Javier F. Medina

Javier F. Medina, Ph.D., is a Professor and Brown Foundation Chair in Neuroscience at Baylor College of Medicine. His research focuses on understanding how neural circuits implement supervised learning to make predictions, particularly in the context of motor control and cognitive functions. His laboratory combines experimental techniques such as electrophysiology, optogenetics, and two-photon imaging with computational modeling and artificial neural networks to uncover the computational principles underlying brain function.

Education

• Postdoctoral Fellowship in Neuroscience, UCSF (2007)
• Ph.D. in Neuroscience, University of Texas, Houston (2000)
• Bachelor of Science in Computer Science and Physics, Drexel University, Philadelphia (1993)

Research Interests
Medina’s work integrates computational neuroscience with experimental approaches to study prediction and error correction in neural circuits. His lab investigates how the cerebellum encodes temporal information, processes sensory input, and adapts through learning. Key topics include supervised learning algorithms, neural coding in Purkinje cells, and the role of prediction errors in motor adaptation.

Publications
His research spans themes in cerebellar circuitry, motor learning, and computational modeling. Recent work includes deep learning strategies for cell-type identification and studies on cerebellar modules for predictive control.

Grants & Labs
Medina leads a lab at Baylor College of Medicine, focusing on experimental and theoretical neuroscience. His work has implications for motor disorders linked to learning deficits, such as ataxia and Parkinson’s disease.