Scientists from the Salk Institute and University of California San Diego report identifying a number of previously unknown types of human brain cells. They’ve also discovered genetic switches that make these neurons.

Understanding the role of these brain cells could help explain how the brain works and what goes wrong in disease. It could also help unravel some of the mysteries of consciousness. But much more work lies ahead, the scientists say, because their study has examined just one part of the brain.

The brain has been likened to a computer network or a telephone switchboard, but that model is misleading. While brain function is partly a product of learning, much of it is hard-wired into the cells themselves. To make sense of this information, scientists must know what kinds of cells they’re dealing with.

Researchers scrutinized the frontal cortex of a human brain and the same region of mouse brains for differing patterns of genetic activity in neurons. These cells may appear structurally indistinguishable from each other. The team identified 16 neural subtypes in the mice and 21 subtypes in the human brain, several of them not known before.


The study was published Thursday in the journal Science. Joseph Ecker and Margarita Behrens of the Salk Institute; and Eran Mukamel of UC San Diego, were the senior authors. Go to j.mp/methylbrain for the study.

For followup work, the scientists say they plan to examine more human and mouse brains, and more regions of these brains, to create what they call a “parts list.” Once that list is complete, they plan to compare the patterns of gene activation in healthy people with patterns of those who have brain diseases.

All told, there are hundreds, perhaps even thousands of different types of brain cells, the Salk and UCSD scientists say. Each type presumably plays a specific role in brain functioning.

For example, some neurons inhibit transmission of signals between other neurons, while others encourage it. The signals could provide information on the color of an object, its motion, the sensation of a mosquito on the skin, a musical note, depending on where in the brain the cells are located.


This specialization bears significance for understanding brain activity and efforts to mimic it through artificial intelligence, said Hongkui Zeng, executive director of structured science at the Allen Institute for Brain Science in Seattle.

“This is a very novel study both technically and conceptually,” Zeng said by email. “Classifying the millions to billions of neurons in an animal’s brain into types and understanding the function of each type is an extremely important step towards understanding how the brain works as a whole.”

“Just like each person is unique, each cell or neuron is also different from all other cells in many ways,” she said. “Thus cell type classification is a very challenging task, one needs to profile a cell from multiple aspects and combine all the information together in order to assign cell type identity correctly. “

“This type of cell type classification research is the first step in deconstructing the neural networks – creating a parts list as mentioned above. Once we have a parts list, we can then try to understand how the different parts – the cell types – are connected together, and how they work together to process information the brain receives. Then we can develop algorithms that simulate this process that is happening in the neural network. And these algorithms should be very useful for the further development of artificial intelligence.”


Models of consciousness traditionally tend to distinguish between certain broad categories of neurons such as those exciting a response and those inhibiting a response. What they don’t do is distinguish between them by location, such as the differences between an excitatory neuron in one part of the cortex and similar excitatory neurons in another part of cortex.

“We know they have striking functional differences, but we did not know how to differentiate them molecularly,” Behrens said. “We now are able to do so.”

Researchers had previously attempted to distinguish different neuronal types by examining their patterns of making RNA, the chemical messenger from DNA that is used to make proteins. But these patterns can change rapidly, making it hard to classify cells.

In addition, only a small percentage of DNA is used for RNA production. So examining DNA directly catches pertinent variations that would otherwise be missed.


To get a more reliable indication of cell type, the scientists examined a property of cells called methylation, which switches genes on and off by adding or subtracting molecules called methyl groups to DNA. This property is more stable. It’s part of a field called epigenetics, the study of chemical alterations to DNA that do not change the underlying sequence of DNA letters.

The team examined the methylation profiles of 2,784 neurons in the human brain, from a deceased 25-year-old man; and 3,377 neurons from the brains of mice. Drilling down further, the team scanned the cells for two types of methylation, one called CG methylation and the other called non-CG methylation.

Non-CG methylation was discovered in plants, and previously not thought to play a major role in animals. But scientists led by Ecker and Behrens have previously found that non-CG methylation is prominent in brain cells, thus discovering differences between cells that previously appeared identical. Ecker is familiar with that kind of methylation from his work heading a plant epigenetics laboratory at the Salk.

The new study builds on preceding research that detected signs of cell types by a less precise method that examines the average methylation properties of many cells in certain parts of the brain. The averages varied, hinting at different populations of neurons by region.


The new study was performed with a method that allows determining the methylation patterns of individual neurons. This single-cell method enabled pinpoint identification of even rare neurons that would otherwise be missed.

For further reading

Plant study illuminates brain

Plants, brains, engineered networks share unifying principles

Genome-controlling map made


Novel Methylation Distinguishes Neuron Types, May Dictate Disease

Human body epigenome maps reveal noncanonical DNA methylation variation


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