The Amateur Mad Scientist: Quarter-Ton Tomato

You may have noticed that front-loading washing machines are rapidly eclipsing the top-loading agitator variety that was once popular. This is a good thing for two reasons: front-loaders save on water, which is obviously good in these environmentally-conscious times. And two: they allow me to perform all manner of extremely unwise experiments. For you see, my 1985 vintage GE washer, original to my 1985 domicile, finally died. And now, I am equipped with a snazzy new front-loader. It uses a high-speed spin cycle to centrifuge the water out of clothes. It’s really quite hypnotic to watch. And, when it’s spinning at full speed, a little scary. For you see, according to the manual, the drum’s maximum spin speed is 1200 RPM. Yes. 1200 RPM. That’s twenty revolutions per second. Holy shit!

Before I go on to the really unwise part of the experiment, let’s do some quick math. Now, I measured a drum diameter of about two feet, which comes out to a radius of, let’s say, one foot. According to other sources, the maximum spin speed of a washer like mine is 900 RPM. To be on the safe side, let’s assume that, at maximum speed, the drum spins at somewhere between 600 RPM (10 RPS) and 1200 RPM (20 RPS). Centripetal acceleration is given by radius times the square of the angular velocity. Therefore, at 600 RPM, the outer edge of the drum is experiencing a centripetal acceleration of 1.203 kilometers per second per second, or about 122 gees. At 1200 RPM, the acceleration is a terrifying 490 gees. That is to say, under the most conservative estimate, my washing machine generates a hundred and twenty times earth’s surface gravity. I say again: holy shit. And I’d like to add: holy fuck!

Now, the first time I did this calculation, I started having all kinds of unwise ideas. I started wondering if I had any sufficiently compact friends I could coerce into climbing into the drum. I started scouring my neighborhood for particularly troublesome squirrels. Ultimately, I decided to test a tomato. I happened to have some tomatoes that were just moldy enough that I was afraid to eat them. Here’s our test subject:


Now, regular readers will be fully aware of the fact that I am insane. But my insanity has its limits. You see, as fun as it is to centrifuge fruits to death in a washing machine, I realized that at some point in the future I might like to do some laundry in my washing machine. That didn’t stop me from proceeding, by any means, but I decided that a watertight container was probably necessary.

I stuck the container in the drum, closed everything up, set the washer for a “Spin and Drain” cycle, and got ready. Our brave test subject had no comment, but he looked about as terrified as a tomato in a plastic bowl can.

I was a little nervous as the washer spun up to full speed. But I discovered that even my cheap-ass camera could take unblurred photos of the drum, which allowed me to confirm that the bowl hadn’t exploded everywhere and voided my warranty.

Notice the way the duct tape curves down towards the center of the lid. It wasn’t doing that when I first put it in. I guess that’s the effect of approximately 100-300 gees (remember, the force is less on the lid because the lid is closer to the drum’s center). But the container valiantly took the abuse. The same cannot be said for the tomato.

HOLY SHIT! Imagine that was your spleen or your brain or something. I’m glad I didn’t talk any of my cousins into that drum… Because 490 gees turns a 1-pound tomato into a 500-pound tomato (quarter-ton tomato! Get it! …sorry…) If I’d talked my 120-pound cousin into taking its place, that’d be 60,000 freakin’ pounds. But then, I might seriously void my warranty, so I’m glad I didn’t.

The Amateur Mad Scientist – Episode 2

Haha! And you thought this was gonna be another of those Life of an English Major “series” that I lose interest in two weeks later and forget about. But no! There are now at least two episodes of the Amateur Mad Scientist. In the last episode, I put five pillbugs in a nasty-ass recycled deli container and tried to force them to breed. This one’s not quite that mean, if for no other reason than no macroscopic organisms are involved. I present to you: the Super-Ghetto Biosphere.

For an enclosure, I decided to use a little glass jar that totally didn’t used to have tartar sauce in it.

To that, I added sand enriched with organic material. Sand I totally didn’t steal from my hermit crabs. And then the water. Nasty-ass water. Water, like, swimming with little critters. Paramecia ‘n’ shit, yo. Sorry…that joke was fucking stupid. But anyway: the water is also fortified with organic matter (not floating aquarium-snail poop, I promise).

And now the keystone of the entire ecosystem: a cutting of the infamously tenacious water wisteria plant (Hygrophilia difformis). Because if experience has taught me anything, there’s nothing plants like more than being sealed in jars.

So that’s the setup as of 6-22-2011. I’ll post pictures over the weeks to come detailing my resounding success (Ha!). Watch this space!

Update: As pf 7-2-2011, the plant is still (somehow) alive, and has deigned to throw down at least one root. Also, algae.

Update: As of 7-7-2011, the plant is still, in spite of my worst efforts, alive, and the algae has proliferated and started consuming all the detritus I was too damn lazy to screen out.

The Size of the Sun

Sun and Earth

In the above image, the tiny red rectangle towards the middle of the Sun represents (approximately) the surface area of the Earth. Meaning that the sunspot above it is almost big enough (approximately; some perspective effects come into play) to encompass the entire surface of the Earth. Odds are that everything you have ever done or seen has taken place in an area smaller than a sunspot. The universe is odd.

(Image courtesy of NASA’s remarkable Solar Dynamics Observatory)

The Amateur Mad Scientist (Part 1)


Oh hi. Didn’t see you there.

Sorry, I haven’t done this for a while. The ol’ sense of humor is kinda rusty. But, it seems that I’m back, and even geekier than ever.

The amateurish picture you see above is of two pillbugs (probably Oniscus spp. Edit: Probably Armadillidum nasatum), the coolest terrestrial crustaceans in existence. Their main functions in the forest ecosystem are consuming detritus and excreting soil (poop). Also, entertaining lonely twenty-somethings on Friday nights. They’re incredibly cute, completely harmless, easy to keep as pets, and if you don’t mind waiting a while, they make great compost. Ha! who needs cats?

But as well as being a nerd, I’m also a man. A manly man. With at least seventeen confirmed chest hairs. So, I like my coffee hot, my whiskey lukewarm, my women buxom (or plain, I’m not picky), and my bugs HUGE. And since the gigantic (we’re talking the size of my nose, and my nose is big. GRRRR!) pill millipede (see below) is native to the tropics and doesn’t do well in captivity, I thought “I’m a nerd. I’ve got spare time. Why not make my own?”

Glomeris marginata

So begins my new series “The Amateur Mad Scientist.” Experiment 1: the evolution through artificial selection of gigantic f**cking pillbugs! I started out with five of the largest Oniscus Armadillidum adults I could pull out of my dad’s compost heap (I’m almost afraid to look in my compost heap after the maggot episode of a few months ago…). Five is a nice number, and easy to keep track of, and most importantly, gives me roughly a 96.8% chance of having at least one male and one female. When they reproduce and the hatchlings grow to full size, I’ll pick the biggest ones and leave them in the experimental colony (the losers I’ll transfer to my aquarium-sized pillbug-millipede colony, after calling them sissies and stealing their lunch money, of course). I’m honestly not entirely sure how long a pillbug generation is, but I imagine (meaning: I hope) I’ll see the effects before too long. Watch this space!

Other Business: I’m going to try to get back into the habit of posting stuff. I’ve got a couple of NetLogo simulations worth talking about, and some other things. So yeah. Watch this space.

EDIT: So two of the pillbugs died and I got to thinking “How would I feel if someone put me in a Tupperware container and tried to breed me into a race of giants?” And I decided that I would, in response, crawl out of the container while my captor was asleep, shit in his eye, and crawl into his ear and eat his brain. The surviving pillbugs are now back in the wild, no doubt talking all kinds of shit about me, none of which, I assure you, is true.

Poor Man’s Liquid Nitrogen

Liquid nitrogen is hard to get, and being someone with no connections and a wild look in his eye, I don’t think I could actually get my hands on any, so I have to settle for watching videos of the stuff in action. I was doing that a few days ago, and ran across this video:

Being a good science nerd, I happen to know a place where I can buy dry ice. And, being a good science nerd, my first thought when I saw this video was “Don’t try this at home? Pffft! I know what I’m doing!” So, I made Poor Man’s Liquid Nitrogen (which I’ll call PMLN, because I’m lazy). Surprisingly, I didn’t manage to injure myself, but heed the following warning!:


Anyway…onward! (But one more note of warning: I didn’t manage to hurt myself, but I did discover that letting a bunch of dry ice fall in your sink drain is a good way to break a garbage disposal…)

What you need to make PMLN. A 20-liter soda bottle, a 3-liter soda bottle, a knife, isopropyl rubbing alcohol (the video recommends 99%, but the best I could find was 91%), and a pair of gloves to protect myself from frostbite.

