Modeling Processes with No Beginning, an Adaptive Middle, and No End

Awhile back, PZ Myers posted a feature about tumor suppressor genes [1] on his blog, Pharyngula. The feature was very complete, and will serve as a good teaching tool. At the beginning, he mentions that cybernetic and homeostatic explanations can sometimes be incomplete. This is because cybernetics and biological homeostasis are based on an key assumption: every process should have an input and output. Tumor suppressor genes make this framework difficult, because there is no distinct "output" for the process of suppression. However, there are still ways in which systems analyses can shed light on phenomena such as tumor suppression. Two newer concepts (allostatic regulation and futile cycles) can provide better mechanisms for these phenomena.

The first involves the cybernetic conceptualization of regulatory pathways vs. what actually happens during the regulation of tumor suppressor genes. Namely, a cybernetic model requires inputs and outputs. While this is traditionally true, there are a few things about this statement that need clarification. One concept deserving of further attention is homeostatic regulation. While the basic concept of homeostasis is relatively straightforward, the idea is far more complicated than simply the sum of its Greek root words [2]. While homeostasis has been defined more formally as stability in the face of perturbation due to negative feedback [3], this concept also requires a host of allostatic mechanisms that make for a more consistent and predictive theory of regulation. In short, what are the rules of absorption for the maintenance homeostatic conditions?

McEwen and Gianaros [4] use the example of various brain networks to illustrate how allostatic mechanisms mitigate various environmental stressors (e.g. perturbations). Brain networks provide us with an example that involves a complex and distributed system with many interrelated and independent components. In this example, neuroplasticity throughout life-history provide a plausible mechanism for allodynamic processes (Figure 1). These processes correspond with functional changes that promote physiological stability (e.g. homeostasis) in the organism.

Figure 1. An example of allostatic load with respect to patterned environmental stimuli (a, b) and a measured physiological response (c, d). COURTESY: Figure 2 in [4].

A differential capacity for neuroplasticity between individuals and brain functions (e.g. learning and memory, HPA axis) leads to two distinct outcomes. The first outcome is allostatic drive, which is adaptive and provides a positive feedback mechanism with respect to environmental stimuli. This mechanism helps to condition the physiology to a wider range of environmental signals. The second outcome is allostatic load, which is maladaptive. This maladaptation occurs in two stages. First, the organism experiences repeated hits of an environmental stimulus to which it cannot compensate. Due to this lack of compensation, the second stage involves a lack of long-term adaptation. This pattern of overstimulation without a proper adaptive response can result in a range of dysregulative conditions, from chronic fatigue to cancers [3]. Yet there can also be allostatic states that are adaptive for the system in question but bad for the organism, particularly over the long term [5].

An important aspect of allostasis is the regulatory nature of anticipatory mechanisms that might respond to environmental stimuli (Figure 2). This allows for an allostatic model to more accurately represent the living nature of physiological systems [5]. Whereas allostatic drive involves positive feedback, allostasis can also involve feedforward control, or a combination of feedforward and feedback information. In cases where the anticipatory mechanisms overcompensate for a set of environmental signals, the physiological system can suffer from overshoot [5]. These results from purely feedforward control without appropriate feedback, and can have significant consequences for nonlinear physiological dynamics.

Figure 2. The relationship between physiological response, adaptation, and allostatic regulation. COURTESY: Figure 1-10 from [5].

There are also links between the short-term regulation of physiology and evolutionary processes that are generally underappreciated. One of these involves the evolutionary constraints of physiological adaptation. For example, individual variation and species-specific mechanisms can determine both the normal and permissable range of function [6]. Yet there is a difference between physiological adaptation and evolutionary adaptation, which can expand this range of function. While allostatic mechanisms can mitigate the former, they cannot result in the latter. The interplay between evolvability, enabling mutations, and allostatic regulatory mechanisms is a topic for future research.

The problem with using a traditional cybernetics model to represent complex biological phenomena is not that they require formal endpoints (although that is a problem). The problem involves determining coherent inputs and outputs, or things that have an affect on or result from a complex process. Consider ocean geochemical cycling. Oceans are a complex system with both fluid and energy flows (currents, gyres) and physical structure (trophic, bathyscape). Some of these flows play a functional role in the system, while others do not. Likewise, processes associated with these flows are both completely internal to the ocean system and provide a tangible output.

There is a version of a cybernetics-like model that may deal fairly well with tumor suppressor gene regulation. I previously reviewed a type of metabolic pathway called the futile cycle [7] here on Synthetic Daisies. The sole purpose of a futile cycle (Figure 3) is to convert one product to another, and then re-convert to its original form, expending energy in the process but producing no distinct output [8]. In some ways, this resembles the repressilator motif in gene regulation [9]. However, the futile cycle might also be applied to gene expression and genetic regulation in its own right, particularly with respect to stochastic gene expression.

Figure 3. Schematic of a typical futile cycle (example is from a metabolic pathway). What is the input, what is the output, and is it anything more than a metaphenomenon? COURTESY: Figure 1 in [8].

