In the 1950s, researchers established that the brain is a computer and the neurons present in it are complex circuits. Many years later, neuroscientists know that these brain circuits exist. But due to lack of resources, no one was able to dig up more.
But now they may disclose what is deep in the brain. Gratitude to a molecule that lights up brighter than before in reaction to subtle electrical alterations that neurons use to compute.
Presently, one of the useful strategies to trail neurons’ electrical activity is with molecules. These brighten up when exposed to calcium ions, a rep for a neuron plug, the juncture when one neuron passes an electrical signal to another. But calcium is not enough fast to catch all the details of a neuron spike. And it doesn’t respond to the indirect electrical changes that lead up to a spike.
To decipher these issues, a team lead by Michael Lin, an associate professor of neurobiology and of bioengineering and a member of the Wu Tsai Neurosciences Institute, and Stéphane Dieudonné, an INSERM research director at the École Normale Supérieure in Paris, concentrated on luminous molecules whose brightness responds directly to voltage differences in neurons, an idea Lin and his team had been working on for years.
There was still a problem that the molecules’ brightness wasn’t always responsive to voltage. So Lin and his team at Stanford used a method called electroporation. In this, researchers use electrical probes to zap gaps in cell membranes, with the side effect that their voltage drops quickly to zero. By zapping a set of prospect molecules, Lin and colleagues could then specify those whose brightness was most responsive. As reported, the resulting molecule, called ASAP3, is the most responsive voltage indicator till now.
Dieudonné and his lab concentrated on another problem: how to scan neurons deep in the brain more efficiently. They found out a new algorithm called ultrafast local volume excitation, or ULoVE, in which a laser rapidly scans several points in the volume around a neuron, all at once.
In the meantime, Lin and colleagues are working on improving their methods and finding more upgraded methods.
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