April 29, 2014

Intra- and Inter-generational Physiological Evolution: three case studies

Evolutionary processes are crucial to driving forward physiological processes. While inter-generational adaptation is considered to be the "gold standard" of evolutionary change, natural selection-driven adaptive processes can also act on intra-generational timescales. Like many epigenetic mechanisms, intra-generational adaptive processes are not known to transmit nor retained over many generations.

In this post, we will discuss three cases of how evolutionary processes (two explicitly intra-generational, one extensively inter-generational) affect the operation of physiological systems. In the case of our inter-generational examples (I and III), physiological processes exhibit their own adaptive dynamics. In the case of our inter-generational example, the macro-evolutionary distribution of gene variants provides a basis for intra-generational adaptation.


I. Role of Intra-generational Selection in tRNA Availability and Translation

Mahlab, S. and Linial, M.   Speed Controls in Translating Secretory Proteins in Eukaryotes: an Evolutionary Perspective. PLoS Computational Biology, 10(1), e1003294 (2014).

This paper deals with transcription and the production of secretory molecules (production of the secretome) as an intra-generational evolutionary process. The secretome involves a vast array of peptides produced via a special ribosomal structure located at the cell membrane (Figure 1). The resulting peptides (manufactured on the outside of this membrane) are then involved in cell-cell communication.

Figure 1. The specialized translational pathway that leads to the production of signaling peptides.

The authors focus on role of tRNA (or transfer RNA) adaptation and the N' terminal of secretory proteins. tRNAs are internal to the translational process, and serve to translate open reading frames of DNA into amino acids. As adaptors, tRNAs are specialized by codon and function. Each type of specialization results in a population (or pool) which has a certain degree of diversity. This results in something called codon usage bias, a concept to which we will return. The N' terminal regions of the signaling peptide are associated with the so-called "fast" tRNAs. Secretory proteins made in this fashion are also found to contain segmental information that allow for various signaling functions. The signaling functionality is in turn a product of adaptation by natural selection within a single human generation (and perhaps even within a single cellular generation). "Fast" tRNAs are just one type of specialized tRNA molecule that exist in different proportions depending on various factors. The consequences of selection on these ratios is to affect the production of some codons (and thus peptides) over others.

Changes in the proportion of tRNA types requires an adaptive mechanism. While the specifics of this mechanism are unknown (but see Figure 2), the amount of diversity is governed by the number of tRNA molecules of a certain specialized type. To illustrate this, I use a conceptual model of translation called the "Hungry, Hungry Hippos" model, named after the popular children's board game (see Figure 3). The game begins with four hippos and a game board full of freely-moving marbles. Then, each hippo eats as many marbles as they can before the marbles are all eaten. This race exemplifies how tRNAs are utilized in the process of translation: mRNA is moved through the ribosome at different speeds, which tRNA molecules compete to bind to the incoming sequence and replicate their information in a new generation of peptides.

Figure 2. The site of translation and the trade-offs inherent in tRNA selection. COURTESY: Figure 1 (a and b) from [2].

Figure 3. The game "Hungry, Hungry Hippos", a model for transcription?

While one might think of this as a stochastic process, tRNA pools adapt to the needs of a given cell, including the speed of translation and amino acid bias. One measure of how these pools evolve is the tRNA adaptation index [1], which is based on the concept of codon usage bias (Figure 4).

Figure 4. the tRNA (codon) adaptation index, a intra-generational natural selection index. CAI is a weighted geometric mean for all categories of codon.

The premise of tRNA adaptation and the potential role of natural selection is that gene expression is correlated with codon bias [3]. Depending on the needs of the cell, the production of proteins can be biased towards certain amino acids through controlling both the speed of translation and the (perhaps more importantly) the composition of tRNA pools. The consequences of this codon bias can be observed when plotted against gene expression (e.g. the production of mRNAs -- see Figure 5). In general, when gene expression (or transcriptional noise) is more active, the greater the bias in codon-specific tRNA activity (in the form of codon frequency).

Figure 5. Changes in codon frequency with respect to gene expression. Figure 2 from [4]. 


II. Inter-generational Selection for Antigens

Forni, D., Cagliani, R., Tresoldi, C., Pozzoli, U., De Gioia, L., Filippi, G., Riva, S., Menozzi, G., Colleoni, M., Biasin, M., Lo Caputo, S., Mazzotta, F., Comi, G.P., Bresolin, N., Clerici, M., and Sironi, M. An Evolutionary Analysis of Antigen Processing and Presentation across Different Timescales Reveals Pervasive Selection. PLoS Genetics, 10(3), e1004189 (2014).

