A cognitive hierarchy model of games

Players in a game are “in equilibrium” if they are rational, and accurately predict other players' strategies. In many experiments, however, players are not in equilibrium. An alternative is “cognitive hierarchy” (CH) theory, where each player assumes that his strategy is the most sophisticated. The CH model has inductively defined strategic categories: step 0 players randomize; and step k thinkers best-respond, assuming that other players are distributed over step 0 through step k − 1. This model fits empirical data, and explains why equilibrium theory predicts behavior well in some games and poorly in others. An average of 1.5 steps fits data from many games

A cognitive hierarchy theory of one-shot games: Some preliminary results

Strategic thinking, best-response, and mutual consistency (equilibrium) are three key modelling principles in noncooperative game theory. This paper relaxes mutual consistency to predict how players are likely to behave in in one-shot games before they can learn to equilibrate. We introduce a one-parameter cognitive hierarchy (CH) model to predict behavior in one-shot games, and initial conditions in repeated games. The CH approach assumes that players use k steps of reasoning with frequency f (k). Zero-step players randomize. Players using k (≥ 1) steps best respond given partially rational expectations about what players doing 0 through k - 1 steps actually choose. A simple axiom which expresses the intuition that steps of thinking are increasingly constrained by working memory, implies that f (k) has a Poisson distribution (characterized by a mean number of thinking steps τ ). The CH model converges to dominance-solvable equilibria when τ is large, predicts monotonic entry in binary entry games for τ < 1:25, and predicts effects of group size which are not predicted by Nash equilibrium. Best-fitting values of τ have an interquartile range of (.98,2.40) and a median of 1.65 across 80 experimental samples of matrix games, entry games, mixed-equilibrium games, and dominance-solvable p-beauty contests. The CH model also has economic value because subjects would have raised their earnings substantially if they had best-responded to model forecasts instead of making the choices they did

Models of thinking, learning, and teaching in games

Noncooperative game theory combines strategic thinking, best-response, and mutual consistency of beliefs and choices (equilibrium). Hundreds of experiments show that in actual behavior these three forces are limited, even when subjects are highly motivated and analytically skilled (Camerer, 2003). The challenge is to create models that are as general, precise, and parsimonious as equilibrium, but which also use cognitive details to explain experimental evidence more accurately and to predict new regularities. This paper describes three exemplar models of behavior in one-shot games (thinking), learning over time, and how repeated “partner” matching affects behavior (teaching) (see Camerer et al., 2002b)

Behavioral Game Theory: Thinking, Learning and Teaching

Game theory is a mathematical system for analysing and predicting how humans behave in strategic situations. Standard equilibrium analyses assume that all players: (1) form beliefs based on an analysis of what others might do (strategic thinking); (2) choose the best response given those beliefs (optimization); and (3) adjust best responses and beliefs until they are mutually consistent (equilibrium)

IsoDOT Detects Differential RNA-isoform Expression/Usage with respect to a Categorical or Continuous Covariate with High Sensitivity and Specificity

We have developed a statistical method named IsoDOT to assess differential isoform expression (DIE) and differential isoform usage (DIU) using RNA-seq data. Here isoform usage refers to relative isoform expression given the total expression of the corresponding gene. IsoDOT performs two tasks that cannot be accomplished by existing methods: to test DIE/DIU with respect to a continuous covariate, and to test DIE/DIU for one case versus one control. The latter task is not an uncommon situation in practice, e.g., comparing paternal and maternal allele of one individual or comparing tumor and normal sample of one cancer patient. Simulation studies demonstrate the high sensitivity and specificity of IsoDOT. We apply IsoDOT to study the effects of haloperidol treatment on mouse transcriptome and identify a group of genes whose isoform usages respond to haloperidol treatment

Detection of the inferred interaction network in hepatocellular carcinoma from EHCO (Encyclopedia of Hepatocellular Carcinoma genes Online)

BACKGROUND: The significant advances in microarray and proteomics analyses have resulted in an exponential increase in potential new targets and have promised to shed light on the identification of disease markers and cellular pathways. We aim to collect and decipher the HCC-related genes at the systems level. RESULTS: Here, we build an integrative platform, the Encyclopedia of Hepatocellular Carcinoma genes Online, dubbed EHCO , to systematically collect, organize and compare the pileup of unsorted HCC-related studies by using natural language processing and softbots. Among the eight gene set collections, ranging across PubMed, SAGE, microarray, and proteomics data, there are 2,906 genes in total; however, more than 77% genes are only included once, suggesting that tremendous efforts need to be exerted to characterize the relationship between HCC and these genes. Of these HCC inventories, protein binding represents the largest proportion (~25%) from Gene Ontology analysis. In fact, many differentially expressed gene sets in EHCO could form interaction networks (e.g. HBV-associated HCC network) by using available human protein-protein interaction datasets. To further highlight the potential new targets in the inferred network from EHCO, we combine comparative genomics and interactomics approaches to analyze 120 evolutionary conserved and overexpressed genes in HCC. 47 out of 120 queries can form a highly interactive network with 18 queries serving as hubs. CONCLUSION: This architectural map may represent the first step toward the attempt to decipher the hepatocarcinogenesis at the systems level. Targeting hubs and/or disruption of the network formation might reveal novel strategy for HCC treatment

