Posts tagged with biology

We eat energy and poop entropy.
Stephen C Stearns

adults, unlike children, rarely cry in public. They wait until they’re in the privacy of their homes—when they are alone or, at most, in the company of one other adult. On the face of it, the “crying-as-communication” hypothesis does not fully hold up, and it certainly doesn’t explain why we cry when we’re alone, or in an airplane surrounded by strangers we have no connection to…

In the same 2000 study, Vingerhoet’s team also discovered that, in adults, crying is most likely to follow a few specific antecedents. When asked to choose from a wide range of reasons for recent spells of crying, participants in the study chose “separation” or “rejection” far more often than other options, which included things like “pain and injury” and “criticism.”

about a paper by Vingerhoets, Cornelius, Heft, Beck

Towards a Model of Adult Crying


Fun coursera on virology.

  • Viruses are so numerous (10³⁰) and filling up everywhere. It gives this Boltzmann flavour of ‘enough stuff” to really do statistics on.

  • Viruses are just a bundle of {proteins, lipids, nucleic acids} with a shell. It’s totally value-free, no social Darwinism or “survival of the fittest” being imbued with a moral colour. Just a thing that happened that can replicate.
  • Maybe this is just because I was reading about nuclear spaces (⊂ topological vector spaceand white-noise processes that I think of this. Viruses have a qualitatively different error structure than Gaussian. Instead of white-noise it’s about if they can get past certain barriers, like:
    • survive out in the air/water/cyanide
    • bind to a DNA
    • spread across a population
    • adapt to the host’s defences
  • … it seems like a mathematician or probabilist could use the viral world of errors to set out different assumptions for a mathematical object that would capture the broad features of this world that’s full of really tiny things but very different to gas particles.
  • Did I mention that I love how viral evolution is totally value-neutral and logic-based?
  • Did I mention how I love that these things are everywhere all the time, filling up the great microspace my knowledge had left empty between man > animals > plants > > bacteria > > minerals?

John Bonner’s slime mould movies (por princetonuniversity)

  • some slimes altruistically sacrifice themselves,
  • the individuals communicate based on micro rules to make a macro (emergent) decision “together”, yet without a central planning slime
  • the slimes move around (like animals), yet also form a “stem” and grow upwards (like plants), yet also shoot spores out of the top (like fungi).

Robert Sapolsky on the Limbic System (por StanfordUniversity)

  • olfactory bulb takes up 40% of a rodent brain’s projections
  • rhine encephalon — originally viewed as to do with olfaction in all species
  • gathers whatever sense-data pertains to emotions
  • Paul McLean’s triune brain (phylogenetic conservation): hypothalamuspituitarybrainstemmidbrain⊕thyroid⊕pancreas⊕heart (robotic, boring—until it goes wrong) + the limbic system (mostly a mammalian invention: birds, reptiles, fish have less complex limbic systems) ⊕ emotional complexity + cortex (gleaming analytical machine of cognitive expertise — greatly expanded in vertebrates, in mammals, in primates, in us — cortex tied to limbic system, not independent)
  • decisions made under duress
  • think about your own mortality (kicking out “CRH”)
  • so limbic influences cortex and vice versa
  • we are “a fancy species”
  • Odene’s curse — lose the capacity for automatic breathing (you die of sleep deprivation)
  • Antonio DiMasio, Descartes’ Error
  • James Pabes
  • the limbic regions compete to control the hypothalamus (they can shush each other up)
  • edge/network/synaptic distance to the hypothalamus
  • every sense has to go through ge;3 synapses to tell the limbic system anything—except olfaction can hop 1.
  • olfaction takes up only 5% of our brain
  • grey matter (nuclei) vs white matter (axon cables wrapped in myelin)
  • amygdala, hippocampus, septum, mammilary bodies, hypothalamus, thalamus, prefrontal cortex
  • frontal cortex: where am I being touched? which note are you playing? how do I do long division? which limb do I want to move? plus long-term planning, gratification postponement, emotional regulation, impulse control
  • frontal cortex is most recently evolved, relatively largest in humans, not fully mylenated until age 25;size of prefrontal cortex in primates grows as size of typical social group
  • amygdala tells you to be afraid and pings the hippocampus: “Hey, remember to be afraid of this in future”