There is also an evolutionary component to such models. Even though the futile cycle produces no output, this does not mean that there cannot be one (or more) functions related to the mechanism. Based on the metabolic function of the futile cycle, there are two potential mechanisms that could be selected for at the level of gene expression:

1) As a regulator. Much like how a throttle regulates the volume of fuel provided into an engine, products are deconverted when too much product exists and reconverted when needed.

2) As an exaptation. Suppose that the original function was for deconversion, but an extra function was built on top of this original function. The mechanism then evolves to counteract overactivity, and supplements production in cells that are evolving towards other functions.

But futile cycles and homeostatic regulation are also intimately linked. Besides serving as a model of metabolic pathway function, it can also be used as a general model of metabolic regulation at the organismal level [10]. It is also noteworthy that futile cycles can be linked together and produce multiple stable states [11], much like allostatic regulation. And much like allostatic regulatory mechanisms, the interplay between evolvability and enabling mutations needs further study. But they both have immense potential to describe the unique nature of actively-adapting (and evolving) physiological systems.

NOTES:

[1] Myers, P.Z.   What are tumor suppressor genes? Pharyngula blog, September 25 (2013).

[2] "homeo" = similar or same, "stasis" = stability in time. But physiology is a complex system that is a dynamic equilibrium, you say? This is exactly why the traditional conception of homeostasis is incomplete.

[3] Sterling, P. and Eyer, J.   Allostasis: a new paradigm to explain arousal pathology. In "Handbook of Life Stress, Cognition, and Health", S. Fisher and J. Reason eds., Wiley and Sons, New York (1988).

[4] McEwen, B.S. and Gianaros, P.J.  Stress- and Allostasis-Induced Brain Plasticity. Annual Reviews of Medicine, 62, 5.1-5.15 (2011).

[5] Schulkin, J.  Rethinking Homeostasis: allostatic regulation in physiology. MIT Press, Cambridge, MA (2003).

[6] Turner, J.S.   The Extended Organism: the physiology of animal-built structures. Harvard University Press, Cambridge, MA (2000).

[7] Alicea, B.   Resistance is a (futile) cycle! Synthetic Daisies blog, September 19 (2011).

[8] Samoilov, M., Plyasunov, S., and Arkin, A.P.   Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations. PNAS USA, 102(7), 2310-2315 (2005).

[9] For more information on the repressilator and its dynamics, please see the following references:  

a) Pokhilko, A., Pinas Fernandez, A., Edwards, K.D., Southern, M.M., Halliday, K.J., and Millar, A.J.   The clock gene circuit in Arabidopsis includes a repressilator with additional feedback loops. Molecular Systems Biology, 8, 574 (2012).

b) Buse, O., Perez, R., and Kuznetsov, A.   Dynamical properties of the repressilator model. Physical Review E, 81(6-2), 066206. 

[10] Loli, D. and Bicudo, J.E.   Control and Regulatory Mechanisms Associated with Thermogenesis in Flying Insects and Birds. Bioscience Reports, 25(3/4) (2005).

[11] Wang, L. and Sontag, E.D.   On the number of steady states in a multiple futile cycle. Journal of Mathematical Biology, 57, 29-52 (2008).

Fireside Science: The Consensus-Novelty Dampening

This content is being cross-posted to Fireside Science. NOTE: this content has not been peer-reviewed!

I am going to start this post with a rhetorical question: why do people often assume that traditional (or common sense) practices are inherently better, even when the cumulative evidence is inconclusive? In discussing political and economic policy-making, Duncan Black and Paul Krugman uses the term "very serious people" (VSPs) [1] to describe important people who back positions that sound serious but are actually wrong-headed and perhaps even dangerous. Part of this "seriousness" stems from appealing to their own authority or broad issues that have always been a legitimate concern.

Recently, such a "very important person" (not a famous scientist, but a VSP in spirit -- and you will see why as we move along) has published an article in Science called "Who’s Afraid of Peer Review?" [2]. This paper involved a experiment to validate quality control in peer-review in open-access journals, and had some useful results that did not particularly surprise me. For example, open-access journals that send out copious amounts of spam encouraging submission of your work may not be reject papers with faked data in them.

To recap the experiment, the author generated a large number of scientific papers with scientific-sounding (but false) results with accompanying bad graphs. The generative model used here is similar in concept to the Dada Engine [3], and the experimental treatment could best be described as 1,000 (or more) Sokal hoaxes. The papers were sent out to the many open-access journals that have popped into existence in the past 15 years, with a fair number of acceptances. There were also many rejections, most notable rejection from PLoS One, perhaps the flagship open-access journal [4].

These data speak for themselves, or do they? HINT: beware of obvious answers offering gifts..... 

There are a number of problems with this article, least of which that it does not distinguish between predatory open-access journals and more reputable ones [5]. But perhaps the real problem with Bohannon's article is that it does not explore: 1) the role of lax editorial standards at traditional peer-review journals, or 2) conceive of this as a problem of false positives rather than a moral failing. This is along the lines of Michael Eisen's (founder of PLoS One) chief criticism with the article [6], and the reason why publication in Science makes it seem a bit like subterfuge.

