Connectome (31 page)

For example, carving the avian brain into regions would yield coarse rules, such as “If two neurons are in HVC, they are likely to be connected to each other.” It's certainly true that a connection between two HVC neurons is more likely than a connection between an HVC neuron and, say, a neuron in a visual region called the Wulst, which doesn't happen at all. Nonetheless, this rule would still be lousy at predicting whether two arbitrary HVC neurons are connected, as this turns out to be quite improbable too.

To make the rule more accurate, it might help to divide HVC into multiple neuron types. I didn't mention it before, but our previous discussion was actually specific to just one type of HVC neuron, the one that sends axons (“projects”) to RA. This neuron type is of special interest because it generates the kind of sequential spiking characteristic of a synaptic chain. We could use it to formulate a revised rule: “If two HVC neurons both project to RA, they are likely to be connected to each other.” This more specific rule could well be more accurate.

Even better would be to make the rule depend on the spike times of the neurons during song: “If two HVC neurons both project to RA, and their spike times during song are one after the other, they are likely to be connected to each other.” If the synaptic chain model is correct, then this rule would be highly accurate at predicting connections.

If we really want to understand how the brain works, we need this third kind of rule, which depends on functional properties of neurons as determined by measurements of spiking. The coarser rules of connection, which depend on region or neuron type, get us only part of the way there. Knowing the regional connections that lead from HVC to the syrinx tells us why HVC neurons have functions related to song. But that's not enough for elucidating why different HVC neurons spike at different times during song.

Likewise, knowing regional rules of connection might tell us why the Jennifer Aniston and Halle Berry neurons do similar things—both are activated by visual stimulation—but no fan would say that they do
exactly
the same thing. We'd like to know why the Jennifer Aniston neuron responds specifically to Jen and not Halle, and vice versa. For this we need something like the part–whole rule of connection, which again depends on the functional properties of neurons.

In the most general sense, decoding connectomes means reading out the roles played by neurons not only in memories but also in thoughts, feelings, and perceptions. If we can succeed at decoding, we'll know that we've finally found rules of connection precise enough for understanding how the brain works. And then we'll be ready to return to the question that we started with, the one that motivates this book: Why do brains work differently?

In elementary school my friends and I tried not to gawk at identical-twin classmates, but we couldn't help staring as we strained to tell them apart. Photos of Siamese twins were even more riveting. We looked at them long and hard while flipping through beat-up copies of the
Guinness Book of World Records.
Twins just seemed spooky, though we weren't sure exactly why.

Native American and African myths
are full of stories about twins. The Navajo people trace their ancestry to the goddess Changing Woman. Impregnated by sunbeams, she bore twin sons named Monster Slayer and Born for Water. They grew up in twelve days, traveled to find their father, the Sun, and went on to engage in deadly combat with giants and monsters.

Many more twins figure in the world's legends and literature. Fraternal twins have always seemed special, and identical twins perhaps even magical. Why do we feel that way? For one thing, identical twins assault our bedrock assumption
that every human being is unique; we're unsettled by their alikeness. But we're also fascinated by the slight differences that are visible if we look closely.

In Greek myths, twins were often the offspring of one mother but two different fathers, one divine and the other mortal, which explained the twins' different natures and fates. Today we know that we can account for those differences by pointing to the genomes of fraternal twins, who share only half of their genes. Identical twins, however, look almost indistinguishable from each other because of their duplicate genomes. I mentioned this claim about identical twins earlier when discussing the genetics of autism and schizophrenia, but it needs some qualification. Recent genomic studies have demonstrated that tiny deviations in DNA sequence
arise during the process of twinning, the divergence of a fertilized egg into two embryos. These deviations might explain why identical twins look slightly different, and perhaps why they don't think and act in exactly the same way. But genes do not fully explain mental aspects that depend on learning. Even for twins who remain conjoined (the term that has replaced
Siamese
) instead of being surgically separated, life experiences do not match exactly. Such twins are literally inseparable, but their memories are not identical.

According to connectionist thinking, identical twins have different memories and minds chiefly because their connectomes differ. Many people have wondered what it would be like to have a twin sibling. Sometimes I fantasize about a mad scientist creating my “connectome twin,” a person with a brain that is wired exactly like mine. Would I be enraptured to meet him? Would my girlfriend grow jealous of our close relationship, complaining about yet another proof of my narcissistic tendencies? I suppose I could confide anything to my twin, who would be guaranteed to understand me. Then again, maybe it would be boring to pour out my problems to someone who thinks in exactly the same ways.

And what if, after a week of getting to know each other, we were kidnapped by a team of crazed gunmen? Let's say they decide to shoot one of us and send the body along with the ransom note, as proof of abduction. Should I fear being shot, or should I be altruistic and volunteer to take the bullet? Maybe it doesn't matter, as all my memories and personality will survive in my twin even if I die, and vice versa. But wait. A week has passed since the mad scientist breathed life into my replica. Our connectomes have been changing since then. They diverged from the first instant after duplication, so our minds are no longer identical.

