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Data Analaysis & Interpretation

Dissertation Research

I acquired, analyzed, and interpreted a wide array of data in my dissertation, ranging from animal behavior to confocal microscopy.  Full details of the associated methods and interpretation are available in the complete dissertation.

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•  Figure 2: Auditory Brainstem Response (ABR)

◦  Auditory physiology test used to determine hearing thresholds in addition to activity of central auditory nuclei - this particular exam is frequently used as part of newborn hearing screenings, since it does not require input from the subject.

•  Figure 4: Gap Detection Analysis

◦  Breakdown of the automated data analysis approach I developed for the animal behavior test for tinnitus (gap detection).  Results of this assay were used to sort test subjects into groups based on tinnitus status.

•  Figure 8: Dorsal Cochlear Nucleus (DCN) Computer-Aided Layer & Frequency Division

◦  The DCN has two key organizing features: (1) layers with unique, functionally distinct cell types and (2) organized distinct distribution of frequency responsive neurons (tonotopic arrangement).  Identified of specific ROIs allows for assessment of unique types of noise-induced damage.

•  Figure 15: Reliability Statistics

◦  Manual counts of sensory hair cells from whole-mount dissected cochlea are subject to rater bias, so I implemented reliability statistics.

•  Figure 23: Inner and Outer Hair Cell Counts

◦  Frequency-specific breakdown of inner and outer hair cell counts from animals sorted into tinnitus positivee (+, ++).

•  Figure 35: Analysis Approach for Excitatory Immunohistochemical Labeling 

◦ This figure was referenced in the written description of the analysis approach used in the image-processing macro I developed to facilitate consistent and efficient processing of all regions of interest for confocal microscopy. 

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