Eisen's other criticism involves the Science article being biased against open-access. I read the article this way as well -- the moral imperative is quite thinly-veiled. The paper takes the tone of a reactionary pundit who thinks a return to traditional norms (perhaps even imagined ones) can solve any social problem. In light of this, here is some vitriol from Michael Eisen on the problem with subscription publishers vis-a-vis this issue:

"And the real problem isn’t that some fly-by-night publishers hoping to make a quick buck aren’t even doing peer review (although that is a problem). While some fringe OA publishers are playing a short con, subscription publishers are seasoned grifters playing a long con. They fleece the research community of billions of dollars every year by convincing them of  something manifestly false – that their journals and their “peer review” process are an essential part of science, and that we need them to filter out the good science – and the good scientists – from the bad. Like all good grifters playing the long con, they get us to believe they are doing something good for us – something we need. While they pocket our billions, with elegant sleight of hand, then get us to ignore the fact that crappy papers routinely get into high-profile journals simply because they deal with sexy topics"

Which one of these is not like the other two? HINT: the guy (on the left) who violated Copyright law. HYPOTHESIS: Open-access is not a crime. COURTESY: Time Magazine cover.

From a phase space (e.g. parametric) perspective, the problem may be that traditional peer review is a sparse sampling of quality control. Of all the possible gatekeepers, we have 3-4 people either chosen at random or chosen explicitly to prime the pump (NOTE: when you suggest reviewers, you prime the pump). Not exactly the kind of strict consensus defenders of the traditional gatekeeper model like to believe exists.

A related observation (also inspired by physics) is something I call the "bifurcating opinion" issue. This occurs more often than one would think (or hope for). For example, one reviewer thinks an article is great, while the other reviewer hates it. The solution might be to add reviewers, but this might simply extend the problem in a manner similar to flipping a coin. Is this a legitimate way to reach consensus on quality control? Or is consensus even necessary?

I will now tell a story about a manuscript I posted [7] to Nature Precedings, a preprint (now archival) service run by a traditional publisher, in 2009. The paper was accepted under limited standards of quality control (there is a screening process, but no formal peer review process). I did so for two reasons: 1) a belief in scientific transparency, and 2) it did not fit cleanly into any existing journal (based on my first-pass approximation of the journal landscape). Soon after posting the paper, I was contacted by a Journal editor, who encouraged me to submit the paper to their Journal (which I did).

Three months later, the editor contacted me and said that 45 reviewers felt they could not be impartial reviewers to the article. So at least my intuitions were vindicated! But what does this say about quality control? Most certainly, the reviewers were not willing to issue a false positive acceptance. But does this come at the expense of rejecting novelty (a false negative)?

A schematic showing a 3-D phase space (demonstrating examples of sparse sampling and bifurcating opinion) of scientific expertise for a given area of research/article. The phenomenon of bifurcating opinion was used to show that agreement amongst reviewers is expected at no better than a chance occurance by [8].

In an article from the Chronicle of Higher Education [9], it is pointed out that open-access journals are in a frontier (e.g. wild-west) phase of development. In that sense, a non-uniform degree of quality control should be expected across a random sampling of journals -- with some degree of predatory enterprise. A representative from Science said this about the results of [2]:

“We don’t know whether peer review is as bad at traditional journals,” he said. “Then again, OA is the growth area in scientific publishing.”

This brings up another issue: does selectivity necessarily reflect quality? In the Bohannon study [2], open-access accepted the fraudulent papers even after they were put through peer-review process. As far as I am aware, the qualitative responses of these reviewers were not considered as a factor in the acceptance of fraudulent articles.

Journals with high selectivity are widely assumed to be better at filtering out noise (e.g. weak results and methods) and potential fraud. However, as long as the rejection rate (100-acceptance rate) exceeds the number of fraudulent manuscripts, selectivity and fraud (or error) detection tend to be two seperate things. Sure, journals with a low acceptance rate are likely to include fewer fraudulent papers. But these same journals will also tend to reject many reasonable, and sometimes even outstanding papers.

It is notable that retractions of papers from highly-selective journals are not that rare. Take the case of Anil Potti, whose data were discovered to be fabricated. The result (as of 2012) is 11 retractions, 7 corrections, and 1 patrtial retraction [10]. Only 2 of these retractions involved an open-access journal (PLoS One). The rest, in fact, involved peer reviewed biomedical journals.

A classification scheme for Type I (B -- or a false negative) and II (C -- or a false positive) error in manuscript evaluation. The goal of peer review should be to minimize the number of manuscripts in categories B and C. Of course, this is not considering manuscripts rejected for non-fraudulent reasons.

What are potential solutions to some of these problems [11]? Particularly, how can we keep selectivity from stifling innovation (e.g. novel interpretations, groundbreaking findings)? Can the concept of crowdsourcing provide any inspiration for this? John Hawks [12] discusses radically-open peer review as done by F1000. The F1000 model operates on the premise of the popularity. The more votes an article gets, the more staying power the article has.

