Sleep manifests in the brain as slow waves moving across the surface at a rate of about one per tenth of a second – or so we thought.
A new study in mice shows that there are patterns of brain activity associated with sleep that we’ve been missing. These patterns reflect the state of individual brain cells rather than the collective activity of millions or billions of neurons.
Furthermore, by measuring these hyperlocal, submillimeter brain signals using single electrodes, researchers have discovered that parts of the mammalian brain may fall asleep for a short nap, while other areas remain fully awake.
“It was a surprise to us as scientists that different parts of our brain actually take a nap while the rest of the brain is awake,” said David Haussler, a bioinformatician at the University of California (UC) Santa Cruz and one of the study’s lead authors.
For about a century, brain-wide patterns of electrical activity have been used to define, in quantitative terms, the difference between sleep and wakefulness. These brain waves are usually detected using an electroencephalogram (EEG), via electrodes placed on the scalp.
But Haussler and his team wondered how we measure sleep and distinguish it from wakefulness. There is clearly some overlap in the brains of animals that remain alert during sleep, a skill known as unihemispheric slow-wave sleep.
In the 1960s, researchers first suspected and discovered how dolphins and other cetaceans were able to rest half of their brains while remaining active, sometimes keeping one eye open to watch for predators and maintain contact with other members of their group.
Seals and birds also exhibit variations of this half-sleep, half-wake sleep – a clever trade-off between sleep and survival.
Humans can also temporarily exhibit asymmetrical sleep patterns that resemble, but do not match, those of animals.
In 2016, researchers at Brown University in the US found that the first night people slept in an unfamiliar place, the left hemisphere of the brain was more alert to unusual sounds than the right. Once we get used to a sleeping environment, this difference disappears.
“It turns out that the human brain is equipped with a less dramatic form of the unihemispheric sleep found in birds and some mammals,” neuroscientist Christof Koch wrote in Scientific American when those results were published.
If the mouse brain is anything to go by, the blurring of wakefulness and sleep in humans may be a neurological trait we share with other animals.
Haussler and his team spent weeks collecting data from nine mice implanted with thin wire electrodes in 10 different brain regions. They fed this data into an artificial neural network that learned to distinguish between sleep and wake states.
Recordings were made from 100 micrometers (one-tenth of a millimeter) of brain tissue. The algorithm could reliably identify sleep-wake cycles based on brief “flickers” in brain cell activity lasting only 10 to 100 milliseconds.
These “hyperlocal” signals suggested that part of the animals’ brains were falling asleep, while other areas remained active and awake. Coincidentally, the researchers noticed that this occurred at the same time that the mouse stopped moving for a moment, almost as if it were “in thought.”
“We could look at the individual times at which these neurons were firing, and it was pretty clear that [the neurons] “We went into a different state,” explains Aiden Schneider, a computational biologist at Washington University in St. Louis, who led the research with David Parks, a computer science graduate student at UC Santa Cruz.
“In some cases, these flickers may be confined to a particular brain region, or perhaps even smaller.”
The team believes their new method of measuring sleep-wake states could reveal new secrets about the way we sleep, if these ‘flickers’ can be observed by other research groups.
“She [the flickers] “Break the rules that you would expect based on a hundred years of literature,” says neuroscientist Keith Hengen of Washington University in St. Louis.
The research was published in Natural Neuroscience.