In addition to being an excellent way to cool things relatively cheaply, dry ice is also a hell of a lot of fun to play with. Warning: dry ice will make plastic brittle, and is a good way to ruin a plastic colander.

Cut the tops off both containers. Poke holes in the smaller one.

Put the smaller container in the larger one (as if you could do it the other way around…) and surround it with chunks of dry ice. I broke my slab up with a hammer, which is a good way to make really, really cold powdered dry ice, which created a lovely crust of ice on the bottom of my sink.

The “cryo-cell” cooling down. If you decide to disregard my warning and try this experiment, note my safety precautions: gloves, a long-sleeved jacket (in case something splashes), and (not pictured) long pants, socks, and shoes. Just in case.

The alcohol has cooled down to the point that it’s no longer boiling furiously. Time to freeze stuff!

Here’s all the stuff I could find to freeze. At bottom: baby spinach leaves. At the top: a leaf from my jade plant.

Julia the jade plant, from whom I stole the leaf. Sacrificing herself for science once again. Houseplants are noble that way.

The spinach leaf going in…

A shattered spinach leaf. As the fellow in the video advises: do not try to eat stuff frozen this way! Not only will it have rubbing alcohol on it (which is not safe to consume, and could, in fact, kill you), but it will be very, very cold and might freeze to your tongue.

A jade plant leaf freezing in the chilled alcohol. Note: you can’t see it here, but that alcohol isn’t actually liquid. It’s more of a slushy gel-type stuff.

The effects of the cryo-cell. It really works!

I didn’t just want to pour the cola from my 20-liter bottle down the drain, so I put it in a glass. Then, being the amateur mad scientist that I am, I thought “I wonder if you can use dry ice like regular ice…” The answer: you certainly can, but don’t do it with cola. The bubbles from the dry ice will agitate it, and make all the carbonation fizz away. So, the cola was flat, but it sure was nice and cold.

Many, many thanks to YouTube user wbeaty for the demonstration that inspired this post. You should check out some of his other videos. I’m not just saying that so he won’t get pissed off that I copied his experiment; his other videos are actually really cool (no pun intended, honestly).

And one final reminder: don’t do this at home!

Pictures of Other Planets

While injecting my daily dose of Internet news, I learned something incredible: we now have what looks like direct photographic evidence of planets orbiting other stars! I found it pretty hard to believe, but there it is, in black and white (or rather, purple and white).

One of the planets was found orbiting the star Fomalhaut, around 25 light-years from Earth.

Photo courtesy of’s Bad Astronomy Blog.

This is a true “Holy shit!” moment. So far, the only planets we’ve found by direct imaging have either been too large to be properly classified as planets, or they haven’t been orbiting actual stars. In short, this is monumental.

It gets better. Much better. The Keck/Gemini observatory gives us this image of the star HR 8799.

Your eyes do not decieve. What you are looking at is two (TWO!!!) planets orbiting HR 8799. Apparently, they saw a third one, too, but I’m too busy picking my jaw up off the floor to go hunting for images.

I am actually too shocked and giddy to write anything useful. Sometimes, the universe sees fit to remind me why I became a science nerd in the first place.

You can read more about both planetary systems here and get the juicy details about the one orbiting HR 8799 here.

Now, if you’ll excuse me, I have to go wipe the drool off my face. And pick my jaw up off the floor.

(NOTE: This seems to me like a pretty good reason to either maintain or replace Hubble. That, and the mystery object it found a couple of months ago)

Hubble Finds a Mystery Object

As is my habit, I was scanning through the news today, and came upon a story that really caught my attention: the Hubble telescope has spotted some sort of mysterious object in space. While this is hardly the first time that’s happened, this time, there’s a twist: the object behaves like nothing else we’ve ever seen. It’s been described as belonging to a possible “new class of astronomical object.” Apparently, it appeared, brightened, and dimmed, and disappeared within a few hundred days. Here’s the really weird part: nobody knows what it is. The way it brightened and dimmed isn’t consistent with a supernova or any other kind of known object. Additionally, it moved so strangely that nobody knows how far away it was. According to astronomers, it could have been anywhere between 130 and 11,000,000,000 light-years away.

Being a sometimes writer of science fiction, it’s hard not to speculate as to what the Mystery Thingy might have been, but even if it was something fairly mundane, this is still pretty exciting.

You can read more about the Mystery Thingy (which I’m hoping will catch on as the object’s official name) here.

Virtual Chemistry

If you’re interested, Virtual Chemistry can now be played with or downloaded here.

A little while ago, I was, once again, idly messing around in NetLogo, having fun with the layout-spring method, which basically treats agents like the nodes of a network of springs, and the links between them as the springs themselves, then computes the dynamics and changes the positions of hte nodes accordingly. Eventually, inspiration struck, and I wondered if it would be possible to build a simulation of chemical bonding. I spent about an hour writing and revising the code, and thus, Virtual Chemistry was born.

It works like this: at the beginning of each simulation run, a random number is generated. This is the number of unique elements that will appear. Arrays are created that store the properties of these elements, namely: complements (which tells the element which other elements it can form bonds with), and maxbonds (which, obviously, tells the element the maximum number of bonds that it can form). Every step, an atom checks for other atoms within the radius “interact-radius” (which the user can set using a slider). If any of the nearby atoms are in the atom’s complement list, there is a ten percent chance that it will form a bond, as long as it hasn’t reached the maximum number of bonds. Atoms also wiggle around randomly to simulate temperature effects.

It took me a while to get this to work and to get rid of a few irritating bugs, but eventually, I got it working, and, not to be immodest, but I was impressed with the kinds of behavior it could produce.

As I watched the simulations unfold, I observed behavior that I hadn’t even considered when I was building the simulation. For example, when the simulated space was packed to a sufficient density with atoms, it began to experience real pressure effects. The way the physics works, bonds hold atoms together, but atoms repel each other. At the start, with the atoms at a low density (and a low enough temperature), certain “molecules” formed. As I added atoms (effectively increasing the pressure), some structures that had been unstable became stable, and some of the structures that had been stable destabilized. I was fairly happy, because I realized that what I was seeing were actual phase changes in my virtual material. Similar phase changes occurred when I changed the temperature, too.

One experimental run in particular is very illustrative. I call it Triad World. In this world, there is only one element (“Element 0”), and each atom of Element 0 can have at most three bonds. Even in a simple world like this, I observed some interesting things.

Here, you can see the atoms, and the three-atom triangles that give Triad World its name. As you can see, these dominate, but there are also other “molecules” which occur quite frequently. The scene above arose at a low temperature and a fairly low pressure.

After adding a few atoms (and thus increasing the pressure), new stable structures emerged. Note the large chain near the center of the image. Only the restraining force exerted by the surrounding atoms prevents the heat from tearing this chain apart. The same force, though, also prevents the two-atom dimers from forming triad,s which they normally would have done.

There are a lot of potential applications for a program like this (more so, perhaps, than my zombie infection simulator), and it’s certainly a lot of fun to play with. The problem is, running the simulation with more than about two hundred atoms slows it down pretty badly. But in order to simulate anything as complicated as, say, a rudimentary biomolecule, thousands of atoms or more would be required. With that in mind, here’s my to-do list of improvements:

  • Optimize the code, if possible, to make it run faster.
  • Write a better bond-forming routine. I’m not happy with the one that’s currently implemented.
  • Tune the attraction and repulsion strengths. Right now, I get the vague feeling that the weird interatomic forces that exist in the simulation are preventing some interesting structures from forming. I know for a fact that they’re preventing any but the most rudimentary chemical reactions.
  • Implement some kind of energy system. Right now, the only energy comes in the form of the random motions induced by the heat. I’d like to make it so that forming bonds consumes energy and breaking bonds releases it.

That’s all for now. I’m hoping to have the complete program up on the NetLogo website soon, and when it’s up, I’ll publish the link.