But should popularity be linked to significance and/or quality? Investigations into the incongruity between popularity and influence suggests that these should be decoupled [13]. Or put another way: is it the percentage of accepted manuscripts that makes a quality journal, or is it that all articles meet certain benchmarks? And if the acceptance criterion is the only acceptable measure of quality, then is it an unfortunate one that stifles innovation [14].

Here's the deal: you give me $1,000, and I'll give you legitimacy, or you pay me a subscription fee, and I'll give you even more legitimacy....... COURTESY: South Park, Scott Tenorman Must Die.

So are there legitimate issues of concern here? Of course there are. But there are also pressing problems with the status quo that are for some reason not as shocking. Fooling people with non-sequiturs and supposedly self-evident experimental design flaws is a clever rhetorical device. But it does not answer some of the most pressing issues in balancing academic quality control with getting things out there (e.g. reporting results and scientific interaction) [15]. In the spirit of non-sequiturs, I leave you with a video clips from Patton Oswalt's TED talk highlighting the lack of quality control in the motivational speaking industry.

Still image from the Patton Oswalt TED talk, which parodied motivational speaking by generating nonsensical passages using the generalized motivational schema (e.g. sentence styles, jargon).

NOTES: 

[1] For more, please see: Black, D.  Everything Liberal Activists Do Is Wrong and Destructive. Eschaton blog, July 30 (2010) AND Krugman, P.  VSP Economics. The Conscience of a Liberal blog, May 7 (2011).

[2] Bohannon, J.   Who’s Afraid of Peer Review? Science, 342, 60-65 (2013). The reason I make this judgmental statement is because it is important to distinguish between legitimate skepticism and fostering a moral panic (e.g. open-access is bad for science, and I'm going to use the organ of a major journal to foster support of the cause). I feel that Bohannon has crossed this line.

For a more nuanced take on the phenomenon of predatory open-access journals, please see: Beall, J. "Predatory" Open-access Scholarly Publishing. The Charleston Advisor, April (2010).

[3] the modeling of non-sequiturs that resemble a particular field's jargon (e.g. legalese, postmodernism) using a recursive transition algorithm. For more on the Dada Engine, please see: Bulhak, A.  On the Simulation of Postmodernism and Mental Debility Using Recursive Transition Networks. CiteSeerX repository (1996).

[4] I have a confession: I was rejected from PLoS One! However, this might not be as "bad" as it sounds, if these two references are correct:

a) Neylon, C.   In defence of author-pays business models. Science in the Open blog, April 29 (2010).

b) Anderson, K.   PLoS’ Squandered Opportunity — Their Problems with the Path of Least Resistance. The Scholarly Kitchen blog, April 27 (2010).

[5] Hawks, J.   "Open access spam" and how journals sell scientific reputation. John Hawks weblog, October 3 (2013).

Of course, conventional journals also rely on the same sense of reputability, whether deserved or not. For more please see: Reich, E.S.   Science publishing: the golden club. Nature News, October 16 (2013).

[6] Eisen, M.   I confess, I wrote the Arsenic DNA paper to expose flaws in peer-review at subscription- based journals. It is NOT Junk blog, October 3 (2013).

Since the Bohannon article deals with a competing publication model, Science should have at least issued a conflict-of-interest disclaimer upon publication. As the Wikipedia cleanup editors would say: this article sounds like an advertisement.

[7] Alicea, B.   Range-based techniques for discovering optimality and analyzing scaling relationships in neuromechanical systems. Nature Precedings, 2845.v1 (2009).

[8] Rothwell, P.M. and Martyn, C.N.   Reproducibility of peer review in clinical neuroscience: is agreement between reviewers any greater than would be expected by chance alone? Brain, 123, 1964-1969 (2000).

[9] Basken, P.   Critics Say Sting on Open-Access Journals Misses Larger Point. Chronicle of Higher Education, October 4 (2013).

[10] Ivanoransky   The Anil Potti retraction record so far. Retraction Watch blog, February 14 (2012).

* or simply Google the names "Yoshitaka Fujii" and "Joachim Boldt" -- their retraction count is astounding.

More insight might be found in the following paper: Steen, R.G., Casadevall, A. and Fang, F.C.   Why has the number of scientific retractions increased? PLoS One, 8(7), e68397.

[11] For a visionary take (written in 1998 and using National Lab pre-print servers as a template for the future) on open-access publishing, please see: Harnad, S.   The invisible hand of peer review. Nature Web Matters, November 5 (1998).

* this reference also discusses self-policing vs. peer consensus and the issue of peer review as a popularity poll.

[12] Hawks, J.   Time to trash anonymous peer review? John Hawks weblog, October 3 (2013).

[13] Solis, B.   The Difference between Popularity and Influence Online. PaidContent, March 24 (2012).