Luckily I'll never be forced to engage in the head-scratching required to solve this distressing philosophical dilemma. We won't be seeing human connectome twins any time soon. But what about worms? I referred in the Introduction to “the” connectome of
C. elegans,
implying that any two worms are connectome twins. But is this really true? Certainly the neurons are identical, so we should be able to take two connectomes, match up their neurons one to one, and check to see whether the connections are the same.

Such a comparison has never been done in its entirety, because it would require two complete
C. elegans
connectomes,
and finding just one was difficult enough. David Hall and Richard Russell
took the shortcut of comparing partial connectomes from the tail ends of worms. They didn't find a perfect match. If two neurons were connected by many synapses in one worm, in all likelihood they were also linked in another worm. But if two neurons were connected by a single synapse in one worm, there might be no synapse at all between them in another.

What caused these variations? The worms had been highly inbred in the laboratory for many generations, by exaggerating the methods used to create purebred dogs and horses.
That made all lab worms genomic twins, but a few differences did remain in their DNA sequences. Could these differences account for connectome variation? Or is such variation a sign that worms learn from experience? Or perhaps the variation is due neither to genes nor to experience, but rather to random sloppiness as the worm's neurons wire together during development. Any of these explanations could be true, but more research is needed to test them.

Did connectome variation affect behavior, giving worms distinctive “personalities”? Hall and Russell did not study this question, so we don't know. Their worms were inbred but otherwise normal. Other researchers have identified genetically defective worms that also behaved abnormally. Finding their connectomes has yet to be done, but after that is accomplished, it should be straightforward to compare the connectomes of abnormal and normal worms if the neurons can be placed in one-to-one correspondence. If there are missing neurons, or additional neurons, then matching the connectomes will be a bit more difficult; still, it should be possible. Research of this type will take off as it becomes easier to find
C. elegans
connectomes.

Comparing the connectomes of animals with big brains will be much more challenging. As I mentioned in the Introduction, big brains vary greatly in number of neurons, so there's no way of placing neurons in one-to-one correspondence. Ideally, we would find some way to match up neurons with similar or analogous connectivity. According to the connectionist mantra, such neurons would also have similar functions, like a Jennifer Aniston neuron in one brain and a Jennifer Aniston neuron in another. The correspondence would not be one to one, as the number of Jennifer Aniston neurons might vary across individuals. (Some people might even lack Jennifer Aniston neurons altogether, having never had the benefit of exposure to her.) This kind of matching would require sophisticated computational methods
yet to be developed.

An alternative approach is to compare connectomes after coarsening them. We could define reduced connectomes for brain regions or neuron types, as described earlier. Since these are expected to exist in all normal individuals, it should always be possible to place them in one-to-one correspondence. Comparing reduced connectomes of big brains would be as simple as comparing worm connectomes.

Previously I argued that regional or neuron type connectomes would be insufficient for understanding our memories, the most unique aspect of our personal identities. But other distinguishing mental characteristics, such as personality, mathematical ability, and autism, seem more generic than autobiographical memories. These properties of minds might be encoded in reduced connectomes.

***

In principle, we could find reduced connectomes by carving up neuronal connectomes. Even for rodent brains, however, finding an entire neuronal connectome is a long way off. An alternative is to develop shortcut methods that find reduced connectomes directly, without requiring neuronal connectomes. Such methods would be technically easier, as they would not require collecting so much image data.

Some neuroscientists would like to use light microscopy to find connectomes for neuron types—an approach pioneered by Cajal, who concluded that two neuron types were connected when one type extended axons into a region occupied by dendrites of the other type. His approach was piecemeal, but with modern technologies it could be applied systematically. To find a neuron type connectome, though, we would have to combine neurons imaged in many brains, as light microscopy can reveal only a small fraction of a single brain's neurons. Therefore, this approach might be less useful for finding differences between individual brains.

Light microscopy could also be used to map regional connectomes. To apply this approach to the cortex, we must map a specific part of the cerebrum that I haven't discussed yet—the cerebral white matter. Recall that the cerebrum atop the brainstem resembles a fruit on a stalk. The “peel” of the fruit is the cortex, otherwise known as the gray matter. Cutting the fruit open reveals its “flesh,” called the white matter, as shown in Figure 48.

 

 

Figure 48. Gray versus white matter of the cerebrum

 

The distinction between gray and white matter was known in antiquity,
but their fundamental difference became clear only after the discovery of neurons. The outer gray matter is a mixture of all parts of neurons—cell bodies, dendrites, axons, and synapses—while the white matter contains only axons. In other words, the inner white matter is all “wires.”

Most white-matter axons come from neurons in the surrounding cerebral cortex. They belong to pyramidal neurons, which constitute about 80 percent of all cortical neurons. Earlier I mentioned that this neuron type has a cell body with a triangular or pyramidal shape, and an axon that travels a long distance from the cell body. Let's refine the picture here. The apex of the pyramid points toward the exterior of the brain. The axon comes straight out of the base
of the pyramid, perpendicular to the cortical sheet, and plunges into the white matter, as Figure 49 shows.