Cedars-Sinai researchers have created computer-generated models to bridge the gap between “test tube” data on neurons and the function of those cells in the living brain. Their study, published in the peer-reviewed journal nature communications, it could help in the development of treatments for neurological diseases and disorders that target specific types of neurons based on their functions.
“This work allows us to begin to view the brain as the complex machine that it is, rather than as a homogeneous piece of tissue,” said Costas Anastassiou, PhD, a research scientist in Cedars’ departments of Neurology, Neurosurgery, and Biomedical Sciences. -Sinai and lead author of the study. “Once we can distinguish between different cell types, rather than saying the whole brain has a disease, we can ask what types of neurons are affected by the disease and tailor treatments to those neurons.”
Neurons are the main functional units of the brain. The signals that pass through these cells, in the form of electrical waves, give rise to all thought, sensation, movement, memory, and emotion.
The study used data from laboratory mice to establish a new method for examining relationships between neuron type and function, and focused on the mouse’s primary visual cortex, which receives and processes visual information. It is one of the best-studied parts of the brain, both in vitro, where the tissue is studied in a dish or test tube outside the living organism, and in vivo, where it is studied in the living animal.
The researchers’ goal was to link the two worlds.
“Based on in vitro studies of genetic makeup and physical structure, we know something about what various classes of neurons look like, but not their function in the living brain,” Anastassiou said. “When we record the activity of brain cells in vivo, we can see which neurons they respond to and what their function is, but not what kinds of neurons they are.”
To link form to function, the researchers first used in vitro data to create computational models of various types of neurons and simulate their signaling patterns.
Next, they took advantage of the latest technology in single-neuron recording to observe activity in the brains of laboratory mice while the mice were exposed to different types of visual stimuli. Based on the shapes of the signals or “spikes” of the neurons in response to visual input, the researchers separated the cells they recorded into six groups.
“Once we had our models and our in vivo data, the fundamental question was which computational models produced the most similar signaling pattern and waveform to each of the six in vivo groups we identified, and vice versa,” Anastassiou said. . “Not all in vivo groups and models were a perfect match, but some were.”
More data and possibly experiments involving more sophisticated visual stimuli may be required to match all computational models and cell groups, and Anastassiou said future studies will be dedicated to refining the method laid out in the current paper.
“There is a wealth of information on the identity of cell types in the human brain, but not on the role of those cell types in cognitive functioning or how they are affected by disease,” Anastassiou said. “There is now a window through which we can look at these things and ask these questions. Clearly we have a long way to go, but we are excited about the next steps on this journey.”
The ultimate goal is to pave the way for life-changing discoveries for patients.
“Our research scientists continually strive to expand our understanding of human brain function at the most detailed level,” said Keith L. Black, MD, chair of the Department of Neurosurgery and the Ruth and Lawrence Harvey Chair in Neuroscience at Cedars. -Sinai. “Pinning down the specific type and function of each neuron may one day lead to the discovery of life-saving treatments for brain diseases and neurological disorders.”
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