The human immune system is a complex system that consists of recognition and defense mechanisms (Figure 6). These mechanisms operate both intracellularly and extracellularly. In addition (see Figure 7), there is both an innate system (which is evolutionarily conserved) and an adaptive system (which is derived but shared among vertebrates). Given this complexity, it is often hard to find the inter-generational underpinnings of intra-generational adaptation. One form of intra-generational adaptation in the immune system involves antigen processing and presentation. This is determined by both the inter-generational evolutionary history of antigen-specific genes and the role of selection within and between generations.

Figure 6. A quick refresher on the human immune system architecture. COURTESY: [5].

In this study, the authors examined the evolutionary history of 45 antigen-specific genes in Homo sapiens. In doing so, they and looked at both the intra-specific variation and inter-specific diversity of genes related to antigen-related processes. This study also used a comparative genomic approach to better understand the evolutionary history of antigen-specific genes in humans. This was done in two different ways. The first was to use several different statistical tests to identify the target of selection. Then, the targets were characterized using low-coverage, whole-genome Sanger sequencing (e.g. high-throughput analysis using next-gen sequencing). In the end, it was found that 9 genes in the antigen processing and presentation (APP) pathway have undergone adaptation within Homo sapiens. Taken collectively, this study gives us a structural view of diversity in the immune system that may predict variation in immune-related physiological responses.

Figure 7. Evolution of adaptive immunity in the Tree of Life. COURTESY: [6]


III. Intra-generational Selection in Tumor Survival (Cancer Evolution)

Ostrow, S.L., Barshir, R., DeGregori, J., Yeger-Lotem, E., and Hershberg, R.   Cancer Evolution Is Associated with Pervasive Positive Selection on Globally Expressed Genes. PLoS Genetics, 10(3), e1004239 (2014).

Much like Evolutionary Psychology, evolutionary views of cancer has become increasingly popular as conceptual models. Unlike Evolutionary Psychology, however, evolutionary views of cancer are not based on attempts to broadly characterize human behavior. The evolutionary view of cancer is similar to the population dynamics of organismal evolution by natural selection. Except that in this case, population processes are intra-generational and occur within specific tissues. What makes them "evolutionary"? For one, cancer can be characterized as a genealogical (branching) process, with many cancer cells originating from a single deleterious mutant (Figure 8).



Figure 8. Oncogenesis as a branching bush (evolution from common descent). COURTESY: [8].

In fact, one could think of evolutionary models of cancer as an instance of evolutionary dynamics rather than the outcome of reproductive fitness. Nevertheless, the usual suspects still participate in the process. For example, genetic variation in the form of standing variation or somatic mutations is selected upon through the process of tumorigenesis [7]. Mutations that are robust to positive selection contribute to the proliferation and microenvironmental maintenance of tumors (Figure 9). This is distinct from the natural selection that acts on germ line cells. Nevertheless, reproductive fitness is still the criterion for selection.

Figure 9. LEFT: Schematic showing the role of selection on cell populations and their microenvironmental ecosystem. RIGHT: comparison of clonal populations and their evolution with organismal species and their evolution. COURTESY: [9].

One important but often overlooked aspect of treating cancer as an intra-generational evolutionary process is that the constituent cells of a tumor can be viewed as replicators. Figure 10 demonstrates how lineages bud from single mitotically-dividing cells given various environmental and microenvironmental triggers. Yet single- cell replicators are also theoretical units upon which selection acts. In the case of Eukaryotic somatic and stem cells, variants can compete to determine the intensity or metastatic ability or a given type of cancer. These replicators also operate in an environmental context that often acts as a source of selection.

Figure 10. Evolutionary process in a single body (e.g. intra-generational cell population). COURTESY: Figure 2 in [10].

Despite some conceptual difficulties, these three studies give us a window into intra-generational adaptive and evolutionary processes. Far from being a black box, these processes are often distinct from but are influenced by inter-generational evolution. While these studies ignore the role of currently hyped adaptive mechanisms such as epigenetics and the microbiome, there is a lesson for interpreting the true contribution of these types of mechanisms on the long-term evolutionary process.

