Art can be used to engage people in science, and science can provide a subject for art, and in various ways, the twain shall meet.

But in Reductionism in Art and Brain Science: Bridging the Two Cultures, Erik Kandel does something both more extreme and more specific than simply joining the two endeavors. Kandel has a long career in the neurosciences, and a long standing interest in art, and he’s combined these two lived experiences to make a very interesting book.

Reductionism is the distillation of something complex into something simpler while still maintaining central or key meaning. Grab the nearest art book and find two pictures of the same thing, one with nearly photographic detail and the other using just a few colors and shapes. Like this:

See the difference? Two bulls, not the same picture.

I won’t show you a picture of science being reductionist because science is reductionist most of the time.

You can reduce art, and you can reduce science. And, you can artfully reduce science and scientifically reduce art. And, the New York School of abstract art and other abstract traditions (people like Turner, Monet, Pollock, de Kooning, Rothko, Louis, Turrell, and Flavin, Kandinsky, Schoenberg, and Mondrian) scientifically reduced art, which forms a good part of the focus of Kandel’s book. A major contribution of this work is a deep and unique understanding of the origin of what we generally call modern art.

The book includes excellent illustrations, is carefully documented, and comprises a scholarly work accessible by any interested party.

Here’s the TOC:

Part I: Two Cultures Meet in the New York School
Introduction
1. The Emergence of an Abstract School of Art in New York
Part II: A Reductionist Approach to Brain Science
2. The Beginning of a Scientific Approach to the Perception of Art
3. The Biology of the Beholder’s Share: Visual Perception and Bottom-Up Processing in Art
4. The Biology of Learning and Memory: Top-Down Processing in Art
Part III: A Reductionist Approach to Art
5. Reductionism in the Emergence of Abstract Art
6. Mondrian and the Radical Reduction of the Figurative Image
7. The New York School of Painters
8. How the Brain Processes and Perceives Abstract Images
9. From Figuration to Color Abstraction
10. Color and the Brain
11. A Focus on Light
12. A Reductionist Influence on Figuration
Part IV: The Emerging Dialogue Between Abstract Art and Science
13. Why Is Reductionism Successful in Art?
14. A Return to the Two Cultures

Burke Medical Research Institute Scientists Show Axon Growth Possible in Central Nervous System

White Plains, NY – May 21, 2014 –Recent findings by Burke Medical Research Institute scientists could one day pave the way for new treatments for spinal cord injuries. The study, published as a cover story, with commentary, in the current issue of the Journal of Experimental Medicine, found, for the first time, that activating a protein known as B-RAF promotes the regeneration of injured axons in the central nervous system of mice. Until now, it was thought that axons—which conduct signals between neurons—could not re-grow or be restored after an injury in higher animals such as mice, or in humans. Injuries, such as those affecting the spinal cord, can damage these axons, making their regeneration an important first step towards possible recovery.

Since earlier studies found that axon growth can be blocked by disabling B-RAF, the researchers wanted to find out if activating B-RAF could—in contrast—help promote axon growth and regeneration.

The team, led by Jian Zhong, Ph.D., director of the Molecular Regeneration and Neuroimaging Laboratory at the Burke Medical Research Institute in White Plains and assistant professor of neurology and neuroscience at Weill Cornell Medical College in New York City, found that axon growth was promoted in three distinct scenarios. These were: in a developing mouse embryo that didn’t have an important normal axon growth signal, in injured sensory neurons whose axons grow into the central nervous system, and then in an injured optic nerve, which is part of the central nervous system.

“Not very long ago, we were not sure if neurons in the mammalian central nervous system could ever regrow axons to any useful lengths at all,” said Dr. Zhong. “Now, we see that by activating the B-RAF protein, the possibility is there. And that possibility could lead to exciting progress in the field of spinal cord injury treatment and rehabilitation.”
While there is no conclusive data on spinal cord injury at the moment, the optic nerve data makes it very likely that the B-RAF activation will also stimulate regeneration after spinal cord injury—though additional research needs to be done, said Dr. Zhong.

