Brocas, Isabelle
I am a Professor at the University of Southern California and the co-director of the Los Angeles Behavioral Economics Laboratory (LABEL) and the Theoretical Research in Neuroeconomic Decision-making (TREND) Institute. My research revisits standard theories of decision-making and aims at better understanding how people make choices, what motivates them and what cognitive limitations prevent them from making rational choices.
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.
Kay, Steve A.
Our laboratory studies the construction and dynamics of complex genetic networks that underlie circadian rhythms in humans, animals and plants. We also develop and use cutting-edge technologies for measuring transcription in live cells, tissues and intact organisms. We use large scale datasets of gene expression or protein content combined with genetics, bioinformatics and computational tools (mathematical modeling), chemical screens and more conventional biochemical approaches. Ultimately our aim is to scale our understanding of the dynamics of circadian clocks from the systems level down to atomic resolution mechanism. We have a strong commitment to translation of our research, in the case of humans for novel cancer drug discovery. We are currently focussing on targeting clock proteins in glioblastoma stem cells, in order to develop novel therapeutics.
Kim, Hosung
The Neuroimaging with Deep Learning Lab (NIDLL) focuses on developing and applying advanced artificial intelligence methods to understand brain health, aging, and disease. Our research integrates multimodal neuroimaging, biosignals, and longitudinal clinical data to characterize individual variability in brain structure and function across the lifespan. A central theme of the lab is the use of deep learning and data-driven modeling to derive biologically meaningful markers—such as regional brain age and system-level brain health indices—that can predict clinical outcomes and treatment response. A major emphasis of NIDLL is on sleep, cerebrovascular function, and the glymphatic system as key modulators of brain aging and neurodegeneration. We develop MRI-based metrics to quantify perivascular spaces, cerebrospinal fluid dynamics, and glymphatic function, and study how their disruption relates to poor sleep quality, accelerated brain aging, and neurodegenerative processes. These methods are applied across diverse populations and neurological conditions, including Alzheimer’s disease, Parkinson’s disease, stroke, epilepsy, and sleep disorders, with the goal of identifying early, noninvasive biomarkers of disease vulnerability and progression. Ultimately, NIDLL aims to bridge computational neuroscience and translational medicine by building predictive models that support precision diagnosis and personalized intervention. By combining large-scale neuroimaging datasets, longitudinal designs, and interpretable AI, our work seeks to inform clinical decision-making and optimize therapeutic strategies for neurological and sleep-related disorders. The lab is led by Dr. Hosung Kim, who mentors trainees and collaborators in developing rigorous, impactful research at the intersection of neuroimaging, artificial intelligence, and brain health. We welcome you to join the lab and participate in our valuable research.
Mather, Mara
Professor of Gerontology, Psychology, and Biomedical Engineering
The autonomic nervous system plays an underappreciated role in age-related change in the brain and cognition. But the sympathetic hub region in the brain (the locus coeruleus) is one of the first brain regions affected by Alzheimer’s disease pathology and deep sleep, a period of high parasympathetic activity, is critical for clearing out the potentially toxic proteins generated by the brain’s activity during the day (it is the aggregation of such proteins that leads to the hallmark plaques and tangles seen in Alzheimer’s disease). Our research is investigating how both sympathetic and parasympathetic function affect brain function and cognition in aging and how interventions that increase parasympathetic activity may enhance brain function in older adults.
Matho, Katherine
Assistant Professor of Pediatrics
How do developmental and genetic programs build brain circuits for complex behavior? My lab investigates this question by integrating developmental neuroscience, molecular genetics, and multi-scale circuit mapping to study cortical sensorimotor circuits underlying goal-directed actions and perception. Using interdisciplinary approaches, such as gene knockin mouse lines and single cell profiling, we examine how neuronal identity and connectivity emerge during development. Our goal is to uncover the molecular and developmental logic of circuit assembly in neurotypical development and how the key building blocks that make up the circuits—cell types—are disrupted in neurodevelopmental disorders. We hypothesize that a temporal patterning program during pregnancy specifies neuron subtype and wiring, shaping sensorimotor function in the mature brain.
