School of Medicine
Research and Training Center for Hearing and Balance


Neural Encoding Laboratory

PIs:
Eric D. Young, Ph.D., Professor of Biomedical Engineering
Murray B. Sachs, Ph.D., Professor of Biomedical Engineering
Bradford J. May, Ph.D., Professor of Otolaryngology/Head and Neck Surgery

Students and Fellows:
Sharba Bandyopadhyay, graduate student
Shanqing Cai, graduate student
Steve Chase, graduate student
Ben Letham, graduate student
Diana Wei-Li Ma, postdoctoral fellow
Tessa Ropp, graduate student
Zachary Smith, postdoctoral fellow
William Tam, graduate student

General Description:

Research in the neural encoding laboratory investigates the representation and processing of complex stimuli in the auditory system. One goal is to understand the relationships between the perception of sound and the responses of auditory neurons. Another is to analyze the effects of hearing impairment on the representation and to investigate signal processing for neural prostheses. Some specific examples of our approach:

  1. Neural circuits in the brainstem auditory system. How is the brain organized for auditory information processing? How are neurons interconnected and how do they interact?

    Examples of research in this area:


  2. The representation of complex stimuli in neural responses. How does the activity of neurons in the brain represent the acoustic environment? How do we discriminate between sounds? How can we understand and model the neural representation of sound?

    Examples of research in this area:

    • Discrimination of consonant-vowel syllables can use neural activity at a variety of time scales. - information about the differences between similar speech sounds is contained in a variety of aspects of the spike trains. Here a measure of information sensitive to the differences between stimuli is used to show that stop consonants differ at the formant frequencies, as expected, but also at high frequencies, where the acoustics of the burst at the release of the stop are important.

    • Receptive fields of auditory neurons can be linear or nonlinear. - Auditory spectral receptive fields become nonlinear in some neurons in the cochlear nucleus. A method of constructing receptive fields for spectral shape (i.e. the frequency content of sounds) gives first and second-order receptive fields. These are used to show that neurons in the ventral cochlear nucleus are reasonably linear, i.e. well-represented by first plus second order models, whereas neurons in dorsal cochlear nucleus are frequently nonlinear. This is the first systematic description of the effects of second-order components of receptive fields.

    • Information about sound localization is distributed across neuron types in the inferior colliculus. - Three neuron type can be recognized in the inferior colliculus, based on response maps. These seem to be connected differently to brainstem auditory neurons, suggesting a difference in the representation of different sound localization cues. Analysis of the representations using mutual information shows that some segregation exists, but generally auditory information is distributed broadly across the response types.

  3. Studies of stimulus representation in animals with hearing impairment. Acoustic trauma is used to produce a hearing loss resembling a sloping high-frequency hearing loss, typical of older listeners and hearing-aid users.
  4. Examples of research in this area:


The BMES 2005 will be held in Baltimore.