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Scientists develop robot that scans information directly from neurons

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Scientists develop robot that scans information directly from neurons Neuroscientists from Georgia Tech and MIT have developed a robotic system that can find and simultaneously record the activity of dozens of neurons in live animals. The breakthrough could help researchers better understand how connected cells interpret signals and transmit information throughout the brain.

Nature's Helen Shen reports:

Scientists develop robot that scans information directly from neurons

The robots are designed to perform whole-cell patch-clamping, a difficult but powerful method that allows neuroscientists to access neurons' internal electrical workings, says Edward Boyden of the Massachusetts Institute of Technology in Cambridge, who is leading the work.

Manually performing the method on live animals requires extensive training to perfect and, as a result, only a handful of neurophysiologists use the technique, says Boyden, who presented at the conference. He is developing the automated tool with Craig Forest at the Georgia Institute of Technology in Atlanta and others. "We think that it helps democratize procedures that require a lot of skill," he says.

In May, the group described how a basic version of the robot can record electrical currents in single neurons in the brains of anaesthetized mice. The robot finds its target on the basis of characteristic changes in the electrical environment near neurons. Then, the device nicks the cell's membrane and seals itself around the tiny hole to access the neuron's contents. On 24 August, Boyden presented results showing that a more advanced version of the robot could be used to identify and probe four neurons at once - and he says he wants to push the design further, perhaps to tap as many as 100 neurons at a time.

This breakthrough could allow for improved drug testing — and even a "periodic table" of neurons in the brain to explain what each of them does and how they interact.

The entire study can be read at Nature.

Images via MIT/McGovern Institute.


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