Courtney Gallen, Ph.D.
Postdoctoral Fellow - Neuroscape
UCSF – Mission BaySandler Neuroscience CenterMC 0444, 675 Nelson Rising LaneSan Francisco, CA 94158
Courtney graduated in 2009 from Penn State with a B.S. in biology, concentrating in neuroscience. As an undergraduate, Courtney worked with Sheri Berenbaum, examining the effects of prenatal testosterone exposure on gender-typed behavior. From 2009 to 2011, Courtney worked in Elliot Stein’s lab at the National Institute on Drug Abuse through the NIH Post-Baccalaureate IRTA program. There, she studied the effects of genetic polymorphisms on reward processing using fMRI.
In Courtney’s graduate work with Mark D’Esposito at UC Berkeley, she used fMRI and graph theory to examine properties of large-scale functional brain networks that support cognitive control processes, such as working memory. One arm of her dissertation research focused on examining modular network reconfiguration due to cognitive control demands. This work showed that the pattern of demand-related reconfiguration is altered by selective attention and normal aging. A second arm of her dissertation work focused on examining the role of baseline brain network properties in predicting training-related cognitive control gains. This work showed that brain network modularity is predictive of training gains in both young and older adults, suggesting that network properties may be a unifying predictor of cognitive training success across populations and interventions.
As a postdoctoral researcher, Courtney is using her previous experiences to develop personalized approaches to cognitive interventions, particularly in a combined cognitive and physical fitness intervention (Body Brain Trainer). Specifically, she is using neural predictors to enhance training outcomes. An additional interest includes generating models to identify an individual’s optimal intervention for cognitive gains. She is broadly interested in how aspects of brain networks support cognitive control and are related to cognitive and neural plasticity. She also anticipates learning various aspects of EEG data collection and analysis.