brain

All posts tagged brain

Book review: Other Minds: The Octopus, the Sea, and the Deep Origins of Consciousness, by Peter Godfrey-Smith.

This book describes some interesting mysteries, but provides little help at solving them.

It provides some pieces of a long-term perspective on the evolution of intelligence.

Cephalopods’ most recent common ancestor with vertebrates lived way back before the Cambrian explosion. Nervous systems back then were primitive enough that minds didn’t need to react to other minds, and predation was a rare accident, not something animals prepared carefully to cause and avoid.

So cephalopod intelligence evolved rather independently from most of the minds we observe. We could learn something about alien minds by understanding them.

Intelligence may even have evolved more than once in cephalopods – nobody seems to know whether octopuses evolved intelligence separately from squids/cuttlefish.

An octopus has a much less centralized mind than vertebrates do. Does an octopus have a concept of self? The book presents evidence that octopuses sometimes seem to think of their arms as parts of their self, yet hints that their concept of self is a good deal weaker than in humans, and maybe the octopus treats its arms as semi-autonomous entities.

2.

Does an octopus have color vision? Not via its photoreceptors the way many vertebrates do. Simple tests of octopuses’ ability to discriminate color also say no.

Yet octopuses clearly change color to camouflage themselves. They also change color in ways that suggest they’re communicating via a visual language. But to whom?

One speculative guess is that the color-producing parts act as color filters, with monochrome photoreceptors in the skin evaluating the color of the incoming light by how much the light is attenuated by the filters. So they “see” color with their skin, but not their eyes.

That would still leave plenty of mystery about what they’re communicating.

3.

The author’s understanding of aging implies that few organisms die of aging in the wild. He sees evidence in Octopuses that conflicts with this prediction, yet that doesn’t alert him to the growing evidence of problems with the standard theories of aging.

He says octopuses are subject to much predation. Why doesn’t this cause them to be scared of humans? He has surprising anecdotes of octopuses treating humans as friends, e.g. grabbing one and leading him on a ten-minute “tour”.

He mentions possible REM sleep in cuttlefish. That would almost certainly have evolved independently from vertebrate REM sleep, which must indicate something important.

I found the book moderately entertaining, but I was underwhelmed by the author’s expertise. The subtitle’s reference to “the Deep Origins of Consciousness” led me to expect more than I got.

Book review: The Human Advantage: A New Understanding of How Our Brain Became Remarkable, by Suzana Herculano-Houzel.

I used to be uneasy about claims that the human brain was special because it is large for our body size: relative size just didn’t seem like it could be the best measure of whatever enabled intelligence.

At last, Herculano-Houzel has invented a replacement for that measure. Her impressive technique for measuring the number of neurons in a brain has revolutionized this area of science.

We can now see an important connection between the number of cortical neurons and cognitive ability. I’m glad that the book reports on research that compares the cognitive abilities of enough species to enable moderately objective tests of the relevant hypotheses (although the research still has much room for improvement).

We can also see that the primate brain is special, in a way that enables large primates to be smarter than similarly sized nonprimates. And that humans are not very special for a primate of our size, although energy constraints make it tricky for primates to reach our size.

I was able to read the book quite quickly. Much of it is arranged in an occasionally suspenseful story about how the research was done. It doesn’t have lots of information, but the information it does have seems very new (except for the last two chapters, where Herculano-Houzel gets farther from her area of expertise).

Added 2016-08-25:
Wikipedia has a List of animals by number of neurons which lists the long-finned pilot whale as having 37.2 billion cortical neurons, versus 21 billion for humans.

The paper reporting that result disagrees somewhat with Herculano-Houzel:

Our results underscore that correlations between cognitive performance and absolute neocortical neuron numbers across animal orders or classes are of limited value, and attempts to quantify the mental capacity of a dolphin for cross-species comparisons are bound to be controversial.

But I don’t see much of an argument against the correlation between intelligence and cortical neuron numbers. The lack of good evidence about long-finned pilot whale intelligence mainly implies we ought to be uncertain.

Connectomes are not sufficient by themselves to model brain behavior. Brain modeling has been limited more by the need for good information about the dynamic behavior of individual neurons.

The paper Whole-brain calcium imaging with cellular resolution in freely behaving Caenorhabditis elegans looks like an important step toward overcoming this limitation. The authors observed the behavior of many individual neurons in a moving nematode.

