Evolution

A week of links

Links this week:

  1. Side effect warnings increase sales by building trust. Similar effects for disclosing conflicts of interest (ungated pdf).
  2. Absorbing information on paper versus kindle. Even without digital search, I often find it easier to find favourite passages in the physical form.
  3. Humans aren’t the only ones fighting wars.
  4. I pointed out a couple of weeks ago that Geoffrey Miller had joined forces with Tucker Max to give sex and dating advice. Their reading list is very good, even if you’re not after any advice. Their suggestions as to which movies might provide insight is quite amusing.
  5. Twin research.

Shaping the brain and humans as complex systems

I linked to this interview with Robert Sapolsky a couple of weeks ago, but after glancing through it again, I felt it worth highlighting two paragraphs (both for your interest and so I can find them again). First, on the evolutionary purpose of the teenage brain:

What I’ve been thinking might actually be going on is that adolescence is something unavoidable that emerges not because it’s so cool and adaptive, but because the adaptive thing is wait a long, long time before you have fully wired up your frontal cortex. Why might that be the case? Alright, so we’re born with our genome, the combination of your mother and father’s genes, that wind up in that first fertilized egg and that’s it. That’s your genetic legacy. Every cell in your body is destined to have that exact same genome. That turns out not to be true in all sorts of interesting ways, but what that also means is that when you’re thinking about what genes have to do with the brain behavior, by definition critically, if the frontal cortex is the last part of the brain to develop it’s the part of the brain least shaped by genes, and most sculpted by the environment and experience. And I think basically the only way you can have a species that is as complex and socially resilient and socially context dependent and all those amazing things we do, the only way you can pull that off is to have a frontal cortex whose development just bears the imprint of everything you experienced along the way—in effect, that’s been freed from whatever extent the genes are deterministic, which is not very. I think ironically what the evolution of the frontal cortex has been about is genetic evolution to free it as much as possible from the straight jacket of genes.

Second, on reductionism in neurobiology:

[R]eductionism doesn’t actually tell you a whole lot about how this stuff works. I mean reductionism is perfect for like telling you why your clock is broken. What you do is you break it down to its component parts. You find the part that’s got a tooth missing from the gear. I guess there’s not a clock on earth that works this way anymore, but your Renaissance clock. You fix the missing tooth, you put it back, you add the pieces back together and it works. The way to understand a complicated system is to understand its component parts. The way in which that steps away from the ideology is the component parts of the genes and the nerve transmitters and the hormones and the early experience. Okay, so that’s a more sophisticated version of reductionism. You got to be reductive about lots of different domains. But nonetheless, even that more multidisciplinary version of reductionism isn’t going to work because that’s not how complex systems work and humans are a complex system. You got these emergent non-linear chaotic properties. What’s that another way of saying? If you knew every individual’s genome and exactly which gene was active at which point, are you going to be able to predict who’s going to do what next? Absolutely not. If you added in knowing the levels of every hormone in their body at that point, if you added in… it doesn’t work that way. The reductionism breaks down because the reductionism breaks down in the same way that like a cloud that isn’t producing enough rain during a drought or something, the solution isn’t to study half the cloud and then get a research grant to study a quarter of the cloud and smaller, smaller pieces and finally understand the reductive basis of the non-rain and add it up together. That’s not how clouds work when they don’t rain. Humans are more like clouds than they are like clocks. We’re not reductive in that way, which is the case for any complex system.

And if you haven’t read the full interview, do it.

A week of links

Links this week:

  1. Academic urban legends spreading through sloppy citation. In PhD land, I have constantly found myself following citation chains that don’t lead to what they claim.
  2. Some progress in the replication wars. I’ll post about some of the specific examples over coming months.
  3. The evolutionary emergence of property rights (ungated working paper). HT: Ben Southwood
  4. Attribute substitution in charities – the evaluability bias. HT: Alex Gyani
  5. Peter Turchin reviews Richard Wrangham’s Catching Fire: How Cooking Made Us Human.
  6. Arnold Kling on Nicholas Wade. Comments and pointer from here.
  7. Polygenic modelling in cattle breeding. Humans next.
  8. An interesting debate on Cato Unbound this month – the libertarian case for a basic income guarantee.

A week of links

Links this week:

  1. Some gold from Robert Sapolsky – what is going on in teenage brains? Plus a bonus interview.
  2. The latest issue of Nautilus (the source of the Sapolsky material) contains a lot of other good material – fruit and vegetables trying to kill you and chaos in the brain among them. I recommend scanning the table of contents.
  3. The changing dynamics of marriage inequality.
  4. Andrea Castillo with an introduction to the neoreaction (including some “homebrewed evolutionists”).
  5. Geoffrey Miller has teamed up with Tucker Max and is offering dating advice informed by evolution.

Our visual system predicts the future

I am reading John Coates’s thus far excellent The Hour Between Dog and Wolf: How Risk Taking Transforms Us, Body and Mind. There are many highlights and interesting pieces, the below being one of them.

First, we do not see in real-time:

When light hits out retina, the photons must be translated into a chemical signal, and then into an electrical signal that can be carried along nerve fibers. The electrical signal must then travel to the very back of the brain, to an area called the visual cortex, and then project forward again, along two separate pathways, one processing the identity of the objects we see, the “what” stream, as some researchers call it, and the other processing the location and motion of the objects, the “where” stream. These streams must then combine to form a unified image, and only then does this stream emerge into conscious awareness. The whole process is a surprisingly slow one, taking … up to one tenth of a second. Such a delay, though brief, leaves us constantly one step behind events.

So how does our body deal with this problem? How could you catch a ball or dodge a projectile if your vision is behind time?