NOTES:
[1] dos Reis, M., Savva, R., and Wernisch, L.   Solving the riddle of codon usage preferences: a test for translational selection. Nucleic Acids Research, 32(17), 5036–5044 (2004).

[2] Pechmann, S. and Frydman, J.   Evolutionary conservation of codon optimality reveals hidden signatures of co-translational folding. Nature Structural and Molecular Biology, 20, 237–243 (2013).

[3] Neame, E.   Structure vs. Codon Bias. Nature Reviews Microbiology, 7, 406 (2009).

[4] Shah, P. and Gilchrist, M.A.   Explaining complex codon usage patterns with selection for translational efficiency, mutation bias, and genetic drift. PNAS, 108(25), 10231-10236 (2011).

[5] The Human Immune System. The Molecules of HIV website (2006).

[6] Danilova, N.   Evolution of the Immune System. MIT OpenCourseWare, Spring (2005).

[7] Anderson, A.R.A., Weaver, A.M., Cummings, P.T., and Quaranta, V.   Tumor Morphology and Phenotypic Evolution Driven by Selective Pressure from the Microenvironment. Cell, 127, 905-915 (2006) AND Magiliocco, A.M.   Tumor Heterogeneity in Breast Cancer, Concepts, and Tools. Figshare.

[8] Looi, M-K.   Cancer, genomes, evolution, and personalized medicine - it's complicated. Wellcome Trust blog, March 7 (2012).

[9] Greaves, M. and Maley, C.C.   Clonal Evolution and Cancer. Nature, 481, 306-313 (2012).

[10] Yates, L.R. and Campbell, P.J.   Evolution of the Cancer Genome. Nature Review Genetics, 13, 795-806 (2012).

April 24, 2014

New Directions in Space, Time, and Thought

Here is the latest news from the realm of Tumbld Thoughts. All features are interesting. In this post, we move from the latest episodes of Cosmos to new directions in economic value and the arXiv, to new directions in practicing research.

I. Making Amphibians Out Of Quarks and Other Tales of Scale


Here are the supplementary readings for Episode 6 of the Cosmos reboot, called “Deeper, Deeper Still”. These are organized by theme. I am not responsible for any groans my puns may cause.



(Episode) Origins…..
A sneak peek for this week. Daily Galaxy blog, April 12 (2014).

Ziggy Stardust and the Extra Dimensions (on Mars?):
Berkowitz, J.   The Stardust Revolution. Prometheus Books (2012).

Greene, B.   The Search for Hidden Dimensions. Richard Dawkins Foundation for Reason and Science. YouTube, May 17 (2010).


A human = 10^30 quarks?
Wolchover, N.   A Jewel at the Heart of Quantum Physics. Quanta Magazine, September 17 (2013).

Carroll, S.   Jaroslav Trnka on the Amplituhedron. Preposterous Universe blog, March 31 (2014).

Filmer, J.   New Discovery Simplifies Quantum Physics. From Quarks to Quasars blog, September 19 (2013).

Huang, C.   Scale of the Universe II. Scaleofuniverse.com.

Tardigrages and Angiosperms:
Stromberg, J.   How Does the Tiny Waterbear Survive in Outer Space?Smithsonian.com, September 11 (2012).

Nichols, P.B., Nelson, D.R., and Garey, J.R.   A family-level analysis of tardigrade phylogeny. Hydrobiologia, 558, 53-60 (2006).

Soltis, P., Soltis, D., and Edwards, C.   Angiosperms. Tree of Life (2005).


Plants Move Towards the Light and Make Food:
Wyatt, S.E. and Kiss, J.Z.   Plant tropisms: from Darwin to the International Space Station. American Journal of Botany, 100(1), 1-3 (2013).

Artificial Photosynthesis. Wikipedia, April 13 (2014).

Carbon is Versatile:
Buckminsterfullerene. Wikipedia, April 13 (2014).

Carbon Nanotube. Wikipedia, April 13 (2014).

Wall of Forever:

Tate, K.   How Gravitational Waves Work (Infographic). Space.com, March 17 (2014).


IMAGES:
Third from top: Book Cover, You are Stardust. Elin Kelsey and Soyeon Kim.

Fourth from top: Ichetucknee Springs, North Florida, USA.

Bottom Image: Evidence for Cosmic Inflation following the Big Bang, COURTESY:BICEP2 Group.