SimHeart 3.0

Some months ago, I wrote a series of posts about the behavior of my NetLogo heart simulation (namely, this one and this other one). SimHeart has been on the backburner since then, partly because I was making some effort (some) to pay attention to my classes, but mostly because I didn’t have any new ideas to implement. Then, a couple of weeks ago, I was messing around in NetLogo, trying to figure out how to get the cells of the grid to obey a switching-on rule similar to the kind of rules you find in neural networks. That, as it turned out, was a huge bust, but I re-used some of the code to build SimHeart 3.0.

This is a pretty radical revision, but, behaviorally, it’s pretty much the same as the old simulator. Still, there are some changes:

  • The cells, not the agents, do most of the work. Whether they fire or not is determined by a stochastic (random) sigmoid function. If a lot of a particular cell’s neighbors have high potential (the primary variable; actually, three varaibles, one for each system, but I’ll get to that later) and the cell’s potential is low enough, then the cell has a very high probability of switching its potential to 1. If not, the potential steadily drops.
  • The AV node is now fully simulated. I mentioned in my previous posts that I wanted to do this, and since the atria and the ventricles are simulated as two different kinds of potential, all I had to do to simulate the AV node was to introduce a third variant of the potential variable. Now, a heartbeat starts at the SA node (meaning a particular cell’s potential is set to 1), the wave travels until it reaches the entry cell for the AV node, triggers another wave (one that’s morphologically different, which I’ll talk about in the next bullet point) in the AV node, which travels to the exit cell, triggering the ventricular beat. This solution has the nice feature of taking care of the AV node’s natural delay for me, as well as realistically limiting the heart rate that the AV node can transmit from the atria to the ventricles. This is, by far, the most important addition.
  • The model now runs faster. Not much faster, but every bit counts, and given how much simpler the code is now, the model is now much more compact and elegant.
  • The model is more realistic. The stochastic potential-based cells are a lot more like how a real heart works than was the old model.
  • The model now takes into account the different sizes of the heart’s components. Because of the way the model works, the longer a cell’s potential takes to decay, the smaller of the particular component being simulated. Thus, the potential in the AV node takes a very long time to decay, making nodal arrhythmias essentially impossible (and making the AV node behave as though it’s very small); the potential in the atria takes a moderate amount of time to decay, making atrial arrhythmias much less common (and making the atria behave as though they’re larger than the AV node, but smaller than the ventricles. I think you see the pattern here.), and the potential in the ventricles decays quickly, making them fairly arrhythmia-prone.
  • The arrhythmias have changed. This isn’t necessarily a good thing, but it’s not crippling, either. The model now produces ventricular tachycardia much more readily than it did before, but the incidence of ventricular fibrillation has been reduced proportionately, and can be hard to differentiate between tachycardia. Unless the parameters are adjusted, atrial arrhythmais don’t occur at all. Still, the model can now incorporate junctional tachycardia (where a spiralling, self-sustaining wave in the AV node stimulates the ventricles to beat too quickly) can now be simulated easily.

And, not mentioned on the list above, the model is now prettier, too, since I was apparently experiencing some aesthetic inspiration when I was writing it. So, in SimHeart tradition (can I call it a tradition after three posts?), I present: the screenshots (note: ignore the weird screwed-up areas. They’re just explanatory text that apparently didn’t transfer into the screenshot. Don’t worry, you’re not missing anything, it’s all explained in the text below):

Periodically (with the period determined by the “s-rate” slider next to the view), the cell labeled “SA” sets its potential to 1, generating the atrial pulse (the red wave). If, for some reason (for example, if the atria are in fibrillation and there’s already a wave passing through the SA node), no wave will be generated.

When the pulse passing through the atria hits the cell labeled “AV1,” if there’s not a wave passing through it at the moment, it triggers a pulse in the AV node (the green wave).

If all goes well, the AV pulse triggers the cell labeled “AV2” which activates the ventricular pulse (the blue wave).

Of course, all does not always go well:

In this case, something has gone wrong with the electrical wave as it moves through the ventricles, causing a deadly spiral wave to form. This is simulated ventricular tachycardia, which will (probably) eventually decay into ventricular fibrillation. As you can see on the ECG, the atrial pulses are still trying to get through, but the AV node can’t activate the ventricles. Although it’s not pictured here, a quick press of the “Defibrillate” button took care of the arrhythmia.

Since the model’s now so much simpler, it’s easier to simulate diseases and treatments. Note the row of blue buttons on the right side of the images. There is, of course, the defibrillate button, which is remarkably effective at terminating arrhythmias. Below that are the “Increase Adrenalin” and “Increase Antiarrhythmics” buttons, the first of which makes the heart depolarize faster, and the second of which makes it depolarize more slowly. The first, as you might expect, makes the heart more arrhythmia-prone, and the second, obviously, makes it less arrhythmia-prone.

The set of buttons below that simulate various cardiac illnesses. “AV Block” makes the AV node’s cells depolarize very slowly, meaning that, when the sinus rate is set to a very high value, not all of the beats are able to get through. This, if I’m not mistaken, represents 2nd-degree AV block, type 1. The button below that, “Sinus Tachycardia”, sets the sinus rate to a very high value, simulating either a disease process or the effect of very strenuous exercise or other stress on the heart. “Long QT Syndrome” is a sort of bastardized version of the real disease, but has the same effect, making the ventricles dangerously more prone to arrhythmia.

All in all, I’m far happier with the new version than I was with either of the old versions. There are still some improvements to be made, however, and I’ll post updates as needed. Soon, I hope to have the model up on the NetLogo website, so that everybody can fiddle around with it.

Ethanol is Not the Answer!

I listen to a lot of NPR, so, needless to say, I’ve been deluged lately with debates about energy prices, energy crises, and possible solutions to both. I also keep hearing a lot about ethanol, and that drives me crazy.

A lot of people are worried because the corn being consumed to produce ethanol is putting a strain on the supply, and driving up the price of corn-based foods (which, in America, seems to be nearly everything). As a result, there are scientists and politicians talking about alternative sources of ethanol.

To me, this is like talking about finding alternate sources of crude oil: it’s a stupid and short-sighted thought. What we need is to phase out fossil fuels altogether, not dig up Alaska or Russia or China or wherever to find more of them; and, in the same vein, what we need is to stop thinking about ethanol altogether, not try to find better ways to produce it!

I’ve got two major problems with ethanol. First, since it’s based on corn, it is inevitably a carbon-based fuel. And since it’s carbon based, basic chemistry will tell you that any products of its combustion will contain carbon dioxide. Seeing as the human race may have already signed its own death warrant, even if we stop pumpin greenhouse gases into the atmosphere today, I think it’s missing the point somewhat to talk about another carbon-based combustion fuel.

Secondly, with the world and the world economy in the state that they’re in, is it really wise to put any more strain on the food supply? With the economy in the toilet and food prices already in the stratosphere, it seems idiotic to me to make it any harder for the poor — in this country and abroad — to afford food.

I also have a third problem with ethanol, and this is the one that irritates me the most: it’s a pretend solution. People who buy ethanol, and politicians who support ethanol, do so primarily to feel like they’re doing something about global warming. But they’re not really doing anything to make the energy economy more carbon-indepenent. To me, ethanol is a solution (a crappy one at best, and at worst, not a solution at all) chosen by rich white people who aren’t willing to take the drastic mesaures needed to keep Homo sapiens sapiens off the endangered species list.

Those are my thoughts.

The Future of Neural Networks

I found this video some time ago when I was searching YouTube for interesting demonstrations of neural networks. It is, by far, the best explanation of modern Neural-Net theory that I’ve ever encountered, and I thought that some of you out in cyberspace might enjoy it as well.

The video is presented by Geoffrey Hinton, a machine-learning pioneer. His treatment of what he calls “Restricted Boltzmann Machine” neural nets is incredibly nuanced and mathematically rigorous, a — and forgive the cliché here — must-see for machine-learning enthusiasts. An excellent presentation based on an excellent idea, and certainly the most brain-like (maybe even mind-like) system I’ve ever seen. Some of the particular Machines he explores can do some fairly amazing things, like natural character recognition and sorting documents by semantic content.  And he manages to throw in a joke or two, as well.

You can find the video here. Enjoy.

