Autopilot (10 page)

Nowhere in Allen's imperative to “become a wizard of productivity” does he suggest that if you must rely on perpetual mnemonic and digital gymnastics to get through your day, maybe you have too much to do. As I've pointed out, the human brain has limits. A modern scientific understanding of our brains shows that each of us has a unique order and structure, which we must learn to understand as much through idleness as activity.

This uniqueness is also what unites us. Recognizing what is universal in humans—self-organization, complexity, and nonlinearity—should liberate and relax us. Self-organizing dynamics are fundamental to how our brains process information. Our nervous system is also a nonlinear dynamic system coupled to our brain. It is our heart's ability to flexibly respond to changes in activity that prevents stroke or heart attack. Reduced heart rate variability is a very good predictor of poor cardiac health.

And it turns out that parts of the brain's default mode network are tightly coupled to regulating variable cardiac rhythms. The anterior cingulate cortex, among other regions, plays an important role in regulating the stress that gets transferred to our heart. Idleness lets the ACC and our nervous system find stable and variable dynamics. Stress reduces the variability in our heart rate: a low level of anxiety forces the heart to be in a state of preparedness, which it cannot maintain indefinitely.

An extreme example of disorder in this system is post-traumatic stress disorder (PTSD). People with PTSD feel like they are constantly on vigil; they can never relax for fear of something violent happening to them again. Therefore, their hearts are constantly on alert, which reduces the variability in its rhythm. Constant overwork can be thought of as a mild form of PTSD.

As Einstein indicated, we should each have the freedom to allow our own order and structure to emerge naturally and spend our days as we wish. Everyone hates working for other people. And being insanely busy all the time is not only bad for you; it also prevents you from discovering the human being you were meant to be.

7

“As he walked up and down … he suddenly stopped dead—for he seemed to hear a voice call through the roar of the wind.”

—Donald Prater,
A Ringing Glass: the Life of Rainer Maria Rilke

In 1912, Rilke was staying at an Italian castle called Duino, owned by a Czech princess. Before coming to Duino, Rilke had been struggling for quite some time. He was still trying to learn how to listen to his unconscious for what he called his life's next “turn.”

Rilke spent hours every day at the castle walking near the
two-hundred
-foot cliffs which overlooked the rough sea. It had been several years since he had written any significant poems. One morning, he received an irritating and tedious business letter. Annoyed, he decided to take his walk on the path between two giant concrete battlements of the castle, near the sheer drop to the sea. A strong Adriatic wind was blowing, called a
bora
in Italian
.

As Donald Prater describes, Rilke heard a voice call through the roar of the wind. What the voice said to him became one of the poet's most famous lines:
Wer, wenn ich schriee, hörte mich denn aus der Engel Ordnungen?

And if I cried out, who would hear me up there among the angelic orders?

Did Rilke hear the wind “speak” that day at the coastal castle? I suggest that the mechanism of “stochastic resonance” helped Rilke suddenly enter a state of heightened awareness.

Stochastic resonance describes any phenomenon where the presence of noise, either internally or externally, in a nonlinear system makes the system respond better than it would without noise. In nonlinear dynamical systems—like the brain—noise can make the system behave in a more orderly fashion. It can also boost weak internal or external signals so that our sensory organs and even our conscious awareness can detect them. Noise and stochastic resonance are essential to consciousness.

When Rilke stepped out onto to the path at the castle that morning, and into the roar of the wind, perhaps the noise amplified a weak signal from deep within Rilke's mind:
If I cried out, who would hear me?

Rilke wrote this line down in a small notebook that he always had with him. He went back to his room, and by evening, the entire first elegy had been composed. He wrote furiously, trying to capture the torrent of words that were now flooding from his consciousness. It was as if the dam inside his brain had burst.

We almost always think of noise as bad. It is a form of interference. It is a nuisance. Too much of it over time can cause hearing loss. Electrical engineers have been struggling to get rid of noise in their systems since the invention of the telephone and computer. Jet engine manufacturers face severe restrictions nowadays on how loud their engines can be near airports. Commercial jetliners are about fifty percent quieter today than they were just twenty years ago.

Nate Silver, in his great book
The Signal and the Noise
, says of noise, “The signal is the truth. The noise is what distracts us from the truth.” While Silver's characterization of the signal and the noise reflects our common sense intuition about noise, there are many circumstances in which the addition of the right amount of noise actually boosts the signal.

Given the ubiquity of noise in the brain and the environment, it is not surprising that evolution has endowed biological systems with the ability to use noise to find the signal. In fact if our brains were without randomness, they would not be able to function.

The great thing about our brains is that they have evolved to find signals and truth without any real effort on our part. In fact our brains do a better job of finding our own truth if we are idle.

In the noise field, stochastic resonance (abbreviated as SR) has become an important area of research over the last thirty years. Here's the revelation: in nonlinear systems, adding a certain optimal amount of noise actually increases the signal-to-noise ratio. In other words, adding noise to a faint signal might actually make the signal stronger.

