Complex neuronal communication behind jump execution
When danger looms, locusts on the ground leap and fly away. The timing and precision of that leap starts with the complex coding of visual information within a single neuron.
In the current edition of the journal Neuron, researchers at Baylor College of Medicine and the University of Utah uncovered three distinct features in the communication process of a sensory neuron that control distinct motor aspects of escape behavior – firing rate threshold, peak firing time and spike count.
"This process has been studied for years but it is only now that we have been able to record firing rates of neurons in freely moving animals," said Dr. Fabrizio Gabbiani, associate professor of neuroscience at BCM. "When movement happens naturally, its relation to neuronal firing is interpreted more easily and accurately."
Jump muscles in the leg
Researchers at the University of Utah created a microchip used along with a digital telemetry system that allowed Haleh Fotowat, a graduate student in the department of neuroscience at BCM, to record the activity of the descending contralateral movement detector (DCMD) neuron and of thoracic motoneurons that control the jump muscles in the leg. The DCMD transmits visual information about the threat to these motoneurons in thoracic motor centers.
"We were able to measure the firing rate of the detector neuron and predict when the insect will jump," said Gabbiani.
In their study, researchers used an image that grew bigger and appeared to be getting closer to trigger the locust’s jump.
The response of the DCMD can be summarized by three essential features: firing rate threshold, peak firing time and spike count.
"As the object gets bigger, the firing rate increases. When the firing rate crosses a certain threshold, about 220 spikes per second, we start to see what we call an initial energy storage phase. Muscles begin to contract to store energy, like loading a spring," said Gabbiani.
The firing rate reaches a peak and then begins to decrease. Researchers say the time of the peak predicts when locusts will jump. Whether locusts will jump at all depends on the number of spikes generated from the time the energy storage phase begins.
"If I know the time of the peak, then I know when they are going to jump," said Gabbiani. "Also, if they start storing energy late, then they can’t generate enough spikes and you can predict with high accuracy that they won’t jump."
The next step is to look at escape behaviors while the insect is in flight.
"Right now, we want to understand this process fully because this is the first time we see this type of encoding of information at different levels in a single neuron firing rate," said Gabbiani. "There is essentially no reason to believe that the encoding of escape behaviors would not be similar in other animals."
Others who took part in this study include Reid R. Harrison, University of Utah, Salt Lake City, UT. Gabbiani is also with the department of computational and applied mathematics at Rice University.
The study was funded by the Air Force Research Laboratory, the Human Frountier Science Program, the National Institute of Mental Health and the National Science Foundation.