Eric D. Young

Affiliations: 
2015 Biomedical Engineering Johns Hopkins University, Baltimore, MD 
Area:
Auditory system
Website:
http://neuroscience.jhu.edu/EricYoung.php
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"Eric Young"
Bio:

(From neuroscience.jhu.edu) 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 representation of the stimulus and those that are strongly non-linear and therefore have specialized sensitivity to particular features of stimuli.
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Mean distance: 13.09 (cluster 17)
 
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Publications

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Issa JB, Haeffele BD, Young ED, et al. (2016) Multiscale Mapping of Frequency Sweep Rate in Mouse Auditory Cortex. Hearing Research
Wu JS, Young ED, Glowatzki E. (2016) Maturation of Spontaneous Firing Properties after Hearing Onset in Rat Auditory Nerve Fibers: Spontaneous Rates, Refractoriness, and Interfiber Correlations. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 36: 10584-10597
Li Y, Ropp TJ, May BJ, et al. (2015) Dorsal Cochlear Nucleus of the Rat: Representation of Complex Sounds in Ears Damaged by Acoustic Trauma. Journal of the Association For Research in Otolaryngology : Jaro. 16: 487-505
Malmierca MS, Young ED. (2014) Inferior colliculus microcircuits. Frontiers in Neural Circuits. 8: 113
Ropp TJ, Tiedemann KL, Young ED, et al. (2014) Effects of unilateral acoustic trauma on tinnitus-related spontaneous activity in the inferior colliculus. Journal of the Association For Research in Otolaryngology : Jaro. 15: 1007-22
Issa JB, Haeffele BD, Agarwal A, et al. (2014) Multiscale optical Ca2+ imaging of tonal organization in mouse auditory cortex. Neuron. 83: 944-59
Slee SJ, Young ED. (2014) Alignment of sound localization cues in the nucleus of the brachium of the inferior colliculus. Journal of Neurophysiology. 111: 2624-33
Bandyopadhyay S, Young ED. (2013) Nonlinear temporal receptive fields of neurons in the dorsal cochlear nucleus. Journal of Neurophysiology. 110: 2414-25
Yu JJ, Young ED. (2013) Frequency response areas in the inferior colliculus: nonlinearity and binaural interaction. Frontiers in Neural Circuits. 7: 90
Young ED. (2013) Which neurons survive the glutamate storm? Journal of Neurophysiology. 110: 575-6
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