A. Abstract and Key Personnel Digital image acquisition and analysis are key to the research goals of the Center. There are currently 24 Center research teams actively using a number of shared hardware/software systems for image acquisition and analysis. Current applications of computer-assisted image processing span a wide range of complexity including 1) use of turn-key systems such as confocal microscopy or digital photomicroscopy for image acquisition through light and electron microscopes;2) use of interactive "computer-aided anatomy" systems for automating the extraction of quantitative information in 2-D and 3-D from histological sections;3) customization of software packages for 3-D reconstruction and rendering from serial image stacks to aid in the visualization and understanding of complex morphological relationships, and 4) software development for the creation of image-analysis paradigms in functional brain imaging. The goals of the Imaging Core are to provide the expertise and technical support required for Center Investigators to derive full benefit from the research tools available in this fast-changing hardware/software environment and to disseminate, where practical, the imaging tools developed here to the wider scientific and clinical community. To achieve this, the Imaging Core will provide support at several levels.
Aim 1 (image acquisition) provides facilities maintenance, user training and/or image-acquisition services on the new shared confocal microscope and shared digital-image acquisition systems for light and electron microscopy.
Aim 2 (image analysis and processing) addresses needs for a centralized base of relevant knowledge and expertise in image analysis and software development to aid in 1) the matching of software application with research goals when a good match exists, 2) the customization of software required when existing applications, or groups of applications, can be modified to fit particular needs, and 3) the de-novo development of image-processing software tools when no other good solution exists.
Aim 3 (dissemination) proposes the further development of virtual teaching and research tools and the continued sponsorship of a website to make them available to the greater scientific community.
|Street, Valerie A; Kujawa, Sharon G; Manichaikul, Ani et al. (2014) Resistance to noise-induced hearing loss in 129S6 and MOLF mice: identification of independent, overlapping, and interacting chromosomal regions. J Assoc Res Otolaryngol 15:721-38|
|Brugeaud, Aurore; Tong, Mingjie; Luo, Li et al. (2014) Inhibition of repulsive guidance molecule, RGMa, increases afferent synapse formation with auditory hair cells. Dev Neurobiol 74:457-66|
|Parker, Mark A; Cheng, Yen-fu; Kinouchi, Hikaru et al. (2014) An independent construct for conditional expression of atonal homolog-1. Hum Gene Ther Methods 25:1-13|
|Yin, Yanbo; Liberman, Leslie D; Maison, Stéphane F et al. (2014) Olivocochlear innervation maintains the normal modiolar-pillar and habenular-cuticular gradients in cochlear synaptic morphology. J Assoc Res Otolaryngol 15:571-83|
|Liberman, M Charles; Liberman, Leslie D; Maison, Stéphane F (2014) Efferent feedback slows cochlear aging. J Neurosci 34:4599-607|
|Shi, Fuxin; Hu, Lingxiang; Jacques, Bonnie E et al. (2014) ?-Catenin is required for hair-cell differentiation in the cochlea. J Neurosci 34:6470-9|
|Wang, Le; Devore, Sasha; Delgutte, Bertrand et al. (2014) Dual sensitivity of inferior colliculus neurons to ITD in the envelopes of high-frequency sounds: experimental and modeling study. J Neurophysiol 111:164-81|
|Chung, Yoojin; Hancock, Kenneth E; Nam, Sung-Il et al. (2014) Coding of electric pulse trains presented through cochlear implants in the auditory midbrain of awake rabbit: comparison with anesthetized preparations. J Neurosci 34:218-31|
|Wan, Guoqiang; Gómez-Casati, Maria E; Gigliello, Angelica R et al. (2014) Neurotrophin-3 regulates ribbon synapse density in the cochlea and induces synapse regeneration after acoustic trauma. Elife 3:|
|Chambers, Anna R; Hancock, Kenneth E; Sen, Kamal et al. (2014) Online stimulus optimization rapidly reveals multidimensional selectivity in auditory cortical neurons. J Neurosci 34:8963-75|
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