Discovery of a Distinct Superfamily of Kunitz-Type Toxin (KTT) from Tarantulas

BACKGROUND: Kuntiz-type toxins (KTTs) have been found in the venom of animals such as snake, cone snail and sea anemone. The main ancestral function of Kunitz-type proteins was the inhibition of a diverse array of serine proteases, while toxic activities (such as ion-channel blocking) were developed under a variety of Darwinian selection pressures. How new functions were grafted onto an old protein scaffold and what effect Darwinian selection pressures had on KTT evolution remains a puzzle. PRINCIPAL FINDINGS: Here we report the presence of a new superfamily of ktts in spiders (TARANTULAS: Ornithoctonus huwena and Ornithoctonus hainana), which share low sequence similarity to known KTTs and is clustered in a distinct clade in the phylogenetic tree of KTT evolution. The representative molecule of spider KTTs, HWTX-XI, purified from the venom of O. huwena, is a bi-functional protein which is a very potent trypsin inhibitor (about 30-fold more strong than BPTI) as well as a weak Kv1.1 potassium channel blocker. Structural analysis of HWTX-XI in 3-D by NMR together with comparative function analysis of 18 expressed mutants of this toxin revealed two separate sites, corresponding to these two activities, located on the two ends of the cone-shape molecule of HWTX-XI. Comparison of non-synonymous/synonymous mutation ratios (omega) for each site in spider and snake KTTs, as well as PBTI like body Kunitz proteins revealed high Darwinian selection pressure on the binding sites for Kv channels and serine proteases in snake, while only on the proteases in spider and none detected in body proteins, suggesting different rates and patterns of evolution among them. The results also revealed a series of key events in the history of spider KTT evolution, including the formation of a novel KTT family (named sub-Kuntiz-type toxins) derived from the ancestral native KTTs with the loss of the second disulfide bridge accompanied by several dramatic sequence modifications. CONCLUSIONS/SIGNIFICANCE: These finding illustrate that the two activity sites of Kunitz-type toxins are functionally and evolutionally independent and provide new insights into effects of Darwinian selection pressures on KTT evolution, and mechanisms by which new functions can be grafted onto old protein scaffolds

Effects of Combinatorial Treatment with Pituitary Adenylate Cyclase Activating Peptide and Human Mesenchymal Stem Cells on Spinal Cord Tissue Repair

The aim of this study is to understand if human mesenchymal stem cells (hMSCs) and neuropeptide pituitary adenylate cyclase-activating polypeptide (PACAP) have synergistic protective effect that promotes functional recovery in rats with severe spinal cord injury (SCI). To evaluate the effect of delayed combinatorial therapy of PACAP and hMSCs on spinal cord tissue repair, we used the immortalized hMSCs that retain their potential of neuronal differentiation under the stimulation of neurogenic factors and possess the properties for the production of several growth factors beneficial for neural cell survival. The results indicated that delayed treatment with PACAP and hMSCs at day 7 post SCI increased the remaining neuronal fibers in the injured spinal cord, leading to better locomotor functional recovery in SCI rats when compared to treatment only with PACAP or hMSCs. Western blotting also showed that the levels of antioxidant enzymes, Mn-superoxide dismutase (MnSOD) and peroxiredoxin-1/6 (Prx-1 and Prx-6), were increased at the lesion center 1 week after the delayed treatment with the combinatorial therapy when compared to that observed in the vehicle-treated control. Furthermore, in vitro studies showed that co-culture with hMSCs in the presence of PACAP not only increased a subpopulation of microglia expressing galectin-3, but also enhanced the ability of astrocytes to uptake extracellular glutamate. In summary, our in vivo and in vitro studies reveal that delayed transplantation of hMSCs combined with PACAP provides trophic molecules to promote neuronal cell survival, which also foster beneficial microenvironment for endogenous glia to increase their neuroprotective effect on the repair of injured spinal cord tissue