II. Clean Room Redux


Here are the supplemental readings for the seventh episode of the Cosmos reboot entitled "The Clean Room". A bit of a departure from the previous episodes in that the focus was on the social consequences of scientific findings. As usual, readings are thematic.


Meteors, Sediments, and Early Earth:
Scientists Building Asteroid Threat Early-Warning System. Space.com, February 20 (2013).

Diverging evolution of early Earth and Mars revealed by meteorites. The Daily Galaxy blog, April 17 (2014).

Appenzeller, T.   Early Earth. National Geographic, December (2006).


Clean Rooms and Isotopes:
Radioactive Decay: a sweet simulation of a half-life. AAAS Science NetLinks.

Radioactive Dating Game. PhET Interactive Simulations.

Lewington, R.   A virtual tour of Applied Materials' clean room. Applied Materials blog.


Chemophobia vs. Public Relations and the role of science:

How corporations corrupt science at the public's expense. Union of Concerned Scientists, Center for Science and Democracy.

Washburn, J.   Science's Worst Enemy: corporate funding. Discover Magazine, October (2007).

"Silent Spring" at 50. The credit, and the blame, it deserves. Big Think blog, June 19 (2012).

Lead poisoning and health. World Health Organization, Fact sheet #379. September (2013).

Needleman, H.L.   The removal of lead from gasoline: historical and personal reflections. Environmental Research, 84(1), 20-35 (2000).

III. Pushing the Boundaries of the arXiv


I guess I am literally pushing the boundaries of the arXiv. On Tuesday, March 25, I submitted a paper called "Contextual and Structural Representations of Market-mediated Economic Value". While they normally announce the paper at Midnight (GMT) the following weekday, this paper was not announced until two days later (Friday morning).


Usually, when a paper is delayed, it means there is an issue with classification. Ultimately, the paper was placed in the q-fin.GN category. Then, 12 days later, arXiv introduced two new categories: q-fin.EC (economics) and q-fin.MF (mathematical finance). While this could be a coincidence, I still like to think that my paper broke their system. Hopefully, it ends up breaks new ground and old paradigms as well.


IV. The New, Potentially Paradigm-busting Paper on the arXiv


How do we assign value to economic transactions? In my latest paper, now available at the arXiv, I approach this problem using a computational and evolutionary approach. "Contextual and Structural Representations of Market-mediated Economic Value" is my first paper in the "q-fin" category (1403.7021, q-fin.GN).



Culturally-mediated biological markets are used to model several aspect of object valuation. Contextual Geometric Structures (CGSs) [1] are used to model individual minds in an agent-based simulation. Read the paper to fully appreciate what this means. While it is a purely computational study, it might also be of interest to behavioral economists and evolutionary anthropologists.

Proceedings of Artificial Life, 13, 147-154 (2012).

IV. Orthogonal Research: slouching towards research enterprise


In lieu of a formal academic position, I am now publishing and conducting work under the affiliation "Orthogonal Research". This is (currently) a money-less start-up, focused on research in mathematical modeling and data analysis. Right now, this just involves myself. However, potential collaborators, co-PIs, and funders are welcome to contact me.

Things are a great deal more serious than this.

The Orthogonal Research Q1 activity report is now available. "Q1" refers to the first quarter of the calendar year, not financial.

April 19, 2014

It's Algorithmic Indulgence for the Masses (or the niche market)


Introducing the latest addition to the Synthetic Daisies blog: Popular Algorithmics. Popular Algorithmics (a takeoff on Popular Mechanics) is a collection of posts originally presented as a series on Tumbld Thoughts. Each entry is a take-off on an established algorithmic approach from the scientific literature. Of particular interest are lesser known algorithmic approaches from the standpoint of both theory and application.

April 11, 2014

Starstuff Squared

This post presents the supplemental readings for the fourth (I) and fifth (II) episodes of the Cosmos reboot. These materials are cross-posted to Tumbld Thoughts.

I. Stellar Evolution is Six Points the Natural Law


Here are the supplemental readings for Cosmos, episode IV: "A Sky Full of Ghosts". The readings are organized by theme, and relate to scenes in the episode.

1. The Speed of Light is Not Attainable:
Life's Little Mysteries Staff   Can Matter Travel at Light Speed? LiveScience, September 27 (2012).

Variable Speed of Light: Einstein's theory of General Relativity. Speed of Light in Gravity blog.