Feeling Aged at Twenty

For a while now, I’ve been noticing a disturbing innner trend: I feel old. Very old. On some occasions, I’ve unironically mumbled “damn kids.” No doubt, this is a product of the rapidly-accelerating advance of technology (Singularity, anyone?), but to me, it doesn’t bode well.

You see, I was an early member of the Internet generation, and when the much-touted “Web 2.0”, user-created internet arrived sometime this decade, it only made sense to me. I’ve always been one to try to keep up or at least keep informed of the latest technical innovations. Now, though, I’m finding that I don’t have the energy to run in the twenty or thirty different directions that my brain is pulling me. There’s too much to read, too much to write, too much to digest, too many Wikipedia queries to make. It’s all just too much, too fast.

To me, this is foreshadowing what is to come. Before long, it will be impossible for the standard human being (I like to call them MOSHes (Mostly Original Substrate Humans), after Kurzweil) to keep up, even if they’ve been — as future children will no doubt be — steeped in the nöosphere since birth. Not only is this trend going to push us towards mind augmentation and transhumanism sooner rather than later, but it hints at things to come. Maybe all this Singularity stuff is crap, a “rapture for nerds” as some of the characters in Charles Stross’s Accelerando sometimes call it, but we’re certainly steaming towards some kind of technosocial discontinuity, if a fairly hip (and wipe that grin off your face!) technophile like myself is already feeling dated and obsolete at twenty!

A Theory of Consciousness

Lately, I’ve been reading Oliver Sacks’s new-ish book Musicophilia. While it’s not quite the tour de force that The Man Who Mistook his Wife for a Hat was, it’s gotten me thinking once again about the neurology of consciousness, and after a few days’ contemplation (and a few years spent reading neurological books), I think I finally have a rough sketch for my own theory of how consciousness comes into existence. Of course, I’m not a neurologist. I don’t know the details of how all this works, and none of it is based on empirical evidence, but that’s the beauty of the Internet: you can talk about ideas abstractly. And, since that’s what I’m good at, that’s what I’m going to do. So, here goes: consciousness.

There are a few structures which are vital to conscious experience. These are:

  • The thalamus
  • The brainstem
  • the prefrontal cortex (and the rest of the cerebral cortex as well)

The other structures are more involved in the contents of consciousness. They are the raw material that the conscious structures process. Here’s how it seems to me that consciousness happens:

  1. Sensory information enters via the brainstem.
  2. The brainstem preprocesses the information and sends it to the thalamus.
  3. The thalamus takes in the preprocessed sensory information and combines it with information about the state of the cortex itself.
  4. The thalamus relays this information to the relevant cortical structures. The prefrontal cortex may play a role here in organizing the arrival of the information, and perhaps in weighting it emotionally.
  5. The cortex processes the sensory information, and the prefrontal cortex reads the results and generates judgments based on emotional weighting from the limbic system. It may generate some of its own emotional reactions as well.
  6. The prefrontal cortex sends the interpreted brain state back to the thalamus. There may also be other loops between the thalamus and the other cortical regions.
  7. The processed mental state enters the thalamus, along with a new set of sensory information.
  8. Repeat.

Of course, this says nothing about memory formation, which is very important for making sense of conscious awareness. It just so happens that I have a theory for how memories form as well.

  1. An emotional signal is sent by the amygdala (or some other part of the emotional system) to the hippocampus, which “reads” sensory information currently being process, thus forming connections between the disparate kinds of information.
  2. This association is stored in the temporal lobe. When the area where the memory structure is stored is activated, the temporal lobe re-activates the relevant structures (those whose particular activity patterns were linked by the hippocampus), and the remembered event is re-experienced.

I’m not really sure how a memory would be recalled in this model, though. I’d venture to guess that it’d have something to do with the prefrontal cortex sending a signal to the temporal lobe, in order to retrieve the memory for comparison to current events.

This little model (and I’ll say it again, I’m not a neurologist. Not even close, so think about this model in the spirit in which it was intended: as a useful idea, not as anything approaching a theory) does shed some useful light on certain kinds of mental illness and the effects caused by certain sorts of brain damage.

  • Schizophrenia: It’s well known that in schizophrenia, the prefrontal cortex is not functioning as it should. Without a properly-functioning cortex, judgments based on memories and sensory information cannot be made properly, and sensory information does not get integrated properly. Also, the prefrontal cortex’s inhibitory connections are less functional as well, which would seem to explain not only the disorganized and unintegrated thought patterns associated with schizophrenia, but also the hallucinations, which could be the result of sensory information going to the wrong place or being integrated improperly. Or, perhaps, the hallucinations and delusions might have something to do with the fact that, without prefrontal cortical direction, the various cortical structures can no longer properly regulate their output.
  • Anterograde amnesia: with damage to the hippocampus comes difficulty forming long-term memories. In this model, that would be because the structure which associates the various neural states with one another is either incapable of doing so, or else it is incapable of moving them into the temporal lobe for permanent storage.
  • Thalamic coma: this may also apply to comas in general, as well as minimally-conscious states, but thsi model only really has something to say about thalamic comas. When the thalamus is damaged, not only can external sensory information not enter the cortex, but the cortical state itself is also prevented from being communicated to the cortex, so there is an absence of both sensation and cognition. The thalamus, however, is divided into two parts, one of which communicates primarily to the cortex, and the other of which is mostly responsible for preprocessing and relaying sensory information. If only the sensory-preprocessor (in the case of vision, this is the lateral geniculate nucleus) were to be damaged, the patient would still likely be able to achieve conscious awareness, but there would simply be no sensory information for them to process.
  • Encephalitis lethargica: in patients with this disorder (which is, according to Oliver Sacks, an extreme form of parkinsonism), the patient is mostly functional, but they are unable to initiate much activity (if any). In this model, that would be because of damage or inactivity of the limbic system, which is crucial in communication emotional meaning to the prefrontal cortex. In patients with severe parkinsonism, there may be difficulty seeing the relevance of actions, and therefore, the actions are not generated. This can also occur with certain kind of brainstem and prefrontal lesions.
  • Depression: in this disease, the prefrontal cortex is known to be less active. However, unlike in schizophrenia, its integrative functions must still be intact. However, its emotional functions become impaired, leading to difficulty forming memories (since the PFC cannot communicate the emotional necessity of remembering something to the hippocampus, and would likely have difficulty sending retrieval signals, too), lack of motivation (since the significance of actions would become unclear), and depressed mood or flat affect (since everything would have the same emotional significance).

I won’t go any further, for fear of over-inflating my ego and for starting to make claims that I have no hope of arguing for. But this, I think, is at least something to get people thinking. Of course, there are a billion things that I haven’t taken into account: the left versus right hemisphere functional disparity, the effects of neurotransmitters, and no doubt I’ve left out quite a few very important brain structures.

Unexpected Consequences

One of the things that’s always fascinated me the most about simulated evolution is the way in which simulated organisms have a tendency to exploit any loophole or weakness in your code for an evolutionary advantage. Although I’ve designed and attempted to design a handful of evolutionary simulations, I’d never until today seen an example of this Darwinian cleverness.

A few days ago, I threw together a simple little evolution simulator in NetLogo. Each of the agents in the simulation had three genes: xcor (position along the x-axis), ycor (position along the y-axis), breednum (the number of daughter agents it spawns when it reproduces), and killpropensity (how likely the agent is to kill a random nearby agent). The simulation produced some interesting — although not terribly fascinating — behavior: those agents that produced the most offspring had a tendency to dominate. There was an interesting dynamic between the “killer” agents and the “peaceful” agents. The killers tended to form low-density groups (since if any of them were too close together, they’d usually kill each other), while the “pacifists” formed dense blooms. For a while, the killers would hold back the pacifists, but eventually, the pacifists would encroach and squeeze out the killers altogether. A typical run looked like this:

The agents inherit the color of their parents, so the coloration isn’t exactly by “species,” but it’s pretty close. As you can see, the green agents are fast-breeding pacifists, rapidly encroaching on the slower-breeding killers toward the center.