Oh, much less. The total memory was four kilobytes. And he did an amazing lot with that. Especially a biologist who was there at the time, called Nils Barricelli, did simulated evolution amazingly well with a memory of four kilobytes. He developed models of evolving creatures forming an ecology, and they showed punctuated equilibrium, exactly the way real species do. It was astonishing how much he could get out of that machine.
Freeman Dyson, via University of David

Birds appear to offer, in their behavior, neurophysiology, and neuroanatomy a striking case of parallel evolution of consciousness. Evidence of near human-like levels of consciousness has been most dramatically observed in African grey parrots. Mammalian and avian emotional networks and cognitive microcircuitries appear to be far more homologous than previously thought. Moreover, certain species of birds have been found to exhibit neural sleep patterns similar to those of mammals, including REM sleep and, as was demonstrated in zebra finches, neurophysiological patterns, previously thought to require a mammalian neocortex. Magpies in particular have been shown to exhibit striking similarities to humans, great apes, dolphins, and elephants in studies of mirror self-recognition.

Evidence that human and non-human animal emotional feelings arise from homologous subcortical brain networks provide compelling evidence for evolutionarily shared primal affective qualia.

“The absence of a neocortex does not appear to preclude an organism from experiencing affective states. Convergent evidence indicates that non-human animals have the neuroanatomical, neurochemical, and neurophysiological substrates of conscious states along with the capacity to exhibit intentional behaviors. Consequently, the weight of evidence indicates that humans are not unique in possessing the neurological substrates that generate consciousness. Non-human animals, including all mammals and birds, and many other creatures, including octopuses, also possess these neurological substrates.”

the Cambridge Declaration on Consciousness, 2012

hat tip to fibrations


Railing against “grey areas” has become a favourite rant topic. People think that they’ve covered their bases and are being really open-minded when they switch from {0,1} to [0,1]—but no false dichotomies are avoided in this transition from discrete to continuous.

Let’s take the example of sex & gender. Most of the tick-boxes and bathrooms we face in life are labelled “M” or “F”, which covers most of us but not all.

(And I want to apply a kernel weighted to extra-count the forgotten individuals, since as minorities they’re more vulnerable. This can be seen in data such as e.g. higher suicide rates and higher murder rates.) The University of Hawai’i’s guidelines for dealing with individuals possessing ambiguous genitalia (Archives of Pediatrics and Adolescent Medicine) use words like

  • chromosomes—XX, XY, or other
  • micropenis, labia-scrotum fusion, gonadal dysgenesis
  • androgen insensitivity syndrome, hypospadias, kiinefelter syndrome, congenital adrenal hyperplasia, Turner’s syndrome
  • true hermaphroditia

which raises the question of where the “grey area” between [M,F] ~= [0,1] could come from. Chromosomes either come in whole units — for example people with Klinefelter’s syndrome have 47 chromosomes “XXY” — or have a much more complicated structure if you want to dig into the DNA string. Other aneuploidies include XYY, monosomy or partial monosomy, trisomy 21 (which I don’t think affects genitals or sex assignment), distal 18q−, mosaicism, the list goes on. How are we going to assign a total order there in order to define a continuous variable? I don’t see any way to—just more possibilities to add to the domain of a categorical variable (and making it much more confusing than the usual gender dummy!).

The paper above, to give another example of non-orderability, notes that various chemicals usually squirt at you in fœtal development but they vary in their squirtular timing. So androgen, progesterone, and so on aren’t mutually fungible (as the different “coloured edges” in Ramsey theory), and además we’re dealing with time series like Ed Küpfer’s pictures of sports scores:



Those kinds of pitures, but with different coloured spiketrains representing the incommensurability of androgen vs testosterone and so on.

