Toward the end of our discussion, I’ll describe how scientists are trying to hack into the molecular machinery of the aging process itself, tinkering with its “inevitability code” in an attempt to reverse the irreversible. As an AARP-eligible father, I embrace this effort wholeheartedly, though as an AARP-eligible scientist, I temper my enthusiasm with a healthy dose of scientific grumpiness.
It will then be time to revisit Langer’s lively septuagenarians, for the results of her time-warp studies will now make more sense. I won’t be sugarcoating the harsh ways in which time can run roughshod over the human experience. But you will come away understanding that there is a lot more to aging than aches and pains and longing to return to the days of the Eisenhower administration.
It’s a good time to grow old
We’ve got it relatively good. For virtually our species’ entire history, human life expectancy was about thirty years. Life expectancy is the benchmark for what’s typical. And it has been steadily rising. Were you living in England in 1850, you generally died in your mid-forties. That figure is four decades longer now. If you were an American in 1900, you died around age forty-nine. It was seventy-six by 1997.
Not true anymore. Americans born in 2015 can expect to live to seventy-eight (it’s a little more for women, a little less for men). If you’ve already made it to your sixty-fifth birthday, you can expect to live nearly twenty-four more years if female and nearly twenty-two more years if male. That’s an astonishing 10 percent jump since the year 2000, and the numbers are expected to go even higher.
If life expectancy gives us a benchmark for what’s typical, what’s possible?
When we look at the years a creature is capable of living, we’re talking about longevity (more properly, longevity determination). This number is regulated, somewhat indirectly, by genes. If you used the term “genetic longevity determination,” researchers in the room would nod their heads in approval.
This notion is different from maximum life span, and both are different from life expectancy. It’s easy to conflate them, which would earn you a frown from those researchers. The scientific journal Nature published succinct definitions a few years back: “Maximum life span is a bald measure of years accumulated. It is not the same as life expectancy, which is an actuarial measure of how long one is expected to live from birth, or indeed from any given age.”
In this view, longevity is the amount of time you could spend on the planet were conditions ideal. Life expectancy is the amount of time you likely will spend on the planet, given that conditions are almost never ideal. It’s the difference between how long you can live versus how long you will live.
So how long can humans live? The oldest person with an independently verifiable birth date celebrated her 122nd party before passing. But most of the oldest people clock in between 115 and 120 years old. You’d have to weather a lot of biological perfect storms to get to your 120th birthday party, of course, and almost none of us will. The probability isn’t zero, though.
We really are learning how to soldier on right to the edge of our expiration dates. And, as the stories throughout this book illustrate, we’re doing it in greater physical and mental health than at any other time in our history.
But these stories can’t tell you how you will age. That’s because aging is quite variable—even individually expressed. There’s an intricate fox-trot between nature and nurture. And the fact that the brain is so flexible, so damnably reactive to its environment, is actually a powerful confounder for many types of brain research. The brain appears hardwired not to be hardwired. Consider the simple act of reading this sentence and discovering I’ve left the period off the end of it The very fact that I did, and that I told you, and that you probably looked to see if I was telling the truth, physically rewired your brain.
How the brain is wired
Whenever the brain learns something, connections between neurons change. What does that look like? Neural circuitry has many options. Sometimes the changes involve neurons growing new connections to the locals. Sometimes the changes involve abandoning certain connections and re-forming new ones somewhere else. Sometimes the alterations only involve electrical relationships between two neurons, something called synaptic strength.
You probably learned in high school that brains are strung together with electrically active nerve cells—neurons—but you may have forgotten what they looked like. To illustrate, I’d like to introduce you to what are easily the First Ladies of my wife’s garden, our two graceful Japanese maples. They’re beautiful creatures, more bush than tree, with elegant, tapered leaves, deeply red in the autumn. These leaves are fastened to complex branches, which gather at a stubby trunk. The trunk is nearly hidden from view, given the exuberance of the branching, and the little you can see quickly dives under the soil. The underground part of the maple splits into a slightly less complex root system, like most plants.
Though neurons come in many shapes and sizes, all follow a basic structure, looking something like our garden’s Grand Dames. Impossibly complex branching structures, called dendrites, exist at one end of a typical cell. Those dendrites gather together into a trunk-like structure termed an axon. Unlike our maple’s trunk, however, there is a bulge at this point of gathering. It’s an important swelling—called the cell body—and its reputation derives from a small spherical shape inside it. This is the nucleus of the neuron. It houses the cell’s command and control structures, the double-ladder-shaped molecule DNA.
Axons can be short and squatty, like our maple’s trunk, or long and slender like a pine tree’s trunk. Many are wrapped in a type of “bark” that’s called white matter. At the other end of the axon lies a root system, just like a plant’s, consisting of branching structures termed telodendria. These usually aren’t as complex as the dendrites, but they serve an important information-transfer function, as we’re about to see.
The brain’s information system runs on electricity, like most light bulbs, and their shape helps them do it. To understand how, imagine pulling one of our Japanese maples out by its roots, and then, while my wife has a heart attack, holding it over the top of our other maple. Don’t let them touch. The root system of the top tree is now hovering over the branches of the bottom.
Now imagine these two trees are neurons. The telodendria (roots) of the upper neuron lie close to the dendrites (branches) of the lower cell. In the real world of the brain, electricity flows from the dendrites of the top neuron down its axon and arriving at the telodendria, where it immediately encounters the space between the two. The gap must be jumped if information is to be transferred. This junction is called a synapse, and the space it creates, the synaptic cleft. How to pole-vault the space?
The solution lies at the tips of those root-like telodendria. There are small bead-like packets at those tips containing some of the most famous molecules in all of neuroscience. They’re called neurotransmitters. I’ll bet you’ve heard of some of them: dopamine, glutamate, serotonin.
When an electrical signal reaches the telodendria of one neuron, some of these biochemical celebrities are released into the synaptic cleft. It’s the equivalent of saying, “I need to send a message to the other side.” The neurotransmitters dutifully sail across the gulf. It’s not a long journey; most of these spaces are only about 20 nanometers in length. Once the neurotransmitters have crossed, they bind to receptors on the dendrites of the other neuron, like a boat tying up to a dock. This binding is sensed by the cell, alerting it with signal that says: “Oh, I better do something.” In many cases, that “do something” means becoming electrically excited too. It then passes along this excitement down the chain from dendrites to axons to its telodendria.
While jumping the space between two neurons using biochemicals is a neat trick, the electrical circuits aren’t usually this simple. If you can imagine lining up thousands of cellular Japanese maples root-to-branch, you’d have something approximating an elementary neural circuit in the brain. And even that’s too simple. The typical number of connections a single neuron makes with other neurons is around seven thousand. (That’s only an average: