The Alaskan nutrient cycle

Paul Klaver has an absolutely breathtaking short film revealing the nutrient cycle spawned (rimshot) by the salmon in Alaska. It’s gorgeous and I just don’t understand how he managed to get some of the shots. Watch it in fullscreen mode.

I have a fond (?) memory of growing up in Portland, Oregon and heading out to “Outdoor School” for a few days, where they attempted to inculcate a love of the outdoors in us city kids. We visited right after spawning season which meant the stream that ran through the camp was surrounded with decaying salmon carcasses, resulting in the entire place smelling of old fish. Lovely, no?

via Explore

How a car engine works

How a car engine works by Jacob O’Neal. I’ve recently been having engine trouble with my car about whose workings I know practically nothing. Nothing!

He has a bunch of other stuff worth checking out, too. I like this animated Cheeatah infographic and this one about porn and dopamine (whose scientific data on ‘porn viewing’ is made up, but whose graphical presentation I love).

In the future, all music will be death metal performed by robots

At least, that’s my takeaway from this story:

The robot band Compressorhead is a trio of hulking metallic machines designed to play real instruments. Stickboy, the four-armed, mohawked, headbanging drummer, who even has a mini-me on the hi-hat. The guitarist, Fingers, has 78 hydraulic fingers — wires stream out from the arms to trigger notes along the entire fretboard. Bones is on the bass.

“They have the poses of rock gods, those robots. The bass player’s definitely the most photogenic,” says Shar Try, who was up on the stage snapping shots of Compressorhead as they banged their heads and swished their hips.

The music video is also excellent. Between this and holographic 3D anime idols, what chance do us meatcreatures have?

Prosthetics are not just for mammals anymore

This article about cyborg plants is full of all sorts of potential scifi goodness.

Cyborg Plant consists of a simple avocado plant (Persea americana) which is nurtured by an attached robotic prosthesis. The prosthesis measures the avocado’s drought stress — indicated by “the position of the leaves and the electrical potential within the trunk” — and irrigates the plant as required. This attachment, which is essentially a spacesuit for plants, enables the avocado to live indoors without human attention for much longer periods of time than would otherwise be possible (the interior of a built space being nearly as hostile for plants as land is for fish).

Or how about:

This might sound like a far-fetched idea, but, as Next Nature notes, a Filipino scientist produced a bio-luminescent Christmas tree by covering it in bio-luminescent bacteria harvested from local squid in 2007, and other researchers have proposed applications for (truly) bio-luminescent plants ranging from lighting highways (which, assuming that the bioluminescent trees would at some point begin to naturalize, might produce the most strikingly beautiful displays of exotic plant invasion imaginable) to crops which glow when they need water. Mushrooms make forests glow; why shouldn’t trees make cities glow?

It also talks about networking plants. As we continue to mechanize food production, cyborg plants are going to become part of our understanding of ‘nature’. What surprises me more, however, is how little this appears in scifi. The concept seems so obvious once you start thinking about it; mammals are made cyborg all the time. Why not plants as well? It often seems that our networked future is entirely too anthro- and mammalian-centric.

Hops flavors

I am from the PNW so of course I love hops. Here are some popular hops flavors:

Centennial: This member of the “American C’s” (along with Chinook, and Cascade) has the most pronounced flowers and citrus. A medium aroma with mid-to-high bittering value makes it a great all-purpose hop. The fantastic grapefruit and subtle pine notes of Bell’s Two Hearted Ale is an excellent example of this hop. Big Hunt always has a fresh keg of this popular beer on tap for you to taste.

Hallertau: Named for the region in Germany it is grown in, it is a staple of many German beers. This noble hop imparts a mild taste with huge aromas of spice and fruit. These usually create the subtle hop flavors of your favorite Hefeweizens and Oktoberfests. The newly-opened Biergarten Haus will have all of your Hallertau needs.

Saaz: This classic hop is known for its spicy and slightly peppery notes. Low alpha acids make this one used primarily for flavoring. When you taste Pilsner Urquell, you’re tasting the Saaz. You can often find this on tap at The Reef.

Challenger: A newcomer to the British beer movement, this flavoring agent starts slightly spicy, but remains fruity throughout: think tart fruits without the bitterness. Coniston’s Bluebird Bitter is a delicious, low alcohol (3.6% ABV) beer exemplifying the new wave of British brewing. CommonWealth usually carries this in bottles.

Warrior: This hop imparts only subtle flavors but is important in American craft beers. It has a large role in some of the bigger beers we’ve come to love due to their huge acid profile (upwards of three times the amount of some varietals). Dogfish 60, 90, and 120 minute beers are great examples of this and can be found anywhere from the revered ChurchKey to the rockin’ DC9.

Fuggles: While a quintessential British ingredient, Fuggles are also used in Belgian ales for their light flavors. Slightly woody and almost earthy tones make it wonderfully mild and multidimensional. Westmalle Triple predominantly uses Fuggles and is available at Brassiere Beck and Belga Café.

Here are a lot of other hops flavors, and of course Wikipedia has more.

[photo from]

Gravity is just entropy; an eternal rot between two objects

Seeing how the entropic theory of gravity by Verlinde is popping up all over the place, I thought I’d write up a summary of what it is so that I don’t forget. Fortunately, I remembered an excellent explanation has already been written elsewhere! So another job well done that I don’t have to do well. Here’s an example from a toy model:

Our toy universe consists of six ‘ray paths’ that form the edges of a tetrahedron. Each ray path can be in two distinct states: occupied or empty. This accounts for a total of 26 = 64 states. Three ray paths meet at each vertex. If all three are empty, the vertex represents ‘a hole’ that gets filled with at least one particle. If any of the three ray paths is occupied, the vertex is ‘full’ and can not contain any particle.

Throw the die, note down the number of spots, and check the corresponding ray path in the tetrahedron:

A) If the ray path is occupied, make it empty, unless doing so would create more than two vertices containing particles.

B) If the ray path is empty, occupy it, unless this would result in zero particle vertices.

Again throw the die and repeat ad infinitum. This simple process creates a sequence of configurations, each of which contains two particles occupying either two different vertices (two particles in two distinct holes), or the same vertex (two particles in the same hole).

In this model there is no explicit force acting between the two particles. So one might naively postulate that both particles will jump randomly from vertex to vertex, and will be as often at the same vertex as at different vertices. This is not the case. The reason is simply that there are 16 states with one hole, against only 6 states with two holes (by allowing only for one and two-hole configurations, 42 of the 64 total number of microstates are forbidden).

Another way of looking at this is that for a given vertex to contain a particle, the three ray paths meeting at that vertex need to be empty. This reduces the entropy (the number of bits needed to describe the tetrahedron universe) by three. For two given vertices to contain a particle, both vertices need to have three empty ray paths. One would therefore expect an entropy reduction of 3 + 3 = 6 bits. However, both vertices necessarily have one ray path in common, and an entropy reduction of 6 – 1 = 5 bits results. However, if both particles are accomodated at the same vertex, both particles dictate the same three ray paths to be empty. In other words: there is 3 common ray paths and an entropy reduction of 6 – 3 = 3 bits results. So, the two particles being together at the same vertex creates a smaller entropy reduction compared to the case of the two particles being seperate. In other words, two particles together at one vertex corresponds to significantly more states than two particles at separate vertices. This is all that is needed for a tendency for both particles to stick together.

That gives the gist of this whole entropic universe idea, and it’s pretty clever. Read the whole post for a more detailed explanation beyond the toy model, along with some excellent explanatory animations.

Why hierarchy matters

During the dot-com boom, it was common to hear about companies with “flat hierarchies” to more flexibly meet new challenges. No longer was there one long chain of command: now most everyone was equal to everyone else. I don’t know whether that concept still exists, but my recent reading into the science of social status has led me to reconsider my previously full-throated support of the concept. Here are some basic reasons why hierarchies are good:

Human beings are social animals, a fact that is central to how we as a species see the world. And like other social animals, whether wolves or chickens or chimpanzees, we sort ourselves into rankings. These rankings aren’t static, they can change over time, but they impose order on social interaction: In the wild, they create a framework for dividing up vital tasks among a group, and because they clearly codify differences in power or strength or ability, they prevent every interaction from disintegrating into an outright fight over mates or resources — someone’s rank tells you how likely she is to beat you in a fight, and you’re less likely to bother her if you already know.

