Braskie, Meredith
Assistant Professor of Neurology
We use neuroimaging, fluid biomarkers, environmental and genetic risk factors, and comorbidities to better understand Alzheimer’s disease (AD) risk - particularly the mechanisms underlying earliest brain characteristics that may signal or contribute to future cognitive decline. I am especially interested in the contributions of vascular, metabolic, and inflammatory risk to AD-relevant brain measures in older adults. I am also interested in disease heterogeneity and how it relates to health disparities and sex differences.
Chang, Karen T.
Associate Professor of Physiology and Neuroscience
Our lab is interested in understanding how neurons communicate with high fidelity to support complex brain functions. We aim to uncover the molecular and cellular mechanisms that enable precise synaptic signaling and to explore how disruptions in these processes contribute to neurodevelopmental and neurodegenerative disorders. Using Drosophila melanogaster as a genetically tractable model system, we integrate electrophysiology, molecular biology, confocal imaging, proteomics, and behavioral analysis to investigate synaptic function and plasticity.
Ching, Christopher
Assistant Professor Of Research Neurology
Dr. Ching’s research focuses on neuroimaging and genomic markers of psychiatric and neurodegenerative disorders. As a core organizing member of the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium, he designs and implements standardized processing and analysis techniques for large-scale neuroimaging studies. He leads the ENIGMA Bipolar Disorder Working Group, an effort pooling data and resources from around the world to improve our understanding of the biological processes driving bipolar disorder, and studies rare copy number variants like 22q11.2 Deletion Syndrome to understand how genetic mutations can lead to increased risk for developing psychiatric illness. He leads several large-scale transdiagnostic neuroimaging and genomic initiatives using machine learning to map common and distinct brain and clinical factors across mental illnesses.
Choupan, Jeiran
Assistant Professor Of Research Neurology
I have been working in the field of neuroimage processing and computational neuroscience since 2009. My focus is on employing advanced neuroimaging and machine learning techniques to improve structural and functional mapping of the brain to study neurodegenerative disorders. In particular, my main research focus is on mapping vascular and perivascular features of the brain across lifespan in health and in the presence of cognitive decline and dementia. Perivascular space is a major component of the brain clearance system and plays an important role in maintaining a healthy functioning brain, particularly in elderly and individuals at risk of neurodegenerative disease.
Christopoulos, Vasileios
Assistant Professor of Biomedical Engineering
Prof. Christopoulos' research focuses on understanding the neural mechanisms underlying higher-order cognitive functions, such as decision-making, motor learning, and motor control. In recent years, he has expanded his research to include clinical studies on patients with brain and spinal cord injuries. His work encompasses intracortical Brain-Machine Interface research in individuals with tetraplegia and the use of functional ultrasound imaging in patients undergoing surgery for brain and spinal cord disorders. His innovative research aims to bridge the gap between basic neuroscience and clinical applications, contributing to advancements in neurotechnology and neurorehabilitation.
Coba, Marcelo
Neurodevelopmental neurodegenerative and psychiatric disease are complex brain disorders, and a multitude of genes have been described to contribute to their pathology with different penetrance. Human genetic studies have discovered many genes associated with disease susceptibility that are usually described as risk factors. For each of these disorders, synaptic proteins have been implicated, in particular those involved in synaptic plasticity and protein complexes associated to the post-synaptic density (PSD). Despite these discoveries, there has been a gap in understanding the underlying mechanisms that contribute to cellular dysfunction in these disorders. Our long-term goal is to determine how candidate risk factors are functionally integrated and how mutations affect their function, not individually, but in developmental signaling networks.
