Neuroimaging

Holschneider, Daniel P.

Professor of Psychiatry & the Behavioral Sciences

Our laboratory focuses on brain imaging in awake, behaving rodents. We use classic methods like autoradiography and positron emission tomography, along with histologic approaches and 3D brain reconstruction. We have been amongst the first to adapt analytic methods that are part of the human functional neuroimaging toolbox (statistical parametric mapping, functional connectivity, network analysis) to autoradiographic and histologic whole brain data sets. This enables voxel-based exploration of cerebral function in models of dopaminergic deafferentation, Huntington’s Disease, brain injury, fear, stress, hyperalgesia, gut microflora alterations, and chemogenetic knockdown. Our expertise includes functional brain mapping, animal behavior, physiologic monitoring (EEG, EMG, EKG, cardiac output), and histochemistry.

Immordino-Yang, Mary Helen

Professor of Education, Psychology & Neuroscience

Professor Mary Helen Immordino-Yang is the Director of USC CANDLE (Center for Affective Neuroscience, Development, Learning and Education). CANDLE’s mission is to bring developmental affective neuroscience into partnership with educational innovation, and to use what is learned to guide the transformation of schools, policy, and the student and teacher experience for a healthier and more equitable society. Our research involves analyzing multi-modal data, including functional and structural neuroimaging (MRI, EEG), and psychophysiological data, from mixed-method studies of adolescent development and effective teaching. During the 2025-2026 academic year, CANDLE will be designing, developing stimuli and collecting data for an upcoming longitudinal study of adolescents’ brain and psychosocial development.

Irimia, Andrei

Associate Professor of Gerontology, Quantitative & Computational Biology, Biomedical Engineering and Neuroscience

Andrei Irimia, PhD, is a biogerontologist and computational neurobiologist studying the effects of genetic, epigenetic, and environmental factors on brain aging. His laboratory uses interpretable deep learning, genomics, and brain imaging to identify and characterize novel risk factors for Alzheimer’s disease and related dementias (ADRD). He also studies accelerated aging, neurovascular calcification, and brain injury as risk factors for ADRD.