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A new way to understand the complex rhythm of the brain


Today, when researchers spend long hours in the lab doing delicate experiments, they can listen to music or podcasts to get through the day. But in the early years of neuroscience, hearing was an essential part of the process. To understand what mattered to neurons, researchers would translate the almost instantaneous signals they send, called “spikes”, into sounds. The louder the sound, the more often the neuron popped up and the higher its rate of fire.

“You can just hear how many pops are coming out of the speaker, and whether it’s really loud or really quiet,” says Joshua Jacobs, associate professor of biomedical engineering at Columbia University. “And it’s a really intuitive way to see how active a cell is. “

Neuroscientists no longer depend on sound; they can record spikes accurately using implanted electrodes and computer software. To describe the firing rate of a neuron, a neuroscientist will choose a time window, say 100 milliseconds, and see how many times it fires. Thanks to the rates of fire, scientists have discovered much of what we know about how the brain works. Examining them in a deep region of the brain called the hippocampus, for example, has led to the discovery of place cells, cells that become active when an animal is in a particular place. This 1971 discovery earned neuroscientist John O’Keefe a 2014 Nobel Prize.

Rates of fire are a useful simplification; they show the overall activity level of a cell, although they sacrifice precise information about peak timing. But the individual spike sequences are so complex and variable that it can be difficult to understand what they mean. So focusing on discharge rates often comes down to pragmatics, says Peter Latham, professor at the Gatsby Computational Neuroscience Unit at University College London. “We never have enough data,” says Latham. “Each trial is completely different.”

But that doesn’t mean studying peak timing is pointless. Although it is difficult to interpret the peaks of a neuron, it is possible to make sense of these patterns, if you know what you are looking for.

This is what O’Keefe was able to do in 1993, more than two decades after discovering place cells. By comparing when these cells triggered to local oscillations – global waveform patterns of activity in a region of the brain – he discovered a phenomenon called “phase precession.” When a rat is in a particular location, that neuron fires around the same time that other neighboring neurons are most active. But as the rat continues to move, this neuron will fire a little before, or a little after, the peak of activity of its neighbors. When a neuron becomes increasingly out of sync with its neighbors over time, it exhibits phase precession. Eventually, since background brain activity follows a repetitive top-to-bottom pattern, it will synchronize with it before starting the cycle again.

Since the discovery of O’Keefe, phase precession has been extensively studied in rats. But no one was sure if this was happening in humans until May, when Jacobs’ team published in the journal. Cell the first evidence of this in the human hippocampus. “This is good news, because things fall into place between different species, different experimental conditions,” says Mayank Mehta, a prominent phase precession researcher at UCLA, who was not involved in the study. .

The Columbia University team made their discovery through ten-year-old recordings of the brains of patients with epilepsy that tracked neural activity as patients navigate a virtual environment on a computer. Patients with epilepsy are often recruited for neuroscience research because their treatment may involve surgically implanted deep brain electrodes, giving scientists a unique opportunity to listen to the triggering of individual neurons in real time.

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