USC Mark and Mary Stevens Neuroimaging and Informatics Institute Newsletter / Summer 2021
New MRI technique detects early blood-brain barrier dysfunction
Drs. Danny JJ Wang and Xingfeng Shao developed a new MRI method called diffusion-prepared arterial spin labeling (DP-ASL) that can detect subtle changes in blood-brain barrier (BBB) dysfunction by measuring water exchange across the BBB. They collaborated with researchers at the University of Kentucky to test whether it can provide a noninvasive imaging biomarker for early BBB problems associated with cerebral small vessel disease, with promising results. The paper was published in May in Alzheimer’s & Dementia.
Read the paper or learn more about the research from our colleagues
Mapping the equity of COVID-19 vaccinations in California
A USC team led by the INI’s Dr. Dominique Duncan studied disparities in COVID-19 vaccination across California’s 58 counties using the Social Vulnerability Index (SVI). They found that vaccination coverage was lower in counties with high socio-demographic vulnerability, particularly along the lines of minority status and language. The study’s authors hope the findings can help inform future vaccine distribution policies to better promote equity.
Connectivity mapping in the basolateral amygdalar complex (BLA)
A team that included the INI’s Dr. Michael Bienkowski, Dr. Ryan Cabeen, and others created a comprehensive connectivity map of the BLA, a region of the brain involved in behaviors such as fear acquisition and addiction. They used machine learning to analyze circuit-tracing data, identifying three new subdivisions of the anterior BLA. The results were published in Nature Communications in May.
Brain structure differences linked to suicide attempts
The INI’s Drs. Neda Jahanshad and Paul Thompson coauthored an analysis of neuroimaging and clinical data from nearly 19,000 people across North America, Europe, Asia, and Australia. Of the individuals studied, 694 had attempted suicide, 6,448 had been diagnosed with depression but had not attempted suicide, and 12,477 were healthy controls. Those who had attempted suicide had slightly less volume in the thalamus, an area of the brain involved in processing sensory and motor signals, and the right palladum, which may be related to reward and motivation, compared to the other groups. The study was published in March in the journal Biological Psychiatry.
New brain age prediction model leads to the discovery of novel genetic markers
A team led by INI Director Dr. Arthur W. Toga and Dr. Kaida Ning used a new mathematical model to predict brain age in a sample of more than 15,000 UK Biobank subjects. The convolutional neural network (CNN) model improved the accuracy of brain age estimates and led to the discovery of new genetic markers linked to brain aging. This may in term help researchers identify other lifestyle factors associated with brain aging. The paper appears in the journal Neurobiology of Aging in September.
USC+Amazon Center funds INI machine learning research
Dr. Paul Thompson, the associate director of the INI, has been selected by the newly launched USC+Amazon Center on Secure and Trusted Machine Learning to co-lead a research project on secure machine learning technologies. Dr. Thompson’s study is one of five projects funded by the center that will focus on enhancing the privacy, security, and trustworthiness of machine learning technologies.
Read more about the award from USC’s Viterbi School of Engineering
BRAIN Initiative’s 2020 “Mapping the Mind” contest
“The Beautiful Brainstem,” a scientific visualization of the brainstem created by the INI’s Jim Stanis, was featured by the BRAIN Initiative as one of the top entries in its 2020 “The Art of the BRAIN: Mapping the Mind” contest. The reconstruction of 23 fiber bundles was created using tractography data from 20 human subjects.
Watch the visualization below and learn more about how it was created
Technology commercialization award from the USC Stevens Center
The INI’s Dr. Tyler Ard is one of this year’s winners of the USC Stevens Center for Innovation’s Technology Commercialization Awards. The award recognizes Dr. Ard’s excellence for developing Schol-AR, an augmented reality smartphone application that allows researchers to add 3D models, videos, and visualizations to scientific materials.
Learn more about Schol-AR and augment your own materials at Schol-AR.io
TRAINING & OUTREACH
NSF awards for undergraduate and teacher training
The INI’s Dr. Dominique Duncan was awarded two supplemental awards from the National Science Foundation for COVID-ARC, a centralized research archive for COVID-19 data. She will use the funding to train four undergraduate students and two teachers from the nearby Francisco Bravo Medical Magnet High School in neuroscience research methods.
People
Welcome New Faculty
Dr. Ioannis Pappas
Dr. Ioannis Pappas joined the INI this summer as an assistant professor of research neurology. He completed his doctoral studies in clinical neuroscience at the University of Cambridge and conducted postdoctoral research at the University of California Berkeley’s Helen Wills Neuroscience Institute. His research includes multimodal studies of patients with stroke and disorders of consciousness resulting from brain injury.
Learn more about Dr. Pappas’ research
Dr. Jeiran Choupan
Dr. Jeiran Choupan, formerly a postdoctoral researcher and research scientist at the INI, is now an assistant professor of research neurology. She has a PhD in biomedical engineering and neuroscience, and employs machine learning and optimization strategies to improve structural and functional mapping of the brain using MRI. She leads a BRAIN Initiative-funded project that maps the brain's perivascular spaces in health, aging, and neurodegenerative disorders such as Alzheimer’s and Parkinson's diseases.
Meet Our Featured Postdocs
Dr. Jiong Zhang
Dr. Jiong Zhang received his doctorate degree in medical image analysis from the Eindhoven University of Technology (TU/e), Eindhoven, the Netherlands, where he focused on developing a computer-assisted large-scale screening program for detecting early diabetic retinopathy. Currently, he is working on the 3D shape modeling and analysis of vasculature in retinal optical coherence tomography (OCT) angiography and magnetic resonance angiography (MRA) images, with special interests in understanding the 3D geometrical and topological changes of vasculature in eye- and brain-related diseases. He is also working on the personalized analysis of cortical folding patterns for more precise quantification of brain atrophy in Alzheimer's Disease.
Dr. Leila Nabulsi
Dr. Leila Nabulsi received her doctorate in anatomy from the National University of Ireland Galway. Her research projects apply diffusion and functional MRI techniques to investigate the structural and functional networks underpinning affective dysregulation in mood disorders. She recently led the first multi-site study using structural connectomics and graph theory within the ENIGMA Bipolar working group, harmonizing the analysis of structural connectivity matrices and advanced network metrics across diverse participating sites. She is also working on lifespan modeling of brain measures, including multishell diffusion MRI measures of brain microstructure, to study development and brain aging, and relating normative data on brain metrics to plasma markers, clinical and genetic measures. She also co-leads the ENIGMA’s GWAS of white matter metrics based on diffusion MRI, and works on implementing advanced deep learning methods on white matter fiber bundles in Alzheimer’s disease.
Dr. Conor Owens-Walton
Dr. Conor Owens-Walton received his doctorate in medicine from the Australian National University in 2020, before moving to the United States to pursue a career in neuroscience. He now works at the INI's Imaging Genetics Center, leading the largest ever study into brain white matter microstructural changes in Parkinson's disease. This study leverages data and expertise from 16 academic sites all around the world. In collaboration with colleagues at UCLA, he also studies structural changes to the brain in people with medication-resistant, temporal lobe epilepsy, investigating whether there are any anatomical signatures present in a patient's brain image that might help predict post-neurosurgical outcomes.
Check back next time to meet three more of our postdocs.
INI In The News
Neuroimaging identifies early-stage dysfunction of the blood–brain barrier
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