Each lever or 'sensillum' can detect a shift in the sand as small as one millionth of a millimetre. The scorpion knows you're there. But its eyes are nearly useless. Now Leo van Hemmen and a team of theoretical physicists from the Technical University of Munich, Germany, have applied mathematics to a neural model dreamed up by zoologists in the 1970s to work out the answer. The neural model assumes that sensory neurons are connected to the ultra-sensitive sensilla on the scorpion's legs.
Vibrations travel out in waves from the prey.
When a sensillum senses the vibrations, it starts to send signals to its neuron. But the neural wiring is set up so that when, a split-second later, the vibrations reach the sensilla on the legs on the far side of the scorpion, they set off 'inhibitory' neurons that switch off the first signals. And this time difference reflects the direction of the prey. Given an 'input' prey position, the new mathematical model uses these time windows to calculate the neuron firing probabilities for each leg, and converts the sum over the eight legs into a probability for the final turning angle of the scorpion. The mathematics models how the eight legs 'vote' on which direction the scorpion should turn.