…For one thing, it turns out that people are ruthlessly clear-eyed judges of their own place in the social hierarchy. This is notable because they tend to be poor judges of just about everything else about themselves. Study after study has shown that people are incorrigible self-inflaters, wildly overestimating their own intelligence, sexual attractiveness, driving skills, income rank, and the like. But not social status, that they turn out to be coldly impartial about.

For example, a team of social psychologists led by Cameron Anderson of the University of California, Berkeley ran a study in which strangers were put into groups that met once a week, and were tasked with solving various collaborative problems. After each meeting, the participants rated their own status in the group and that of their teammates. By and large, people’s self-evaluations matched up with how their peers rated them.

…In a 2003 study by Larissa Tiedens and Alison Fragale, both then at Stanford University, subjects who displayed submissive body language were found to feel more comfortable around others who displayed dominant body language than around those who also displayed submissive body language — and to like those with more dominant posture better, as well. People, it seems, prefer having their evaluation of social hierarchy confirmed, even when they see themselves at the bottom of it.

Perhaps the strongest, if the most surprising, evidence for the importance of clearly delineated social hierarchies is work that suggests that more inequality can make for better teams…Galinsky and his fellow researchers found that NBA teams with greater pay disparities not only won more, but ranked higher in categories like assists and rebounding, suggesting a higher degree of cooperation. The clearer the status imbalance, the researchers argued, the less question there is about where one stands.

Now clearly inequality per se is not a good thing. But there are situations where inequality between individuals is good. We are intensely social animals and function better as a group when we have a status; it’s better to have a low-entropy social pattern than a high-entropy one. Social status even affects us biologically; it changes the number of dopamine receptors we have in the basal ganglia which (should) affect how we value things and how pleasurable activities are. Inequality, it seems, is in our very brains.

Social status, novelty-seeking, and dopamine

Dopamine sure seems to do a lot of things these days, doesn’t it? It’s most commonly thought to be the mechanism for prediction error which is used for reward-based learning, but it is also linked to sociability, pain, and a ton of other things.

One of its mechanisms relates to social dominance. Eight years ago, Morgan et al. published a paper concerning social dominance in monkeys. They wanted to show how there is a profound environmental influence on dopamine function, so they separated monkeys into housing blocks of four apiece. Whereas before there was little difference in dopamine (D2) levels between monkeys, after three months of living together the monkeys that had become dominant showed a more than 20% increase in dopamine receptor density, with the most submissive showing no change. Unrelated to our point, but still interesting, they also showed that the submissive monkeys were much more inclined to self-administer cocaine; the dominant monkeys were much less likely to do so.

Dopamine receptor density is therefore an environmental and cultural phenomenon – at least in monkeys. What about people? It turns out we’re pretty much the same way. If you do the same PET scan on people that you did on monkeys, their dopamine level (D2/3 in the striatum) correlates (r^2 ~ 0.5) with a measure of human social status. So we’re not that different, after all. Just remember it’s not dopamine that drives dominance, but dominance that drives dopamine. Why? Who knows?

Dopamine levels in the same area are related to other aspects of behavior besides just dominance. If you perform the same measure of dopamine receptor availability but compare it to sensation-seeking, or novelty seeking, you get an altogether different type of curve. Here we instead see an inverted U-shaped curve. Using modeling, they suggest that those with the greatest need to seek sensational activities have both low receptor availability and high dopamine occupancy. I suppose the low-sensation seekers have low receptor availability and low dopamine occupancy (ie, few binding sites along with a lower volume of dopamine to bind).

Are these two phenomena related? They both look at the receptor availability of a certain population of dopamine receptors (D2/3). But just because the dopamine receptors are the same and in roughly the same place doesn’t mean the connectivity is the same. Are these all the same circuit? Does dominance affect novelty-seeking? Someone really needs to find an animal model to start testing these propositions.

References
Gjedde, et al., 2010. Inverted-U-shaped correlation between dopamine receptor availability in striatum and sensation seeking. Link.