2. Relativity Is Not Rocket Science -- it's much harder:
Minute Physics   Relativity Isn't Relative. YouTube, March 28 (2013).

Wolfson, R.   Simply Einstein: Relativity Demystified. W.W. Norton (2003).

3. The Earth is Not a Sphere (and the horizon is an illusion):
Choi, C.Q.   Strange but true: Earth is not a sphere. Scientific American, April 12 (2007).

Tyson, N.D.   On Being Round. Natural History Magazine, March (1997).

4. The Universe is Not Flat:
Archive of images from the Hubble telescope (Hubblesite).

Weiss, M.   What Causes the Hubble Redshift? Original Usenet Physics FAQ (1994).

5. Life in Space is Not Easy to Understand:
Loftin, R.B. and Kenney, P.   Training the Hubble space telescope flight team. IEEE Computer Graphics and Applications, 15(5), 31-37 (1995).


Halpern, P.   How large is the observable universe? The Nature of Reality blog, October 10 (2012).

Ceurstemont, S.   What a trip through a wormhole would look like. New Scientist TV, March 13 (2012).

6. Other Things that are Not Well-known:

History of Cyanotype. COURTESY: Alternative Photography and John Herschel.



II. The Lightness of Starstuff


Here are the supplementary readings for the fifth episode of the Cosmos reboot. The readings are organized by theme and observation. These relate loosely to scene and observation.

This Style of Popularization is Frustrating:
Orzel, C.   Cosmos F*$&ing Loves Science. Uncertain Principles blog, March 31 (2014).

Camera Obscura:


Mo Tse and Questioning Cultural Convention:
Fraser, C.   Mohism. Stanford Encyclopedia of Philosophy (2010).


Chinese Culture, Strategy, and Innovation. Chapter 2 of "Innovative China", T.C.R. van Someren and S. van Someren-Wang. Springer-Verlag (2013).

Al-Hazen's Book of Optics.

Replacing the Extramission Theory of Vision:
Madan, U.   The Beginnings of Sight. The Weekend Historian blog, May 26 (2009).

Graziano, M.   How Consciousness Works. Aeon Magazine, August 23 (2013).


The Strange World of Light:
Dzierba, A.   QCD with a light touch. American Scientist, April (2009). Book Review of "The Lightness of Being" by Frank Wilczek.

The Standard Model, Part 2: QCD. Spontaneous Symmetry blog, June 27 (2009).





Siegel, E.   The Cosmic Speed Limit. Starts with a Bang! blog, April 26 (2013).


April 6, 2014

Fireside Science: The Structure and Theory of Theories

This content is being cross-posted to Fireside Science. This post represents a first-pass approximation (and is perhaps a confounded, naive theory in itself). Hope you find it educational at the very least.


Are all theories equal? In an age where creationism is making its way into the school curriculum (under the guise of intelligent design) and forms of denialism and conspiracy theory are becoming mainstream, this is an important question. While classic philosophy of science and logical positivist approaches simply assume that the best theories evolve through the scientific process, living in an era of postmodernism, multiculturalism, and the democratization of information, demands that we think about this in a new way.

Sense-making as Layers of Information
By taking cues from theoretical artificial intelligence and contemporary examples, we can revise the theory of theories. Indeed, we live in interesting times. But what is a theory --  and why do people like to say it's "just a theory" when they disagree with the prevailing model? One popular view of theory is that of "sense-making" [1]: that is, theories allow us to synthesize empirical observations into a mental model that allows us to generalize without becoming overwhelmed by complexity or starting from scratch every time we need to make a predictive statement.

The process of making sense of the world by building theories. Keep this in mind as we discuss the differences between naive and informed theories. COURTESY: Figure 2 in [1b].

Yet sense-making is not the whole story, particularly when theories compete for acceptance [2]. Are all theories equal, or are some theories more rigorous than others? This question is in much the same vein as the critique of "absolute facts" in postmodern theory. To make sense of this, I propose that there are actually two kinds of theory: naive theories and informed theories. Naive theories rely on common sense, and can often do very well as heuristic guides to the world. However, they tend to fall apart when presented with counter-intuitive phenomena. This is where informed theory becomes important. Informed theories are not synonymous with scientific theories -- in fact, some ancient beliefs and folk theories can fall into this category alongside formal scientific theories. We will see the reasons this nominal equivalence (and non-equivalence of more naive theories) as we go through the next few paragraphs.

