Eomesodermin, a target gene of Pou4f2, is required for retinal ganglion cell and optic nerve development in the mouse.

The mechanisms regulating retinal ganglion cell (RGC) development are crucial for retinogenesis and for the establishment of normal vision. However, these mechanisms are only vaguely understood. RGCs are the first neuronal lineage to segregate from pluripotent progenitors in the developing retina. As output neurons, RGCs display developmental features very distinct from those of the other retinal cell types. To better understand RGC development, we have previously constructed a gene regulatory network featuring a hierarchical cascade of transcription factors that ultimately controls the expression of downstream effector genes. This has revealed the existence of a Pou domain transcription factor, Pou4f2, that occupies a key node in the RGC gene regulatory network and that is essential for RGC differentiation. However, little is known about the genes that connect upstream regulatory genes, such as Pou4f2 with downstream effector genes responsible for RGC differentiation. The purpose of this study was to characterize the retinal function of eomesodermin (Eomes), a T-box transcription factor with previously unsuspected roles in retinogenesis. We show that Eomes is expressed in developing RGCs and is a mediator of Pou4f2 function. Pou4f2 directly regulates Eomes expression through a cis-regulatory element within a conserved retinal enhancer. Deleting Eomes in the developing retina causes defects reminiscent of those in Pou4f2(-/-) retinas. Moreover, myelin ensheathment in the optic nerves of Eomes(-/-) embryos is severely impaired, suggesting that Eomes regulates this process. We conclude that Eomes is a crucial regulator positioned immediately downstream of Pou4f2 and is required for RGC differentiation and optic nerve development.

High-sensitivity rod photoreceptor input to the blue-yellow color opponent pathway in macaque retina.

Small bistratified cells (SBCs) in the primate retina carry a major blue-yellow opponent signal to the brain. We found that SBCs also carry signals from rod photoreceptors, with the same sign as S cone input. SBCs exhibited robust responses under low scotopic conditions. Physiological and anatomical experiments indicated that this rod input arose from the AII amacrine cell-mediated rod pathway. Rod and cone signals were both present in SBCs at mesopic light levels. These findings have three implications. First, more retinal circuits may multiplex rod and cone signals than were previously thought to, efficiently exploiting the limited number of optic nerve fibers. Second, signals from AII amacrine cells may diverge to most or all of the approximately 20 retinal ganglion cell types in the peripheral primate retina. Third, rod input to SBCs may be the substrate for behavioral biases toward perception of blue at mesopic light levels.

NOVEL PHANTOMS AND POST-PROCESSING FOR DIFFUSION SPECTRUM IMAGING

High Angular Resolution Diffusion Imaging (HARDI) techniques, including Diffusion Spectrum Imaging (DSI), have been proposed to resolve crossing and other complex fiber architecture in the human brain white matter. In these methods, directional information of diffusion is inferred from the peaks in the orientation distribution function (ODF). Extensive studies using histology on macaque brain, cat cerebellum, rat hippocampus and optic tracts, and bovine tongue are qualitatively in agreement with the DSI-derived ODFs and tractography. However, there are only two studies in the literature which validated the DSI results using physical phantoms and both these studies were not performed on a clinical MRI scanner. Also, the limited studies which optimized DSI in a clinical setting, did not involve a comparison against physical phantoms. Finally, there is lack of consensus on the necessary pre- and post-processing steps in DSI; and ground truth diffusion fiber phantoms are not yet standardized. Therefore, the aims of this dissertation were to design and construct novel diffusion phantoms, employ post-processing techniques in order to systematically validate and optimize (DSI)-derived fiber ODFs in the crossing regions on a clinical 3T MR scanner, and develop user-friendly software for DSI data reconstruction and analysis. Phantoms with a fixed crossing fiber configuration of two crossing fibers at 90° and 45° respectively along with a phantom with three crossing fibers at 60°, using novel hollow plastic capillaries and novel placeholders, were constructed. T2-weighted MRI results on these phantoms demonstrated high SNR, homogeneous signal, and absence of air bubbles. Also, a technique to deconvolve the response function of an individual peak from the overall ODF was implemented, in addition to other DSI post-processing steps. This technique greatly improved the angular resolution of the otherwise unresolvable peaks in a crossing fiber ODF. The effects of DSI acquisition parameters and SNR on the resultant angular accuracy of DSI on the clinical scanner were studied and quantified using the developed phantoms. With a high angular direction sampling and reasonable levels of SNR, quantification of a crossing region in the 90°, 45° and 60° phantoms resulted in a successful detection of angular information with mean ± SD of 86.93°±2.65°, 44.61°±1.6° and 60.03°±2.21° respectively, while simultaneously enhancing the ODFs in regions containing single fibers. For the applicability of these validated methodologies in DSI, improvement in ODFs and fiber tracking from known crossing fiber regions in normal human subjects were demonstrated; and an in-house software package in MATLAB which streamlines the data reconstruction and post-processing for DSI, with easy to use graphical user interface was developed. In conclusion, the phantoms developed in this dissertation offer a means of providing ground truth for validation of reconstruction and tractography algorithms of various diffusion models (including DSI). Also, the deconvolution methodology (when applied as an additional DSI post-processing step) significantly improved the angular accuracy of the ODFs obtained from DSI, and should be applicable to ODFs obtained from the other high angular resolution diffusion imaging techniques.