Cell fate specification during Caenorhabditis elegans male tail development

The cells of the specialized mating structures of the nematode Caenorhabditis elegans adult male tail develop from sex-specific divisions of postembryonic blast cells. One male-specific blast cell, B, is the precursor to all the cells of the copulatory spicules. Both cell interactions and autonomous fate specification mechanisms are utilized in the B lineage to specify fate.

During development the anterior daughter of B, B.a, generates four distinct pairs of cells. Cell ablation experiments indicate that the cells of each pair respond to positional cues provided by other male-specific blast cells. F and U promote anterior fates, Y.p promotes some posterior fates, and the B.a progeny promote posterior fates. The cells within each pair may also interact.

The lin-3/let-23 signalling pathway, identified for its function in C. elegans hermaphrodite vulval induction, mediates the signal from F and U. Reduction-of-function mutations in lin-3 (EGF-like signal), let-23 (receptor), sem-5 (adaptor), let-60 (ras), or lin-45 (raf) disrupt the fates of the anterior cells, and mimic F and U ablation. In addition, ectopically expressed lin-3 disrupts the fates of the posterior cells, and can promote anterior fates even in the absence of F and U.

A genetic screen of over 9000 mutagenized gametes recovered 22 mutations in 20 loci that disrupt fate specification in male tail lineages. Seven of these mutations may represent new genes that play a role in male tail development.

The first division of the B cell is asymmetric. The gene vab-3 is required for specification of B.a fates, and it may represent a factor whose activity is localized to the B.a cell via the gene lin-17. lin-17 acts both at the first division of the B cell and at specific other cell divisions in the lineage.

Value Estimation and Comparison in Multi-Attribute Choice

The following work explores the processes individuals utilize when making multi-attribute choices. With the exception of extremely simple or familiar choices, most decisions we face can be classified as multi-attribute choices. In order to evaluate and make choices in such an environment, we must be able to estimate and weight the particular attributes of an option. Hence, better understanding the mechanisms involved in this process is an important step for economists and psychologists. For example, when choosing between two meals that differ in taste and nutrition, what are the mechanisms that allow us to estimate and then weight attributes when constructing value? Furthermore, how can these mechanisms be influenced by variables such as attention or common physiological states, like hunger?

In order to investigate these and similar questions, we use a combination of choice and attentional data, where the attentional data was collected by recording eye movements as individuals made decisions. Chapter 1 designs and tests a neuroeconomic model of multi-attribute choice that makes predictions about choices, response time, and how these variables are correlated with attention. Chapter 2 applies the ideas in this model to intertemporal decision-making, and finds that attention causally affects discount rates. Chapter 3 explores how hunger, a common physiological state, alters the mechanisms we utilize as we make simple decisions about foods.

Essays in revealed preference theory and behavioral economics

Time, risk, and attention are all integral to economic decision making. The aim of this work is to understand those key components of decision making using a variety of approaches: providing axiomatic characterizations to investigate time discounting, generating measures of visual attention to infer consumers' intentions, and examining data from unique field settings.

Chapter 2, co-authored with Federico Echenique and Kota Saito, presents the first revealed-preference characterizations of exponentially-discounted utility model and its generalizations. My characterizations provide non-parametric revealed-preference tests. I apply the tests to data from a recent experiment, and find that the axiomatization delivers new insights on a dataset that had been analyzed by traditional parametric methods.

Chapter 3, co-authored with Min Jeong Kang and Colin Camerer, investigates whether "pre-choice" measures of visual attention improve in prediction of consumers' purchase intentions. We measure participants' visual attention using eyetracking or mousetracking while they make hypothetical as well as real purchase decisions. I find that different patterns of visual attention are associated with hypothetical and real decisions. I then demonstrate that including information on visual attention improves prediction of purchase decisions when attention is measured with mousetracking.

Chapter 4 investigates individuals' attitudes towards risk in a high-stakes environment using data from a TV game show, Jeopardy!. I first quantify players' subjective beliefs about answering questions correctly. Using those beliefs in estimation, I find that the representative player is risk averse. I then find that trailing players tend to wager more than "folk" strategies that are known among the community of contestants and fans, and this tendency is related to their confidence. I also find gender differences: male players take more risk than female players, and even more so when they are competing against two other male players.

Chapter 5, co-authored with Colin Camerer, investigates the dynamics of the favorite-longshot bias (FLB) using data on horse race betting from an online exchange that allows bettors to trade "in-play." I find that probabilistic forecasts implied by market prices before start of the races are well-calibrated, but the degree of FLB increases significantly as the events approach toward the end.