Chew-WGA 0.9 - The Windows 7 Patch
Mozell Gentges
1. Our aim has been to quantify the monosynaptic connections of trigeminal interneurones and spindle afferents onto jaw-elevator motoneurones as a step towards identifying common features in organization of monosynaptic inputs onto motoneurones. We have used the intracellular variant of the spike-triggered averaging method to examine the connections of single identified trigeminal interneurones and jaw-elevator muscle spindle afferents onto single jaw-elevator motoneurones. The interneurones examined lay in the region immediately caudal to the trigeminal motor nucleus. The experiments were performed on rats anaesthetized with pentobarbitone, paralysed and artificially ventilated. 2. Ten EPSPs and eight IPSPs were obtained from examining the connections of seventeen interneurones to thirty-six motoneurones, suggesting a functional connectivity of 50% for individual interneurones onto elevator motoneurones. Fourteen EPSPs were obtained from examining the connections of thirteen spindle afferents onto twenty-seven motoneurones, giving a functional connectivity of 52% for individual spindle afferents onto elevator motoneurones. The amplitudes of the EPSPs elicited by interneurones ranged from 7-48 microV (mean = 17, S.D. = 12.5, n = 10) and from 7 to 289 microV (mean = 64, S.D. = 76.0, n = 14) for the spindle-mediated EPSPs; the difference in the two means was not significant (P = 0.07). 3. However, the amplitude of averaged responses obtained by signal averaging methods are dependent on the assumption that the postsynaptic response occurs following every impulse in the presynaptic neurone. We therefore estimated the percentage of sweeps which contained EPSPs triggered by the presynaptic neurone under study. In essence the method used consisted of visual inspection of the individual sweeps comprising an average in order to assess the occurrence of EPSPs within six separate time windows, each of duration +/- 0.3 ms. Five windows were placed at randomly selected times on
Chew-WGA 0.9 - The Windows 7 Patch
Stochastic leaky integrate-and-fire models are popular due to their simplicity and statistical tractability. They have been widely applied to gain understanding of the underlying mechanisms for spike timing in neurons, and have served as building blocks for more elaborate models. Especially the Ornstein-Uhlenbeck process is popular to describe the stochastic fluctuations in the membrane potential of a neuron, but also other models like the square-root model or models with a non-linear drift are sometimes applied. Data that can be described by such models have to be stationary and thus, the simple models can only be applied over short time windows. However, experimental data show varying time constants, state dependent noise, a graded firing threshold and time-inhomogeneous input. In the present study we build a jump diffusion model that incorporates these features, and introduce a firing mechanism with a state dependent intensity. In addition, we suggest statistical methods to estimate all unknown quantities and apply these to analyze turtle motoneuron membrane potentials. Finally, simulated and real data are compared and discussed. We find that a square-root diffusion describes the data much better than an Ornstein-Uhlenbeck process with constant diffusion coefficient. Further, the membrane time constant decreases with increasing depolarization, as expected from the increase in synaptic conductance. The network activity, which the neuron is exposed to, can be reasonably estimated to be a threshold version of the nerve output from the network. Moreover, the spiking characteristics are well described by a Poisson spike train with an intensity depending exponentially on the membrane potential.
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