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A new way to understand the intricate rhythm of the brain


Today, when researchers they spend long hours in the lab performing awkward experiments, maybe listening to music or podcasts to spend the day. But in the early years of neuroscience, hearing was an essential part of the process. To understand what neurons care about, researchers would translate the almost instantaneous signals they send, called “spikes,” into sound. The louder the sound, the more often the neuron jumped – and the higher its firing speed.

“You can only hear how many shots come out of the speakers even if it’s really loud or really quiet,” says Joshua Jacobs, an associate professor of biomedical engineering at Columbia University. “And it’s a really intuitive way to see how active the cell is.”

Neuroscientists no longer depend on sound; they can accurately record spikes using built-in electrodes and computer software. To describe the rate at which neurons burst, a neuroscientist will select a time window – say, 100 milliseconds – and see how many times it will activate. Through shooting rates, scientists have discovered much of what we know about how the brain works. For example, their examination in a deep part of the brain called the hippocampus, led to the discovery of site cells – cells that become active when an animal is in a particular site. This 1971 discovery awarded neuroscientist John O’Keefe the 2014 Nobel Prize.

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Shooting rates are a useful simplification; they show the overall level of cell activity, although they sacrifice accurate information about jump times. But the individual rows of spikes are so intricate and so changeable that it can be difficult to understand what they mean. So focusing on dismissal rates often comes down to pragmatics, says Peter Latham, a professor at the Gatsby Computational Neuroscience Unit at University College London. “We never have enough data,” Latham says. “Every single trial is completely different.”

But that doesn’t mean that studying jump times is pointless. Although interpreting neural spikes is inconvenient, finding meaning in these patterns is possible if you know what you are looking for.

O’Keefe was able to do that in 1993, more than two decades after he discovered the cells of the place. Comparing the time when these cells burst with local oscillations – total patterns of activity like waves in the brain – he discovered the phenomenon of so-called “Phase precession”. When a rat is in a certain location, that neuron will fire at about the same time as other nearby neurons are most active. But as the rat moves, that neuron will fire up a little sooner or a little later, the peak activities of its neighbors. When a neuron becomes more and more synchronized with its neighbors over time, it shows phase precession. Eventually, since background brain activity follows a repetitive up-and-down pattern, it will return to synchronizing with it before restarting the cycle.

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Since O’Keefe’s discovery, phase precession has been intensively studied in rats. But no one knew for sure if it was happening to people until May, when Jacobs’ team published it in a magazine Cell the the first evidence of this in the human hippocampus. “This is good news because things get in place in different species, in different experimental conditions,” says Mayank Mehta, a prominent precession phase researcher from UCLA, who was not involved in the study.

The Columbia University team came to their discovery with decades-old images from the brains of epileptic patients tracking neural activity as patients moved in a virtual environment on a computer. Patients with epilepsy are often recruited for neuroscience research because their treatment may include surgically implanted deep brain electrodes, giving scientists a unique opportunity to eavesdrop on the release of individual neurons in real time.



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