[T]he brains visual circuits have devised an ingenious way of helping us. The brain anticipates the actual location of the object, and moves the visual image we end up seeing to this hypothetical new location. In other words, your visual system fast forwards what you see.

Very cool concept, but how would you show this?

Neuroscientists … have recorded the visual fast-forwarding by means of an experiment investigating what is called the “flash-lag effect.” In this experiment a person is shown an object, say a blue circle, with another circle inside it, a yellow one. The small yellow circle flashes on and off, so what you see is a blue circle with a yellow circle blinking inside it. Then the blue circle with the yellow one inside starts moving around your computer screen. What you should see is a moving blue circle with a blinking yellow one inside it. But you do not. Instead you see a blue circle moving around the screen with a blinking yellow circle trailing about a quarter of an inch behind it. What is going on is this: while the blue circle is moving, your brain advances the image to its anticipated actual location, given the one-tenth-of-a-second time lag between viewing it and being aware of it. But the yellow circle, blinking on and off, cannot be anticipated, so it is not advanced. It thus appears to be left behind by the fast-forwarded blue circle.

A quick scan of the Wikipedia page on the flash-lag effect suggests there are a few competing explanations, but it’s an interesting idea all the same. It would explain that feeling of disbelief when a batter swings at and misses a ball that moves unexpectedly in the air. They would have seen it in precisely the place they swung.

The below video provides a visual illustration.

A week of links

Links this week:

  1. Why idiots succeed.
  2. Rory Sutherland on social norms.
  3. Economics incentives versus nudge (pdf). Don’t forget that basic economic mechanisms can work.
  4. We’re related to our friends.
  5. Are there really trillion dollar bills on the sidewalk?
  6. A bash of the Myers-Briggs test. Personally, I’m a fan of the big five plus g. On g, the heritability of chimp IQ.
  7. Talent versus practice. Talent wins this one.
  8. Throwing away money on brain science.

A week of links

Links this week (or closer to a month):

  1. It’s reigning men. How our convict past explains our glass ceiling.
  2. Rory Sutherland on measurebation.
  3. The genetics of investment biases (ungated version). HT: Tyler Cowen.  Basically another confirmation of the three laws of behaviour genetics.
  4. Rats regret bad decisions.
  5. Matt Ridley on fat.
  6. Pulling apart the research on the destructiveness of female hurricanes – Paul Frijters and Andrew Gelman.
  7. Sendhil Mullainathan on the limits to big data.

Genes and socioeconomic aggregates

In April, a Conference on Genetics and Behaviour was held by the Human Capital and Economic Opportunity Global Working Group at the University of Chicago.

The videos for the conference are now up, so as I watch through them, I’ll post links and some brief thoughts. The first session, with videos linked below, was on Genes and Socioeconomic Aggregates. The video and audio are average at times, and you might want to get the slides (links provided where available) as they are hard to read in the video at times. However, there are some good bits in all of the presentations.

Gregory Cochran: Genetics and Society (slides)

Cochran laid out some ideas that should be in the minds of economists, although he does not focus much attention on selling the ideas. Unfortunately, the questions at the end got derailed by epigenetics (my views approximate Cochran’s). One interesting argument by Cochran is that human environments tend be variable, as, in a Malthusian world, good times (when people breed like mad) tend to be followed by bad (too many people) which tend to be followed by good (people died in the bad). As a result, epigenetic transmission based on the current environment may be a poor strategy.

When Cochran posted this video on his blog, some interesting discussion followed in the comments – they are worth checking out.

Enrico Spolaore: Ancestry and the Diffusion of Economic Development: Facts and Questions (slides)

Spolaore touches on his work concerning genetic distance and the diffusion of development (I have posted about it here, here and here). He is extending this work to look at the diffusion of fertility reduction from France (where the demographic transition first occurred), and is getting similar results.

Steven Durlauf: Two Remarks on the Inference of “Macro” Genetic Effects (slides)

I did not get much from Durlauf’s presentation, although some of the questions were interesting. Steve Hsu deflates the “it’s all too hard” message when he points out that animal breeding is now using genetic data.

Henry Harpending: Some Quantitative Genetics Approaches

Harpending discusses his work on how assortative mating can mimic strong selection. I sense this presentation might be difficult to follow if you aren’t familiar with his work (a link to that is here). Not much value in the question session, which gets derailed by issues concerning scaling when estimating heritability.

Aldo Rustichini: Determinants of Inequality and Intergenerational Mobility (slides)

A tough presentation to follow – you need to use the slides to have a chance of getting across it – and not recommended for those not mathematically inclined. The highlight is Greg Cochran trying not to jump out of his chair between the 7 and 8 minute mark due to some comments about heritability. Cochran also deflates the idea that there is a high level of false paternity in humans – for more on that, check out this post by Razib Khan.

Is poverty genetic?

Quamrul Ashraf has pointed me to an episode of Through the Wormhole with Morgan Freeman titled “Is Poverty Genetic?”

The official version of the video is below (payment required?), although it is blocked in Australia (Australians lead the world in digital piracy, despite being willing to pay for content. This sort of thing is why). Below that is another version I managed to find on YouTube – so go for it.

The good: The coverage of Ashraf’s work with Oded Galor on genetic diversity and economic development (my posts on their work are here), experiments on capuchin monkeys’ sense of fairness, and our sense of shame.

The so-so: The opening piece on Eric Turkheimer’s research on the heritability of IQ was OK, but when tied into the next section on differences in brain development, it goes a bit awry. A few concepts that would have helped – IQ heritability increases with age, differences that emerge after birth can be genetic, and genes shape their environment.

The not so good: Kin selection being spun as sacrifice for the benefit of the species. The overall conclusion.

Not sure: The econophysics of poverty.