Then — and this is where the unexpected behavior and exploitation of loopholes I was talking about comes in — I introduced a new variable: mutationrate. It controls, obviously enough, how rapidly the agents mutate. Very quickly, every run started to look like this:

As you can see, this blue species has very rapidly come to dominate. You can’t see it, but this species has a rather high mutation rate. It took me a while to figure out why the fast-mutators were at such an enormous advantage. Then, I remembered that, in this simulation, the agents were competing for space, and in such a competition, the fittest organisms would be the ones that can maximize the space filled by their offspring. Since x-position and y-position were treated as genes, they were being mutated right along with the other variables, and since a rapidly-mutating position allowed the agents to jump farther from their parents and fill space more rapidly, fast mutation was an enormous advantage. It was such an enormous advantage that, even though the extremely large mutations the fast-mutators experienced prevented the evolution of any other behavior (because those genes tended to get so randomized that they effectively didn’t get passed on), they were still far more successful than any of the other species.

After I corrected for this ludicrous advantage (by setting it so that mutation rate couldn’t work on the position genes), this is what I got:

For a moment, I thought I’d solved the problem, until I inspected some of the agents and discovered that they had stopped mutating altogether. The sneaky intelligence of the genetic algorithm strikes again! I suppose that mutating would become something of a maladaptive behavior once the organism had optimized all of its other behaviors, since, after optimization was reached, any organism that mutated could only be at a disadvantage.

I realized that the only fix for this would be to force the mutation rate to stay above 2 (it’s a peculiarity of the random-number-generation code I cobbled together for this simulation that, at a mutation rate less than 2, no mutations occur). I thought that all I’d get would be the simulation I started with, but I was pleasantly surprised to discover that there was actually quite a diversity of mutation rates, and that none of these rates was at a particularly huge advantage over any of the others. This is what a run of the fixed simulator produced:

Those numbers you see hovering over every agent are the mutation rate. It appears that there’s not really an advantage to having a mutation rate above the usual 2, but it does seem that there’s not a disadvantage, either. So I can finally call this simulation fixed.

This experience reminded me that there’s a reason genetic algorithms are so popular in AI research, and that brings us to the moral of this little story: Darwinian evolution is a lot smarter than us. When writing evolutionary simulations, if there’s a loophole or a workaround or an exploit to be found in your code, then evolution will find it. Plan accordingly.

NOTE: Someone requested an image with the organisms color-coded by “kill propensity.” Since you asked nicely, and since I agree that that would be a good image to have up here, here you go. The organisms that are the darkest have the lowest probability of killing their neighbors, and the ones that are closer to white are very likely to kill:

As you can see, the situation is as I described in the body of the post: the killers have too great a tendency to limit their own growth, and are easily out-competed by their more peaceful counterparts.

SimHeart — Now Available for Download

All right, as promised, I’ve finally figured out a way that people can download SimHeart to play with it themselves. Many thanks to the folks at NetLogo for automating so much of the process, and thanks to for the free file hosting.

The file is kind of large because, in order for it to work, I had to put a bunch of Java modules into the folder with it, but it shouldn’t take too long to download, even over a slow-ish Internet connection. When you’ve downloaded it, you’ll need to extract the file to your desktop. I recommend an unzipping program like WinZip or WinAce. The program should (major, major emphasis on should) work on Macs and PCs, but I make no guarantees.

To run the simulation, go into the folder into which you’ve extracted SimHeart, and double click on the HTML file there. It should open up in a new window, and you should see the simulation screen. If you don’t, either you don’t have an up-to-date version of Java, or something went wrong in the download process, or I made a mistake zipping the files. If you checked the previous two things, please leave a comment and describe the problem, and I’ll try to help, although I make no claims to be very good at this kind of thing.

Also, I must provide the obligatory legal disclaimer: I take no responsibility if this file somehow damages your system. To my knowledge, there is absolutely nothing in the file that should do so, but you never know, something might have gotten corrupted or damaged along the way. Also, this software is for entertainment purposes only, and should not be taken as any form of medical advice. I’m not sure why anybody would, but you never know.

Download SimHeart 2.0 here.

If you already have the latest version of NetLogo installed on your computer, you can download the muchhere. If you’re interested in this kind of thing, you should go ahead and download NetLogo (you can do that here). Not only will it allow you to download a much smaller file, but NetLogo comes with a whole cornucopia of fascinating little simulations, and there are more you can download from the Internet. smaller .nlogo file

Okay, apparently, that site decided to get rid of the file, so if you want to have a look at SimHeart, you can find it here, on the NetLogo community models page.

If you have trouble with either of these files, please let me know by commenting on this post. If you don’t want to do that for some reason, send an e-mail to asymptote [døt] inverse [át] gmail [døt] com (Sorry about all the weird characters in there, but that account gets enough spam as it is, without ever having broadcast the address on the Internet, so I figured I’d better obfuscate as much as possible).

I’ll try to update the files as I revise SimHeart, but I seem to be at a point where there’s not much more I can do with it, at least not without rewriting most of the code. I’ll be sure to post updates as they come.

SimHeart 2.0

It seems that every time I sit down to work on my heart-simulation project, I get a lot more done than I was expecting. In my last post on the subject, I talked about how I wanted to integrate a more realistic model of the atrioventricular (AV) node, the little bundle of nerve fibers that carries the contraction impulse from the atria at the top of the heart to the ventricles on the bottom. Apparently, I’d entirely misjudged the difficulty of this effort, since, once the solution occurred to me, I was able to implement it in about five minutes.

Here’s what I did. As I said before, each cell in the simulation has two variables assigned to it: ARefrac, which determines whether or not an atrial impulse can pass through the cell; and VRefrac, which determines whether a ventricular impulse can pass through. I solved the AV-realism problem by simply introducing a global variable called AVRefrac that determines whether or not the AV node can accept an impulse. Basically, every time a simulated electrical “spark” strikes the simulated node, as long as AVRefrac is equal to or less than zero, it sets AVRefrac’s value to a user-specified constant I call AV-delay. So, basically, now the ventricles can only respond as fast as the AV node will allow, just like a real heart! When I saw how beautifully my little fix had worked, I was thrilled!

So, my simulated heart is now more realistic than ever. For example, I did a few runs with the refract-length value (the value that determines how quickly cells recover their ability to fire after each firing) set very short so that arrhythmias would occur frequently, so that I could study their effects. Before long, my simulated heart went into atrial flutter/fibrillation (a condition where the small pumping chambers at the top of the heart expand and contract quickly and chaotically, often leading to a dangerously fast ventricular rate. I was amazed to see something very similar to the many atrial-fibrillation EKG’s I’ve looked at:

(Note: in the simulated EKG, I’ve separated the atrial and ventricular signals, since whenever the ventricular rate got very fast, it obscured all the atrial activity, and I wanted to be able to study the atrial activity as well)

Given my tendency towards oversimplified simulations that produce peculiar behavior, the resemblance this bears to real supraventricular tachycardia (fast heart rate caused by the atria, which is often seen in atrial flutter or fibrillation) was frankly, surprising. After about half a second of atrial flutter, the atria begin to fibrillate, producing that classic irregular ventricular response.

Note the extremely high ventricular rate that shows up towards the end of the ECG. That’s a rather unrealistic product of my simulation, since whenever one of the waves of excitation collided with the back of a previous wave, it had a tendency to collapse into a tachycardic or fibrillatory spiral.

There are some forms of supraventricular tachycardia that terminate on their own. They’re called “paroxysmal” supraventricular tachycardia, and my simple little simulation actually managed to produce a run of it!

Some forms of atrial fibrillation occur in the presence of heat block (which, in its most common form, is basically a very slow AV node that doesn’t conduct every impulse that passes to it). In those cases, the fibrillation is frequently asymptomatic or minimally symptomatic, since the heart doesn’t end up racing. When I set the AV-delay parameter higher than usual, I observed this very same phenomenon.

Eventually, the aforementioned wave-collision problem had become annoying enough that I decided to re-write part of the simulation so that there was a small probability that an electrical spark could actually cross a cell that had not entirely recovered. That solved a lot of my problems.

In the re-written simulation, atrial fibrillation still produces that classic irregular ventricular heartbeat, and this time, since the waves are more collision-tolerant, the behavior doesn’t immediately degenerate into ventricular fibrillation, which gives me a chance to actually study it properly.

More updates as they’re warranted. And for those reader(s?) who are wondering what the hell has been wrong with me lately, don’t worry, I’ll be turning the blog over to my old cynical, sarcastic self very shortly.