[14] I was once told that to be accepted for publication, a scientific article should not have too many novelties in it. For example, an article that has a novel theoretical position or method is okay, but not both (or additional novelties). This was anecdotal -- however, this seems to be a built-in conservative bias of the peer-review system.

UPDATE (11/5)! What is the optimal level of novelty relative to scientific impact? For a large-scale analysis, please see: Uzzi, B., Mukherjee, S., Stringer, M., and Jones, B.   Atypical Combinations and Scientific Impact. Science, 342, 468-472 (2013).

[15] Food for thought: does peer-review and standards actually harm science by excluding negative results from the literature? For more about this and the replicability crisis in science, please see this article (which I will be coming back to in a future post): Unreliable research: trouble at the lab. Economist, October 19 (2013).

50,000 visits and counting.....and the Cynic's Rule

Synthetic Daisies has reached another milestone. About a year ago, I posted on reaching the 20,000 visit mark (according to Blogger's analytics engine). In the past year, nearly 30,000 additional visits (and 64 posts) have accumulated, making for 50,000 total visits as of October 19th, 2013. These days, I am averaging about 80-95 visits a day, with occasional days of 200+ visitors. Not bad for blog with 210 posts on fairly high-concept, mostly academic topics.

Here are two pieces of interesting data: one is a graph of visitors for every month of the blog's existence (I didn't do much blogging the first two years), and the other is a table of the Top 8 posts (compare with the Top 10 posts in last year's report).

Two things to note about the table. One, the length of time a post has been around does not correspond to the number of total readers (there are posts from 2009 with fewer than 15 visits). Likewise, some of the most visited posts are from earlier this year. Second, word length also does not correspond with the number of visits (something I was curious about). Perhaps novelty, timeliness, and being associated with an existing social network (e.g. CoE) are key. Or perhaps the Cynic's Rule of social media popularity plays a role. Check back on this in another year.

Game Theory of Shutting Things Down

Here is a series I did on my micro-blog, Tumbld Thoughts that discusses various aspects of the US Government Shutdown. This is largely a review of blog entries and opinion pieces that cover the strategic aspects behind the shutdown. At first, I was going to do my own theoretically-oriented (and more speculative) post on this topic, but subsequently found that a lot of the work has already been done for me. I conclude with my own thoughts on the strategy of gridlock. 

How the Game Proceeds

In this section, I will be reviewing the role of game theory and game-theoretic thinking in the current US Government gridlock crisis. This introduces the game-theoretic framework and potential mitigating factors. Prior to doing this research, my initial thought was that a game-theoretic model of suicide bombing would be the best way to model the government shutdown and its resolution [1]. However, this standoff can also (and perhaps more effectively) be modeled using the Game of Chicken [2]. 

In the Game of Chicken, the two parties drive towards each other and decide to deploy one of two strategies: remain steadfast, or swerve. The first individual to swerve loses the game. While the strategies are played simultaneously, the goal is to swerve last. However, if no one swerves, both parties lose. Unlike the case of two race car drivers displaying their bravado, there are multiple criteria that determine whether or not each side will decide to swerve first. Several of the comments in [2] suggests that the current showdown is an example of an incomplete information conflict bargaining model [3], which suggests that due to a bilateral misunderstanding of position, no one knows what the actual bargaining space looks like.

But what does this bargaining space look like? Is it only shaped by strategic interactions (e.g. maximizing individual or joint payoffs), or is it partitioned by disjoint worldviews. Jonathan Chait [4] discusses the standoff as a consequence of Republican intellectual insularity (a term called epistemic closure). According to him, the Democratic position that capitulating to political ransom will only lead to further hostage-taking requires a response which the Republicans are unable to conceptualize. For example, it may be that Ted Cruz and others in the Tea Party cannot conceptualize an outcome that does not involve a zero-sum outcome [5]. 

Player Strategy and Strategic Nuances

Now, we will discuss the underpinnings of why a game-theory explanation might and might not work well to model the current US Government gridlock crisis. As it turns out, there are many subtleties that must be considered to better understand the conflict. In other words, a simplistic game theory model (e.g. Chicken or Suicide Bomber) might not offer much insight. 

Is this simply a problem of inadequate mental modeling of political reality, or cryptic signaling on the part of the Republican side? Thomas Edsall introduces us to the role of collective anger as a cryptic signal in political motivations [6]. In [7], Jon Chait recaps the positions of Obama and Boehner and the nature of their negotiations. This article suggests that Boehner's position is weak despite the rhetoric. In fact, the entirety of Republican negotiating rhetoric (up until this point) has been a series of over-aggressive negotiating blunders [8]. But perhaps another part of the problem involves a poor understanding of what is at stake. Matt Yglesias [9] explains why the debt ceiling is not at all like, say, a home mortgage, and why understanding complex phenomena through simple analogies can oftentimes misstate the actual goals and payoffs. 

