A New Way to Understand the Intricate Rhythm of the Brain

Today, when researchers they spend long hours in the lab doing deceptive experiments, they could listen 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 the neurons were worried about, the researchers translated into sound the almost instantaneous signals they sent, called “spikes.” The louder the sound, the more often the neuron sounds – and the higher its rate of fire.

“You can only hear how much pop 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 that’s a really intuitive way to see how active a cell is.”

Neuroscientists no longer depend on sound; they can record tips accurately using implanted electrodes and computer programs. To describe the firing rate of a neuron, a neuroscientist will select a time window – for example, 100 milliseconds – and see how many times it will fire. Through shooting rates, scientists have discovered a lot about what we know about how the brain works. Examination in a deep region of the brain called the hippocampus, for example, led to the discovery of local cells – cells that become active when an animal is in a particular location. This 1971 discovery won neuroscientist John O’Keefe a 2014 Nobel Prize.

Shooting rates are a useful simplification; they show the general level of activity of a cell, even if they sacrifice accurate information about the spike time. But individual sequences of tips are so complicated, and so variable, that it can be difficult to understand what they mean. So the focus on shooting rates often falls short of pragmatics, says Peter Latham, a professor in the Gatsby Computational Neuroscience Unit at University College London. “We never have enough data,” Latham says. “Every process is completely different.”

But that doesn’t mean that studying spike time is useless. Although interpreting the peaks of a neuron is complicated, finding meaning in these schemes is possible, if you know what you are looking for.

That’s what O’Keefe was able to do in 1993, more than two decades after he discovered the cells of the place. Comparing the time when these cells fired at local oscillations – generally activity wave patterns in a brain region – he discovered a phenomenon called “Phase Precession”. When a mouse is in a particular place, that neuron will shoot around the same time that other neighboring neurons are more active. But as the mouse continues to move, that neuron will fire a little earlier, or a little later, the peak activity of its neighbors. As a neuron becomes increasingly synchronized with its neighbors over time, it shows a phase precession. In the end, since the background brain activity follows a repetitive pattern, up and down, it will return to synchrony with it, before resuming the cycle again.

Since O’Keefe’s discovery, phase precession has been studied intensively in mice. But no one knew for sure if it would happen to the man until May, when the Jacobs team published it in the magazine. Cell u first evidence of this in the human hippocampus. “This is good news, because things fall into place under 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 decades of brain recordings of epileptic patients who monitored neural activity while patients were navigating in a virtual environment on a computer. Epilepsy patients are often recruited for research in neuroscience because their treatment may involve surgically implanted brain electrodes, which give scientists the unique opportunity to hear the focus of individual neurons in real time.

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