Learning Research and Development Center
Professor of Psychology
University of Pittsburgh
Professor of Neurosurgery
University of Pittsburgh Medical Center
Executive Board Member
Center for the Neural Basis of Cognition
Professor of Radiology
University of Pittsburgh
Dr. Schneider investigates dynamic cortical processing in human behavioral and brain imaging studies and computer simulation models. Behavioral and brain imaging studies focus on the understanding of human learning, executive control and attention.
Research examines cortical areas involved in learning including frontal, parietal, and cingulate cortex, subcortical structures (e.g., hippocampus) and sensory processing areas (e.g., thalamus and visual cortex). The brain imaging research utilizes functional Magnetic Resonance Imaging (fMRI) to produce high 3D spatial resolution (near millimeter) maps identifying the location and relative activation of stages of the visual system and Diffusion Tensor Imaging (DTI) to map cortical connectivity.
These data provide the basis for detailed tracking of the dynamics of cortical processing. We are developing methods to map human network level cortical processing. Behavioral and brain imaging data details how rapidly and in what forms attention moves and what are the component structures of learning (goal popping, memory retrieval, feedback processing). These methods are applied in pre-surgical planning to minimize damage during surgery.
Welcome to the Schneider Laboratory
Our research focuses on mapping the functional and anatomical network structure of the brain.
Using various methods, including fMRI and High Definition Fiber Tracking (HDFT), our goal is to characterize the "information superhighways" of the brain and how they change with experience.
Eagle, S. R., Puccio, A. M., Agoston, D. V., Mancinelli, M., Nwafo, R., McIntyre, P., Agnone, A., Tollefson, S., Collins, M., Kontos, A. P., Schneider, W., Okonkwo, D. O., & Soose, R. J. (2023). Association of plasma biomarkers with sleep outcomes and treatment response after mild traumatic brain injury. Neurotrauma Reports, 4(1), 251–254.
Jha, R.R., Kumar, B.V.R., Pathak, S.K., Schneider, W., Bhavsar, A., & Nigam, A. (2023.) Undersampled single-shell to MSMT fODF reconstruction using CNN-based ODE solver. Computer Methods and Programs in Biomedicine.
Schneider, W., Wu, Y., Watson, A., Kedziora, K., Pathak, S., Zhao, Y., et al. (2023). Fasciculus axonal connective tissue multiscale imaging (FACTMI): connectome mapping of optic nerve with 16 µm MRI at 14T and 0.1 µm histology. In 2023 ISMRM &; ISMRT Annual Meeting & Exhibition (ISMRM 2023).
Pathak, S., Wu, Y., Gorantla, V., Zor, F., Kulahci, Y., Watson, A., Zhao, Y., & Schneider, W. (2022). Fasciculus axonal connective tissue (FACT) mapping of porcine optic nerve for accurate connectome mapping. Poster Presentation, ISMRM Conference, London, England.
Bhat, S. B., Kumar, B.V.R., Kalamkar, S.R., Kumar, V., Pathak, S., & Schneider, W. (2022). Modeling and simulation of the potential indoor airborne transmission of SARS-CoV-2 virus through respiratory droplets. Physics of Fluids
Filipiak, P., Shepherd, T., Basler, L., Zuccolotto, A., Placantonakis, D.G., Schneider, W., Boada, F.E. & Baete, S.H. (2022). Stepwise stochastic dictionary adaptation improves microstructure reconstruction with orientation distribution function fingerprinting. Computational Diffusion MRI. CDMRI 2022. Lecture Notes in Computer Science, vol 13722. Springer, Cham.