"Wavelet Analysis of
Olfactory Nerve Response to Stimulus"
by
Lewalle, J., Peek, F.W. and Murphy, S.J.
ABSTRACT
Multiunit electrophysiological activity recorded by gross
electrodes from the olfactory nerve was analyzed by
wavelet decomposition, a relatively new method of signal
processing. The analysis was run on data from the unstimulated
olfactory system as well as on data evoked in response to six
different odorant stimuli. Like Fourier analysis, wavelet
analysis provides a spectral decomposition of the signal. Unlike
Fourier, wavelet analysis also locates the
dominant spectral features in time. The output of a
wavelet analysis can be further processed to enhance selected
features. In our data the increased amplitude of
the nerve response evoked by stimulation was the most obvious
feature, but efforts to learn from it were unproductive.
The temporal pattern of receptor cell activity was much more
yielding. The analysis resolved the nerve activity into
three classes of events based on duration.
On wavelet maps these classes of events
separate out into three shifting and overlapping but
distinct bands, one of which we interpreted as being associated
with individual receptor cell firings and the other two
as short and somewhat longer duration
bursts of activity that we attribute to the synchronized
firing of a group of receptor cells. This interpretation is supported
by experiments in which waveforms simulating action potentials
and bursts of action potentials are added to recorded data.
Stimulation of the olfactory system with odorant
molecules evokes a significant
increase in the number of short duration bursts, and an amplitude
increase that can be related to the number of receptor cells
responding. Changes in the patterns of wavelet
events can be associated with synchrony of cell firing,
reset times for bursts of firing,
and possibly other physiological dynamics. Anecdotal differences in
activity patterns with different odorants were observed, but
without sufficient repeatability to allow reliable discrimination
among them. While this study is clearly preliminary in that
regard, it shows the potential of the wavelet method for
contributing to the understanding of olfaction.