Analyze images with algorithms to realize accurate “video” study of neuron behavior

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Recently, MIT’s engineer team invented an automated method to analyze microscope images using computer algorithms and guide the “robotic arm” to target cells to realize the research and analysis of the specific behavior of neurons.
Analyze images with algorithms to realize accurate “video” study of neuron behavior
Analyze images with algorithms to realize accurate “video” study of neuron behavior
It is understood that this technology can enable more scientists to study single neurons and understand how a single neuron can realize the cognitive, sensory and other functions of the human brain through its interaction with other cells. In addition, researchers can also use this technology to understand how neural circuits are affected by brain disorders.
The associate professor of MIT bioengineering explained: “Understanding the communication mode of neurons is the basis of basic and clinical neuroscience. When neurons are working or neurons are in a sick state, we hope to let you see what is happening in the cells through this technology.”
In the past 30 years, neuroscientists have been using a technique called “patch” to record the potential activity of cells. The specific implementation of this technology is to use a small hollow glass tube to contact the cell membrane of neurons, and then open a small hole on the membrane to observe. This technology usually takes a graduate student or postdoctoral student several months to learn and operate. Especially in mammalian brain, this technology will be more difficult to learn.
Previously, there are two types of “subsidy” technology. One is blind and random selection of location. Because researchers cannot see the specific location of cells, they can only record the location of each attempt to find the exact location of cells. Another method is to use image guidance, but the accuracy of this method is not high.
Analyze images with algorithms to realize accurate “video” study of neuron behavior
Analyze images with algorithms to realize accurate “video” study of neuron behavior
In 2012, Boyden and his colleagues invented a method of automatic patch repair. They wrote a computer algorithm, which can guide the straw to aim at a cell according to a characteristic called electrical impedance.
This method also shows how difficult it is to manually search for the cell position before, because even using the algorithm, it is also through the continuous attempt and calculation of the computer to approach the final position. The specific process is that if there are no cells around, the current will decrease, the impedance will also decrease, and the tip will move. When the tip reaches a cell, the current will not flow, and the impedance will increase rapidly, so that the computer can make the tip quickly lock the cell position.
When the tip of the pipette is locked, it stops on the cell surface, and then uses a vacuum pump to form a closed space between the membrane and the tip through suction. Then, the electrode through the membrane will record the potential activity inside the cell.
Analyze images with algorithms to realize accurate “video” study of neuron behavior
Although this technology has achieved high accuracy, it still cannot be used to target specific cells. In order to achieve accurate directional operation, researchers began to try to complete the operation manually by combining automatic image guidance technology. However, it is worth noting that after the tip of the pipette enters the brain, the nearby cells will move automatically, so the manual operation is very difficult.
Therefore, based on the combination of various imaging technologies, researchers proposed an algorithm to move the pipette into a target cell of about 25 microns. In order to achieve this higher accuracy, the system combines the image technology with the technology using impedance characteristics.
Then the researchers used a two-photon microscope to image the cells, and then used a pulsed laser to send infrared rays into the brain to brighten the cells designed to express fluorescent proteins for easy tracking and recognition.
Now, using this latest method, researchers can successfully target cells with a success rate of 20%. This is similar to the performance of trained scientists in the process of manual operation.
With the development of brain-computer interface technology and the continuous warming of biotechnology, this research method will become a key basic technology, paving the way for the in-depth study of specific neuron behavior. In addition, it is undoubtedly a great progress to replace students with computers or robots and reduce the time spent by students in repetitive work. At the same time, the computer video of this research is also very convenient for sharing research, and to some extent, it realizes the integration of resources. This technology will also greatly promote the research of unexplained diseases (such as Alzheimer’s disease or schizophrenia) in the medical field..

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