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.
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
Jha, R.R., Pathak, S.K., Nath, V., Schneider, W., Kumar, B.V.R., Bhavsar, A., & Nigam, A. (2022) VRfRNet: Volumetric ROI fODF reconstruction network for estimation of multi-tissue constrained spherical deconvolution with only single shell dMRI. Magnetic Resonance Imaging, Volume 90, 1-16.
Huang S.Y., Witzel, T., Keil, B., Schneider, W., et. al., (2021). Connectome 2.0: Developing the next-generation ultra-high gradient strength human MRI scanner for bridging studies of the micro-, meso- and macro-connectome. <I> Neuroimage.</I>
Jha, R.R., Gupta, H., Pathak, S.K., Schneider, W., Kumar, B.V.R., Bhavsar, A., & Nigam, A. (2021). "Enhancing HARDI reconstruction from undersampled data via multi-context and feature inter-dependency GAN." EEE 18th International Symposium on Biomedical Imaging (ISBI), 1103-1106.
Krieger, D., Shepard, P., Soose, R., Puccio, A.M., Beers, S., Schneider, W., Kontos, A.P., Collins, M.W., & Okonkwo, D.O. (2021). Symptom-dependent changes in MEG-derived neuroelectric brain activity in traumatic brain injury patients with chronic symptoms. Medical Sciences, 9(20),1-30.
Onkonkwo, D.O., Puffer, R.C., Minhas, D.S., Beers, S.R., Edelman, K.L., Sharpless, J., Laymon, C.M., Lopresti, B.J., Benso, S., Puccio, A.M., Pathak, S., Ikonomovic, M.D., Mettenburg, J.M., Schneider, W., Mathis, C.A., and Mountz, J.M. (2021) "PET Imaging of Neurodegeneration in Two Subjects With a History of Repetitive Trauma and Cognitive Decline." Frontiers in Neurology.