A digital sequence method of dynamic olfactory characterization

Measurements of system dynamics, such as input–output frequency response estimation, have been widely used in neuroscience. Dynamic characterization of sensory systems has been particularly useful because both the amplitude and time-dependent properties of sensory input signals can often be accurately controlled. However, chemoreceptors have proved less amenable to these approaches because it is often difficult to accurately modulate or measure chemical concentration at a sensory receptor. New methods of dynamic olfactory stimulation have recently been introduced that combine controlled mechanical release of odorant with detection by photoionization of surrogate tracer gas mixed with the odorant. We have developed a modified version of this approach based on rapid binary switching of odorant flow using pseudo-random binary signals (maximum-length sequences, or M-sequences) generated by a software shift register. This system offers several advantages over previous methods, including higher frequency range stimulation, experimental simplicity and the possibility of computational efficiencies. We show that there is predictable dynamic odorant concentration at the sensory receptor and we explore the stimulation parameters as functions of total air flow rate and spatial location. A typical application of the system is shown by measuring the frequency response function of a Drosophila electroantennogram.