In [10], the nature of partisan conflict are explored. This was written before the current crisis, so it offers some perspective. Basically, there are two novel arguments here: that local interests that work to get people elected do not align well with solving national-level problems, and that financial debates are often polarizing by nature. On the other hand, the Republican side may have two covert goals in their negotiations [11]. The first is that Republicans will only agree to a scenario that will give them leverage. To model this in terms of a payoff matrix, an "epistemic" [12] pure strategy suite is selected by the Republican players so as to create nothing but winner-take-all outcomes based on their beliefs about the consequences. The second is that Republicans cannot directly admit to their actual strategy, lest they appear to be the instigators. In the long run (since this is an unstable strategy), they risk losing leverage on this basis alone.

Perhaps things are less complex than the roots of partisan conflict suggest. In [13], Anatole Kaletsky considers this conflict from the standpoint of maximizing rational decision-making. This is partially a matter of timing the ultimate response. For example, it may benefit the Republicans to wait until the debt limit deadline to capitulate. On the other hand, there are pressures to capitulate before then, which may lead the Democrats to overplay their hand. This could further radicalize the Republican position, which could lead to less willingness to compromise in future standoffs.

Finally, it may be that the actual number of negotiators is hard to approximate using simple models. Dylan Matthews (Wonkblog) interviewed Daniel Diermeier from Northwestern University that provides some additional insight into modeling the crisis [14]. The first involves the asymmetry of the negotiation: the President (representing the Democrats) is actually dealing with a caucus rather than a single individual (Boehner). The second point involves the reversion point of the negotiators: all parties are influenced not just by their position and the most rational outcome, but by public (e.g. voters, bankers) opinion as well. This may require a hierarchical model of agent interactions on each side of the game [15]. Perhaps things aren't as dysfunctional as we like to believe.

Another game-theoretic approach that might explain features of the shutdown involves the "hold-up" problem [16], which enables good-faith exchanges in two-party transactions. In this scenario, a lack of faith in government can make one party inherently less invested in any bi-partisan agreement. Similarly, a significant investment by the Republicans to keep the government shut down could backfire, giving the Democrats less incentive to give their opponents anything in negotiation. But perhaps game theory is not the only game in town. One alternate perspective suggests that the shutdown is a natural by-product of a historical fluctuations and a government that is too centralized and hierarchical to respond to such (predictable) challenges [17].

Further Developments: the Distractor Game

To further understand the strategy of political intransigence (a minority shareholder trying to get their own way), I present something called the "distractor game", which can be applied to many problems in which a weaker position attempts to gain a reward through distraction (or a high-cost, high-risk, and seemingly nonsensical strategy). In the poster, a toy example is used, but can be generalized to a wide variety of interactions. 

The distractor game resembles both the sneaker strategy found among evolutionarily stable mating strategies and the bait-and-switch tactic used in marketing. The difference lies in the payoff structure. While this might explain the broader tactic of intransigence, there may be an even broader tactic of "freezing things in stasis in the face of social change" that remains unexplored.

NOTES:

[1] Siquera, K. and Sandler, T.   Games and Terrorism: recent developments. CREATE Research Archive, April 1 (2009) AND Jacobson, D. and Kaplan, E.H.   Suicide Bombings and Targeted Killings in (counter-) Terror Games. Conflict Resolution, 51, 772-792 (2007).

[2] amurdie   Game of Chicken and the US Government Shutdown: What Game Theory Can Tell Us About Likely Outcomes. Duck of Minerva blog, September 30 (2013).

[3] Fearon, J.D.   Rationalist Explanations for War. International Organization, 49(3), 379-414 (1995).

[4] Chait, J.   How Republicans Failed  to Understand the Democrats’ Debt-Ceiling Logic. Daily Intelligencer, October 7 (2013).

[5] Keller, B.   The Right Gets its 60's.  New York Times, September 29 (2013).

[6] Edsall, T.B.   Anger can be power. NYT Opinionator, October 8 (2013).

[7] Chait, J.   John Boehner Too Embarrassed to Defend His Own Extortion Demands. Daily Intelligencer, October 8 (2013). 

[8] Krugman, P.   Aggressive Blunderers. Conscience of a Liberal blog, October 3 (2013).

[9] Yglesias, M.   The Debt Ceiling Is Nothing Like Your Mortgage. Moneybox, October 8 (2013).

[10] El-Erian, M.   How game theory explains Washington's horrible gridlock. The Atlantic, January 15 (2013).

[11] Sargent, G.   The Morning Plum: A clarifying moment of Washington dysfunction. The Plum Line, October 9 (2013).

[12] Chait, J.   Why  the Shutdown Is Leading  to Debt Default; or, What Happens When You Take Hostages Without a Plan. Daily Intelligencer, October 2 (2013).

In this case, an epistemic strategy suite is one that is restricted to strategies that allow one to argue from a certain set of premises.

[13] Kaletsky, A.   Game theory and America’s budget battle. Reuters, October 3 (2013).

[14] Matthews, D.   How a game theorist would solve the shutdown showdown. Wonkblog, October 4 (2013).

[15] Bottom picture is from: Synnaeve, G.   Bayesian Programming and Learning for Multi-Player Video Games: application to RTS AI. PhD Thesis (2012).

