThis five-year (2009–2014) project is funded by the National Institutes of Health in the U.S. This study is conducted by Drs. Yana Yunusova and Lorne Zinman in collaboration with Drs. Ronnie Green and Gary Pattee at the University of Nebraska-Lincoln.

The project has three goals.

Goal one is to identify instrumental measures of bulbar function that are sensitive to bulbar amyotrophic lateral sclerosis (ALS) onset and progression. Currently, we identify changes in speech by listening to speech. Usually, the disease might be quite advanced when changes are detectable by ear. We need to be able to diagnose changes in the bulbar function as early as possible to provide timely management of the symptoms and, in the future, administer medical therapies.

Goal two is to understand the course of disease progression in the bulbar system over time. This work is motivated by the need to be able to predict how bulbar ALS will develop in different individuals so that, again, management of symptoms can be planned in advance.

Goal three is to understand what parts of the bulbar (speech) mechanism affect most of the speech intelligibility decline. Speech intelligibility is the ability to be understood by listeners. Patients with bulbar ALS can become less intelligible over time. Identification of specific speech subsystems (components of the speaking apparatus; i.e., the voice box, muscles of the tongue or the face, or soft palate) is essential in order to offer a targeted intervention in the future.

In this study, patients with ALS are asked to undergo a speech recording every three months. The function of the voice box, breathing muscles, soft palate, face and tongue are recorded during an approximately 30-minute session.

Read the description published in the Journal of Visual Experiments.

Neuroanatomical correlates of motor and cognitive dysfunction in ALS

BrainThis project was funded by the ALS Society of Canada (through the Bernice Ramsay Discovery Grant) and is conducted by Drs. Yunusova and Zinman in collaboration with Drs. Sandra Black at Sunnybrook Research Institute (SRI), Donald Stuss at Baycrest Centre for Geriatric Care and Greg Stanisz at SRI.

The primary aim of this study is to improve our understanding of the cognitive, motor and brain changes that occur in patients with ALS. Cognition is evaluated using a new computerized test that we have developed and named the ALS computerized frontal battery (ALS-CFB).

This test probes areas of the brain that have never been evaluated before in subjects with ALS and can easily be performed in clinic on patients at all phases of the disease no matter how severe their motor deficit. Motor (speech and limb) and brain changes are measured using state-of-the art instruments and imaging techniques, which are extremely sensitive and objective measures.

Relating the cognitive, speech and brain changes that occur in ALS as the disease progresses helps us to understand better why this disease occurs and how it progresses. This information is of vital importance as learning more about how ALS affects the brain may help us to design and test new promising treatments for this devastating disease.

Speech movement classifications for diagnosing and treating ALS

This five-year project (2013–2018) is funded by the National Institutes of Health in the U.S. This study is conducted in collaboration with Dr. Jordan Green at MGH Institutes of Health Professions in Boston, U.S., and Drs. Jun Wang and Thomas Campbell at the University of Dallas Texas.

The project will lead to more accurate and efficient speech motor assessments, and to new pathways of oral communication for people with speech impairments, such as a real-time silent speech interface (a device that generates speech in response to silently produced movements of the tongue, lips and jaw).

The project has three goals.

Goal one is to determine the diagnostic accuracy for machine learning analyses of speech movements and standard clinical measures of speech involvement for diagnosing bulbar ALS at an early stage.

Goal two is to determine if our instrumental speech movement measures are more stable and sensitive to decline in speech production than currently used clinical measures of speech involvement in people with ALS. 

Goal three is to determine the accuracy of online, automatic speech movement recognition in individuals with varying levels of speech impairment due to ALS using a silent speech interface and self-learning algorithm.

Patients with ALS are asked to undergo a comprehensive speech assessment at each session lasting approximately 90 minutes.

A demonstration of a real-time, silent speech interface is currently under development.