An Italian physicist at the NATO International School of Climatology named Roberto Benzi introduced SR in the early 1980s to explain the recurrence of the Earth's ice-age cycle, which happens every one hundred thousand years. This is also the cycle of the eccentricity of the Earth's orbit. The idea very simply is that there are two “energy wells” or a double well that represent two states of the climate—frozen or warm—that the earth oscillates between.

When the Earth is in one side of the well it's on average much warmer; when it's on the other side of the well it's much colder on average. Benzi postulated that the combination of random or “stochastic” perturbations in the orbit in addition to the eccentricity was what caused the climate cycle; in other words, it was noise. He called the combination of eccentricity and noise “stochastic resonance” to mean that the noise amplified the effect of the eccentricity. In Earth's case, the source of the noise was small random wobbles in the eccentric orbit that pushed the state of the climate into one state or the other.

Consider the following diagrams:

Imagine that the black marble in the picture represents the state of the climate at any given time.

The wavy line the marble is resting on represents the Earth's orbit. When the climate is in one of the wells (+1 or –1) it is either an ice-age or warm. When time (t) = 0 in the upper left illustrations, the probability that the climate will jump to the opposite state is very low.

Imagine now that we animate these illustrations and the wavy lines move up and down, and also start to jiggle around randomly. What makes the marble jump from one dip to the other?

The resonance happens when the noise and the orbit combine in just the right way to produce a large change and the marble jumps over the threshold, which could not happen without the noise.

One of the most famous demonstrations in biology of SR came in the 1990s when a group led by Frank Moss at the University of Missouri at St. Louis showed that paddlefish use electrical noise in muddy river water to locate their prey.

Paddlefish feed on plankton in North American rivers. The turbulence and mud make for conditions of near zero visibility. And plankton are tiny. The “paddle” on the paddlefish is actually an electrosensory antenna that responds to the low frequency electrical fields that the plankton emit.

A giant group of plankton causes background noise in the water. Moss's group found that when they injected an optimal amount of electrical noise into water the paddlefish were able to find plankton that were farther away. This noise enhancement was also demonstrated in the mechano-receptors of crayfish, the antenna of crickets, and in the brains of rats.

Human and animal neurons are nonlinear threshold devices, and as such they actually experience benefits from noise. In fact, it is likely that without noise they would not function at all. When something excites a brain enough, it temporarily changes its dynamics completely. In the case of a neuron it goes from resting to firing off an action potential.

Our neurons communicate with each other via an unbelievably complicated choreography that involves the electrical and chemical coordination of firing patterns among these neurons. Signals travel back and forth, partially synchronizing or desynchronizing their activity as necessary. Each neuron has a dynamic threshold for firing action potentials. In other words, the thresholds change over time. Neurons respond randomly and differently to stimuli, and this response is then randomly integrated to the network to which the neuron belongs.

With around a hundred billion neurons packed into your skull, each firing hundreds of times per second, the inside of the brain is filled with noise. But is this noise bad? It could be that the spontaneous, intrinsic activity of the default mode network provides the necessary background noise for the brain to be able to process information. Abnormal functioning of the default mode network might give you too much or too little brain noise.

Noise can in fact help neurons detect weak signals from the environment or from other neurons.

The figure above shows a typical sinusoidal wave represented by the blue line—aka “the signal.” This could be anything from a sound, an image, a train of action potentials from other neurons, or perhaps even a great poem in your unconsciousness. The dotted line represents the neuron's threshold for firing.

Note that the blue line never crosses the threshold. Therefore, the solid black line above the dotted line that represents the output of the neuron does nothing. This is a weak signal without noise. It is undetectable.

Now look what happens when we add the right level of noise to the blue signal, represented by the jagged and squiggly red line. Parts of the noise cross the neuron's threshold (dotted black line) and therefore the neuron fires action potentials, represented by the sold black vertical bars above the black output line.

Notice that where the noise crosses the threshold and causes the neurons to fire, the firing rate corresponds with the frequency of the underlying signal. Therefore the output characterizes the weak signal.

Information is actually transmitted by the noise.

This mechanism also works on the sensory level, so that noise amplifies sub-threshold sounds. Noise can also enhance weak images. A well-known image in the literature on the visual perception of stochastic resonance is Big Ben in London (reproduced from Simonotto, 1998).

On the left, Big Ben is digitized on a 1–256 gray scale at a 256 by 256 pixel resolution.

Each pixel in the picture fires when it crosses a threshold, using the same kind of algorithm as the brain's neurons. Turning up the noise a little bit by increasing the maximum and minimum random values produces the middle image. This is the resonant noise intensity.

This noise level plus the signal—the weak image of Big Ben—creates the clear image in the middle. The right amount of noise improves the signal to noise ratio. Turning the noise up too high creates the degraded image on the right. When you plot this on a graph, you get what is called an inverted U shaped curve.