A team led by Drs. Jeremy Freeman and Misha Ahrens recently recorded the activity of approximately 80,000 neurons firing in the brain of a zebrafish larvae. The technique they implemented is called light-sheet microscopy. Briefly, the scientists genetically engineer zebrafish neurons to emit a fluorescent signal just after the neuron fires. Laser beams are the shot through the fish so that the activated neurons will glow and an overhead microscope records the whole thing. Of course, this technique only works because the zebrafish are entirely transparent, so don’t expect to have your brain scanned in this manner any time soon.
“At the beginning of the movie, the fish is resting and the forebrain region on the far-right is flashing away. That may represent whatever the fish is thinking about when it’s just hanging out.
Scientists then created the illusion that the fish was drifting backwards by sliding bars in front of its eyes. Its intent to swim to catch up was measured with electrodes on its muscles. When the bars start sliding, a few neurons sitting just behind the eyes light up followed by a huge cascade of activity, including massive pulses initiating swimming.”
“There must be fundamental principles about how large populations of neurons represent information and guide behavior,” says neuroscientist Jeremy Freeman of Janelia Farm Research Campus in Ashburn, Virginia. “In this system, where we record from the whole brain, we might start to understand what those rules are.”
We know that the processing of sensory input and the generation of behavior involves large networks of neurons, and Dr. Freeman believes that observing networks with this sort of technology will enable us to gain deeper insight to how the brain functions.
It is important to note that the temporal resolution is fast enough to identify which neurons are involved in a given behavior but too slow to count how many times they fire. Thus, there is no way that this technique could ever decipher the neural computations that take place at the millisecond timescale in the human brain.
I think we’ll probably need nanobots to ever fully decode the brain…
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