The Ravenous Brain: How the New Science of Consciousness Explains Our Insatiable Search for Meaning

by Bor, Daniel

  This mixing up of whole nuggets of ideas happens in various ways in the DNA code. Entire sections of genetic code (called transposons, or “jumping genes”) can jump around the genome, breaking off from one location and reattaching to another.

  The source and behavior of these bouncing clumps of genetic letters is fascinating. Some of these jumping pieces of DNA might simply be a kind of life within a life—a ragbag collection of genetic letters that has chanced upon a way of surviving and reproducing, sometimes entirely within the dense, tangled forest of DNA strands. Just as an organism evolves through the generations, stumbling upon better beliefs about the environment, so are these jumping pieces of DNA code shaped by evolution—though their world is the cramped home of the set of DNA letters. But this isn’t the entire story: If these leaping sections of genetic code cause catastrophic failure in the function of their host, the organism, then they, too, will cease to exist. At the same time, if they can in any way aid their host, then they will have a greater chance of survival themselves.

  Most of these micro replicating machines (as Richard Dawkins might call them) are in fact remnants of viral invasions. If they were officially classed as a life-form, viruses might well steal the crown as the most supremely successful types of organisms on the planet. There are more viruses than all organisms put together. Viruses have probably existed as long as life has. They can only replicate when infecting a host cell, and because of this they are not normally classed as organisms in their own right. We have an ambivalent relationship with bacteria: We know that, although some may harm or kill us, we need them in our guts to digest food. Indeed, we have what were once bacterial invaders in every living cell, in the form of mitochondria, to supply us with energy. We resolutely loathe viruses, though—all they seem to do is make us ill. But perhaps we shouldn’t be so hasty. A picture is emerging to show that viruses, too, may have their benefits.

  Viruses, even smaller on the whole than bacteria, are also the most diverse and therefore the most creative forms of replicating machines on the planet. Their adaptability allows the flu virus, for instance, to infect us year after year, while antibiotic resistance in bacteria, the more boring, less flighty cousin of viruses, usually takes some decades to build up. The whole flu virus globally mutates each year, making it far more effective against us and more dangerous (in one sense this seems particularly creative and clever of the virus, but it’s simply the result of a particularly unstable [RNA-based], fluid viral genome, with older versions losing their foothold because of mutations and widespread immunity in the infected population following the infection). Newer versions are able to infect us again, as if we’ve been exposed to a different virus.

  There are two complementary views of this viral gate-crashing of an organism. From one perspective, the virus is simply exploiting its newfound information about a decent potential home. A slight modification of this view is from the position of a single gene and the evolutionary pressures that it faces. Say this gene does indeed capture something useful about the world. It might nevertheless be amid a bunch of bad ideas, living on a sinking ship of a rather inadequate virus species. But if the virus becomes a new composite life-form, say, by turning into a portion of the DNA code within a bacterium, then this act might just save the gene from drowning, and the good idea is preserved.

  But, from another viewpoint, the host organism may not strive too hard to repel this ready-made set of potentially useful genetic ideas, since one or two may spell survival in an otherwise catastrophic environment. With these interspecies packets of DNA information, there comes the enticing possibility of a substantial innovation for the organism, of a novel perspective in a difficult, dynamic world.

  There is in fact increasing evidence that this chopping and changing of DNA is an incredibly common process, vital for evolutionary success, and present in all species, including humans. And while other interspecies gene-swapping is a powerful, though admittedly dangerous, way of absorbing new genetic ideas, by far the greatest source of evolutionary innovation is the virus.

  Although viral injections of DNA code are extremely common in bacteria, the human genome is also positively littered with viral material—as much as 50 percent of our genome consists of scars from ancient viruses burning their way into our code. But it’s also clear that some of these invasions have dramatically helped us, either by transporting useful results from other species or by shaking up our own code to give the possibility of new traits: For instance, one such viral donation of DNA is thought to have been responsible for the creation of the placenta in early mammals.

  This common genetic intermixing, either between similar species or resulting from viral invasion, raises the speculative suggestion that one reason the DNA code of life is so utterly universal is that it facilitates the injection of chunks of novel genetic ideas from diverse sources. If this is true, then even if it can so often appear to be marked by such a cruel sequence of violent battles in the external world, the whole biological realm can also be seen in part as a strangely collaborative process to optimize collections of internal, DNA-based ideas.

  COOPERATION AND DIFFERENT LEVELS OF INFORMATION PROCESSING

  In science, we know that the universe is not built on a string of an infinite number of unrelated facts. Scientists instead strive to detect the underlying patterns—the relationships between atoms of information and the overall informational structure. Interrelationships are universal and highly layered. For instance, quarks combine to make subatomic particles, which group together in the form of atoms, that bond with others in a molecule, which link up to build a protein, which interacts with other proteins in the mechanics of a living cell, which has its specific role to play inside the organ of a system of a human, who is an employee in a department of the regional building of a national sector of a global firm with branches all over a planet orbiting a star that is part of a galaxy.

