Latent variable models for neural data analysis

The brain is perhaps the most complex system to have ever been subjected to rigorous scientific investigation. The scale is staggering: over 10^11 neurons, each making an average of 10^3 synapses, with computation occurring on scales ranging from a single dendritic spine, to an entire cortical area. Slowly, we are beginning to acquire experimental tools that can gather the massive amounts of data needed to characterize this system. However, to understand and interpret these data will also require substantial strides in inferential and statistical techniques. This dissertation attempts to meet this need, extending and applying the modern tools of latent variable modeling to problems in neural data analysis.

It is divided into two parts. The first begins with an exposition of the general techniques of latent variable modeling. A new, extremely general, optimization algorithm is proposed - called Relaxation Expectation Maximization (REM) - that may be used to learn the optimal parameter values of arbitrary latent variable models. This algorithm appears to alleviate the common problem of convergence to local, sub-optimal, likelihood maxima. REM leads to a natural framework for model size selection; in combination with standard model selection techniques the quality of fits may be further improved, while the appropriate model size is automatically and efficiently determined. Next, a new latent variable model, the mixture of sparse hidden Markov models, is introduced, and approximate inference and learning algorithms are derived for it. This model is applied in the second part of the thesis.

The second part brings the technology of part I to bear on two important problems in experimental neuroscience. The first is known as spike sorting; this is the problem of separating the spikes from different neurons embedded within an extracellular recording. The dissertation offers the first thorough statistical analysis of this problem, which then yields the first powerful probabilistic solution. The second problem addressed is that of characterizing the distribution of spike trains recorded from the same neuron under identical experimental conditions. A latent variable model is proposed. Inference and learning in this model leads to new principled algorithms for smoothing and clustering of spike data.

Toppling Analysis of Precariously Balanced Rocks under Earthquake Excitation

Toppling analysis of a precariously balanced rock (PBR) can provide insights into the nature of ground motion that has not occurred at that location in the past and, by extension, realistic constraints on peak ground motions for use in engineering design. Earlier approaches have targeted simplistic 2-D models of the rock or modeled the rock-pedestal contact using spring-damper assemblies that require re-calibration for each rock. These analyses also assume that the rock does not slide on the pedestal. Here, a method to model PBRs in three dimensions is presented. The 3-D model is created from a point cloud of the rock, the pedestal, and their interface, obtained using Terrestrial Laser Scanning (TLS). The dynamic response of the model under earthquake excitation is simulated using a rigid body dynamics algorithm. The veracity of this approach is demonstrated by comparisons against data from shake table experiments. Fragility maps for toppling probability of the Echo Cliff PBR and the Pacifico PBR as a function of various ground motion parameters, rock-pedestal interface friction coefficient, and excitation direction are presented. The seismic hazard at these PBR locations is estimated using these maps. Additionally, these maps are used to assess whether the synthetic ground motions at these locations resulting from scenario earthquakes on the San Andreas Fault are realistic (toppling would indicate that the ground motions are unrealistically high).

Model systems for the study of drug hypersensitivity

I. It was not possible to produce anti-tetracycline antibody in laboratory animals by any of the methods tried. Tetracycline protein conjugates were prepared and characterized. It was shown that previous reports of the detection of anti-tetracycline antibody by in vitro-methods were in error. Tetracycline precipitates non-specifically with serum proteins. The anaphylactic reaction reported was the result of misinterpretation, since the observations were inconsistent with the known mechanism of anaphylaxis and the supposed antibody would not sensitize guinea pig skin. The hemagglutination reaction was not reproducible and was extremely sensitive to minute amounts of microbial contamination. Both free tetracyclines and the conjugates were found to be poor antigens.

II. Anti-aspiryl antibodies were produced in rabbits using 3 protein carriers. The method of inhibition of precipitation was used to determine the specificity of the antibody produced. ε-Aminocaproate was found to be the most effective inhibitor of the haptens tested, indicating that the combining hapten of the protein is ε-aspiryl-lysyl. Free aspirin and salicylates were poor inhibitors and did not combine with the antibody to a significant extent. The ortho group was found to participate in the binding to antibody. The average binding constants were measured.

Normal rabbit serum was acetylated by aspirin under in vitro conditions, which are similar to physiological conditions. The extent of acetylation was determined by immunochemical tests. The acetylated serum proteins were shown to be potent antigens in rabbits. It was also shown that aspiryl proteins were partially acetylated. The relation of these results to human aspirin intolerance is discussed.

III. Aspirin did not induce contact sensitivity in guinea pigs when they were immunized by techniques that induce sensitivity with other reactive compounds. The acetylation mechanism is not relevant to this type of hypersensitivity, since sensitivity is not produced by potent acetylating agents like acetyl chloride and acetic anhydride. Aspiryl chloride, a totally artificial system, is a good sensitizer. Its specificity was examined.

IV. Protein conjugates were prepared with p-aminosalicylic acid and various carriers using azo, carbodiimide and mixed anhydride coupling. These antigens were injected into rabbits and guinea pigs and no anti-hapten IgG or IgM response was obtained. Delayed hypersensitivity was produced in guinea pigs by immunization with the conjugates, and its specificity was determined. Guinea pigs were not sensitized by either injections or topical application of p-amino-salicylic acid or p-aminosalicylate.