“These significant findings represent the importance of basic research for rehabilitation and the effects it will continue to have on how we approach treatment and help patients with various injuries, including those to the spinal cord,” says Rajiv R. Ratan, M.D., Ph.D, executive director of Burke Medical Research Institute and professor of neurology and neuroscience at Weill Cornell Medical College.

Scientists from the Burke Medical Research Institute included Dr. Zhong as well as Kevin J. O’Donovan, Ph.D., Kaijie Ma, B.M., and Hengchang Guo, Ph.D. Also contributing to the study were scientists from Harvard Medical School, Temple University School of Medicine, Icahn School of Medicine at Mount Sinai, and Centre Hospitalier Universitaire de Quebec in Canada. The study was supported by the National Institutes of Health, the Whitehall Foundation and the Burke Foundation.

Kurzweil presents a provocative exploration of the most important project in human-machine civilization—reverse engineering the brain to understand precisely how it works and using that knowledge to create even more intelligent machines.

Kurzweil discusses how the brain functions, how the mind emerges from the brain, and the implications of vastly increasing the powers of our intelligence in addressing the world’s problems. He thoughtfully examines emotional and moral intelligence and the origins of consciousness and envisions the radical possibilities of our merging with the intelligent technology we are creating.

Certain to be one of the most widely discussed and debated science books of the year, How to Create a Mind is sure to take its place alongside Kurzweil’s previous classics.

I think there are three key ideas in this book about which I have varying opinions. First, he presents a model of how the brain works. Second, he suggests that we can, in essence, reverse engineer the brain using computing technology. Third, he discusses the rate at which computing technology becomes more capable of doing such a thing, both qualitatively and quantitatively. He ties these idea together with reference to artificial intelligence theory.

Regarding the second point, I have no doubt that we will someday be able to produce a non-biological brain. Brains are physical entities that emerge with very little specification as to architecture, have incredibly dense circuitry that carries enough information for otherwise reasonable people to assert that its information storage capacity is infinite (which it is not, of course), and that involves interactivity among components that allows for some amazing things to happen. I think that when we get close to making a mechanical brain, we would probably want to set aside many of the ways in which actual brains function, in order to create a more effective computing solution, because the brain is a product of Natural Selection and is thus not necessarily all that well deigned. The trick will be sorting out that which is good design for mechanical implementation of human braininess from that which is not good design. Regarding the third point, the expansion of computational abilities, I’m sure the basic ideas Kurzweil lays out are reasonable but furturism about technology seems to run into the same problem over and over again: Somebody invents a qualitatively distinct way of doing something that totally changes the game, and after that, this new way of doing things quantitatively evolves. Predicting the qualitative shifts has been difficult.

My biggest problem with Kurzweil’s book is in relation to the first point, a theory about how the brain’s cortex works. He asserts that the cortex is a self organizing entity that responds to information, creating an ability to manage and recognize patterns. My problem with this is that Kurzweil seems to have not read Deacon’s work (such as The Symbolic Species: The Co-evolution of Language and the Brain and Incomplete Nature: How Mind Emerged from Matter. I’m not saying that Kurzweil is wrong in thinking of the cortex as self organizing in response to the challenges and inputs of pattern recognition. I’m simply saying that this property of the cortex, and of the human mind, has already been identified (mainly by Deacon) and that Kurzweil should sit down with Deacon and have a very long conversation before writing this book! (Well, ok, the next book.) I don’t think they’ve done that yet.

An oystercatcher is a wading bird of the family Haematopodidae, distributed in one genus, Haematopus. As is the case with many coast loving birds, there has been confusion about the limits of the 11 or so species known to exist worldwide. That itself is an interesting story (Hocke 1996), but one we will not go into now.