  Humans have an unrivaled intellect with which to detect, reflect, and amplify information structures. But if information processing really is a deep river surging through all life, it’s natural to assume that one of its major veins will be the representation of structure and levels of meaning in the biology of the cell.

  The celebrated evolutionary biologist Richard Dawkins has made famous the idea of “selfish genes,” whereby the prime locus of evolution is the genes that travel through time, passing via reproduction from one host to the next. Hosts are simply organisms, though in Dawkins’ language they are termed “survival machines.” Organisms are relegated to being the mere carriers of those collections of genes, each of which evolution has molded to be a supreme, selfish survivor across the generations. There is no doubt that the concept of a selfish gene is a powerful one, backed up by considerable evidence.

  In many genomes, though, one needs to go a level below that of genes to find the true winners (Dawkins’ definition of “gene” is different from the standard one, and he would class selfish, noncoding DNA as genes, too). Smaller sequences of DNA, not coding for proteins—and therefore not classed as genes in the standard definition—sometimes nicknamed selfish DNA, can hide quite happily in a genome and even replicate like crazy. For instance, there are thought to be up to a million copies of the Alu sequence in each human, constituting a staggering 10 percent of our genome, even though this sequence doesn’t actually code for any protein. No organism is likely to ever support such utterly prolific, selfish reproduction of a gene. But these tiny sequences of DNA have found winning ways to live and breed within the world of the chromosome, remaining largely invisible to the rest of the cell, let alone the outside world.

  Evolution isn’t confined just to genes, though, or to their baby brothers, these small DNA strands. Darwin’s theory of natural selection was based on the organism as a whole, and this level still, in some ways, feels like the most useful one to focus on when discussing evolutionary pressures, since it encompasses not just the sum of each individual gene within a creature’s genome, but also any g
enetic ideas that emerge over and above this simple sum, via the complex ways that genes and their effects can interact. For instance, the creation of the human brain involves thousands of genes in an incredibly sophisticated, intricate collaborative enterprise.

  Occasionally there may well be more purely selfish genes that survive in ways that inhibit the survival of the host. Humans are prone to so many genetic disorders that it’s amazing we survive at all. Actually, if some selfish gene were really disadvantageous to its host, at least early in life, the host would die before reproducing, and the gene would be lost. Over many generations, the gene, on average, that promotes the well-being of the host is more likely to hitch a successful ride through the generations. So there is a pressure for genes to be selfish, but in an enlightened way, to collaborate, coordinate, and play their small part in ensuring that their host, this “survival machine,” flourishes.

  Admittedly, it is somewhat a matter of perspective, but I believe something is missing from the view of evolution as individual genes striving for immortality via this hopping maneuver between organisms. Instead, a more parsimonious way to describe evolution may be that it is an active competition of ideas for survival, with those concepts more accurately capturing relevant details of the world being more likely to persist. This is a deliberate overgeneralization—such a definition would include fields such as the scientific enterprise and capitalism. Crucially, though, for biological evolution, although this perspective shares the assertion with the selfish-gene position that organisms may just be stepping stones for something more central to persist through time, this ideas-centric definition places no limits on the domain in which evolution works, potentially applying to any level at which ideas compete.

  Another, related difference is that a selfish-gene view would prefer a gene to resist any form of change, whereas the ideas-centric view would assume that a gene may welcome change in its own code, if this is related to a better idea, including one that is represented collectively by a set of genes. Dawkins has argued that manipulations in mutation rates, say, are the selfish imposition of a single mutation-causing gene on the unwanted identity changes of all the others. In heavy contrast, a perspective of evolution in terms of the primacy of blind ideas would suggest that all genes may appreciate such erosion of their identity, when it’s clear that their ideas aren’t fitting with the world, and that such a manipulation of mutation rates, in such a pointed way, and as a reaction to heavy stresses, is a solid collective strategy to increase the chances of finding saving innovations.

  This potential for atoms of ideas to be built up to higher concepts is a crucial feature of evolution. If my mind could not ever combine basic features of the world into objects or categories, if all memories for me could only be incredibly simple, single ideas, such as “black” or “a dot,” instead of “computer” or “fruit,” then my understanding of the world would utterly disintegrate. Similarly, many ideas might well apply at the simple level of the gene, but other, more sophisticated, and possibly far more useful, blind beliefs might require the complex interaction of hundreds of genes; at higher levels, certain concepts might even exist only by the way that many organisms behave as an ensemble. Intriguingly, there may well be an evolutionary pressure toward these more advanced ideas, made up of lower-level components, since these compound concepts would tend to be more accurate, intelligent, and powerful.

