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:

             Paul Nelson, Ph.D., postdoctoral fellow

 Sean Slee, Ph.D., postdoctoral fellow

 Amanda Lauer, Ph.D., postdoctoral fellow

 Josh Vogelstein, graduate student

 Tessa Ropp, graduate student

 Matt Roos, graduate student

 William Tam, graduate student

 Ben Haeffele , graduate student

 Yang Li, 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:

o    What's a cerebellar circuit doing in the auditory system? - a review of the circuitry and functional properties of the dorsal cochlear nucleus, with speculations about the role of this nucleus in the brain.

o    Somatosensory input to the DCN carries information about the position of the pinna - The DCN receives both auditory and somatosensory inputs. The somatosensory ones in the cat respond to stretch of the muscles that are used to move the external ear (pinna). This suggests a role of the DCN in coordinating information about the location of sounds in space.

o    DCN principal cells respond to spectral edges, which requires additional inhibitory effects in DCN - DCN principal cells give a peak discharge rate to rising spectral edges centered near BF. This response cannot be fully explained by the current known circuitry of the DCN.

o    Synaptic transmission from auditory nerve to ventral cochlear nucleus was studied using cross-correlation of simultaneously-recorded spike trains, showing short-latency non-depression transmission and an unexpected mode in which VCN neuron spikes occur in an autonomous limit-cycle-like behavior, as opposed to 1:1 spiking with the auditory nerve fibers.

 

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:

o    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.

 

o    Receptive fields of auditory neurons can be linear or nonlinear. - 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. The nonlinearity in dorsal cochlear nucleus is mainly caused by the effects of sound level, possibly through the actions of inhibitory interneurons.

 

o    Neurons in dorsal cochlear nucleus are more linear at low spectral contrast.  - The linearity of receptive fields depends on the degree of spectral contrast (meaning the fluctuation of sound levels in the sound spectrum). In addition, the gain of neurons increases at low contrasts. These effects occur in the auditory nerve, but are stronger in the dorsal cochlear nucleus.

 

o    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. Information is also coded in temporal aspects of spiking, like first spike latency.

 

o    Perceptual forward masking corresponds well to the properties of neurons in inferior colliculus - The dynamic range of perceptual forward masking is very wide, up to 80 dB, whereas in the auditory nerve, the dynamic range is 30 dB or less. The inferior colliculus seems to have inhibitory inputs that widen its dynamic range for masking to correspond to that seen psychophysically.

 

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.

Examples of research in this area:

o    Neurons in impaired ears and recruitment - in impaired ears, sounds become louder more rapidly with intensity than in normal ears. This recruitment phenomenon is a problem for hearing aid design and often limits what can be done. We show that auditory nerve fibers do not behave as expected by the standard model of recruitment. However some neurons in ventral cochlear nucleus (choppers but not primarylikes) do behave as expected, suggesting that aspects of recruitment involve changes in central neurons, not just changes in the cochlea.

 

o    A model of auditory-nerve responses in ears with hearing impairment - this computational model is intended to be useful in testing hearing-aid signal processing strategies.i

 

o    Inhibition of central neurons is reduced following acoustic trauma - Neurons in dorsal cochlear nucleus normally give responses strongly affected by inhibition. After acoustic trauma, inhibitory areas are reduced. Loss of inhibition with hearing loss probably reduces the selectivity of neurons for complex stimuli.