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Computational Neuroscience of Audition

Welcome to the Computational Neuroscience of Audition Lab

Our lab studies the neural and computational mechanisms of hearing. Everyday hearing - understanding a sentence, recognizing a voice, or picking out the melody of a song - is a feat of biological engineering. Machine hearing systems are just beginning to catch up to their biological counterparts and still lag behind them in many respects. The long-term goal of the lab is to understand and model the neural computations that underlie human hearing, and to use these insights to improve machine systems and aid in the treatment of sensory deficits. Our lab focuses on measuring human brain responses using functional MRI as well as intracranial recordings from patients undergoing electrode implantation as a part of their clinical care. We also collaborate with animal physiology labs to understand how the human brain differs from other species, as well as address questions that are difficult to answer using human neuroscience methods alone.

A key focus of the lab is on developing novel computational and experimental methods that allow us to exploit the full potential of these different recordings techniques.

Our computational work has two focuses:

  1. Developing data analysis methods that reveal underlying structure from high-dimensional neural responses to natural stimuli
  2. Testing computational models that attempt to replicate the neural computations and perceptual abilities of the human auditory system.

Lab Members

Samuel Norman-Haignere, Ph.D.

Samuel Norman-Haignere, Ph.D.
Principal Investigator


Neural mechanisms of hierarchical temporal integration

Representation of speech and music in non-primary auditory cortex

Testing computational models of human auditory cortex

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Contact Us

  Computational Neuroscience of Audition Lab
601 Elmwood Ave
Rochester, NY 14642