I was sitting around without much to do, so I opened up SimHeart and let it run in the background. When I checked in on it again a few minutes later, I’d discovered some very interesting behavior:

Apparently, some of the standard sort of atrial fibrillation had started, then, spontaneously self-organized into a coordinated wave spiraling cyclically through the atria. You can see the wave in the screenshot.

This really grabbed my attention, so I watched it for a while, and discovered that, strangely enough, the wave was quite stable.

Not even the normal sinus beats, which occasionally inserted themselves in the path of the wave, were very good at disrupting it. Not long after this screenshot, it degenerated rather suddenly into normal atrial fibrillation.

Then, while having a look at the pictures a few minutes later, I realized something: my simulation had produced true atrial flutter. What I saw before and called atrial flutter was really just organized fibrillation. This, though, exhibits all the classic features of atrial flutter: rapid atrial waves with a sawtooth shape. In this case, since I had the ventricular response set to be fairly quick, it turned into quite realistic atrial tachycardia.

I tried to save the state of the simulation so that I could study it later, but as there are some features of NetLogo with which I’m not entirely familiar, I wasn’t able to do it. So, for now, I guess I’ll just keep running HeartSim in the background until I see that rhythm again.

The Trouble With Science Fiction

Over the years, I’ve been developing an aversion to modern science fiction — both literary and cinematic. So, in the true spirit of blogging, I thought I’d share some of my complaints and suggestions with the world that is the Internet. Here goes.

My chief complaint is that science fiction these days is all too frequently just about the science, never the fiction. In fact, a great deal of it reads like a lengthy, flowery technical manual, or like something written by a futurist. Nowadays, very little time is taken in character development or plot structuring. This problem plagues sci-fi movies with an especial severity. Now, many will no doubt protest that the “sci” is what sci-fi is all about, but I beg to differ. To me, it seems  that sci-fi should only ever be deployed as a tool to allow the telling of stories that aren’t possible in other genres. For example, there are few genres that can so eloquently explore the ramifications of mankind’s creations the way AI-centric sci-fi does. Interspecies tolerance — or lack thereof — speaks potently about our own tolerances and intolerances of each other, in a way that is frequently more poignant and direct than the literarily bogged-down novels of the past.

There is of course a much more serious problem with modern science fiction, and that is that it all seems to be written or filmed by a bunch of pimply adolescent technophiles with about the same amount of imagination as the average armadillo. Most science fiction novels — at least those by the “up and coming” writers — seem to be getting uncomfortably close to the gauzy rococo fantasies explored in the fantasy genre and Japnese anime (I must take a moment to warn my readers, I am terribly un-fond of anime. I think that it’s a bloated, stereotyped medium that Westernizes more sloppily than almost any other Japanese format). While I have no problem per se with either of these, I think that they tend to make the work clichéd and uninteresting. After all, how many angsty twentysomething protagonists with blue hair do we really need?

And as for the lack of imagination, if imagination were oxygen, then somewhere in the world would be a huge pile of asphyxiated sci-fi writers. About seventy-five percent of them would be screenwriters. It seems to me that there are about five science-fiction plots out there, and that whenever a young writer wants to get into the business, they simply pick one, add on some extra bits, throw in some filler, and call it a day. Now, this may indeed be the way that most novels are written — after all, there is only a finite number of plots out there, they’re bound to get re-used eventually — but the problem with that is that science fiction is a very dense pocket of literature, and any excess overlap brings it dangerously close to homogenity. What happened to the Arthur C. Clarkes, the Charles Strosses, the Isaac Asimovs, and the Phillip K. Dickses (Yes, Dickses. I am going out of my way to avoid being juvenile here, give me a break.)? What happened to the ebullient, enterprising spirit that made sci-fi great? After all, as I said before, science fiction is merely a stepladder to reach the previously-inaccessible reaches of literature. What happened to the galaxy-spanning civilizations, the beings composed of ions and magnetic fields, the self-made destructions of civilizations, and the kind of remarkable creativity of a story like Asimov’s “The Nine Billion Names of God”?

Here are my suggestions to my fellow writers of science fiction, in my standard, convenient, lazy, bulleted format:

  • Don’t be afraid to step outside of humanity. What science fiction really needs right now is somebody with the talent to make readers feel connected to a character of an entirely different species. Anyone who can do that — or has done that — with any elegance can have my pocket protector.
  • Don’t rely on archetypes and stereotypes. If your writing has become the standard test-of-the-hero’s-mettle stuff, then smack yourself in the face with your manuscript.
  • Only use sci-fi where it is truly needed. Some stories can be told much more elegantly within the confines of a far less exotic genre. Imagine if John Steinbeck had been born a generation later, and had tried to express the beautiful themes of Of Mice and Men as a space opera. The mind recoils.
  • Don’t, I repeat, don’t be a slave to the genre. Sci-fi does not necessarily need pitched space battles, homogenous gray-skinned aliens, and advanced weapons to be great. Isaac Asimov did it without aliens altogether. Arthur C. Clarke went beyond the whole “Take us to your leader” thing. And Charles Stross went — and is going — beyond the idea of humanoids as the only viable kinds of aliens. And none of the previous needed any kind of blinky, flashing lights or space battles to do what they did. I suppose what I’m trying to say is, don’t write anything that resembles any science fiction movie produced in the last thirty years.

Those are my thoughts. Enjoy.

Wherefore Universe?

Today, as I sat around idly ruminating, a question which has often troubled me bubbled back up in my mind: why does the Universe exist? What is it about the laws of physics that somehow magically cause a Universe to come into being.

I’ve thought long and hard about this problem, and the other day, I believe that I may have hit upon a possible solution. Here goes.

We think of the Universe as a fairly orderly place. Even when we deal with really peculiar theories like the Standard Model and Quantum Mechanics, the Universe is orderly. Cause and effect always, always applies. Well, not quite. Imagine a cloud of gas floating in interstellar space. Now, imagine that you have some sort of super-microscope, and you zoom in on part of the cloud. Eventually, you can see the gas molecules, and then, the individual atoms. As you zoom in yet further, the nucleus of a single atom becomes visible, then the quarks and gluons that make up the interior of a single nucleon. Keep zooming in. It’s going to take a while, even at this rate. Your ultimate goal is to reach 10-35 meters, the so-called Planck length, which is 10-20 times the diameter of a single proton. This is it: the bottom of the Universe. There is no meaningful distance smaller than the Planck length. I know that seems nonsensical, but bear with me.

You see, to measure the position of anything, you have to bounce something off it, whether that be a photon, an electron, a proton, whatever. In order to determine the position with greater accuracy, you have to bounce the particle — let’s assume it’s a photon for our purposes — with a higher energy. The angle at which the photon returns to you allows you to determine the position of the target particle. Well, as it turns out, there is a theoretical limit to this precision. Once you know the particle’s location down to an error of less than 10-35 meters, such measurement requires so much energy that the measurement would produce a microscopic black hole, which would trap the bouncing photon, and prevent the information on the particle’s position from ever reaching you. So, it’s not meaningful to talk about any distance smaller than the Planck length, since nothing can interact with anything smaller than that.

The peculiarities at the Planck scale are legion. Not only can you not measure anything smaller, but space itself becomes unpredictable, twisting and warping and bubbling. Particles appear from nowhere and then swirl away into nothing. Energy is created and destroyed. And the important thing, causality does not seem to apply. Events can occur on the Planck scale without any cause in the Universe.

You might — if you were brave enough to actually read through that long, drawn-out description — be wondering what this has to do with the cause of the Universe. Well, I’m just getting to that.

You see, our current physical models of the Universe cannot actually tell us what happened before about 10-45 seconds prior to the beginning (that number, incidentally, is the Planck time. There is no meaningful time interval shorter than the Planck time, as there is no meaningful spatial interval shorter than the Planck length). That is because, before 10-45 seconds, the baby universe was smaller than the Planck length, which means that our traditional notions of space, time, and causality do not apply.

So, perhaps this is the answer to why the universe exists: there is no cause, or if there is, we cannot comprehend it, because causality is different or nonexistent at such tiny scales. Perhaps at such scales, where causality is so flexible, events can cause themselves. Or perhaps, even more paradoxically, effect can precede cause. So, perhaps, the origin of the Universe and the laws of physics were one and the same thing: the Universe itself.

Think about it.

