@article {Tseng10809, author = {Hua-an Tseng and Farzan Nadim}, title = {The Membrane Potential Waveform of Bursting Pacemaker Neurons Is a Predictor of Their Preferred Frequency and the Network Cycle Frequency}, volume = {30}, number = {32}, pages = {10809--10819}, year = {2010}, doi = {10.1523/JNEUROSCI.1818-10.2010}, publisher = {Society for Neuroscience}, abstract = {Many oscillatory networks involve neurons that exhibit intrinsic rhythmicity but possess a large variety of voltage-gated currents that interact in a complex fashion, making it difficult to determine which factors control frequency. Yet these neurons often have preferred (resonance) frequencies that can be close to the network frequency. Because the preferred frequency results from the dynamics of ionic currents, it can be assumed to depend on parameters that determine the neuron{\textquoteright}s oscillatory waveform shape. The pyloric network frequency in the crab Cancer borealis is correlated with the preferred frequency of its bursting pacemaker neurons anterior burster and pyloric dilator (PD). We measured the preferred frequency of the PD neuron in voltage clamp, which allows control of the oscillation voltage range and waveforms (sine waves and realistic oscillation waveforms), and showed that (1) the preferred frequency depends on the voltage range of the oscillating voltage waveform; (2) the slope of the waveform near its peak has a strongly negative correlation with the preferred frequency; and (3) correlations between parameters of the PD neuron oscillation waveform and its preferred frequency can be used to predict shifts in the network frequency. As predicted by these results, dynamic clamp shifts of the upper or lower voltage limits of the PD neuron waveform during ongoing oscillations changed the network frequency, consistent with the predictions from the preferred frequency. These results show that the voltage waveform of oscillatory neurons can be predictive of their preferred frequency and thus the network oscillation frequency.}, issn = {0270-6474}, URL = {https://www.jneurosci.org/content/30/32/10809}, eprint = {https://www.jneurosci.org/content/30/32/10809.full.pdf}, journal = {Journal of Neuroscience} }