The results of this analysis of the torques at the base of a vibrating mass rate sensor show that they are complex to interpret. For example, yaw acceleration, a, produces a dc torque component, as well as a time-variable one proportional to cos[2. m sin(. m t)]. Yaw velocity, a, produces a time-variable torque proportional to cos(. m t) sin[2. m sin(. m t)]. This term gives a torque at double the haltere vibration frequency, . m. Mechanosensory cells in the bases of the halteres presumably re synchronously with the haltere vibration. Because of the high frequency of vibration, amplitude information for a is probably coded by recruiting more and more cells to re. Thus, yaw and pitch rate information could be coded by the number of mechanosensors ring e very cycle or half-cycle, giving a high data sampling rate. One can conjecture from an engineering point of view how this information might be demodulated by the y , but it boggles the mind how it might be done with real neurons.

Dipteran insect ight stabilization in the daytime is probably dominated by inputs from the compound eyes and aerodynamic hair patches and antennae. In the dark, or under low-light conditions, it is reasonable to expect roll, pitch, and yaw signals from the haltere sensors to play a signi cant role in stabilizing ight. That the ght stabilization system has three sensory input modalities (inertial, visual, and aerodynamic) argues for its complexity. How a y decodes this information and uses it to stabilize its ight is going to remain a mystery for some time.

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