Michael I. Miller

About

Michael I. Miller is the Bessie Darling Massey Professor and Director of Biomedical Engineering at Johns Hopkins University, as well as co-director of the Kavli Neuroscience Discovery Institute. He specializes in data science, computational neuroscience, medical imaging, computational anatomy, and pattern theory. His research focuses on understanding and diagnosing neurodegenerative diseases by analyzing the functional and structural characteristics of the human brain in health and disease, including conditions such as Huntington’s disease, Alzheimer’s disease, dementia, bipolar disorder, schizophrenia, and epilepsy. Miller develops new tools to analyze patient brain scans derived from advanced medical imaging technologies, aiming to predict the risk of neurological disorders years before clinical symptoms appear. His lab is working on cloud-based methods to build and share libraries of brain images and algorithms related to neuropsychiatric illnesses. He has co-founded four start-up companies and has authored over 200 peer-reviewed publications and two highly cited textbooks on random point processes and computational anatomy. Miller earned his BS from the State University of New York at Stony Brook and his MS and PhD from Johns Hopkins University. He has held faculty positions at Washington University in St. Louis before joining Johns Hopkins in 1998, where he was named the Herschel and Ruth Seder Professor in Biomedical Engineering in 2003 and the director of biomedical…

Research topics

• Neuroscience
• Computer Science
• Sociology
• Political Science
• Medicine
• Psychology
• Engineering
• Materials science
• Pathology
• Engineering ethics

Selected publications

• The Brain Chart of Aging: Machine‐learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans

  Alzheimer s & Dementia · 2020 · 172 citations

  INTRODUCTION: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging database (11 studies; 10,216 subjects). METHODS: Three brain signatures were calculated: Brain-age, AD-like neurodegeneration, and white matter hyperintensities (WMHs). Brain Charts measured and displayed the relationships of these signatures to cogni…

  DOI

• STalign: Alignment of spatial transcriptomics data using diffeomorphic metric mapping

  Nature Communications · 2023-12-08 · 135 citations

  articleOpen access

  Spatial transcriptomics (ST) technologies enable high throughput gene expression characterization within thin tissue sections. However, comparing spatial observations across sections, samples, and technologies remains challenging. To address this challenge, we develop STalign to align ST datasets in a manner that accounts for partially matched tissue sections and other local non-linear distortions using diffeomorphic metric mapping. We apply STalign to align ST datasets within and across technol…

  PublisherOA PDFDOI

• Visualizing synaptic plasticity in vivo by large-scale imaging of endogenous AMPA receptors

  eLife · 2021 · 82 citations

  Elucidating how synaptic molecules such as AMPA receptors mediate neuronal communication and tracking their dynamic expression during behavior is crucial to understand cognition and disease, but current technological barriers preclude large-scale exploration of molecular dynamics in vivo. We have developed a suite of innovative methodologies that break through these barriers: a new knockin mouse line with fluorescently tagged endogenous AMPA receptors, two-photon imaging of hundreds of thousands…

  DOI

• Amidst an amygdala renaissance in Alzheimer’s disease

  Brain · 2023-12-18 · 58 citations

  articleOpen access

  The amygdala was highlighted as an early site for neurofibrillary tau tangle pathology in Alzheimer's disease in the seminal 1991 article by Braak and Braak. This knowledge has, however, only received traction recently with advances in imaging and image analysis techniques. Here, we provide a cross-disciplinary overview of pathology and neuroimaging studies on the amygdala. These studies provide strong support for an early role of the amygdala in Alzheimer's disease and the utility of imaging bi…

  PublisherOA PDFDOI

• A guide to the BRAIN Initiative Cell Census Network data ecosystem

  PLoS Biology · 2023-06-30 · 52 citations

  articleOpen accessCorresponding

  Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the…

  PublisherOA PDFDOI

Recent grants

• Tracing Spread of Pathology Within The HD Brain via Automated Neuroimaging

  NIH · $2.4M · 2018–2023

• NIH Grant U01NS082085

  NIH · $1.1M · 2015

• Continued Development and Maintenance of MriStudio

  NIH · $3.6M · 2013–2023

Frequent coauthors

• Susumu Mori

  Johns Hopkins University

  234 shared

• Laurent Younès

  Johns Hopkins University

  112 shared

• Ulf Grenander

  110 shared

• Daniel J. Tward

  University of California, Los Angeles

  101 shared

• J. Tilak Ratnanather

  Johns Hopkins University

  100 shared

• Andréia V. Faria

  88 shared

• Kenichi Oishi

  75 shared

• Marilyn Albert

  Johns Hopkins University

  74 shared

Education

• PhD, Biomedical Engineering

  The Johns Hopkins University

  1983

Awards & honors

• IEEE Biomedical Engineering Thesis Award (1982)
• Johns Hopkins Paul Ehrlich Graduate Student Thesis Award (19…
• NSF Presidential Young Investigator Award (1986)
• Inaugural Johns Hopkins University Gilman Scholar (2011)
• Fellow of the American Institute for Medical and Biological…

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