Naive and informed theories can be distinguished by their degree of "common sense". Normally, common sense is a value judgement. In this case, however, common sense involves a lack of information. Naive theories tend to be intuitive rather than counterintuitive. Naive theories are constructed only from immediate observations and abductive reasoning between these observations. Naive theoretical synthesis can be thought of as a series of "if-and-then" statements. For example, if A and B are observed, and they can be linked through co-occurrence or some other criterion, then they are judged to be plausible outcomes.

The role of abductive theories in organizations. COURTESY: Free Management Library.

Informed theories, on the other hand, utilize deduction and can be divided into working theories (e.g. heuristics) and deep theories that explain, predict, and control. Working theories tend to utilize inductive logic, whereas deep theories tend to rely upon deductive logic. Since deep theories are inductive, they tend to be multi-layered constructs with mechanisms and premises based on implicit assumptions [3]. As a deductive construct, a deep informed theory can lead to inference. Inference gives us a powerful way to predict outcomes that are not so intuitive. The inference of common ancestors in phylogenetic theory allows us to reconstruct common ancestors to extant species that may look nothing like an "average" or a "cross" between these descendants.

A contingency table showing the types and examples of naive and informed theories.



NAIVE


INFORMED

SHALLOW


Cults, Philosophies based on simple principles


Pop-psychology and pop-science

DEEP


Conspiracy theories

Scientific theories

Naive and informed theories can also be distinguished by their degree of complexity. As they are based on uninformed intuition, naive theories are self-evident and self-complete, perhaps too much so. Fundamentalist religious belief and denialist-based political philosophies are based on simple sets of principles and are said by some to be tightly self-referential [4]. This inflexible self-referential capacity these theories rely on common sense over social complexity. Conspiracy theories and denialist tendencies are deeper versions of naive theories [5], but unlike their informed counterparts, do not get by on objective data, and are particularly resistant to updating [6]. By contrast, formal theories are based on abstractions and possess incompleteness-tolerance. This is often by necessity, as we cannot observe every instance of every associated process we would like to understand.

Sometimes the deepest naive theories lead to conspiracies. I have it on the highest authority.

Theory of Ontological Theories?
This leads us to an interesting set of questions. One, are the informed theories that currently exist in many fields of inquiry inevitable outcomes? Second, why are some fields more theoretical than others, and why are theory and data more integrated in some fields but not others? This is a question of historical contingency vs. field-specific structure. Is the state of theory in different areas of science due to historical context or a consequence of the natural laws they purport to make sense of? To answer these three questions, we will not briefly examine five examples from various academic disciplines. Underlying many of these approaches to informed theory is an assumption: theories are a search for ontological truths rather than the product of interactions among privileged experts. This is where informed theories hold an advantage -- they can change gradually with regard to new data and hypotheses while also remaining relevant. This is an ideal in any case, so let us get to the examples:

1) Economics has an interesting relationship to theory. Formal macroeconomic theory involves two schools of thought: freshwater and saltwater. The former group favors the theories of the free-market, while the latter group adhere to Keynesian principles. However, there are also adherents of political economy, who favor models of performativity over formal mathematical models. Since the financial crisis of 2008, there has been a rise of interest in alternative economic theories and associated models, perhaps serving as an example of how theories change and are supplanted over time. And, of course, a common naive theory of economics is based on confounding micro- (or household) and macro- (or national-scale) economics.

2) Physics is though of as the gold standard of scientific theory. For example, "Einstein" is synonymous with "theory" and "genius". The successes of deep, informed theories such as relativity and quantum mechanics is well-known. Aside from explanation and prediction of physics theory are logical consistency and grand unification as an enterprise that can often be separated from experimentation. As the gold standard of scientific theory, physics also provides a theoretical conduit to other disciplines, sometimes without modification. We will discuss this further in point #5.


 This book [7] is a statement on self-anointed "bad" theories. The statement is: although string theory is structurally elegant, it is not functionally elegant like quantum gravity. But does that make quantum gravity a superior theory?

3) In neuroscience and cell biology, theories are as often deemed superfluous and inherently incomplete in lieu of ever more data. This is partially due to our level of understanding relative to the complex nature of these fields. Yet many naive and informed social theories exist, despite the complexity of the social world. So what is the difference? It could be a matter of neuroscientists and cell biologists not being oriented towards theoretical thinking. This may explain why computation neuroscience and systems biology exist as fields quite independent of their biological counterparts.

