Suzana Herculano-Houzel’s “The Human Advantage”

L 341: The preface opens with the question “Are we special?” and concludes that we are not. I disagree and cite the author’s evidence in the preface. Having an advantage is special. I suspect there is some PC war going on among biologists around the word ‘special’ (and ‘progress’). I think her biology is fine.

L 508: I am confused here as I am in all similar books on whether there is an assumption that the brains of our ancestors of more than 4 million years are like no animal brains today. Today’s animal brains have evolved too, but I suspect not as much. I take it that there are no species alive today with brains much like any of our ancestors since 4 MYago, until recently, of course.

L 551: Why is the ratio of brain mass to organism mass relevant? Just because von Heller proposed so? What is magic about “isometric growth”? One reason that big animals have big brains is that they can afford them. Big brains can be smarter than small brains and this leads to big brains and big animals to afford them.

L 652:

Is he saying that the eye of the large animal has more pixels? If that is what means, that is what he should say. I know physical scaling laws and it takes less computing to drive a scaled up version of a vehicle. If it is scaled up by a linear factor of s then the time scales by s−½. There is an obvious and simple question here: “Has a large animal more muscles than a small one?”. If so, that is not a simple scaling phenomenon. Instead of weighing the brain, they should count its neurons.

L 705:

OK that’s better.

L 756: “Genetic and cellular particularities aside, could it be that the simplest reason for our remarkable cognitive capabilities, matched by none, was a remarkable number of neurons?”
Ahh, at last.

L 841: I think the book turns a corner here.

Intelligence has been bred out of cows but their brains did not get smaller.

L 895:

This is like polling people. Statisticians have ways of counting people even in states like Nevada where there is even more clustering. The author has a good scheme, however.

L 955: The soup idea is good. One could divide the brain along classical parts and get even much mode detail.

L 1378: I am not impressed with the exponent n (allometrc exponent) in the relationship
neuron count = (brain mass)n
It does not tell me anything.

This advantage seems not to apply to small primates. Perhaps there is an unspoken assumption that large primates are newer and that the advantage arises as we evolve to larger species. This assumption may be correct but it should be made explicitly. In other taxa later species are not always larger.

I propose that the primates evolved some as yet unidentified brain advantage that considerably increased the adaptive advantage on a large neuron count in the cortex. This in turn caused pressure for bigger brains and in turn pressure for bigger primates to hold them. This also explains the anomalous exponent.

Perhaps an equally good proposal is that the new primates had a mutation that let us pack more neurons in a given space. But that would not explain the anomalous exponent.

This logic is perilous for the monkeys are not older then humans. Must we assume that today’s monkey has the same neuron counts as our common ancestor? (The author soon admits (L 1429) to some of these problems.)

L 1436: I do not believe that neuronal scaling rules are in the DNA except perhaps that there is something in the DNA that impacts the advantage of high neuronal count.

L 1615:

Nature seems to have simple default scaling rules. They works pretty well for most things. For hardware that deals with information (nerves) they are all wrong. Somehow evolution discovered that with the primates. I suggest the question to ask is “How are the default rules implemented?”. A slightly different proposal is that some yet unnoticed mutation in early primates (logic, whatever) made more neurons much more advantageous.

L 1521:

That is the nearest the author has come to saying that smaller is earlier, and incidentally that in a lineage, the common ancestor was more like the smaller. Other books make this same silent assumption as well.

L 1706: The previous section speaks about where signals go. We need much more such information— the connectome.

L 1904: I am at a loss to know what “The brain of a human is too big for its body.” means.

L 2185:

I don’t buy that, but I grant it is a good hypothesis. Neuron count is not the only thing that our DNA controls. I suggested earlier that early primates had a mutation leading to much selective pressure for a higher neuron count.

L 2563: “It comes as no surprise that the largest animals have the largest brains.” Clearly said, but I disagree. The only explanation of this that I see is that a larger animal can afford a larger brain, and the larger brain is better. If bigger isn’t better, why change? I know why bigger animals need bigger legs and that reason does not apply to the brain. If bigger is better then we can imagine that we evolve to be bigger in order to feed a bigger better brain. This has all to do with the gradient of “Mt. Improbable”. Figure 8.1 suggests that there are additional advantages of big. The author goes on to express some of these ideas.

L 3080:

One reason not to change is that some solution was found early that was close to optimal and no improvement was possible.

L 3221:

A neuron devoted to long term memory should not need to fire very often.

L 3248:

That is the optimistic comment. The pessimistic comment is “We do not idle efficiently.”. Incidentally, neither do modern CPU’s.

L 3285: I get 3∙10−10 Watts per neuron. That makes 25 Watts per human brain.

L 3853: The author admits, in her footnote, an “abundant evidence of small and large genetic changes of consequence to human anatomy and physiology”. I would suggest even more changes in our DNA that directs brain morphogenesis aside from neuron count.

I agree with the epilog. Being upright with an opposable thumb is a great benefit. Getting more cerebral cortex neurons was difficult and necessary. I think it is not the whole brain story, however. Whether the ‘rest of the story’ is more important is not the question.

I am a quarter way thru the book and I am feeling set up, but set up in the best sense of the word. You might detect impatience in my notes as I read. Then later things turn out as I wanted as if the old ideas were presented to be shot down.

There seems to be an assumption, unspoken here and in some other books that:

I think that the bottom line is that the neuron count of the cerebral cortex, and especially the frontal cortex makes us us. This is what a computer designer would expect. Cooking made that possible. (constant density of glia too)
The author’s site. The TED talk there is a good brief summary of the book.
The numeric labels of the horizontal axis of figure 8.1 are wrong. I think that the “100,000” should be moved right one factor of 10.
Olszewsky’s name is misspelled as Olzewsky’s three times in the book.