Throughout the cerebral cortex, neurons are arranged in six distinct layers, easily visible under a microscope. A team of MIT neuroscientists discovered that these layers also exhibit distinct patterns of electrical activity, consistent across many regions of the brain and across several animal species, including humans.
The researchers found that in the upper layers, neuron activity is dominated by rapid oscillations called gamma waves. In deeper layers, slower oscillations called alpha and beta waves predominate. The universality of these patterns suggests that these oscillations likely play an important role in the brain, the researchers say.
The work is published in Natural neuroscience.
“When you see something so consistent and pervasive in the cortex, it plays a very fundamental role in what the cortex does,” says Picower Professor of Neuroscience Earl Miller, a member of MIT’s Picower Institute for Learning and Memory. and one of the lead authors of the new study.
Imbalances in how these oscillations interact with each other could be involved in brain disorders such as attention deficit hyperactivity disorder, researchers say.
“It is known that overly synchronous neuronal activity plays a role in epilepsy, and we now suspect that different synchronization pathologies may contribute to many brain disorders, including disorders of perception, attention, memory and motor control. In an orchestra, one instrument playing out of sync with the rest can disrupt the coherence of the entire piece of music,” says Robert Desimone, director of MIT’s McGovern Institute for Brain Research and one of the leading authors of the study.
André Bastos, an assistant professor of psychology at Vanderbilt University, is also a lead author of the paper. The lead authors are Diego Mendoza-Halliday, a researcher at MIT, and Alex Major, a postdoctoral fellow at MIT.
Activity layers
The human brain contains billions of neurons, each with its own electrical modes of operation. Together, groups of neurons with similar patterns generate oscillations of electrical activity, or brain waves, which can have different frequencies. Miller’s lab has previously shown that high-frequency gamma rhythms are associated with the encoding and retrieval of sensory information, while low-frequency beta rhythms act as a control mechanism that determines what information is read into working memory.
His lab also discovered that in parts of the prefrontal cortex, different layers of the brain exhibit distinctive oscillation patterns: faster oscillation on the surface and slower oscillation in deeper layers. One study, conducted by Bastos while he was a postdoctoral fellow in Miller’s lab, showed that when animals performed working memory tasks, lower frequency rhythms generated in deeper layers regulated higher gamma rhythms. frequency generated in the surface layers.
In addition to working memory, the cerebral cortex is also the seat of thinking, planning, and high-level processing of emotions and sensory information. In all regions involved in these functions, neurons are arranged in six layers, and each layer has its own distinctive combination of cell types and connections to other areas of the brain.
“The cortex is organized anatomically into six layers, no matter whether you look at mice, humans, or mammalian species, and this pattern is present in all cortical areas in every species,” says Mendoza-Halliday. “Unfortunately, many studies of brain activity have ignored these layers, because when you record the activity of neurons, it’s difficult to understand where they are in the context of these layers.”
In the new paper, the researchers wanted to determine whether the layered oscillation pattern they observed in the prefrontal cortex was more widespread, occurring in different parts of the cortex and across species.
Using a combination of data acquired in Miller’s lab, Desimone’s lab, and the labs of collaborators at Vanderbilt, the Netherlands Institute for Neuroscience, and the University of Western Ontario, the researchers were able to analyze 14 different areas of the cortex, from four species of mammals. . This data included recordings of electrical activity from three human patients who had electrodes inserted into their brains as part of a surgical procedure they were undergoing.
Recording from individual cortical layers was difficult in the past because each layer is less than a millimeter thick. It is therefore difficult to know from which layer an electrode records. For this study, electrical activity was recorded using special electrodes that record all layers at once and then feed the data into a new computational algorithm designed by the authors, called FLIP (French Identification Procedure layers based on frequency). This algorithm can determine which layer each signal comes from.
“Newer technology allows all layers of the cortex to be recorded simultaneously. This opens up a broader perspective on the microcircuits and allows us to observe this pattern in layers,” explains Major. “This work is exciting because it both informs a fundamental model of microcircuitry and provides a robust new technique for studying the brain. It doesn’t matter whether the brain is performing a task or at rest and can be observed in just five hours.” at 10 seconds.”
Across all species, in every region studied, the researchers found the same layered pattern of activity.
“We did a massive analysis of all the data to see if we could find the same pattern in all areas of the cortex, and lo and behold, it was everywhere. It was a real indication that what had been observed before in a few areas was different.” representing a fundamental mechanism across the cortex,” says Mendoza-Halliday.
Maintain balance
The results support a model previously proposed by Miller’s lab, which proposes that the brain’s spatial organization helps it incorporate new information, carried by high-frequency oscillations, into existing memories and brain processes, which are maintained by low frequency oscillations. . As information moves from one layer to the next, input can be incorporated as needed to help the brain perform particular tasks such as baking a new cookie recipe or remembering a phone number.
“The consequence of a laminar separation of these frequencies, as we observed, could be to allow the superficial layers to represent external sensory information with faster frequencies, and the deep layers to represent internal cognitive states with higher frequencies. slower frequencies,” Bastos explains. “The high-level implication is that the cortex has multiple mechanisms involving both anatomy and oscillations to separate ‘external’ from ‘internal’ information.”
According to this theory, imbalances between high and low frequency oscillations can lead either to attention deficits such as ADHD, when higher frequencies dominate and too much sensory information comes in, or to delusional disorders such as schizophrenia. , when the low frequency oscillations are too strong. strong and there is not enough sensory information entering it.
“The proper balance between top-down control signals and bottom-up sensory signals is important for everything the cortex does,” says Miller. “When balance goes out of whack, you get a wide variety of neuropsychiatric disorders.”
Researchers are now studying whether measuring these oscillations could help diagnose these types of disorders. They’re also studying whether rebalancing oscillations could change behavior — an approach that could one day be used to treat attention deficits or other neurological disorders, the researchers say.
The researchers also hope to work with other labs to further characterize layered oscillation patterns in different brain regions.
“Our hope is that with enough standardized reporting, we will begin to see common patterns of activity across different domains or functions that might reveal a common mechanism of computation that can be used for motor outputs, for vision, for memory and attention. et cetera,” says Mendoza-Halliday.
More information:
A ubiquitous spectrolaminar pattern of local field potential power across the primate cortex, Natural neuroscience (2024). DOI: 10.1038/s41593-023-01554-7. www.nature.com/articles/s41593-023-01554-7
Provided by the Massachusetts Institute of Technology
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