[16] Che, Y-K. and Sakovics, J.   The hold-up problem. Ideas repository, NEP-ALL-2006-09-11 (2006).

[17] MacKensie, D.   The maths that saw the US shutdown coming. New Scientist, October 10 (2013).

Academic Commentary via Digital Media (exploratory)

Here are four short features cross-posted from my micro-blog, Synthetic Daisies. They are all (in one form of another) commentary on various academic topics using either social media (blogs, bulletin boards) or simulations/games. These include Simulating Sub-second Social Movements (I), Angst-as-Commentary: the case of Evolutionary Psychology (II), Adaptability and Evolvability of Humans (III), and A Cognitively Dissonant Truth (IV).

I. Simulating Sub-second Social Movements

Here are two pieces of news about fluctuations in virtual financial markets. In the first [1], an ad-hoc experiment was done to verify whether or not BAWSAQ (an internal stock market in the video game GTA 5) is subject to collective behavior.

Normally, the stock markets in this game are dominated by random fluctuations, but occasionally fluctuations in stock values can be linked to insider trading events. 

But perhaps the BAWSAQ market is truly dynamic, responding a wider range of events (and player interactions) in the game world. To test this, players coordinated a stock dump using a subreddit for GTA Markets.

The results were negative, as there was no immediate response to a massive change in supply/demand. However, this does not preclude longer-term effects on the market. Is collective behavior present in other virtual markets? The recent takedown of the Silk Road online drug exchange provides the second example. 

As bitcoins are used for many illicit activities, their value is tied (in part) to these activities. Soon after Silk Road was shut down, values of Bitcoins on the Mt. Gox and Bitstamp exchanges experienced a severe but short-term crash [2].

In this case, short-term crash means that the currency's value plummeted and partially recovered after three hours. A bit less ultra-fast than a flash crash, but much more of an immediate effect than any potential fluctuations in the BAWSAQ.

II. Angst-as-Commentary: the case of EP

Here is a recent thread on angst-as-commentary surrounding the scientific merits of Evolutionary Psychology (EP). This particular thread was triggered by an online exchange between PZ Myers and Robert Kurzban [3]. PZ "despises" evolutionary psychology for reasons explicated in his discussion. Kurzban's response (as a representative of the field) is that PZ is expressing a visceral response to what has become representative of the EP field in most people's minds. 

While the field is indeed diverse (and apparently hard to find the boundaries of), this tendency for behavioral adaptationism and the defense of morally questionable behaviors as being innate is summarized in Annalee Newitz's provocatively-titled io9 column "Rise of the Evolutionary Psychology Douchebag" [4]. However, given the article's title and examples, it is unclear whether the douchebags in question are supposed to be all members of the EP community or just the people who have used EP to advance their own biased and misogynistic views of human nature. 

Are the alleged misdeeds and pseudo-scientific tendencies of EP really deserved? Jerry Coyne, while having his own problems with the field [5], feels that at least part of this angst comes from ideonational bias rooted in the nature vs. nurture wars of the 20th century. In PZ Myers' response, he argues that many of the research topics in EP are difficult to address using the methods generally employed by the researchers in question [6]. I'm sure this debate will continue for some time to come. 

In the end, it is hard to distinguish whether EP represents a strict adaptationist view of human behavior, or whether it is merely drawing on supposed analogues with the human past, or something more powerful. However, one issue here seems to be that the boundaries of EP are poorly defined. Biocultural anthropologists, primatologists, and social psychologists are lumped together without much regard to their relative contributions to the EP literature (or the noteriety of the EP reputation). Much like the lumpers and splitters of biological taxonomy, a reasoned critique (or defense) of EP should draw these lines more carefully.

III. Adaptability and Evolvability of Humans: new perspectives

Here are a number of posts related to the evolution and adaptability of humans, with particular relevance to cases where evolvability and adaptability runs up against its own limits. The first article [7] is an interview with David Attenborough, in which he argues that humans have stopped evolving. This has engendered some interesting responses from the blogosphere [8], and can be contrasted with molecular mechanisms that initially accelerated human evolution during the Pleistocene [9].

Are humans still evolving? And what are the implications of this question on generalized adaptive mechanisms (e.g. neuroplasticity). Perhaps there is an interplay between our adaptive capacity and technology (or ability to manipulate things [10]) that has driven human biological and cultural evolution. If so, is it reasonable to think that this trend will continue into the future [11]. Whether it resembles hereditary (e.g. Darwinian) evolution is another matter.

The next two articles look at two ways to view adaptability: as a generalized response to rapid fluctuations in the environment, and as a robust anatomical configuration. In the case of humans [12], it is argued that cultural innovations tied to rapid climate changes during the Pleistocene led to a high degree of adaptability in the our species.

But there are other ways for an organism to be highly adaptable, some on which can be useful lessons to technologists. In [13], the modular radial symmetry of the octopus and associated behaviors [14] are touted as a way to avoid the fragility inherent in centralized complex systems.

