Though we have all determined
[1] that someone is asleep, or that we have been asleep, the gold-standard scientific verification of sleep requires the recording of signals, using
electrodes, arising from three different regions: (1) brainwave activity, (2) eye movement activity, and (3) muscle activ- ity. Collectively, these signals are grouped together under the blanket term “polysomnography” (PSG), meaning a readout (graph) of sleep (somnus) that is made up of multiple signals (poly). It was using this collection of measures that arguably the most important discovery in all of sleep research was made
in 1952 at the University of Chicago by Eugene Aserinsky (then a graduate student) and Professor Nathaniel Kleitman, famed for the Mam- moth Cave experiment discussed in chapter 2. Aserinsky had been carefully documenting the eye movement patterns of human infants during the day and night. He noticed that there were periods of sleep when the eyes would rapidly dart from side to side underneath their lids. Furthermore, these sleep phases were always accompanied by remarkably active brainwaves, almost identical to those observed from a brain that is wide awake. Sandwiching these earnest phases of active sleep were longer swaths of time when the eyes would calm and rest still. During these quiescent time periods, the brainwaves would also become calm, slowly ticking up and down
[2]. As if that weren’t strange enough, Aserinsky also observed that these two phases of slumber (sleep with eye movements, sleep with no eye movements) would repeat in a somewhat regular pattern throughout the night, over, and over, and over again. With classic professorial skepticism, his mentor, Kleitman, wanted to see the results replicated before he would entertain their validity. With his propensity for including his nearest and dearest in his experimenta- tion, he chose his infant daughter, Ester, for this investigation. The findings held up. At that moment Kleitman and Aserinsky realized the profound discovery they had made: humans don’t just sleep, but cycle through two completely different types of sleep. They named these sleep stages based on their defining ocular features: non–rapid eye movement, or NREM, sleep, and rapid eye movement, or REM, sleep. Together with the assistance of another graduate student of Kleitman’s at the time, William Dement, Kleit- man and Aserinsky further demonstrated that REM sleep, in which brain activity was almost identical to that when we are awake, was intimately con- nected to the experience we call dreaming, and is often described as dream sleep. NREM sleep received further dissection in the years thereafter, being subdivided into four separate stages, unimaginatively named NREM stages 1 to 4 (we sleep researchers are a creative bunch), increasing in their depth. Stages 3 and 4 are therefore the deepest stages of NREM sleep you expe- rience, with “depth” being defined as the increasing difficulty required to wake an individual out of NREM stages 3 and 4, compared with NREM stages 1 or 2.
In the years since Ester’s slumber revelation, we have learned that the two stages of sleep—NREM and REM—play out in a recurring, push-pull battle for brain domination across the night. The cerebral war between the two is won and lost every ninety minutes, fn2 ruled first by NREM sleep, followed by the comeback of REM sleep. No sooner has the battle finished than it starts anew, replaying every ninety minutes. Tracing this remarkable roller- coaster ebb and flow across the night reveals the quite beautiful cycling architecture of sleep, depicted in figure 8. On the vertical axis are the different brain states, with Wake at the top, then REM sleep, and then the descending stages of NREM sleep, stages 1 to 4. On the horizontal axis is time of night, starting on the left at about eleven p.m. through until seven a.m. on the right. The technical name for this graphic is a hypnogram (a sleep graph).
Had I not added the vertical dashed lines demarcating each ninety- minute cycle, you may have protested that you could not see a regularly repeating ninety-minute pattern. At least not the one you were expecting from my description above. The cause is another peculiar feature of sleep: a lopsided profile of sleep stages. While it is true that we flip-flop back and forth between NREM and REM sleep throughout the night every ninety minutes, the ratio of NREM sleep to REM sleep within each ninety-minute cycle changes dramatically across the night. In the first half of the night, the vast majority of our ninety-minute cycles are consumed by deep NREM sleep, and very little REM sleep, as can be seen in cycle 1 of the figure above. But as we transition through into the second half of the night, this seesaw balance shifts, with most of the time dominated by REM sleep, with little, if any, deep NREM sleep. Cycle 5 is a perfect example of this REM-rich type of sleep.
Why did Mother Nature design this strange, complex equation of un- folding sleep stages? Why cycle between NREM and REM sleep over and over? Why not obtain all of the required NREM sleep first, followed by all of the necessary REM sleep second? Or vice versa? If that’s too much a gamble on the off chance that an animal only obtains a partial night of sleep at some point, then why not keep the ratio within each cycle the same, placing similar proportions of eggs in both baskets, as it were, rather than putting most of them in one early on, and then inverting that imbalance later in the night? Why vary it? It sounds like an exhausting amount of evolutionary hard work to have designed such a convoluted system, and put it into biological action.
We have no scientific consensus as to why our sleep (and that of all other mammals and birds) cycles in this repeatable but dramatically asymmetric pattern, though a number of theories exist. One theory I have offered is that the uneven back-and-forth interplay between NREM and REM sleep is necessary to elegantly remodel and update our neural circuits at night, and in doing so manage the finite storage space within the brain. Forced by the known storage capacity imposed by a set number of neurons and con- nections within their memory structures, our brains must find the “sweet spot” between retention of old information and leaving sufficient room for the new. Balancing this storage equation requires identifying which mem- ories are fresh and salient, and which memories that currently exist are overlapping, redundant, or simply no longer relevant.