Control of the firing patterns of vibrissa motoneurons by modulatory and phasic synaptic inputs: a modeling study.
Vibrissa motoneurons (vMNs) generate rhythmic firing that controls whisker movements, even without cortical, cerebellar, or sensory inputs. vMNs receive serotonergic modulation from brain stem areas, which mainly increases their persistent sodium conductance (g(NaP)) and, possibly, phasic input from a putative central pattern generator (CPG). In response to serotonergic modulation or just-suprathreshold current steps, vMNs fire at low rates, below the firing frequency of exploratory whisking. In response to periodic inputs, vMNs exhibit nonlinear suprathreshold resonance in frequency ranges of exploratory whisking. To determine how firing patterns of vMNs are determined by their 1) intrinsic ionic conductances and 2) responses to periodic input from a putative CPG and to serotonergic modulation, we construct and analyze a single-compartment, conductance-based model of vMNs. Low firing rates are supported in extended regimes by adaptation currents and the minimal firing rate decreases with g(NaP) and increases with M-potassium and h-cation conductances. Suprathreshold resonance results from the locking properties of vMN firing to stimuli and from reduction of firing rates at low frequencies by slow M and afterhyperpolarization potassium conductances. h conductance only slightly affects the suprathreshold resonance. When a vMN is subjected to a small periodic CPG input, serotonergically induced g(NaP) elevation may transfer the system from quiescence to a firing state that is highly locked to the CPG input. Thus we conclude that for vMNs, the CPG controls firing frequency and phase and enables bursting, whereas serotonergic modulation controls transitions from quiescence to firing unless the CPG input is sufficiently strong.
Harish
Omri
O
Department of Physiology and Neurobiology, Faculty of Health Sciences, Ben-Gurion University, Be'er-Sheva, Israel.
Golomb
David
D
D000200:Action Potentials / Q000502:physiology*; D000222:Adaptation, Physiological; D000465:Algorithms; D000818:Animals; D002412:Cations / Q000378:metabolism; D003198:Computer Simulation; D017097:Electric Impedance; D008564:Membrane Potentials / Q000502:physiology; D008959:Models, Neurological; D009043:Motor Activity / Q000502:physiology; D009046:Motor Neurons / Q000502:physiology*; D010507:Periodicity; D011188:Potassium / Q000378:metabolism; D051381:Rats; D012701:Serotonin / Q000378:metabolism; D013569:Synapses / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*; D014738:Vibrissae / Q000502:physiology*
D002412:Cations; D012701:Serotonin; D011188:Potassium