Adult coastal oystercatchers (some species are not coastal) eat all sorts of animals found in the intertidal zone, including shellfish of all sorts, depending on availability. They get their name from their tendency to prey on bivalves (including oysters). Oystercatchers have long heavy beaks which allow them to open these bivalves using various methods (de Hoyo, 1996). At least one method they use for this is to jam the beak into the bivalve and cut the muscle that normally would be used by the bivalve to “clam up.” This strategy is thought to be dangerous, because if the bivalve closes on the beak, then you’ve got this damn bivalve attached to your beak for the rest of the day. If the bivalve in question happens to be attached to the substrate (as are oysters and mussels, typically), then the Foraging Fail is more serious; The bird may have shoved its head under water to get at the bivalve. If not, the tide may be on its way in anyway. Either way, the bird may drown.

Here’s the interesting evolutionary story, which has to do with development.

Adult oystercatcher photo by Steppeland Click here for attribution

Adult oystercathers have a long beak and long legs to facilitate intertidal feeding behaviors, including wading and bivalve predation. But one method of bivalve predation is potentially deadly. So, baby oystercathers have to learn how to do this. Trial and error is not an option. The very first error a baby oystercatcher makes may be its last earthly act before going off to oystercatcher heaven (and there is no oystercatcher heaven). Instead, they must learn using some other learning method. One might expect oystercatcher genes to be selected to make oystercatchers automatically good at this dangerous act. The problem here is that the neural mechanisms underlying the process are higher order integrative systems using a wide range of sensory inputs and motor commands. Organisms with brains can’t evolve pre-programmed genetically tuned neural mechanisms that operate at any level of detail. The brain that runs this finely tuned process must be shaped by experience (learning).

What we see in nature is this: Baby oystercatchers follow their mothers around all day, every day, for many days, watching, watching, constantly watching. They internalize what they are observing, and after many instances of observing the bivalve predation technique, are able to do it.

Baby oystercatcher Photo by Haukur H. Click here for original

That part is interesting; Oystercatchers are an example of evolution NOT solving a complex behavioral problem by pre-programming neural circuits at a fine level of detail. This conforms to what we know about how brains develop (Deacon 1997). It is very difficult or impossible to pre-program complex cortical functions such as language, general intelligence, mathematical abilities, or even something simpler like catching an oyster using genes coding for neural connections. Rather, experience (learning, environment, culture) shapes the brain during development.

And, this part is also interesting (and in relation to oystercatchers, most interesting): The baby oystercatchers, while following around their mothers with their brains being shaped by experience to attain the appropriate skill level, retain a small and ineffective juvenile beak. The babies are incapable of trying what may well be fatal until some time in their development when a hormonal shift occurs, causing their beaks to grow to adult size. It did not have to be this way: It is not true that baby birds typically have non-adult beaks until the last minute (though there is a wide range of developmental trajectories for bird beaks). The long-retained small beak, caused by the timing of hormonal development, facilitates learning in the particular way that conforms to the overall oystercatcher adaptation.

Well, that certainly is a nice story, but it is also based on common knowledge of bird behavior, development, and ecology. How do we really know that oystercatchers actually risk death while foraging for bivalves? Well, we know this because we know this. This is probably one of those pieces of knowledge that is generally known by natural historians, is written down as a generalization in a number of authoritative or semi-authoritative books, and for which there is a handful of anectdotal examples buried somewhere in the pre-PDF, pre-Google, pre-Medline ancient literature. And therefore, lost in obscurity and of no possible value.

But wait, there are scholars who still read actual books and printed journals! And it turns out, this can be useful and interesting. There is indeed an ancient, obscure anecdotal case, and it is brought to us via Tetrapod Zoology Blog. In Clam attacks and kills oystercatcher, Darren Naish describes a publication from 1946 in The Auk (a classic bird journal) in which a brief account is provided of an oystercatcher having got its beak stuck in the clam, as it were.

In this case, an adult Haematopus palliatus (American oystercatcher) got its beak stuck in a Mercenaria mercenaria (hard shelled clam) in South Carolina, in 1939.

It drowned, and the soft tissue of its neck was scavenged by crabs. What a way to go.

Baldwin, W. P. (1946). Clam catches oyster-catcher The Auk, 63, 589-589

Deacon, T. (1997) The Symbolic Species: The Co-Evolution of Language and the Brain. Norton.

