SPaN-AD Research

• Speech Biomarkers for Early Disease Detection: We are developing and validating AI- and NLP-based speech biomarkers that detect subtle acoustic, articulatory, and language changes before clinical symptoms appear in Alzheimer’s disease and related disorders.
• Algorithm Development for Clinical Translation: We are designing robust machine learning and deep learning algorithms that automate the identification and classification of disease-related speech changes, creating tools that are accurate, scalable, and ready for real-world clinical use.
• Multimodal Neuroscience of Speech: We combine brain (EEG), muscle (EMG), kinematic, and advanced MRI modalities (7T, ASL, EEG-fMRI) to map the neural and physiological foundations of speech motor control in both healthy aging and neurodegenerative disease.
• Cerebrohemodynamics and Communication: We examine how cerebral blood flow and vascular health in speech and executive brain regions shape communication, influence dementia risk, and drive disease progression.
• Biomarker-Driven Speech Research: We link speech alterations to plasma and cerebrospinal fluid biomarkers (e.g., phosphorylated tau, neurofilament light), genetic profiles, and vascular/metabolic factors, uncovering how systemic health is mirrored in speech.
• Remote Data Collection Platforms: We are building digital platforms for remote speech and health data capture, enabling large-scale, inclusive studies and broadening participation to diverse and underserved populations.
• Disease-Specific Investigations: We pursue deep phenotyping across Alzheimer’s disease, vascular dementia, Lewy body disease, Parkinson’s disease, and ALS, advancing cross-disease insights into how speech reflects neurobiological integrity.
• Within-Group Phenotyping for Precision Diagnostics: We focus on individual and subgroup variability in disease onset and progression, with the goal of creating personalized risk profiles and advancing precision diagnostics.

These projects are supported by the National Institutes of Health (NIH), the Massachusetts AI and Technology Center for Connected Care (MassAITC), and the American Speech-Language-Hearing Foundation (ASHFoundation). We are deeply grateful for their support, which makes it possible to drive innovation, translate discoveries into clinical practice, and train the next generation of scientists committed to advancing brain health and dementia research.