4) Theoretical constructs associated with evolution by natural selection are the consensus in evolutionary biology. This wasn't always the case, however, as 19th century German embryologists and 18th century adherents to Lamarkian theory had competing ideas of how animal diversity was produced and perpetuated. However, Darwinian notions of evolution by natural selection did the best job at synthesizing previous knowledge about natural history with a formal mechanism for descent with modification. In popular culture, there has always been a resistance to Darwinian evolution. Usually, these divine creation-inspired naive theories are embraced as a contrarian counterbalance to deep, informed theory advocated by scientific authorities. In this case, theories have a social component, as Social Darwinism (a social co-option of Darwinian evolution) was popular in the 19th and early 20th centuries.

5) Because informed theories can explain invariants of the natural world, they often cross academic disciplines. Sometimes these crosses are direct. Evolutionary Psychology is one such example. Evolutionary theory can explain biological evolution, and as we are the products of evolution, the same theory should explain the evolution of the human mind. A simple analogical transfer, but much harder to yield the same results. But sometimes theories cross into domains not because of their suitability for the problem at hand, but because they are mathematically rigorous and/or have great predictive power in their original domain. The "quantum mind" is one such example of this. Is "quantum mind" theory any better or more powerful than a naive theory about how the mind works? It is unclear. However, this co-option suggests that even the most reputable informed theories can be cultural artifacts. A real caveat emptor.

Roger Penrose et.al [8] will tell us about everything, in the spirit of physics and mathematics.

Properties of the Theory of Theories
The inherent dualisms of the theory of theories stems from deeper cognitive divisions between matter-of-fact and abstract thinking. As cultural constructs, matter-of-fact theories are much more amenable to narrative structures that permeate folklore and pseudo-science. This does not mean that abstract theories are "better" or any more "scientific" than matter-of-fact formulations. In fact, abstract theories are more susceptible to cultural blends [9] or symbolic confabulation [10], as these short-cuts aid us in conceptual understanding.

Scientific theories tend to be abstract, informed ones, but scientific theories that are more well-known by the general public have many features of naive theories. Examples of this include Newtonian physics and the Big Bang. There is a certain intuitive satisfaction from these two theories that are not offered by, say, quantum theory or Darwinian evolution [11]. This satisfaction arises from consistency with one's immediate sensory surroundings and/or existing cultural myths. Interestingly, naive (and mythical) versions of quantum theory and Darwinian evolution have arisen alongside the more formal theory. These faux-theories use their informed theory counterparts as a narrative template to explain everything from the spiritual basis of the mind (Chopra's Nonlocality) to social inequalities (Spencer's Social Darwinism).

But what about beauty in theory? Again, this could arguably be a feature of naive theorizing. Whether it is the over-application of parsimony or an over-reliance on elegance and beauty [7], informed theories require a degree of initial convolution before such features can be incorporated into the theory. In other words, these things should not be goals in and of themselves. Rather, deep, informed theories should be robust enough to be improved upon incrementally without having to be being completely replaced [12]. The beauty of parsimony and symmetry should only considered to be a nice side-benefit. There is also a significant role for mental and statistical models in theory-building, but for the sake of relative simplicity I am intentionally leaving this discussion aside for now.

Tides go in, tides go out. When it's God's will, it's a short and neat proposition. When it's more complicated, then it's scientific inquiry. COURTESY: Geekosystem and High Power Rocketry blogs.

In a future post, I will move from the notion of a theory of theories to the need for an analysis of analyses. Much like the theory of theories, a deep reconsideration of analysis is also needed. This has been driven by the scientific replication crisis, the proliferation of data (e.g. infographics) on the internet, and the rise of big data (e.g. very large datasets, once again enabled by the internet). 

NOTES:
[1] Here are a few references on the cognition of sense-making, particularly as it related to theory construction:

a) Klein, G., Moon, B. and Hoffman, R.F.   Making sense of sensemaking I: alternative perspectives. IEEE Intelligent Systems, 21(4), 70–73 (2006).

b) Pirolli, P., & Card, S.   The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. Proceedings of the International Conference on Intelligence Analysis (2005).