Hockey, P (1996) Family Haematopodidae (Oystercatchers) in del Hoyo, J.; Elliot, A. & Sargatal, J. (editors). (1996). Handbook of the Birds of the World. Volume 3: Hoatzin to Auks. Lynx Edicions. ISBN 8487334202

del Hoyo, J., Elliott, A. and Sargatal, J. (1996) Handbook of the Birds of the World. Vol. 3: Hoatzin to Auks. Lynx Edicions, Barcelona.

Hat Tip: Virginia Hughes. Who also has something interesting on Coffee.

Larger brains have evolved a number of times. It seems that there has been a trend over several tens of millions of years of evolution of larger brains in various clades, such as carnivores and primates. There is probably a kind of arms race going on among various species in which a larger brain is an asset.

However, as you imply, a really large brain (like the extraordinarily large human brain) seems to be very rare. One of the reasons for this is that there are at least two major kinds of costs of a large brain that outweigh the benefits. One kind of cost is the energetic expense of having this large brain. Over 10% of the day to day energy demands of an adult human go to the brain. The total energy requirement of an infant can be over 60% while the brain is both a relatively large proportion of the infant’s body, and is undergoing a great deal of growth. The brain tissue is very picky about things like the temperature it requires for normal function and the kind of nutrient it needs.

The other negative, which is also a positive, is that behavior mediated by cerebral function (roughly, “thinking”) requires learning. Organisms with larger brains are not born “knowing” what to do. This is a benefit because it allows for more flexibility in behavior and it allows for kinds of behaviors that probably can’t be “programmed” genetically. The down side is that a lot of learning needs to happen, and it has to happen in the right way, or you get a dysfunctional individual.

The challenge of behavioral biologists interested in humans is to ascertain how the costs and benefits of a large brain interact with the environment of adaptation in which we see this large brain emerge over evolutionary time.

How many species of early hominid existed at any one point in time?

Sahelanthropus tchadensis, Orrorin tugenensis, Ardipithecus ramidus, Australopithecus anamensis, Australopithecus afarensis, Kenyanthropus platyops, Australopithecus africanus, Australopithecus garhi, Australopithecus aethiopicus, Australopithecus robustus, Australopithecus boisei, Homo habilis, and Homo georgicus is a short list of species that lived from about 6.5 or so million years ago to about 1.8 million years ago. Many of them lived during the “golden age of the hominid” between about 4 and 2 million years ago. There are others not listed here that are being or have recently been proposed.

With some clades of primates, we know that the species differences are seen entirely or almost entirely in the non-skeletal parts. This suggests that this number of species is a severe underestimate of the actual numbers. We also know that many primates have moderate size or small ranges, and this list comes from only a handful of localities across the region in which hominids lived, so there must be more species living in areas not sampled by the fossil sites. And, the rate of discovery of new species has not slowed down, or at least, it is reasonable to say that we can expect that the more that we look, the more we find, for the foreseeable future.

So the prospect that several, perhaps quite a large number, of hominid species would have existed at one point in time across most of Africa and possibly west Asia, is a near certainty. You would need a guidebook to figure out what you were looking at if you went back in a time machine to this region.

How many of them interacted and what was this interaction like?

Another common feature of primates is that many social primates do get into inter-species groups. There are various advantages to this. As long as food competition is minimal, mixed species groups may form to decrease predator pressure, for instance.

My personal feeling is that there was likely a fair amount of interaction between different hominid species. One reason for this is that not long after the first appearance of chipped stone tools, we see them in the record over a fairly large area. My guess (and it is only a guess at this point) is that stone tool use is more widespread at, say, 2.2 million years ago than it could have been if it was only practiced by one species. Interaction among species would facilitate the spread of this technology. That is only a guess, of course, and there are a lot of other ways to look at the data.

What caused those that disappeared to do so?

Perhaps there was a mass extinction related to increaced drying of the environment between 2 and 1.5 million years ago. Perhaps the rise of Homo erectus led to all of the others being outcompeted (or eaten for food!?) I find it interesting that relatively little is written about this. This may be in part because the time period we need to understand has fewer well dated deposits with fossil than we would like to address such questions.