| Faculty Member | Research Interests |
|---|---|
| Kelly R. Bijanki, Ph.D. | Human intracranial neurophysiology, affective neuromodulation and neuroimaging |
| J. David Dickman, Ph.D. | Neural computation of motion, spatial navigation, magnetoreception and regenerative repair |
| Fabrizio Gabbiani, Ph.D. | Computation of sensory processing and sensorimotor transformations in the CNS |
| Benjamin Hayden, Ph.D. | Professor, Department of Neurosurgery. Human intracranial neurophysiology, Reward, decision-making, executive control, cognition, anxiety, depression |
| Jay Hennig, Ph.D. | Computational neuroscience, NeuroAI, learning in neural population activity, reinforcement learning. |
| Daoyun Ji, Ph.D. | Neural circuit mechanisms in memory formation, consolidation, recall and utilization |
| Xiaolong Jiang, Ph.D. | Dissecting cortical microcircuits in epilepsy and autism-spectrum disorders |
| Caleb Kemere, Ph.D. | Machine learning and closed-loop experiments for memory and translation |
| Vaishnav Krishnan, M.D, Ph.D. | Epilepsy and Emotional Behavior; home-cage behavioral analysis of genetic mouse models of epilepsy or epilepsy risk |
| David Lipshutz, Ph.D. | Algorithmic models of learning and adaptation in neural circuits, analysis of biological and artificial neural representations. |
| Atul Maheshwari, M.D. | Computational analysis of EEG in epilepsy and ADHD in mice and humans |
| Matthew McGinley, Ph.D. | Auditory cognition; multiphoton imaging and whole-cell recording in behaving mice |
| Javier F. Medina, Ph.D. | Reverse engineering neural algorithms for prediction in cerebellar circuits |
| Jochen Meyer, Ph.D. | Mechanisms of cortical network dysfunction in genetic and acquired epilepsies, with emphasis on glioblastoma-related hyperexcitability and childhood absence epilepsy. Multimodal, chronic in vivo recordings in awake mice using 2-photon and widefield imaging of diverse fluorescence reporters, EEG and behavioral measurements. |
| T. Dorina Papageorgiou, Ph.D. | Elucidation the brain mechanisms of induced learning following injury, using real-time fMRI neurofeedback training: neurorehabilitation of cortical blindness, speech dysarthria, and chronic pain syndromes; Machine learning and advanced quantitative approaches to model visual perception |
| Ankit Patel, Ph.D. | Computational neuroscience of visual cortex; artificial neuroscience; theories of deep learning |
| Robia G. Pautler, Ph.D. | Functional brain imaging in animal models of Alzheimer’s disease |
| Nicole Provenza, Ph.D. | Neurophysiology underlying cognition and emotion, psychiatric neuromodulation, deep phenotyping, human neuroscience in the real-world. |
| Jacob Reimer, Ph.D. | Brain states and attention, functional connectomics and fluorescence imaging in mice |
| Ramiro Salas, Ph.D. | Brain imaging of psychiatric disorders. |
| Md. Abul Hassan Samee, Ph.D. | Developing computational tools to elucidate the molecular mechanisms underlying neurodevelopment and neurodegeneration. Specifically, develop machine learning and AI tools to model single-cell and spatial omics data and predict the consequence of human genetic variants. |
| Sameer A. Sheth, M.D, Ph.D. | Cognitive neurophysiology using human intracranial recordings and neuromodulation for psychiatric disorders |
| Nora Vanegas-Arroyave, M.D. | Connectomics, Precision Medicine and Neuromodulation in Neurodegenerative diseases. |
| Jeffrey M. Yau, Ph.D. | Identify principles that unify the senses and how sensorimotor functions go awry |
| Qiancheng Zhao, Ph.D. | Molecular and cellular mechanisms, as well as the neurocircuitry underlying our interoception. |
Baylor College of Medicine
Baylor College of Medicine
Baylor College of Medicine
Dr. David Dickman's lab is studying the mechanisms in the pigeon brains that help them navigate, with the hope of using that knowledge to better understand the human brain in diseases like Alzheimer’s, where people often lose their sense of orientation.