User:Jadrian Miles/Thesis proposal feedback

Feedback on my October 2010 thesis proposal included /dhl notes from during the talk, /jfh email after the talk, /dhl meeting notes after Spike's email, and conversations with other committee and faculty members that were not recorded. Feedback on the style and organization of my talk was synthesized into the HOWTO page Give a talk. Feedback on the content of my ideas and their individual presentation is listed on this page. The committee has asked that I formally respond to these comments.

1. Spike pointed out two issues with the thesis statement. The term "unambiguous" may be meaningless in this context, and the statement that the solution to this system could not be computed using other, single-scale models may be unprovable.
   • Rewrite the thesis statement to be more straightforward, to use clear terminology, and to claim only empirically demonstrable characteristics of the contribution.
2. Peter expressed a desire for more direct comparison to a greater variety of related work, in particular global macrostructure models such as Gibbs tracking and spin-glass models. Direct comparison to related work of other sorts, including signal regularization schemes and microstructure models, is also needed.
   • Expand discussion of related work throughout the introduction chapter to give a more detailed point-by-point comparison, with forward references into later chapters where differences between the existing work and the new work are discussed and/or demonstrated experimentally. In particular, include spin-glass and Gibbs tracking models as inputs to the established clustering techniques for the evaluation step in chapter 2.
3. Several commenters felt that the distinction between the geometry-based curve-clustering process and the image-based bundle-adjustment process was insufficiently clear.
   • Expand the overview section (1.1) to explain each step of the final modeling system in terms of its input, output, and algorithm, and point to the chapter in which each step is first described.
4. Spike and others were concerned that the "black-box math" used to describe the curve-clustering algorithm's cluster configuration energy function is insufficiently specific. What is the principled reason for the algorithm to choose a middle ground between 300,000 singleton clusters and one whole-brain cluster?
   • The energy function for curve clustering is made explicit in section 2.2.3. The tradeoff between bounding surface curvature on one hand and curve reconstruction error and average cross-sectional area
5. Eugene asked for clarification of the order in which curve clusters are selected for candidate merges, whether the overall clustering algorithm is greedy, and the consequences of different ordering choices and clustering algorithms.
   • The heuristics used to select clusters for candidate merges and the algorithm for doing the full-brain clustering based on the results of these candidate merges are described in section 2.2.4. The clustering energy function is designed to choose a good clustering even under an adversarial ordering of merge candidates. Different orderings and algorithms are investigated informally and discussed in this section.
6. David and Spike both felt that the anatomical assumptions and prior knowledge that are applied to various steps in the macrostructure-fitting process required stronger justifications from the biological literature.
7. Chad and others were concerned that the nature of the optimization algorithm for image-based bundle refinement is not specified. How does it relate to established techniques?
8. Ben asked how image differences would be translated into a space of candidate bundle refinements.
9. The entire committee asked how the image-based bundle-adjustment optimization algorithm would avoid overfitting.
10. Peter asked how the model will accomodate white matter fascicles that terminate outside of the brain.
11. Spike asked how the modeling system's macrostructure reconstruction will be validated, whether it would be stable across subjects and acquisitions, and whether it would correspond reasonably (perhaps in a subset relationship) with anatomists' conception of the macrostructure.
12. Spike asked whether the fitting process would be idempotent, up to variation due to noise. If not, would chained applications of the process converge quickly? If not, why not? If so, what is the nature of the fixed-point solution?
13. David mentioned that the stated choice of a Rician distribution for axon diameters seems inappropriate.
14. Ben and others expressed concern about the feasibility of the proposed research schedule.