On Friday, researchers announced the completion of a map of every neuron in the brain of a male fruit fly. The "connectome" provides a tool that can accelerate neurobiology research. But it also provides an opportunity to do some science on its own, as the connectome of a female Drosophila had been completed earlier this year. The work also provided the team behind it the opportunity to refine tools that are likely to be applied to ever-more complex nervous systems, including (potentially) those of vertebrates.

The new work involved a collaboration between biologists at the Howard Hughes Medical Institute's Janelia Research Campus and computer scientists at Google—both acknowledge that neither could have done the project without the other. Preparation of an entire brain for imaging at the necessary resolution requires a distinct set of skills, as does interpreting what those images indicate. But building a complete picture of the hundreds of millions of synapses in a brain as small as the fruit fly's is a task that can't be achieved by humans in a manageable amount of time.

The people behind the effort expect that in the long term, the effort will be worth it, as the connectome could give neurobiologists a valuable tool for understanding how the brain works.

Read full article

Comments

Fruit flies aren't exactly famous for their brainpower; you've probably drowned more than one in a wine glass left too long on the patio table. And yet, working with roughly 140,000 neurons—a brain smaller than a poppy seed—Drosophila can sort through a huge range of smells in a fraction of a second, and then retain the memory of that scent for a long time.

In this, they do much better than current "electronic noses." Even the most advanced ones on the market tend to be expensive, painfully narrow in what they can detect, and quick to forget an odor the moment they learn a new one.

So why not just copy the fly? That's the question a growing number of researchers have been asking—including Kevin Max and Yang Shen at the Okinawa Institute of Science and Technology, whose new algorithm, Spi-Fly, is described in a paper recently published in the journal Neuromorphic Computing and Engineering.

Read full article

Comments