Realism and interfaces in philosophy of mind and metaphysics

In an earlier post, I discussed three theories of perception: naive realism, critical realism, and interfaces. To remind you of the terminology: naive realism is the stance that the world is exactly as we perceive it and critical realism is that perception resembles reality, but doesn’t capture all of it. Borrowing an image from Kevin Song: if naive realism is a perfect picture then critical realism is a blurry one. For a critical realist, our perception is — to move to another metaphor — a map of the territory that is reality; it distorts, omits details, adds some labels, and draws emphasis, but largely preserves the main structure. Interfaces, however, do not preserve structure. Borrowing now from Donald Hoffman: consider your computer desktop, what are the folders? They don’t reflect the complicated sequence of changes in magnetization in a thin film of ferromagnetic material inside a metal box called your hard-drive, not even at a coarse-grained level. Nor do they hint at the complicated information processing that changes those magnetic fields into the photons that leave your screen. But they do allow you to have a predictable and intelligible interaction with your computer, something that would be much more difficult with just a magnetized needle and a steady hand. The interface does not resemble reality, it just allows us to act. Although the comments section of the earlier post became rather philosophical, my original intention was to stay in the realm of the current scientific discourse on perception. The distinction between realism and interfaces, however, also has a rich philosophical history — not only in epistemology but also in metaphysics — that I want to highlight with a few examples in this post.

Helicobacter pylori and stem cells in the gastric crypt

Last Friday, the 4th Integrated Mathematical Oncology Workshop finished here at Moffitt. The event drew a variety of internal and external participants — you can see a blurry photo of many of them above — and was structured as a competition between four teams specializing in four different domains: Microbiome, Hepatitis C, Human papillomavirus, and Helicobacter pylori. The goal of each team was to build mathematical models of a specific problem in their domain that were well integrated with existing clinical and biological resources, the reward was a start-up grant to the project that seemed most promising to the team of judges. As I mentioned earlier in the week, I was on team H. Pylori — lead by Heiko Enderling with clinical insights from Domenico Coppola and Jose M. Pimiento. To get a feeling for the atmosphere of this workshop, I recommend a video summary of 2013’s workshop made by Parmvir Bahia, David Basanta, and Arturo Araujo:

I want to use this post to summarize some of the modeling that we did for the interaction of H. Pylori and gastric cancer. This is a brief outline — a reminder of sorts — and concentrates only on the parts that I was closely involved in. Unfortunately, this means that I won’t cover all the perspectives that our team offered, nor all the great work that they did. I apologize for the content I omitted. Hopefully, I can convince some other team members to blog about their experience to give a more balanced perspective.

This post also won’t cover all that you might want to know about bacteria and gastric cancer. As we saw earlier, fun questions about H. Pylori span many length and temporal scales and it was difficult to pick one to focus on. Domenico pointed us toward Houghton et al.’s (2004) work on the effect of H. Pylori on stem cell recruitment (for a recent survey, see Bessede et al., 2014), and suggested we aim our modeling at a level where we can discuss stem cells quantitatively. The hope is to use the abundance of stem cells as a new marker for disease progression. In the few days of the workshop, we ended up building and partially integrating two complimentary models; one agent-based and one based purely on ODEs. In the future, we hope to refine and parametrize these models based on patient data from Moffitt for the non-H. Pylori related gastric cancers, and from our partners in Cali, Colombia for H. Pylori related disease.

From H. pylori to Spanish colonialism: the scales of cancer.

Yesterday was the first day of the 4th Integrated Mathematical Oncology Workshop here at Moffitt. This year, it is run jointly with the Center for Infection Research in Cancer and is thus focused on the interaction of infection disease and cancer. This is a topic that I have not focused much attention on — except for the post on canine transmissible venereal tumor and passing mentions of Human papillomavirus (HPV) — so I am excited for the opportunity to learn. The workshop opened with a half-day focused on getting to know the external visitors, Alexander Anderson’s introduction, and our team assignments. I will be teammates with Heiko Enderling, Domenico Coppola, Jose M. Pimiento, and others. We will be looking at Helicobacter pylori. Go team blue! If you are curious, the more popularly known HPV went to David Basanta’s team, it will be great to compete against my team leader from last year. As you can expect, the friendly trash talking and subtle intimidation has already begun.

