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A Computational Approach for Quantifying Motor Behaviors in Spinocerebellar Ataxias to Improve Early Detection of Motor Signs and Precisely Estimate Disease Severity and Disease Change

Award Number: R01NS117826
ORGANIZATION: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 04/15/2021
PERIOD OF PERFORMANCE END DATE: 03/31/2026

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A Computational Approach for Quantifying Motor Behaviors in Spinocerebellar Ataxias to Improve Early Detection of Motor Signs and Precisely Estimate Disease Severity and Disease Change - ABSTRACT The spinocerebellar ataxias (SCA) are debilitating neurodegenerative diseases that impact a range of human behaviors including arm function, speech, and vision. Tools that can quantify motor deficits in a granular and objective manner are needed to support early recognition of clinical disease onset, more sensitively determine efficacy of a therapy, and make personalized predictions about disease progression. Such tools are needed for upcoming disease modifying clinical trials in SCAs, in order to reduce sample size and trial duration and better understand how a given therapy modifies human behaviors. Powered off of the currently available primary outcome measures for these rare ataxias, clinical trials are likely to face patient recruitment and retention challenges, especially with multiple co-occurring clinical trials. These challenges may impede or slow our ability to successfully discover therapies for our patients. We have recently made substantial progress in capturing multimodal behavioral signals from speech, eye movement, and arm motor function using everyday technologies: a microphone, iPhone camera, and computer mouse. Our initial data indicate that these scalable technologies have strong potential to extend current clinical assessments in ataxia and that our novel machine learning approach for generating disease severity estimates performs better than the traditional regression model approach. Our algorithms are able to quantitatively identify signs of ataxia and parkinsonism in SCA individuals' speech and arm movement, even when absent on clinical assessment. Furthermore, our novel severity estimation algorithm enabled measurement of disease progression more sensitively than clinical scales. We propose to substantially expand longitudinal data collection and further develop our novel analytic approaches to train more powerful models for characterizing and quantifying human motor behavior. The technologies developed have the potential to facilitate clinical trials aimed at bringing disease modifying therapies to individuals with SCA. While the focus of this project is on SCA, the novel methodological approaches and data generated are applicable to other neurodegenerative diseases affecting movement and speech. Furthermore, this project will bring new insight into how motor abnormalities initially arise and progress. The overall goal of this project is to develop widely available systems for improving early detection of clinical disease onset, severity assessment, and prognostication of spinocerebellar ataxias while simultaneously learning how these disorders impact fine-grained motor behavior.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = $474,690 )
2025	2025	THE GENERAL HOSPITAL CORPORATION	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	5	3/17/2025	NON-COMPETING CONTINUATION	$474,690
														Subtotal = $474,690

Issue Date FY: 2024 ( Subtotal = $516,097 )
2024	2024	THE GENERAL HOSPITAL CORPORATION	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	001	4	4/9/2024	NON-COMPETING CONTINUATION	$37,245
2024	2024	THE GENERAL HOSPITAL CORPORATION	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	4	3/8/2024	NON-COMPETING CONTINUATION	$478,852
														Subtotal = $516,097

Issue Date FY: 2023 ( Subtotal = $534,869 )
2023	2023	THE GENERAL HOSPITAL CORPORATION	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	3	3/30/2023	NON-COMPETING CONTINUATION	$534,869
														Subtotal = $534,869

Issue Date FY: 2022 ( Subtotal = $537,775 )
2022	2022	MASSACHUSETTS GENERAL HOSPITAL, THE	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	2	4/14/2022	NON-COMPETING CONTINUATION	$537,775
														Subtotal = $537,775

Issue Date FY: 2021 ( Subtotal = $555,308 )
2021	2021	MASSACHUSETTS GENERAL HOSPITAL, THE	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Extramural Research Programs in the Neurosciences and Neurological Disorders	000	1	4/1/2021	NEW	$555,308
														Subtotal = $555,308

Grand Total All Awards = $2,618,739

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A Computational Approach for Quantifying Motor Behaviors in Spinocerebellar Ataxias to Improve Early Detection of Motor Signs and Precisely Estimate Disease Severity and Disease Change

Award Number: R01NS117826

ORGANIZATION: NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 04/15/2021

PERIOD OF PERFORMANCE END DATE: 03/31/2026

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