So how do you get total orderability (necessary for a “grey area”) from a time series of incommensurable chemtrains? I don’t see it. The geometry is more interesting than just a line segment.

Further reading: transgender mathematician (Leigh Noble), transgender computer programmer (Tim Chevalier @eassumption), transgender economist (Deirdre McCloskey @deirdremcclosk), transgender electrical engineer (Lynn Conway). Jeff Eugenides’ Middlesex.


inside the cell

…how fast things happen inside cells.

…a white blood cell responding to inflammation.

Cells are very crowded

Image: “The structure of the cytoplasm" from Molecular Biology of the Cell. Adapted from D.S. Goodsell, Trends Biochem. Sci. 16:203-206, 1991.

… a synaptic vesicle, which is the part of a neuron that releases neurotransmitters from one neuron to another. …I assumed that the authors crammed all the different proteins into the [diagram]…. But in fact, the diagram below omits ⅓ of the proteins so real membranes are even more crowded…. paper … we should think of membranes as packed with proteins like a cobblestone pavement.
A neural vesicle studded with proteins
Image: “Molecular Model of an Average SV" from Molecular Anatomy of a Trafficking Organelle, Takamori et al, Cell. 2006 Nov 17;127(4):831-46.

Molecules move very very fast

You may wonder how things get around inside cells if they are so crowded. …[M]olecules move unimaginably quickly due to thermal motion. A small molecule such as glucose is cruising around a cell at about 250 miles per hour, while a large protein molecule is moving at 20 miles per hour. Note that these are actual speeds inside the cell, not scaled-up speeds. I’m not talking about driving through a crowded Times Square at 20 miles per hour; to scale this would be more like driving through Times Square at 20 million miles per hour!

Because cells are so crowded, molecules can’t get very far without colliding…. In fact, a molecule will collide with something billions of times a second and bounce off in a different direction. Because of this, molecules are [on] a random walk through the cell … diffusing…. A small molecule can get from one side of a cell to the other in ⅕ of a second.

As a result of all this random motion, a typical enzyme  … interact with 500,000 [molecules] every second. …[Y]ou might wonder how the different pieces just happen to move to the right place. In reality, they are covering so much ground in the cell so fast that they will be in the “right place” very frequently just by chance.

In addition, a typical protein is [spinning] a million times per second. Imagine proteins crammed together, each rotating at 60 million RPM, with molecules slamming into them billions of times a second. This is what’s going on inside a cell.

The incredible speed and density of cells also helps explain why it’s so difficult to simulate what’s happening inside a cell. Even with a supercomputer, there’s way too much going on inside a cell to simulate it without major simplifications. Even simulating a single ribosome is a huge computational challenge.

Molecular motors sprint, not walk

.. Like a mechanical robot with two lumbering feet, a kinesin motor protein can be seen in the video at the 2 minute mark dragging a monstrous bag-like vesicle along a microtubule track. (This should be what you see in the YouTube preview frame at the top of the page.) These motor proteins move cargo through the cell if diffusion isn’t fast enough to get things to their destination, which is especially important in extremely long cells such as neurons. …

… these mechanical walkers…sprint at 100 steps per second. If you watch the video again, imagine it sped up to that rate.

Cells are powered by electric motors spinning at 40,000 rpm

Mitochondria also provide a fascinating look at just how fast things are inside cells. You may know that mitochondria are the power plants of cells; they take in food molecules, process it through the famous citric acid cycle, and then use oxygen to extract more energy… ATP….


Image from David Goodsell, ATP Synthase, December 2005 Molecule of the Month

… Mitochondria use the energy from oxidizing food to pump protons out of the cell, creating a voltage of 170mV across the cell. This voltage causes a complex enzyme to spin, and the mechanical energy of this spinning enzyme creates the ATP molecules that energize the rest of the cell.

…these enzymes spin at up to 700 revolutions per second, which is faster than a jet engine. …

If you’re interested in more about this mechanical motor, you’ll probably enjoy PDB’s molecule of the month article.

