In the real world, odors don't happen one puff at a time. Animals move through, and subsequently distort, plumes of odor molecules that constantly drift, changing direction as the wind disperses them.
Now, by exploring how animals smell odors under naturalistic conditions, Rockefeller University scientist Maria Neimark Geffen and her colleagues reveal that the brain encodes these swirling, complex patterns of molecules using surprisingly little neural machinery. The findings suggest a new theory of how animals smell.
In their work, which will appear in the February 26 issue of Neuron, Geffen, a fellow at Rockefeller's Center for Studies in Physics and Biology, analyzed the brain activity of locusts as they smelled plumes of different odors generated by odor molecules released for varying durations and at varying intervals - not in metronome-like Odors simplified. In the real world, plumes of odor molecules drift randomly in the air, swept to and fro by whatever might be. Scientists now show that the locust brain uses three simple rules (reds, greens and blues) to encode the complex and ever-changing odor signals of these plumes.
pulses as is typically done in odor studies. "In their habitat, animals don't have the luxury of smelling something for one second and then trying to figure out what it is," says Geffen. "They are getting this ever-changing signal. So how does the olfactory system encode the dynamics of that signal?"
The answer, it turns out, is surprisingly simple.
When Geffen and her colleagues from Harvard University and the California Institute of Technology initially looked at how the olfactory system responded, the results looked daunting. Even though a small population of neurons was activated in response to each odor, the pattern of activation differed from neuron to neuron. Consider, Geffen says, that each neuron is the source of a flashing light. If the population of neurons all started flashing, each neuron would appear to be flashing in a frenetic and uncoordinated fashion relative to all the others. It would be hard to envision a set of rules that coordinates such complex activity. But by looking at how the population of neurons function together, Geffen and her colleagues found that these vastly different responses could be explained by a very simple model.