Martinez, et al. 2010. Dopamine type 2/3 receptor availability in the striatum and social status in human volunteers. DOI

Morgan, et al. 2002. Social dominance in monkeys: dopamine D2 receptors and cocaine self-administration. Link.

[monkey photo from]

Superorganisms = organism

People like to talk about ants as ‘superorganisms’. Of course, we’re all kind of superorganisms, built out of a structure of captured cells and using home-grown bacteria to function. But when we talk about ants, wasps, and termites, we mean something else. Each insect on its own seems to be an independent organism – though they can’t all survive away from the colony – but in reality, the colony is the organism.

In PNAS, Hou et al. apply the metabolic scaling law to eusocial insect colonies. Individual organisms have a metabolic rate that scales as the 3/4 power of body mass. Along with this are laws scaling reproductive organ mass, total biomass, and organism (colony) growth with metabolism. Individual ants do not follow this law: worker ants have almost no reproductive organs while the queen has tons of ’em.

The figure above shows the body mass vs. metabolic rate for some (non-ant/wasp/termite) insects and for various colonies as a whole. And the curves are the same! If you look at the other predictions, they all turn up exactly on the curve, too. So it is only when you consider the colony as a whole that eusocial insect act as a proper organism. Iain Couzin once mentioned to me that ants in a colony act analogously to neurons in a brain, though I can’t for the life of me remember how that was. But see, the individual ant is just like a lonely neuron: meaningless.

The cycle of the city of ants

E.O. Wilson has a story in the New Yorker! About ants! It’s not great as literature, per se, but it is quite interesting. Imagine ant fanfic: that’s basically what this is. Like a preening middle schooler, he tries to show off all the fun little things he knows about how ants live. That’s not meant as too much of a knock, because maybe that’s the point: the story’s not about immersing yourself in the characters so much as about conveying knowledge about the characters. Read it and learn.

[picture from]

Ecology of the canine subway

Here’s an interesting Financial Times article on the ecology of stray dogs in Moscow:

The dogs divide into four types, he says, which are determined by their character, how they forage for food, their level of socialisation to people and the ecological niche they inhabit.

Those that remain most comfortable with people Poyarkov calls “guard dogs”. Their territories tend to be garages, warehouses, hospitals and other fenced-in institutions, and they develop ties to the security guards from whom they receive food and whom they regard as masters. I’ve seen them in my neighbourhood near the front gate to the Central Clinical Hospital for Civil Aviation. When I pass on the other side with my dog they cross the street towards us, barking loudly.

“The second stage of becoming wild is where the dog is socialised to people in general, but not personally,” says Poyarkov. “These are the beggars and they are excellent psychologists.” He gives as an example a dog that appears to be dozing as throngs of people walk past, but who rears his head when an easy target comes into view: “The dog will come to a little old lady, start smiling and wagging his tail, and sure enough, he’ll get food.” These dogs not only smell who is carrying something tasty, but sense who will stop and feed them.

The beggars live in relatively small packs and are subordinate to leaders. If a dog is intelligent but occupies a low rank and does not get enough to eat, he will separate from the pack frequently to look for food. If he sees other dogs begging, he will watch and learn.

The third group comprises dogs that are somewhat socialised to people, but whose social interaction is directed almost exclusively towards other strays. Their main strategy for acquiring food is gathering scraps from the streets and the many open rubbish bins. During the Soviet period, the pickings were slim, which limited their population (as did a government policy of catching and killing them). But as Russia began to prosper in the post-Soviet years, official efforts to cull them fell away and, at the same time, many more choice offerings appeared in the bins. The strays flourished.

The last of Poyarkov’s groups are the wild dogs. “There are dogs living in the city that are not socialised to people. They know people, but view them as dangerous. Their range is extremely broad, and they are ­predators. They catch mice, rats and the occasional cat. They live in the city, but as a rule near industrial complexes, or in wooded parks. They are nocturnal and walk about when there are fewer people on the streets.”

It’s an interesting story of what happens when a domesticated animal is, in a sense, redomesticated, or undomesticated. These dogs have also learned how to use the subway system to get from place to place. Surely that is a novel behavior you wouldn’t expect from animal psychology? What’s interesting is that not all the dogs have learned how to do this but, presumably, are able to pass on the ability to other dogs who follow them. Do we have a little animal culture here?