IV. A Cognitively Dissonant Truth

Here is a series of articles on the relationship (ranging from ambivalent to downright hostile) libertarians have with climate change. Is it simply driven by ideological bias, or is it simply another instance of (perhaps fashionable) denialism [15]? In [16], Jason Collins from Evolving Economics blog offers some first-impression thoughts on the phenomenon.

Massimo Pigliucci [17] explores this theme further, focusing on the philosophical underpinnings of the objections. He argues that climate change skepticism is largely based on a lack of evidence-based evaluation resulting from a violation of libertarian moral values.

Michael E. Mann [18] and George Monbiot [19] provide complementary explanations: the former is based on the rigidity of the economist's mindset, the latter is based on assumptions about property rights. The Mann explanation [19] arose from interviews with Nate Silver for his book "The Signal and the Noise".

Mann chief critique arises from Silver's naive cost-benefits analysis of the climate change, which does not take into account the true cost of carbon emissions nor the naturalistic and long-term perspectives of a climate scientist. In a manner similar to Pigliucci, Monbiot points to the rigidity of the libertarian (and conservative) views on property rights, and how effective climate change policy would violate the logic of this worldview.

NOTES:
[1] Roose, K.   GTA5 Players' Crazy Stock Scheme. Daily Intelligencer, October 2 (2013).

[2] McMillan, R.   Bitcoin values plummet $500M, then recover, after silk road bust. Wired, October 2 (2013).

[3] Myers, P.Z.   SkepChick EvoCon panel. Skepchick blog (2013).

Kurzban, R.   What Does PZ Myers Despise? Evolutionary Psychology blog, August 2 (2013).

[4] Newitz, A.   The Rise of the Evolutionary Psychology Douchebag. io9 Magazine, June 2 (2013).

[5] Coyne, J.   Another lame attack on evolutionary psychology. Why Evolution is True blog, September 1 (2013).

Myers, P.Z.  Jerry Coyne gets everything wrong, again. Pharyngula blog, September 1 (2013).

For background, read: Coyne, J.   Is Evolutionary Psychology Worthless? Why Evolution in True blog, December 10 (2012).

MetaFilter   An evolutionary psychology debate. February 4 (2009).

Mitchell, M.   Can Evolution Explain How the Mind Works? A Review of the Evolutionary Psychology Debates. Complexity, 3(3), 17–24 (1999).

University of Plymouth SALMON, Evolutionary Psychology. Department of Psychology.

[6] On the other hand, part of this whole debate could be a fundamental miscommunication between academic fields (and challenges to their academic territory). Two painful examples of this: 

* Cognitive scientist critiquing Evolution: Blogginheads TV   Jerry Fodor vs. Elliott Sober. March 20 (2010).

* Evolutionary biologist critiques of Economics: Auld, C.   Anti-economist watch: David Sloan Wilson edition. Chris Auld blog, September 26 (2011). 

[7] Furness, H.   Sir David Attenborough: humans have stopped evolving. The Telegraph, September 10 (2013).

Read this interview in tandem with the following paper: Crabtree, G.   Our fragile intellect, Part II. Trends in Genetics, 29(1), 3-5 (2012). Then compare and contrast with [2] and [3].

* the map in the first figure is courtesy National Geographic Interactive.

[8] For one such example, see: Dunsworth, H.   We are not the boss of natural selection. It is unpwnable. Mermaid's Tale blog, September 13 (2013).

[9] Hawks, J.   Why Human Evolution Accelerated. John Hawks Weblog, December 12 (2007).

[10] Hashimoto, T., Ueno, K., Ogawa, A., Asamizuya, T., Suzuki, C., Cheng, K., Tanaka, M., Taoka, M., Iwamura, Y., Suwa, G., and Iriki, A.   Hand before foot? Cortical somatotopy suggests manual dexterity is primitive and evolved independently of bipedalism. Philosophiocal Transactions of the Royal Society B, 368, 20120417 (2013).

* part of a special issue on tool use in humans and other species.

[11] For more on technologically-driven adaptability, check out proceedings of the h2.0 conference, sponsored by MIT in 2007.

[12] Massey, N.   Humans May Be Most Adaptive Species. Scientific American ClimateWire, September 25 (2013).

[13] Sagarin, R.   When Catastrophe Strikes, Emulate the Octopus. Wired, March 21 (2012).

[14] Mike Mike   Do octopuses play? Cephalove blog, July 27 (2010).

[15] Frank, A.   Welcome to the age of denial. NY Times Op-ed, August 21 (2013).

[16] Collins, J.   Climate Change and Libertarianism. Evolving Economics blog, September 9 (2013).

[17] Pigliucci, M.   Why do libertarians deny climate change? Rationally Speaking blog, May 27 (2010).

[18] Mann, M.E.   FiveThirtyEight: The Number of Things Nate Silver Gets Wrong About Climate Change. HuffPo Green, September 24 (2012).

[19] Monbiot, G.   Why libertarians must deny climate change, in one short take. George Monbiot's blog, January 26 (2012).