Characterization of autonomic release sites using the time-frequency analysis of junction potentials in smooth muscle

The determination of probability of neurotransmitter release from neuronal release sites and their electrical characterization is an issue of central interest in neurophysiology. For autonomic nerves, this can be done by analysing the inflexions in the rising phases of the evoked junction potentials (EIPs) recorded from smooth muscle. Since these inflexions contain time-varying frequency information, we have applied recent methods of time-frequency analysis based upon wavelet transforms on ElPs to characterize autonomic neuronal function. We find that these methods allow accurate and convenient charaderization of individual release sites, and that their probability of release falls between 0.002 and 0.003. These results are compared with those reported earlier using analogue filtering techniques. The present method is advantageous as regards automation, accuracy and suppression of noise.