Thinking about thinking leaves me thinking about nothing

Edge.org’s question of the year this year was a little boring, sadly. It is normally a chance to hear interesting people give interesting answers to interesting questions. This year is about the Internet. Boo, navel-gazing. As always, there’s still some interesting answers. Here’s one that I particularly liked by Steven Quartz:

Consider, for example, our tendency to reduce human thought to a few distinct processes. We’ve been doing this for a long time: Plato divided the mind into three parts, as did Freud. Today, many psychologists divide the mind into two (as Plato observed, you need at least two parts to account for mental conflict, as in that between reason and emotion). These dual-systems views distinguish between automatic and unconscious intuitive processes and slower and deliberative cognitive ones. This is appealing, but it suffers from considerable anomalies. Deliberative, reflective cognition has long been the normative standard for complex decision-making — the subject of decision theory and microeconomics. Recent evidence, however, suggests that unconscious processes may actually be better at solving complex problems.

Based on a misunderstanding of its capacity, our attention to normative deliberative decision-making probably contributed to a lot of bad decision-making. As attention turns increasingly to these unconscious, automatic processes, it is unlikely that they can be pigeon-holed into a dual-systems view. Theoretical neuroscience offers an alternative model with 3 distinct systems, a Pavlovian, a Habit, and a Goal-Directed system, each capable of behavioral control. Arguably, this provides a better understanding of human decision-making — the habit system may guide us to our daily Starbucks fix (even if we no longer like it), while the Pavlovian system may cause us to choose a pastry once there despite our goal of losing weight. But this too likely severely under-estimates the number of systems that constitute thought. If a confederacy of systems constitute thought, is their number closer to 4 or 400? I don’t think we have much basis today for answering one way or another.

Consider also the tendency to treat thought as a logic system. The canonical model of cognitive science views thought as a process involving mental representations and rules for manipulating those representations (a language of thought). These rules are typically thought of as a logic, which allows various inferences to be made and allows thought to be systematic (i.e., rational).

I tend to think that we have a further problem. Since we have ‘consciousness’ and ‘free will’, people have this feeling that we should be able to remember everything we do, and have reasons for doing it. Of course, neuroscientists know that every memory is a poor reconstruction of something that happened in the past; and further, we know that we perform actions all the time that are outside of our conscious perception, and sometimes even inaccessible to our conscious mind. Think of all those times someone mumbles a few words, then refuses to admit that they said anything at all when questioned. How weird is it that a perfectly healthy person can say something, and not remember it at all?

What it comes down to is the fact that most of our intuitions about how we work and reason and live are wrong, and even though we have some evidence of how different processing streams work in the brain, we’re a long, long way off from understanding how we think.

[picture from]

Why old people shrink

Here’s why I’ll end up 5’2″ by the time I die:

Degeneration with age interferes with the normal process of regaining height, and by 60 a loss of two inches is not uncommon.

There are 23 jellylike intervertebral disks that act as shock absorbers between the spinal vertebrae, Dr. Härtl said. The disks, which are as much as 88 percent water, are compressed during the day as standing, moving and vibration squeeze out fluid. Then at night, when the body is flat and at rest, the disks reabsorb fluid like sponges.

As we get older, degenerative processes interfere with reabsorption, Dr. Härtl said. Blood supply and circulation diminish, and the disk material stiffens.

[picture from]

A horror movie for neuroscience

I have vague recollections of seeing a video where someone’s skull was wide open while scientists prodded it with some instrument of torture. Poke here, the person moves their mouth uncontrollably; poke there and they see everything in red. I was blown away; it was far and away one of the coolest things I’d ever seen, and is almost certainly one of the main reasons I got interested in neuroscience. I saw it in fourth or fifth grade, so I had recently been worrying that it was something of a fake. Nope! I just found out that it was Dr. Wilder Penfield who performed these experiments. He would operate on people with severe epilepsy and attempt to destroy the cells that caused the disease. Before he did that, however, he’d stimulate their brains with an electrode and ask them what they felt. Classic neuroscience right there, folks.

So watch these poor saps get their brains prodded! It is one of the coolest things you’ll ever watch.