Modeling the Value of Strategic Actions in the Superior Colliculus

In learning models of strategic game play, an agent constructs a valuation (action value) over possible future choices as a function of past actions and rewards. Choices are then stochastic functions of these action values. Our goal is to uncover a neural signal that correlates with the action value posited by behavioral learning models. We measured activity from neurons in the superior colliculus (SC), a midbrain region involved in planning saccadic eye movements, while monkeys performed two saccade tasks. In the strategic task, monkeys competed against a computer in a saccade version of the mixed-strategy game ”matching-pennies”. In the instructed task, saccades were elicited through explicit instruction rather than free choices. In both tasks neuronal activity and behavior were shaped by past actions and rewards with more recent events exerting a larger influence. Further, SC activity predicted upcoming choices during the strategic task and upcoming reaction times during the instructed task. Finally, we found that neuronal activity in both tasks correlated with an established learning model, the Experience Weighted Attraction model of action valuation (Camerer and Ho, 1999). Collectively, our results provide evidence that action values hypothesized by learning models are represented in the motor planning regions of the brain in a manner that could be used to select strategic actions

Leading-effect vs. Risk-taking in Dynamic Tournaments: Evidence from a Real-life Randomized Experiment

Two 'order effects' may emerge in dynamic tournaments with information feedback. First, participants adjust effort across stages, which could advantage the leading participant who faces a larger 'effective prize' after an initial victory (leading-effect). Second, participants lagging behind may increase risk at the final stage as they have 'nothing to lose' (risk-taking). We use a randomized natural experiment in professional two-game soccer tournaments where the treatment (order of a stage-specific advantage) and team characteristics, e.g. ability, are independent. We develop an identification strategy to test for leading-effects controlling for risk-taking. We find no evidence of leading-effects and negligible risk-taking effects

Best-of-Three Contests: Experimental Evidence

We conduct an experimental analysis of a best-of-three Tullock contest. Intermediate prizes lead to higher efforts, while increasing the role of luck (as opposed to effort) leads to lower efforts. Both intermediate prizes and luck reduce the probability of contest ending in two rounds. The patterns of players‟ efforts and the probability that a contest ends in two rounds is consistent with „strategic momentum‟, i.e. momentum generated due to strategic incentives inherent in the contest. We do not find evidence for „psychological momentum‟, i.e. momentum which emerges when winning affects players‟ confidence. Similar to previous studies of contests, we find significantly higher efforts than predicted and strong heterogeneity in effort between subjects

A Survey of Experimental Research on Contests, All-Pay Auctions and Tournaments

Many economic, political and social environments can be described as contests in which agents exert costly efforts while competing over the distribution of a scarce resource. These environments have been studied using Tullock contests, all-pay auctions and rankorder tournaments. This survey provides a review of experimental research on these three canonical contests. First, we review studies investigating the basic structure of contests, including the contest success function, number of players and prizes, spillovers and externalities, heterogeneity, and incomplete information. Second, we discuss dynamic contests and multi-battle contests. Then we review research on sabotage, feedback, bias, collusion, alliances, and contests between groups, as well as real-effort and field experiments. Finally, we discuss applications of contests to the study of legal systems, political competition, war, conflict avoidance, sales, and charities, and suggest directions for future research. (author's abstract

Tectonic stress regime of the Cascades region and tectonic classification of large calderas

Typescript.Thesis (Ph. D.)--University of Hawaii at Manoa, 1986.Bibliography: leaves 361-395.Photocopy.xviii, 395 leaves, bound ill. 29 c

A Review of Stata 3.1.

Stata 3.1 is a program for data management, graphics, and statistical analysis. Since Version 2.1 was reviewed by Pederson (1991), Stata has added several platforms, third-party products, supporting services, and many features of interest to econometricians. The result is that Stata 3.1 integrates fast and reliable manipulation of data with high-powered statistical analysis. For users who do no more than run regressions, the new features do not detract from the feel of ease and control Stata gives the researcher working with any data set, large or small. A unique system to disseminate user-written programs lets Stata grow continuously without becoming unwieldy, ensuring that Stata will become a standard package in several branches of applied statistics. This review summarizes the hardware requirements of Stata, demonstrates a short but typical Stata session, and discusses some of the unique elements of Stata. Copyright 1994 by John Wiley & Sons, Ltd.

Effects of cathepsin proteolytic network dynamics on extracellular matrix degradation in biological machines and invasive disease

Proteases are enzymes that degrade proteins and play a major role in cellular homeostasis. When proteins are aged, defective, or just extracellular proteins taken up by the cell, these proteins are degraded by enzymes in the lysosomes, such as cysteine cathepsins. In addition to their proteolytic activity inside lysosomes, cathepsins secreted from cells degrade extracellular matrix (ECM) with differing affinities in tissue destructive diseases. These potent enzymes are known to be upregulated in tissue destructive diseases, but researchers have been limited in their ability to successfully target cathepsin dysfunction in these diseases. It is important to not only understand how these enzymes remodel the ECM, but also how these proteases interact with each other, to effectively dose inhibitors to regulate cathepsin dysfunction therapeutically. The objective of this research was to develop a mechanistic understanding of how cathepsins interact with ECM and each other for tissue remodeling as produced and regulated by living cells. With the hypothesis that cells secrete multiple species of cathepsins, which exhibit complex cathepsin-cathepsin interactions between potent cathepsins K, L, S, and V, which reduces the concentrations of cathepsins and thus expected protein degradation. This work developed a mechanistic model to quantify the interactions between cathepsins and ECM substrates, designed mutations to interrupt cathepsin-cathepsin interactions, and explored the role of proteolysis in destabilizing the fibrin-based matrix of biological machines.Ph.D

Single cell deconvolution of myeloblasts reveals depletion of HSCs and expansion of inflammatory Granulocyte-Monocyte Progenitors (GMPs) associated with adverse outcomes in Chronic Myelomonocytic Leukemia (CMML)

Myeloblasts are associated with adverse outcomes and define transformation to acute myeloid leukemia in all chronic myeloid neoplasms. Myeloblasts represent hematopoietic stem and progenitor cells (HSPCs) that express CD34, but are never resolved into stem and progenitor subpopulations during clinical evaluation. Therefore, how expansion of myeloblasts reshapes the HSPC compartment and its impact on clinical outcomes remains undefined. To address this important feature of disease progression, we transcriptionally and immunophenotypically mapped CD34 + HSPCs at single cell resolution for 66 samples from 45 patients with CMML. Single cell-RNA sequencing was performed on 137,578 CD34 + enriched HSPCs from 39 CMML samples and integrated with 63,672 publicly available CD34 + normal HSPCs (Fig A). We overlaid each CMML sample on a pseudotime projection of differentiation trajectories from normal samples to establish sample-specific aberrancies in HSPC states. This mapping classified samples into HSPC-biased groups of monocyte (mono)-bias, megakaryocyte erythroid (ME)-bias, and normal-like, respectively enriched for GMP, MEP, and HSC transcriptional signatures (Fig B). These groups were associated with distinct clinical genomic characteristics and were congruent with patient-specific bulk sequencing. For example, ME biased cases had statistically higher hemoglobin and mono-bias cases were associated with adverse survival, inflammatory clinical correlates, and RAS pathway mutations (Fig C). Importantly, we identified significant depletion of HSC across CMML that was most pronounced in the mono-bias group. This was validated by flow cytometry in 26 CD34 + enriched samples, which showed HSC numbers decreased as myeloblasts expanded and disease progressed (Fig D,E)