To be frank, before yesterday, I’ve only ever heard of H. pylori once and knew nothing of its links to stomach cancer. The story I heard was associated with Barry J. Marshall and J. Robin Warren’s award of the 2005 Nobel Prize in Physiology and Medicine “for their discovery of the bacterium Helicobacter pylori and its role in gastritis and peptic ulcer disease”. In 1984, Marshall was confident in the connection between H. pylori, inflammation, and ulcers, but the common knowledge of the day was that ulcers were caused by things like stress and smoking, not bacteria. The drug companies even happened to have an expensive drug that could manage the associated stomach inflammation, and given the money it was bringing in, nobody was concerned with finding some bacterium that could be cured with cheap antibiotics. Having difficulty convincing his colleagues (apart from Warren), Marshall decided to drink a Petri dish of cultured H. pylori, and within a few days grew sick, developing severe inflammation of the stomach before finally (two weeks after the ingestion) going on antibiotics and curing himself. This dramatic display was sufficient to push for bigger studies that eventually lead to the Nobel prize; I recommend listening to Warren’s podcast with Nobel Prize Talks or his acceptance speech for the whole story.

This is a fascinating tale, but from the modeling perspective, the real excitement of H. pylori and its role in stomach cancer is the multitude of scales that are central to the development of disease. We see important players from the scale of molecules involved in changing stomach acidity, to the single-cell scale of the bacteria and stomach lining, to the changes across the stomach as a whole organ, and the role of the individual patient’s life style and nutrition. These are the usual scales we see when modeling cancer, and dovetail nicely with Anderson’s opening remarks on the centrality of mathematics in helping us bridge the gaps. However, in the case of H. pylori, the scales go beyond the single individual at which Anderson stops and extend to the level of populations of humans in the co-evolution of host and pathogen, and even populations of groups of humans in a speculative connection to a topic familiar to TheEGG readers — the evolution of ethnocentrism. In preparation for the second half of the second day and the intense task of finding a specific question for team blue to focus on, I wanted to give a quick overview of these scales.

Bernstein polynomials and non-linear public goods in tumours

By analogy, or maybe homage, to standard game theory, when we discuss the payoffs of an evolutionary game, we usually tell the story of two prototype agents representing their respective strategies meeting at random and interacting. For my stories of yarn, knitting needles, and clandestine meetings in the dark of night, I even give these players names like Alice and Bob. However, it is important to remember that these are merely stories, and plenty of other scenarios could take their place. In the case of replicator dynamics there is so much averaging going on that it is often just better to talk about the payoffs as feedback between same-strategy sub-populations of agents. The benefit of this abstraction — or vagueness, if you prefer — is that you don’t get overwhelmed by details — that you probably don’t have justification for, anyway — and focus on the essential differences between different types of dynamics. For example, the prisoner’s dilemma (PD) and public goods (PG) games tell very different stories, but in many cases the PD and linear PG are equivalent. Of course, ‘many’ is not ‘all’ and my inclusion of ‘linear’ should prompt you to ask about non-linear public goods. So, in this post I want to provide a general analysis of replicator dynamics for non-linear public goods games following the method of Bernstein polynomials recently used by Archetti (2013, 2014). At the end, I will quickly touch on the two applications to mathematical oncology that Archetti considers. SInce I am providing a more general analysis, I will use notation inspired by Archetti, but defined more precisely and at times slightly differently — some symbols will be the same in name but not in value, so if you’re following along with the paper then pay close attention.

From realism to interfaces and rationality in evolutionary games

As I was preparing some reading assignments, I realized that I don’t have a single resource available that covers the main ideas of the interface theory of perception, objective versus subjective rationality, and their relationship to evolutionary game theory. I wanted to correct this oversight and use it as opportunity to comment on the philosophy of mind. In this post I will quickly introduce naive realism, critical realism, and the interface theory of perception and sketch how we can use evolutionary game theory to study them. The interface theory of perception will also give me an opportunity to touch on the difference between subjective and objective rationality. Unfortunately, I am trying to keep this entry short, so we will only skim the surface and I invite you to click links aggressively and follow the references papers if something catches your attention — this annotated list of links might be of particular interest for further exploration.