Revolutionary Tiny Sensor Reveals Hidden Neuron Activity

Arthur T Knackerbracket has processed the following story:

Implantable technologies have significantly improved our ability to study and even modulate the activity of neurons in the brain. However, neurons in the spinal cord are harder to study in action.

If we understood exactly how neurons in the spinal cord process sensation and control movement, we could develop better treatments for spinal cord disease and injury," said Yu Wu, a research scientist who is part of a team of Rice University neuroengineers working on a solution to this problem.

We developed a tiny sensor, spinalNET, that records the electrical activity of spinal neurons as the subject performs normal activity without any restraint," said Wu, who is the lead author of a study about the sensor published in Cell Reports. Being able to extract such knowledge is a first but important step to develop cures for millions of people suffering from spinal cord diseases."

According to the study, the sensor recorded neuronal activity in the spinal cord of freely moving mice for prolonged periods and with great resolution, even tracking the same neuron over multiple days.

Up until now, the spinal cord has been more or less a black box," said Lan Luan, an associate professor of electrical and computer engineering and a corresponding author on the study. The issue is that the spinal cord moves so much during normal activity. Every time you turn your head or bend over, spinal neurons are also moving."

During such movements, rigid sensors implanted in the spinal cord inevitably disturb or even damage the fragile tissue. SpinalNET, however, is over a hundred times smaller than the width of a hair, which makes it extremely soft and flexible nearly as soft as the neural tissue itself.

This flexibility gives it the stability and biocompatibility we need to safely record spinal neurons during spinal cord movements," said Chong Xie, an associate professor of electrical and computer engineering and bioengineering and a corresponding author of the study. With spinalNET, we were able to get low-noise signals from hundreds of neurons."

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