  Indeed, the most common level for useful ideas to emerge is almost certainly that of combinations of genes. In analogous fashion, massive cooperation is an integral aspect of how the brain processes information: A single neuron represents only a tiny portion of one memory, say the face of my daughter, but it will also represent tiny portions of thousands of other memories, too. My memory of my daughter’s face is not carried by a single neuron, but is the emergent property of the interactions of thousands. Likewise, a complex multicellular organism will have tens of thousands of genes or more, and any one gene might have multiple functions and only play a small part in creating any one trait. One very telling, multilayered example of this point is that 20,000 genes, 80 percent of the entire genome, are required to create your brain and to support its proper functioning so that your consciousness will flourish.

  Even before true life began, chemical components within a proto-creature would almost certainly have combined to make a conglomerate that carried an idea that was better than the sum of its parts. There was no design or magic to this blind insight—just the random combination of physical building blocks, and an evolutionary pressure to favor any possibilities that were superior at remaining stable and making copies. Within life, there is enormous scope for the emergence of complex ideas formed from groups of genes, owing to the millions of generations and billions of interacting genetic ideas that each single organism represents.

  Some forms of bacteria, for instance, combine forces in aggregates, generating far more successful defenses than is possible alone, and within this collaborative structure different bacterial cells can even take on different roles, so that they closely resemble a multicellular organism. One stage further, true multicellular organisms use extensive division of labor, with many different cell types each playing their small part in keeping the organism alive and able to reproduce.

  Although there are famous cases of close, intelligent collaboration among animals, such as social insects, there is increasing evidence that plants communicate and collaborate as well. For instance, reminiscent of wealthy older people becoming philanthropists, Douglas firs have been known to share soil resources with saplings of the same species (not just direct progeny) via underground fungal networks. And when tomato plants are attacked, they release both airborne and underground chemicals that neighboring plants can read in order to raise their own defenses.

  It also appears, intriguingly, that some ecosystems that are particularly robust to change manage to self-organize structural properties. In Niger, for example, there are sections of dense vegetation alternating with barren regions, forming patterns resembling a tiger’s stripes, so that ecosystems can continue to maintain some vegetation even when the average resources would otherwise be too low to support it.

  This possible, high-level, “intelligent” information processing still has its foundations within the DNA that is the ultimate source of such behavior. But the connection between this top-level, ecosystem-based idea and a single section of DNA is increasingly remote: This concept at the apex of an informational hierarchy is supported by the knitting together of ideas on each of the multiple levels below (ecosystem above collections of organisms above physical characteristics of those organisms above the interaction of genes, and so on). Perhaps this relationship is just as remote as that between a conscious thought and the activity of a single neuron.

  And although talking about evolution beyond the realm of the organism is controversial, wherever there are competing ideas between information carriers capable of change, something resembling evolution in all but name may well occur.

  It’s possible that some particularly complex ideas can really only be supported by a group of organisms, and that if an idea helps keep them all alive, then, again, evolution could, in principle, step in to favor this information chunk. Although the transmission of that information down the generations still involves genes, the point of evolutionary pressure essentially resides at the level of the concept, in this case the group of creatures, as if they were a single system. In similar fashion, we wouldn’t claim that the stock market rose 1 percent today because of the physical laws that govern how fundamental particles interact, even though the stock market wouldn’t exist without such particles.

  So in this way, from the level of short sections of DNA all the way up to ecosystems and beyond, evolutionary pressures could in principle weed out those ideas incongruent with survival, while favoring any concepts that capture something accurate and crucial about the world. And one part of this process may well be the encouragement of the complex combination of ideas at t
he lower level to form more enlightened blind concepts a level above.

  GENIUS CELLS

  So far I’ve only discussed information management within DNA. But if the other organisms around you are performing the same genetic informational tricks, how do you inch ahead in the evolutionary arms race? One potential way is to start storing and changing information using other tools within a cell, to build additional layers, not just in terms of the domain and structure of ideas, but also in their computation.

  In almost every realm imaginable, science has been revolutionized by computers. For a couple of days last week, I analyzed a large fMRI dataset—or rather my computer did, since there were well over 3 billion calculations needed to reach the results. Computers are unrivaled tools for the scientist, helping enormously in both the collection and analysis of information.

  Similarly, if an organism won the random mutation lottery and got its hands on a better biological form of computation, the rewards would be enormous.

  So far, DNA-based ideas can only get updated by evolution; in other words, by generations of organisms passing by, and those with genes—or collections of genes—that are able to persist over time being selected over those that cannot. That is in some ways a painfully inefficient way to learn something about the environment, with many millions of life-forms extinguishing before the lesson is fully learned. A far better approach would be to gather relevant knowledge about the surroundings within the lifetime of the organism.

  This sounds like the realm of animals, but in fact many single-celled organisms, including bacteria, process information in this dynamic way.