Life Imitates Art: A Somewhat Twisted Look at Parasites

Everybody knows the story. It shows up in a lot of sci-fi movies: a secondary character gets attacked by some sort of creature that latches onto their head and forces them to do its nefarious bidding. Well, as it turns out, this isn’t science fiction. Such phenomena are actually observed in nature (thus the lame “life-imitates-art” reference in the title). As it turns out, there actually exist a few species of insect and virus that alter (and sometimes control) the host’s brain. As a service to those warped-minded individuals (such as myself) who find this kind of thing fascinating, I present to you, dear reader, the List of the Most Disgusting and Interesting Parasites I Could Find:

AUTHOR’s NOTE: I take no responsibility for any vomiting or nightmares resulting from reading through this list…

  • Emerald Cockroach Wasp (Ampulex compressa): This nasty little insect mounts the back of a cockroach, jabs its stinger through the back of the roach’s head, and using a precise set of sensors, guides the stinger, brain-surgeon-like, into the part of the cockroach’s brain that controls the escape reflex, injecting it with a venom. The wasp then — and this is the part that really blew me away — leads the now “zombified” cockroach around by the antenna, until they reach the wasp burrow, where they, in the standard fashion, lay an egg inside the cockroach, which eventually hatches, and the cockroach gets eaten from the inside out. As usual. Credit for the article upon which this bullet point is based goes to this site.
  • Hairworm (Spinochorodes tellini): This was the first of the creepy brain-parasites I learned about. This diabolical little nematode enters a grasshopper’s body, and steadily grows until it occupies nearly all of the space within the grasshopper’s exoskeleton. Then, when it’s time for the worm to escape and mate — which it can only do in the water — it forces the cricket to drown itself in a puddle, thus freeing the hairworm to frolic and breed. You can learn more here.
  • Rabies: All right, this one’s not as obscure as the others, but I still find it fascinating, in a macabre sort of way. I mean, rabies is practically the perfect parasite: it induces violent behavior in those infected by it, which leads to biting and scratching, which are the perfect methods of transmission of the virus! It’s hard to get much more direct than that. I’ve always though that a form of rabies that could spread more easily (perhaps even through mere close contact) would make a great basis for a horror film.
  • The Ichneumon Wasp: This wasp is the creepiest, in terms of sheer gore. The female wasp stabs her ovipositor (that’s such a cool word…an ovipositor is basically a tube that a female insect uses to insert or deposit eggs) into a caterpillar, and injects some eggs. Before long, wasp larvae hatch and eat the caterpillar from the inside out. This, too, would probably make a good horror movie.
  • Lancet Fluke (Dicrocoelium dendriticum): This fluke loves mammalian livers. In order to spread to a new liver, the parasites, excreted in the host’s feces, must be eaten by a snail. Then, when an ant drinks moisture from the snail’s trial (why it would do this is beyond me; snail slime is nasty), it becomes infected with juvenile flukes. These spread into the tiny little bundle of neurons the ant calls a brain (all right, it’s actually called a “ganglion” if you want to be specific). There, they lie in wait, controlling the host ant’s actions until nightfall, when they force the ant to climb a blade of grass, and latch on, waiting to be eaten by a liver-bearing herbivore. Creepy. Thanks to Carl Zimmer’s article The Return of the Puppet Masters for information about this one.
  • Toxoplasma gondii: This nasty little parasite lives in cats, and spreads from cat to cat mainly via rats and other small mammals. The creepy thing is that, although otherwise normal-seeming, T. gondii-infected rats are completely unafraid of the smell of cats, a scent which normally terrifies them. Kind of makes you wonder: who among us might at this very moment be under the influence of…the parasites. Heh…silly idea…the parasites are our friends…the parasites want to help us…Hm…I don’t know what compelled me to write that… Credit for pretty much all of this bullet point also goes to Carl Zimmer.

I’ll amend this list if I run across any other interesting additions.

Memorizing the Periodic Table

Partly out of boredom, and partly out of irritation at never, ever knowing the atomic weight of a particular element, I have decided to embark on the journey to memorize the entire periodic table (well, all the elements up to and including Uranium, at least). But what would even give me such a peculiar idea? Well, blame Oliver Sacks. I was reading through his book The Man Who Mistook His Wife For a Hat (excellent book, by the way, for those who haven’t read it), and I was particularly intrigued by his discussion when talking about numerical savants’ familiarity with numbers: Dmitri Mendeleev, the developer of the periodic table, carried around a deck of cars with the elements’ properties listed on them, and looked them over until he knew them by heart. I’ve always wanted to learn something this thoroughly (and, in fact, I had a set of cars like this myself when I was younger). So, there you have it. I’ll keep my reader(s?) abreast of my progress.

A Debate

 Author’s Note: These are my personal (and sometimes inaccurate) ruminations on the idea of a simulated universe. I don’t claim to know anything about the philosophical treatment this idea has already been given, nor do I know much about any of the arguments. If I’ve stolen someone’s idea, I apologize…I didn’t do it intentionally.

Bob sat on the great stone platform atop the mountain, gazing down over the endless convolutions of the Great Valleys below him. His face bore a look of the most intense concentration. His brow was furrowed, and his eyes were distant and contemplative. It was in this state that Alice found him. She ascended the great staircase and seated herself next to him.

“So there you are.”

“Yes.” It was nothing more than a pleasantry, for Bob was far too lost in thought for any real communication.

“What on Earth could you be thinking about with such intensity?” Bob did not answer, but instead maintained his tense posture for another minute or so, then relaxed, and looked up at Alice.

“I’m sorry, what did you ask?”

“What are you thinking about with such intensity?”

“Oh, well…I’ve just been considering something.”

“Well, what?” A look passed across Bob’s face, and Alice realized with concern that he could very easily lapse back into mute contemplation.

“I’ve just been wondering…it seems to me that we are living in a simulated world?”

“What? What do you mean by that?”

“I simply mean that the Universe that we see is really just an assemblage of data in a computer somewhere, and that the physical laws we observe – and their consequences, such as our own sentience – are simply processes within that computer. You know, program instructions.” Alice rolled her eyes surreptitiously, then crossed her arms.

“Not this subject again!”

“Well, I believe it deserves consideration!”

“Why? It’s an entirely foolish idea!”

“Why’s that?”

“Well, how could we possibly find ourselves in a computerized Universe? No computer could ever manage such a feat of simulation, and even if it could, it wouldn’t be able to produce the robust world we observe!”

“That’s where you’re wrong, I believe.” Bob had now turned fully towards her, and had fixed her with the challenging gaze that was his trademark.

“Oh, really? And have you any evidence of my wrongness?”

“Of course. You know – you should know better than anyone else – that I never make a claim without having a good argument to support it.”


“Okay. Since I am going to base my argument on the idea that a computer likely simulates the universe we live in, I’ll make my argument from a computer-based standpoint, even though essentially any suitable substrate could simulate our Universe. Now, consider a simple electronic circuit.”

“All right.”

“Right. This circuit consists of a small mathematical processor, a few registers for storing data, and all the other necessary equipment for a circuit to work properly.”

“I’m with you so far.”

“Now, say this circuit, on every tick of its internal clock, performed the following calculation: take the value stored in the data registers – call it x – and squared it, then multiplied it by some constant k, then subtracted from the result the value j times x, j being another constant, then stored all of that back in the data registers, and repeated the process ad infinitum.”

“I don’t quite see your point here, Bob. I must confess that I’m rather confused.”

“That is because you’re not thinking about things correctly. Okay, I’ll give you a hint. What would a system such as the one I’ve described represent?”

“Some mathematical function, I think.”

“Go up one more level of abstraction.”

“What do you mean? There are no other levels of abstraction in this system. Either it is a system consisting of electrons darting from atom to atom in a silicon circuit, or it is an abstract mathematical system. There is nothing else!”

“Ah, but you’re wrong on that account! For, think about physical laws!”

“What about physical laws?”

“Are they not just a higher level of abstraction than pure mathematics?”

“Hm…no, I don’t believe they are.”

“I think our definitions of ‘abstraction’ may differ. For now, I’m defining ‘abstraction’ to mean ‘representation,’ or something to that effect.”

“Ah, I see. Well, given that definition, I suppose I’d have to agree: physical laws could be seen as a third level of abstraction.”

“Right. Now, back to my imaginary circuit. Think about what its third level of abstraction would be.”

Alice thought for a moment, and then her face lit up.