(There’s also a longer narrated version at the BioVisions website.)

The above text is by Ken Shirriff.

It makes sense to me that if my muscles do things on the order of hundredths of seconds, then the chemical interactions to cause something like “arm, go up” has to be happening several orders of magnitude below what my consciousness evolved to notice.

Hearing the speeds of biological molecules made me wonder how heavy / fat these fast-moving molecules are relative to hydrogen (familiar Schroedinger stuff) or quantum chemistry. DNA is apparently 6 orders of magnitude heavier than hydrogen ion.

Follow-up thought on gerontology: If you think on the decades scale, your body starts falling apart after 3 or 4 and is pretty much useless by 8, 9, or 10 — if it even lasts that long. But think about how many molecular things have to happen to make you be yourself for even a minute. Let’s say it’s tens of millions. Then multiply that by 100 trillion cells and a 60×24×365×10 = 6½ orders of magnitude difference between a minute and a decade, for a total O(10^28) molecular thingies to make a life. That’s not so short.

Robert Sapolsky on Language and schizophrenia

  • importance of FOXP2
  • Take away FOXP2 from mice and they talk less complexly.
  • Give mice our human FOXP2 and they talk more.
  • Humans missing FOXP2 can’t do they no talkin be wrongly.
  • Babel → pidgin → creole
  • all creoles have the same grammar
  • …smells like…one inherent human language???
  • ecological factors: rainforest & biodiverse ecosystems tend to produce polytheistic cultures (more linguistic diversity, “more diversity” in many areas)
  • 90% of Earth’s languages will be extinct in not so long.
  • hunter-gatherers have a higher frequency of click languages
  • "Language is how we outsmart plants" —Steven Pinker
  • language is sequential; toolmaking is sequential
  • cooperation — game theory — kin selection — and, lying.
  • Dogs put the lid on their fear pheromones by tucking their tails.
  • A lot of the brain controls facial expressions. (important if you want to lie)
  • Game theory with communication, with semanticity, with syntax, with grammar — all traits of our language — improve outcomes in the game.

Minute 23 — Schizophrenia

  • Sequential thinking is impaired. (Can’t tell a story in an order that will make sense to others.) (Actually that sounds like me.)
  • Loose associations. (Can’t keep straight within one sentence whether “boxer” refers to dog or occupation. Gold caddy vs Cadillac)
  • (So I guess homophones differ among languages and thus schizophrenics of different languages tangent predictably based on their language?)
  • Difficulties with abstraction. (Fact vs parable vs rumour) Always interpret as concrete reality.
  • "Apple, banana, orange. What do these words have in common?" "They’re all multisyllabic words." "OK, that’s true. Anything else?" "Yes. They all have letters with closed loops." Symbolic function of language not working for them.
  • "What’s on your mind?" "My hair." "Can I take your picture?" "I don’t have a picture to give." "Can you write a sentence for me?" "A sentence for me."
  • Belief that they participated in historical events.
  • "What do apples, oranges, and bananas have in common?" "They’re all wired for sound."
  • Hallucinations. The defining feature.
  • Most hallucinations are auditory but we don’t know why.
  • People experience very structured hallucinations, not random ones. But neurologically it looks random. epsilon;
  • In fact papers have been published about the most common hallucinations. Commonest voices, in order: Jesus, Satan, the political leader.
  • The story of a schizophrenic Maasai.
  • After a really abhorrent violation of social convention, they locked her away and she died. Sound familiar? Oh well, I guess she knew what was coming to her and ∴ tacitly rationally agreed to her punishment, right?
  • Nuopharmacology evolving from trying to cure hallucinations to trying to cure disordered thought.
  • Elderly schizophrenics lose the positive symptoms (hallucinations, delusions, loose associations) and the negative symptoms (flat affect and withdrawal) dominate.
  • Schizophrenia sets on in late adolescence/early adulthood—make it to  30 without it, you’re probably safe.
  • Anchored in the frontal cortex.

(por StanfordUniversity)