tory cilium, which is a typical property of biological systems containing small number of molecules. Although it is well known that Ca2+ is required for the occurrence of STA, it is unclear how the 
action of signaling pathways regulating the intensity and time course of cAMP and the Ca2+ influx through CNG channels modulate the rise time, decay time, latency and adaptation of sensory responses to odorants. Thus, the model simulated pulses of cAMP that activate CNG channels. The Ca2+ influx through these channels rises the intracellular leading to the activation of CAC channels. Moreover, Ca2+ binds to CaM, which desensitizes the CNG channels through a decrease in its affinity for cAMP. In addition, NCKX restores the intracellular Ca2+ levels. A diagram of the model is shown in 5E, target~targetmax 2 where target refers to the molecule that has been analyzed, targetmax is the maximum activation of the target, nHILL is the Hill coefficient and K1/2 is the concentration of the ligand required to fully activate half of the total amount of the target. The curves have parameters for the components of the model in accordance with experimental published values . As a final point, the model simulated brief paired pulses of cAMP separated by multiple ISIs to reproduce the results of STA AMI-1 price obtained with EOG recordings. We simulated the general pharmacological effects of IBMX, okadaic acid and monensin in the EOG signal, which slowed down the kinetics and increased the levels of adaptation. The model presents the typical recovery percentage from adaptation versus ISIs PubMed ID:http://www.ncbi.nlm.nih.gov/pubmed/19664276/ for the control condition, IBMX, okadaic acid and monensin. Also, the ISI50 obtained from the simulated curves reproduced the ISI50 obtained experimentally. In addition, the model fitted the kinetics of the EOG responses to odorants. Simulated Regulation of Transduction and Adaptation effects of IBMX, okadaic acid and monensin also increased the rise time and decay time of EOG responses. The latency of EOG responses to odorants was not simulated explicitly, once it depends on upstream signaling cascades that were not considered in the model, including the binding of odorant to GPCR, the activation of Gaolf and AC3. Therefore, the simulated latencies are smaller and represent only the time lag between the release of cAMP and activation of CNG and CAC channels. In the model, the dynamics of the cAMP signal is determined by its rate of production and hydrolysis in the cilium. To simulate the control condition, paired pulses of free cAMP with duration of 100 ms, amplitude of approximately 6 mM and a rate of hydrolysis of 25 s21 reproduced accurately the results of the control group. To simulate the effects of the inhibition of PDE, phosphatase and GPCR internalization, we changed the peak amplitude and rate of hydrolysis of cAMP. The amplitude of free cAMP pulses was increased to approximately 15 mM and the hydrolysis decreased to 0.4 s21 to model the effects of IBMX, okadaic acid, and monensin. Consequently, these changes in the dynamics of cAMP prolonged the Ca2+ signals, CNG currents and CAC currents, reproducing the experimental data. The cAMP input used to simulate these effects are provided in the 7 Regulation of Transduction and Adaptation 8 Regulation of Transduction and Adaptation frequencies of cAMP pulses of 100 ms reproduced the experimental EOG response to odorant puffs of the same frequency and duration. E: Result of the model to pulses of cAMP of 5 s and 1 s reproduced the ex