Radiology Personnel

Tara Madhyastha, Ph.D.

Research Assistant Professor


My research interest is in development of new methods for quantifying change in functional networks of the brain using neuroimaging. I have an extensive background in modeling of complex systems in computer architecture, cognition and behavior in educational systems, and nonlinear influence in marriage. In the past I have been responsible for multimodal neuroimaging data collection and analysis in the Seattle Longitudinal Study (N~160, data collected at 4 time points). My current emphasis is on characterization of dynamic fluctuations of connectivity within intrinsic networks, and how these fluctuations are affected by age and neurodegenerative disease.

Recent Publications

See all publications on Scopus

Vascular Risk Factors and Findings on Brain MRI of Elderly Adult American Indians: The Strong Heart Study
Shibata D., Suchy-Dicey A., Carty C., Madhyastha T., Ali T., Best L., Grabowski T., Longstreth W., Buchwald D.
Neuroepidemiology. 2019 Jan:173-180

Overview of the cholinergic contribution to gait, balance and falls in Parkinson’s disease
Morris R., Martini D., Madhyastha T., Kelly V., Grabowski T., Nutt J., Horak F.
Parkinsonism and Related Disorders. 2019 Jan

Telomere Length and Magnetic Resonance Imaging Findings of Vascular Brain Injury and Central Brain Atrophy
Suchy-Dicey A., Muller C., Madhyastha T., Shibata D., Cole S., Zhao J., Longstreth W., Buchwald D.
American Journal of Epidemiology. 2018 Jun:1231-1239

Quantitative cerebrovascular pathology in a community-based cohort of older adults
Rane S., Koh N., Boord P., Madhyastha T., Askren M., Jayadev S., Cholerton B., Larson E., Grabowski T.
Neurobiology of Aging. 2018 May:77-85

Uncovering dynamic functional connectivity of Parkinson’s disease using topological features and sparse group lasso

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2018 Jan:423-434

Running neuroimaging applications on Amazon Web Services: How, when, and at what cost?
Madhyastha T., Koh N., Day T., Hernández-Fernández M., Kelley A., Peterson D., Rajan S., Woelfer K., Wolf J., Grabowski T.
Frontiers in Neuroinformatics. 2017 Nov

A reproducible neuroimaging workflow using the automated build tool “Make”
Madhyastha T., Koh N., Askren M.
The Practice of Reproducible Research: Case Studies and Lessons from the Data-Intensive Sciences. 2017 Oct:297-304

Findings of Vascular Brain Injury and Structural Loss from Cranial Magnetic Resonance Imaging in Elderly American Indians: The Strong Heart Study
Suchy-Dicey A., Shibata D., Madhyastha T., Grabowski T., Longstreth W., Buchwald D.
Neuroepidemiology. 2017 Jun:39-47

Total Brain and Hippocampal Volumes and Cognition in Older American Indians: The Strong Heart Study
Cholerton B., Omidpanah A., Madhyastha T., Grabowski T., Suchy-Dicey A., Shibata D., Nelson L., Verney S., Howard B., Longstreth W., Montine T., Buchwald D.
Alzheimer Disease and Associated Disorders. 2017 May:94-100

Empirical comparison of diffusion kurtosis imaging and diffusion basis spectrum imaging using the same acquisition in healthy young adults
Wang S., Peterson D., Wang Y., Wang Q., Grabowski T., Li W., Madhyastha T.
Frontiers in Neurology. 2017 Mar