Eric Young PhD

Professor Emeritus of Biomedical Engineering

eyoung@bme.jhu.edu
Telephone Number: 410-955-3164
Fax Number: 410-955-1299

Department of Biomedical Engineering
Johns Hopkins University School of Medicine
720 Rutland Ave.
Baltimore, MD 21205
Room: Traylor 505
Lab Page
Areas of Research
Systems, Cognitive + Computational Neuroscience
Neural Circuits, Ensembles + Connectomes

Graduate Program Affiliations

Biomedical Engineering Program

Neuroscience Training Program

Auditory Perception and Neurophysiology; Organization of Central Auditory System

The aim of our work is to understand the representation and processing of complex signals in the auditory system. The work has two facets: understanding the neural mechanisms that determine input/output processing in specific neurons; and defining the nature of stimulus representations at various levels of the system.

In pursuing the first goal we are interested in how cells in the brainstem auditory system interact with their inputs and with one another to produce their outputs. We use a combination of cross-correlation techniques, which allows us to study interactions in local neuronal circuits, neural modelling, which allows us to test hypothesized modes of functioning for neurons, and pharmacological blockade which allows us to manipulate the components of neural circuits. For example, we have shown that the outputs of the principal cells of the dorsal cochlear nucleus (DCN) are substantially affected by a local inhibitory interneuron in the DCN. This interneuron?s properties lead to very unusual and unexpected modes of integration in DCN principal cells, whereby their responses to complex stimuli (noise, speech, etc.) are not easily predicted from a summation of their responses to narrowband stimuli (tones).

We are using a novel systems-identification method to pursue the second goal. Neurons are characterized by their weighting of energy at various frequencies and times using a two dimensional weighting function. This function can be linear, simply summing the weighted energy across frequency and time, or non-linear, in which interactions of energy at different frequencies are considered. With these methods, we can characterize neurons in the central auditory system as belonging to two classes: those that provide a simple linear (or weakly nonlinear) generalized tonotopic represntation of the stimulus and those that are strongly non-linear and therefore have specialized sensitivity to particular features of stimuli.


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