They still can’t reliably map the neurons they observed to standard C. elegans neuron names:

The neural position validation experiments presented here, however, have led us to conclude that worm-to-worm variability in neuronal position in the head is large enough to pose a formidable challenge for neuron identification.

But there are enough hints about which neurons do what that I’m confident this problem can be solved if enough effort is devoted to it.

My biggest uncertainty concerns applying this approach to mammalian brains. Mammalian brains aren’t transparent enough to be imaged this way. Are C. elegans neurons similar enough that we can just apply the same models to both? I suspect not.

I’d like to see more discussion of uploaded ape risks.

There is substantial disagreement over how fast an uploaded mind (em) would improve its abilities or the abilities of its progeny. I’d like to start by analyzing a scenario where it takes between one and ten years for an uploaded bonobo to achieve human-level cognitive abilities. This scenario seems plausible, although I’ve selected it more to illustrate a risk that can be mitigated than because of arguments about how likely it is.

I claim we should anticipate at least a 20% chance a human-level bonobo-derived em would improve at least as quickly as a human that uploaded later.

Considerations that weigh in favor of this are: that bonobo minds seem to be about as general-purpose as humans, including near-human language ability; and the likely ease of ems interfacing with other software will enable them to learn new skills faster than biological minds will.

The most concrete evidence that weighs against this is the modest correlation between IQ and brain size. It’s somewhat plausible that it’s hard to usefully add many neurons to an existing mind, and that bonobo brain size represents an important cognitive constraint.

I’m not happy about analyzing what happens when another species develops more powerful cognitive abilities than humans, so I’d prefer to have some humans upload before the bonobos become superhuman.

A few people worry that uploading a mouse brain will generate enough understanding of intelligence to quickly produce human-level AGI. I doubt that biological intelligence is simple / intelligible enough for that to work. So I focus more on small tweaks: the kind of social pressures which caused the Flynn Effect in humans, selective breeding (in the sense of making many copies of the smartest ems, with small changes to some copies), and faster software/hardware.

The risks seem dependent on the environment in which the ems live and on the incentives that might drive their owners to improve em abilities. The most obvious motives for uploading bonobos (research into problems affecting humans, and into human uploading) create only weak incentives to improve the ems. But there are many other possibilities: military use, interesting NPCs, or financial companies looking for interesting patterns in large databases. No single one of those looks especially likely, but with many ways for things to go wrong, the risks add up.

What could cause a long window between bonobo uploading and human uploading? Ethical and legal barriers to human uploading, motivated by risks to the humans being uploaded and by concerns about human ems driving human wages down.

What could we do about this risk?

Political activism may mitigate the risks of hostility to human uploading, but if done carelessly it could create a backlash which worsens the problem.

Conceivably safety regulations could restrict em ownership/use to people with little incentive to improve the ems, but rules that looked promising would still leave me worried about risks such as irresponsible people hacking into computers that run ems and stealing copies.

A more sophisticated approach is to improve the incentives to upload humans. I expect the timing of the first human uploads to be fairly sensitive to whether we have legal rules which enable us to predict who will own em labor. But just writing clear rules isn’t enough – how can we ensure political support for them at a time when we should expect disputes over whether they’re people?

We could also find ways to delay ape uploading. But most ways of doing that would also delay human uploading, which creates tradeoffs that I’m not too happy with (partly due to my desire to upload before aging damages me too much).

If a delay between bonobo and human uploading is dangerous, then we should also ask about dangers from other uploaded species. My intuition says the risks are much lower, since it seems like there are few technical obstacles to uploading a bonobo brain shortly after uploading mice or other small vertebrates.

But I get the impression that many people associated with MIRI worry about risks of uploaded mice, and I don’t have strong evidence that I’m wiser than they are. I encourage people to develop better analyses of this issue.

Book review: The Myth of Mirror Neurons: The Real Neuroscience of Communication and Cognition, by Gregory Hickok.

This book criticizes hype from scientists and the media about embodied cognition, mirror neurons, and the differences between the left and right brain hemispheres. Popular accounts of these ideas contain a little bit of truth, but most versions either explain very little or provide misleading explanations.

A good deal of our cognition is embodied in the sense that it’s heavily dependent on sensory and motor activity. But we have many high-level thoughts that don’t fit this model well, such as those we generate when we don’t have sensory or motor interactions that are worth our attention (often misleading called a “resting state”).