[2] Here are some references that will help you understand the "hows" and "whys" of theory competition, with particular relevance to what I am calling deep, informed theories:

a) Steiner, E.   Methodology of Theory-building. Educology research Associates, Sydney (1988).

b) Kuhn, T.   The structure of scientific revolutions. University of Chicago Press (1962).

c) Arbesman, S.   The Half-life of Facts. Current Press (2012).

[3] sometimes, naive theorists will accuse deep, informed theorists of being "stupid" or "irrelevant". This is because the theories generated do not conform to the expectations and understandings of the naive theorist.

Paul Krugman calls one such instance "the myth of the progressive economist": Krugman, P.   Stupidity in Economic Discourse 2. The Conscience of a Liberal blog, April 1 (2014).

[4] Religious fundamentalist and  denialist groups also seem to theorize in a deep naive manner, using a tightly self-referential set of theoretical propositions. In these cases, however, common sense is replaced with a intersubjective (e.g. you have to be part of the group to understand) self-evidence. The associated logical extremes tend to astound people not in the "know".

a) Example from religious fundamentalism: Koerth-Baker, M.   What do Christian fundamentalists have against set theory? BoingBoing, August 7 (2012) AND Simon, S.   Special Report: Taxpayers fund creationism in the classroom. Politico Pro, March 24 (2014).

For a discussion of Nominalism (basic math) vs. Platonism (higher math) in Mathematics, please see: Franklin, J.   The Mathematical World. Aeon Magazine, April 7 (2014).

b) Example from climate change denialism: Cook, J. and Lewandowsky, S.   Recursive Fury: facts and misrepresentations. Skeptical Science blog, March 21 (2013).

[5] for one such example, please see: Roberts, D.   Conservative hostility to science predates climate science. Grist.org, August 12 (2013).

For a more comprehensive background on naive theories (in this case, the development of naive theories of physics among children) please see the following:

a) Reiner, M., Slotta, J.D., Chi, M.T.H., and Resnick, L.B.   Naive Physics Reasoning: a commitment to substance-based conceptions. Cognition and Instruction, 18(1), 1-34 (2000).

b) Vosniadou, S.   On the Nature of Naive Physics. In "Reconsidering Conceptual Change: issues in theory and practice", M. Limon and L. Mason, eds., Pgs. 61-76, Kluwer Press (2002).

For the continued naive popularity of the extramission theory of vision, please see the following:

c) Winer, G. A., Cottrell, J. E., Gregg, V., Fournier, J. S., & Bica, L. A. (2002). Fundamentally misunderstanding visual perception: Adults' beliefs in visual emissions. American Psychologist, 57, 417-424.

[6] sometimes, theories that are denialist in tone are constructed to preserve certain desired outcomes from data that actually suggest otherwise. In other words, a narrative takes precedence over a more objective understanding. Charles Seife calls this a form of "proofiness".

For more, please see: Seife, C. Proofiness: how you're being fooled by numbers. Penguin Books (2011).

[7] Smolin, L.   The Trouble with Physics. Houghton-Mifflin (2006).

[8] Penrose, R., Shimony, A., Cartwright., N., and Hawking, S.   The large, the small, and the human mind. Cambridge University Press (1997).

[9] Fauconnier, G.   Methods and Generalizations. In "Cognitive Linguistics: foundations, scope, and methodology". T. Janssen and G. Redeker, eds, 95-128. Mouton DeGruyter (1999).

[10] Confounds are a psychological concept that identifies when ideas and deep informed theories are confused or otherwise condensed for purposes of superficial understanding or misinterpretation. In the case of creationists, such intentional confounds are often used to generate doubt and confusion of subtle and complex concepts.

a) Role of confabulation in cognition (a theory): Hecht-Nielsen, R.   Confabulation Theory. Scholarpedia, 2(3), 1763 (2007).

b) Example of intentional confounding from anti-evolutionism: Moran, L.A.   A creationist tries to understand genetic load. Sandwalk blog, April 1 (2014).

[11] By "conforming to intuitive satisfaction", I mean that Newtonian physics explains the physics of things we interact with on an everyday basis, and the Big Bang is consistent with the idea of divine creation (or creation from a singular point). This is not to say that these theories were developed because of these features, but perhaps explains their widespread popular appeal.

[12] Wholesale replacement of old deep, informed theories is explained in detail here: Kuhn, T.   Structure of Scientific Revolutions. University of Chicago Press (1962).

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