 of (1-1/D), where D is the dimension in which the processors are arranged. A three-dimensional arrangement of, say, 100 processors will give a greater boost than a two-dimensional arrangement of those same processors, due to reduced signal latency. The same kind of speedup can be achieved in our nervous and circulatory systems with a D of greater than three. A rule of thumb common in the halls of Intel was programmed into our bodies eons ago; the fractal arrangement of our biological sensors and the nerves that connect them are designed for speed.
The brain represents the height of biological information processing and transmission. But for years, it’s been considered a noisy instrument. Neurons code information with binary electrical events called spikes, shocking one another like tiny batteries. Once a neuron receives enough input that its voltage passes a certain threshold, it will spike in turn, sending its signal to downstream neurons. Fluctuations in the summed output of the brain’s 100 billion neurons, as measured by an electroencephalogram, or EEG, are much smaller than the amplitude of individual spikes, and were long thought to be epiphenomenal: pointers to various brain states, but not an information-carrying signal in itself. In other words, noise.
Slow oscillations in the brain are coherent over large anatomical distances, in the same way you can hear the bass from your neighbor’s sound system better than the treble.
Yet, as we saw with genetic expression, interactions among many discrete elements can be incredibly useful. It’s becoming clear that the so-called noise seen in an EEG is actually an important signal, and one that is crucial to neural computation. The fluctuation of the summed output of the brain’s neurons feeds back to affect the resting potential of those neurons, bringing them closer to or farther from spike threshold. Slow oscillations (as found in drowsy or sleeping animals) are coherent over large anatomical distances, in the same way you can hear the bass from your neighbor’s sou