Humans probably have mirror neurons. They have some value in helping us imitate others. But that doesn’t mean they have much affect on our ability to understand what we’re imitating. Our ability to understand a dog wagging its tail isn’t impaired by our inability to wag our tails. Parrots’ ability to imitate our speech isn’t very effective at helping them understand it.

Mirror neurons have also been used to promote the “broken mirror theory” of autism (with the suggestion that a malfunction related to mirror neurons impairs empathy). Hickok shows that the intense world hypothesis (which I’ve blogged about before) is more consistent with the available evidence.

The book clarified my understanding of the brain a bit. But most of it seems unimportant. I had sort of accepted mild versions of the mirror neuron and left-brain, right brain hype, but doing so didn’t have any obvious effects on my other beliefs or my actions. It was only at the book’s end (discussing autism) that I could see how the hype might matter.

Most of the ideas that he criticizes don’t do much harm, because they wouldn’t pay much rent if true. Identifying which neurons do what has negligible effect on how I model a person’s mind unless I’m doing something unusual like brain surgery.

Book review: Self Comes to Mind: Constructing the Conscious Brain by Antonio R. Damasio.

This book describes many aspects of human minds in ways that aren’t wrong, but the parts that seem novel don’t have important implications.

He devotes a sizable part of the book to describing how memory works, but I don’t understand memory any better than I did before.

His perspective often seems slightly confusing or wrong. The clearest example I noticed was his belief (in the context of pre-historic humans) that “it is inconceivable that concern [as expressed in special treatment of the dead] or interpretation could arise in the absence of a robust self”. There may be good reasons for considering it improbable that humans developed burial rituals before developing Damasio’s notion of self, but anyone who is familiar with Julian Jaynes (as Damasio is) ought to be able to imagine that (and stranger ideas).

He pays a lot of attention to the location in the brain of various mental processes (e.g. his somewhat surprising claim that the brainstem plays an important role in consciousness), but rarely suggests how we could draw any inferences from that about how normal minds behave.

Book review: The Intelligence Paradox: Why the Intelligent Choice Isn’t Always the Smart One, by Satoshi Kanazawa.

This book is entertaining and occasionally thought-provoking, but not very well thought out.

The main idea is that intelligence (what IQ tests measure) is an adaptation for evolutionarily novel situations, and shouldn’t be positively correlated with cognitive abilities that are specialized for evolutionarily familiar problems. He defines “smart” so that it’s very different from intelligence. His notion of smart includes a good deal of common sense that is unconnected with IQ.

He only provides one example of an evolutionarily familiar skill which I assumed would be correlated with IQ but which isn’t: finding your way in situations such as woods where there’s some risk of getting lost.

He does make and test many odd predictions about high IQ people being more likely to engage in evolutionarily novel behavior, such as high IQ people going to bed later than low IQ people. But I’m a bit concerned at the large number of factors he controls for before showing associations (e.g. 19 factors for alcohol use). How hard would it be to try many combinations and only report results when he got conclusions that fit his prediction? On the other hand, he can’t be trying too hard to reject all evidence that conflicts with his predictions, since he occasionally reports evidence that conflicts with his predictions (e.g. tobacco use).

He reports that fertility is heritable, and finds that puzzling. He gives a kin selection based argument saying that someone with many siblings ought to put more effort into the siblings reproductive success and less into personally reproducing. But I see no puzzle – I expect people to have varying intuitions about whether the current abundance of food will last, and pursue different strategies, some of which will be better if food remains abundant, and others better if overpopulation produces a famine.

He’s eager to sound controversial, and his chapter titles will certainly offend some people. Sometimes those are backed up by genuinely unpopular claims, sometimes the substance is less interesting. E.g. the chapter title “Why Homosexuals Are More Intelligent than Heterosexuals” says there’s probably no connection between intelligence and homosexual desires, but there’s a connection between intelligence and how willing people are to act on those desires (yawn).

Here is some evidence against his main hypothesis.

A post titled Neanderthals had differently organized brains reports evidence that Neanderthal brains did not have a larger volume devoted to intelligence (or at least that part of intelligence needed to handle social interactions in large groups) than humans.

A key fact is that “eye-socket size is correlated with latitude” – at least within a species.

Neanderthals were adapted to high latitudes, and had larger eye-sockets.

That suggests a relatively large part of their brain was devoted to the visual cortex, and it seems somewhat plausible to suspect that much of that involved low-level processing needed to make up for darker conditions at higher latitudes.

So Neanderthals’ larger skull size doesn’t imply any important advantage.