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A new way to understand the complex rhythms of the brain



Currently as a researcher For long, tricky experiments in the lab, you can spend the day listening to music and podcasts. But in the early days of neuroscience, hearing was an important part of this process. To understand what a neuron is interested in, researchers convert the near-instantaneous signal (called a “spike”) that a neuron sends into sound. The louder the sound, the more frequent the neuron’s signal and the higher the firing rate.

“You can hear how big the speaker is, whether it’s really big or really quiet,” said Joshua Jacobs, an associate professor of biomedical engineering at Columbia University. “This is a very intuitive way to see how active a cell is. The way.”

Neuroscientists no longer rely on sound. Embedded electrodes and computer software can be used to accurately record spikes. To explain the firing rate of neurons, neuroscientists choose a time frame (for example, 100 milliseconds) and look at the number of firings. Scientists have discovered most of our understanding of how the brain works through firing rates. For example, a deep examination of the brain called the hippocampus revealed place cells. These cells become active when the animal is in a specific position. This discovery in 1971 won the 2014 Nobel Prize for neuroscientist John O’Keefe.

Emissivity is a convenient simplification. It shows the overall activity level of the cell, at the expense of accurate information about peak hours. However, the individual spike sequences are so complex and diverse that it is difficult to understand what they mean. Therefore, Peter Latham, a professor of computational neuroscience at the University College London, said that the focus on emissivity usually results in practical ones. “There is not enough data. We did, “says Latham. “Every attempt is completely different.”

But that doesn’t mean it doesn’t make sense to study peak hours. Neuronal spikes are difficult to interpret, but once you know what you’re looking for, you can find meaning in these patterns.

This was the creation of O’Keefe in 1993, more than 20 years after the place cells were discovered.By comparing the time of excitement of these cells with local vibrations (overall wave-like activity patterns in the brain region), he found a species. “Phase pre-session”. When the mouse is in a particular location, the neurons fire at the same time when other nearby neurons become most active. However, as the mouse continues to move, the neurons gradually activate before and after the peak activity of their neighbors. Over time, as neurons become more and more out of sync with their neighbors, phase shifts occur. Ultimately, background brain activity follows a repetitive up-and-down pattern that regains synchronization before resuming the cycle.

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

A team at Columbia University discovered a finding in a 10-year-old epilepsy patient’s brain record that tracked the patient’s neural activity navigating a virtual environment on a computer. Epilepsy patients are often employed in neuroscience research because treatment of epilepsy patients may include surgical implantation of deep brain electrodes.

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