“Aha! It seems to be the equations of motion for an accelerating projectile subject to air resistance!”

“Very good!”

“But what was the point of the whole exercise?”
“Be patient! I was coming to that! Now, couldn’t one argue – rather convincingly – that in many ways, the creation of this circuit has also brought into existence an accelerating projectile subject to air resistance?”

“No, I don’t think so. The projectile is not real, it’s merely an abstract representation, created by us, its conscious observers.”

“I’ll ignore your little play on the definition of ‘abstraction’ there, for the moment. So, you say that the circuit’s ‘higher-level’ meaning as an accelerating projectile exists only in the minds of us, its conscious observers?”

“Yes, that’s what I said.”

“Well, you’ve stumbled right into my philosophical trap, then! For, is not the mind itself little more than a circuit, similar to (but, of course, infinitely more complicated than) the circuit we are discussing?” Alice looked blindsided for a moment, then recovered.

“The mind is something different. Your little circuit is fixed in time. It cannot observe itself nor rewire itself. The brain can.”

“Ah, yes, but, still, on the cellular level, is not the brain only a ‘system of electrons darting from atom to atom in a biological circuit’, as you said before?” Alice looked as though she had been physically struck.

“Oh, dear…I believe that’s checkmate…Hm…”

“Yes, you see? There can exist such abstractions, the mind being the primary one!” Alice knitted her brow while her toe fidgeted with a pebble.

“Okay, I concede that such abstractions are possible in our Universe. But since our observation is necessary to bring these abstractions – such as the one of the projectile in your nice little argument a moment ago – to light.”

“Ah, I was hoping you’d try to wiggle free in that way, for I have the perfect rebuttal!”

“And what’s that?”

“Imagine a computer, a huge computer. As big as the Earth, if you like, or bigger. It has memory cells for the storage of data, and processors for the computation of the effects of physical laws. Now, furthermore, let’s say that this computer is running a program that simulates the interaction of a huge number of elementary particles, based on physical laws that are the same as those in this Universe.”

“All right, I follow you so far.”

“Right. Now, let’s further suppose that this computer was allowed to run long enough that the Computed Universe experienced the Big Bang, the formation of ‘normal’ matter, the coalescence of stars and galaxies, and the formation of planets, and all the requisite molecules of life. And then, let’s assume that life does indeed begin in this Computed Universe, and that it evolves to the point where it has developed something like a complex nervous system – what resemblance it actually bears to a nervous system is immaterial, it just must fulfill a very similar function. Then, through the slings and arrows of Darwinian evolution – you don’t disagree that Darwinian evolution would necessarily take place, do you?” Alice shook her head. She knew that evolution was a principle based merely on the idea that the more fit an organism is for its environment, the more likely it will be to be represented in the next generation, and this principle is completely ignorant of the material composition of what is actually evolving. “Good. Then, we have Darwinian evolution, and let’s assume that it produces self-aware organisms. Now, do we not have that ‘secret ingredient’ necessary to allow the universe to be viewed in an abstract way?” Alice was at a loss for words, and she had to work to keep her mouth from falling agape.”

“Oh dear…I seem to have argued myself into a corner…if I allow for the existence of conscious minds, then it seems that I must inevitably fall to your argument…” Bob looked rather satisfied with himself, but then Alice took on a very resolute expression. “Wait! Would not this giant computer still require the observation of its operators in order to see the abstract things – the conscious observers – that it represents?” Bob smiled knowingly, and Alice realized that he would soon deliver his finishing blow.

“No more than our Universe requires a godlike figure to observe it in order for ourselves to exist.” Alice nearly fell off the rock. Then, she steadied herself, and a smile crossed her lips.

“Ah, but you have forgotten your original claim! How can you claim that we live in a simulated Universe? All you have done is to prove that it is possible that we might be, not that it is inevitable, or even likely!” It was Bob’s turn to grin.

“I was waiting for you to recover, so that I could philosophically knock you down once more.” Alice feigned offense.

“Oh, you philosophical sadist!” They both had a good laugh, then Bob suddenly grew serious.

“Now, for the final blow!”

“I’m ready.”

“Let’s assume that some species in some Universe – simulated or not – created a computer simulation of a Universe. Suppose furthermore that that simulation was rich enough that observers – conscious entities – could arise within it. Then suppose that these Computed Observers created their own Computed Universes – for it seems inevitable that any such Universe-Computing race would compute more than one Universe – and within these Computed Computed Universes, Thrice-Computed Universes arose. This would continue until the ‘Nth-Time-Computed Universes’ became too small – for any Computed Universe must necessarily be smaller than the Universe in which it is computed – for conscious observers to arise. Despite this limitation, is it not obvious that there would be an immense hierarchy of simulated Universes for every ‘real’ Universe?” Alice nodded gravely, her defeat seeming imminent. “So, given the laws of probability, since there is such a hugely larger number of Computed Universes, compared to the original few ‘real’ ones, isn’t it much more likely that we find ourselves in a Computed Universe.” Alice sighed loudly, but then a glimmer of hope touched her countenance. After a few moments’ introspection, she smiled.

“Unless, of course, some of the current findings of cosmology prove true, and there is an infinite number of ‘real’ Universes!”

“I don’t follow.”

“Well, consider it! If there is an infinite number of ‘starter’ Universes – that is, ones that are not simulated – there would then be an infinity of Computed Universes, too, but only an infinity, since the mathematical laws of infinite numbers are so slippery. Then, the probability that we find ourselves in a Computed Universe is only one-half, since there is an equal number of both.” Bob looked flabbergasted.

“Oh, dear! I hadn’t even considered that! Excellent riposte, Alice!”

“Thank you!”

“But, wait! Suppose that instead of a finite hierarchy of Computed Universes, the hierarchy was infinite!”

“How would that even be possible.”

“Well, suppose that the infinite ‘starter set’ of Universes was itself simulated, and the Universe in which they were simulated was also simulated, and so on out to infinity!” Alice laughed. It was now her turn to be sadistic.

“But, Cantor showed that an infinity is an infinity. Even if an infinity of initial universes produced an infinity of simulated ones, their numbers would still be equal!” Bob seemed almost to deflate.

“Well, one could get around that by supposing that there is only a single Universe.”

“Not really.” Alice was now philosophizing at full steam, ready to make the kill. “Since, in an infinite Universe – which ours appears to be, based on telescopic observations – there will be regions too far apart to communicate, which are separated by the insurmountability of the speed of light, so that no information can ever pass between them. These regions might as well be separate Universes. This position would only be strengthened if the physical laws could vary from one such region to the next. No matter what you do, unless the Universe is closed and finite – which seems unlikely given the data – then we only have a fifty-percent chance of finding ourselves in a Computed Universe after all!”

Bob was silent for a long time, his head bowed. Then, he began to emit a peculiar rhythmic sound, a little repetitive squeaking. Concerned that he might actually be weeping, Alice leaned in to comfort him, but then the squeaking erupted into chuckling, then into uproarious laughter. Alice was confused.

“What’s so amusing?” Bob stopped laughing, shot her an impish grin, and extended his hand. In his palm was a coin. Alice joined in his laughter, and said, “If it comes up heads, we’re living in a real Universe…otherwise…”

Windows of Lucidity, Again

In a previous post, I pondered what caused some people suffering from degenerative brain diseases (such as Alzheimer’s and Creutzfeldt-Jakob disease) to suddenly, for short periods of time, regain their lost faculties, and even their ravaged short-term memories. Well now, having read Norman Doidge’s excellent book The Brain that Changes Itself, I believe that I may have an answer.

Doidge’s book discusses the rapidly-growing field of neuroplasticity, the study of how the brain can “re-wire” itself. It’s been shown that stroke patients who are left with minimal muscle control on one side of their body can, over time, re-train their brains, through long and arduous practice, to use that side again. After long hours of daily training, they begin to recover use of their affected limbs. That’s neuroplasticity at work.

Therefore, couldn’t this idea also be applied to the kind of brain damage that results from, say, Alzheimer’s? Over time, as the brain attempts to work around the damage caused by the disease, might it not discover a “hidden pathway” that allows it to function normally, if only for a while? It certainly seems possible. This might also go some way to explain why windows of lucidity are so painfully transient: the damage accumulating from the disease process rapidly wipes out these newfound pathways.

Just food for thought.