A new way to understand the complex rhythms of the brain

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Today, as a researcher For long hours of tricky experiments in the laboratory, they may listen to music or podcasts to spend the day. But in the early days of neuroscience, hearing was an important part of this process. In order to figure out what neurons care about, researchers will convert the nearly instantaneous signals (called “spikes”) they send into sound. The louder the sound, the more frequent the neuron’s signal-its firing rate is also higher.

Joshua Jacobs, associate professor of biomedical engineering at Columbia University, said: “You can hear how loud the loudspeaker is and whether it is really loud or really quiet.” “This is a very intuitive way to see how active the cells are. the way.”

Neuroscientists no longer rely on sound; they can use implanted electrodes and computer software to accurately record spikes. In order to describe the firing rate of a neuron, a neuroscientist will select a time window-say 100 milliseconds-and look at the number of firings. Through the firing rate, scientists have discovered most of our understanding of how the brain works. For example, examining them deep in the brain called the hippocampus led to the discovery of location cells-these cells become active when the animal is in a specific location. This discovery in 1971 won the 2014 Nobel Prize for neuroscientist John O’Keefe.

Emissivity is a useful simplification; they show the overall activity level of the cell, although they sacrifice precise information about the peak time. But the individual spike sequences are so complex and so varied that it is difficult to figure out their meaning. Therefore, Peter Latham, a professor in the Gatsby Department of Computational Neuroscience at University College London, stated that the focus on emissivity usually comes down to pragmatics. “We never had enough data,” Latham said. “Every trial is completely different.”

But this does not mean that it is meaningless to study peak time. Although interpreting neuronal spikes is tricky, it is possible to find meaning in these patterns if you know what you are looking for.

This is what O’Keeffe was able to do in 1993, more than twenty years after the discovery of location cells.By comparing the time of excitation of these cells with the local oscillations (the overall wave-like activity pattern of the brain area), he found a kind of “Phase precession.” When the mouse is in a specific location, the neuron will fire at the same time when other nearby neurons are most active. But as the mouse keeps moving, the neuron will activate little by little before or after its neighbor’s activity reaches its peak. Over time, when a neuron becomes more and more out of sync with its neighbors, it will exhibit phase precession. Eventually, since the background brain activity follows a repetitive up-and-down pattern, it will regain synchronization before starting the cycle again.

Since the discovery of O’Keefe, people have conducted in-depth research on the phase precession of rats. But until Jacobs’ team published an article in the journal in May, no one was sure whether it would happen to humans. cell This Its first evidence in the human hippocampus“This is good news because things are changing under different species and different experimental conditions,” said Mayank Mehta, a well-known phase precession researcher at the University of California, Los Angeles, who was not involved in the study.

The Columbia University team discovered their findings through ten-year-old records of epilepsy patients’ brains, which tracked the patients’ neural activity as they navigated a virtual environment on a computer. Patients with epilepsy are often recruited for neuroscience research because their treatment may involve surgical implantation of deep brain electrodes, which provides a unique opportunity for scientists to eavesdrop on the firing of individual neurons in real time.

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