Samuel V. Norman-Haignere

Samuel V. Norman-Haignere, Ph.D. is an Assistant Professor at the University of Rochester with appointments in the Department of Biostatistics and Computational Biology, Department of Biomedical Engineering, and Department of Neuroscience within the School of Medicine and Dentistry. His research focuses on understanding the neural and computational mechanisms that underlie human hearing, particularly how the brain processes natural sounds like speech and music.

Dr. Norman-Haignere received his BA in Cognitive Science from Yale University in 2010 and his Ph.D. in Neuroscience from Massachusetts Institute of Technology in 2015. His doctoral work was conducted under the advisement of Josh McDermott and Nancy Kanwisher. He then completed postdoctoral training at Massachusetts Institute of Technology (2015-2017), École Normale Supérieure (2017-2018), and Columbia University (2018-2021).

Dr. Norman-Haignere's research centers on cognitive computational neuroscience, specifically investigating how the human brain perceives and understands natural sounds. His lab, the Computational Neuroscience of Audition Lab, focuses on three main areas:

• Neural mechanisms of hierarchical temporal integration - studying how the brain integrates information across multiple timescales from milliseconds to minutes
• Representation of speech and music in non-primary auditory cortex - identifying distinct neural populations that respond selectively to speech, music, and singing
• Testing computational models of human auditory cortex - developing models that replicate the nonlinear computations of the human auditory system

Analysis of Dr. Norman-Haignere's recent publications reveals a consistent focus on auditory neuroscience and computational modeling. His work spans multiple methodologies including fMRI, intracranial recordings, and computational modeling approaches. A key theme across his recent work is temporal integration in auditory processing, with several papers examining how the brain processes information across different time scales. His research also shows strong interdisciplinary connections between neuroscience, computer science, and cognitive psychology.

Dr. Norman-Haignere has received several scientific awards including:

• Poster Award (2019)
• Poster Award (2015)
• NSF Graduate Research Fellowship (2010-2015)

Dr. Norman-Haignere actively mentors graduate students and postdoctoral scholars in his lab. Current lab members include Postdoctoral Scholar Dana Boebinger, Research Technicians Zehua Kcriss Li and Guoyang Liao, and graduate students Joseph Jaeger (Biomedical Engineering), Pavel Rjabtsenkov (Neuroscience), David Skrill (Statistics), and Xinzhu (Claire) Wang (Statistics). His lab employs a range of methodologies including functional MRI, intracranial recordings from patients, and computational modeling to investigate auditory processing.

The Computational Neuroscience of Audition Lab, located at 601 Elmwood Ave, Rochester, NY 14642, maintains active collaborations with animal physiology labs to understand cross-species differences in auditory processing and address questions that cannot be answered using human neuroscience methods alone. A key focus of the lab is developing novel computational and experimental methods to fully exploit various neural recording techniques.