Simulation and parameter estimation of dynamics of synaptic depression

Abstract

Synaptic release was simulated using a Simulink sequential storage model with three vesicular pools. Modeling was modular and easily extendable to the systems with greater number of vesicular pools, parallel input, or time-varying parameters. Given an input (short or long tetanic trains, patterned or random stimulation) and the storage model, the vesicular release, the replenishment of various vesicular pools, and the vesicular content of all pools could be simulated for the time-invariant and time-varying storage systems. From the input stimuli and either a noiseless or a noisy output, the parameters of such storage systems could also be estimated using the optimization technique that minimizes in the least square sense the error between the observed release and the predicted release. All parameters of the storage model could be evaluated with sufficiently long input-output data pairs. Not surprisingly, the parameters characterizing the processes near the release locus, such as the fractional release and the size of the immediately available pool and its coupling to the small store, as well as the state variables associated with the immediately available pool, such as its vesicular content and replenishment, could be determined with fewer stimuli. The possibility of estimating parameters with random inputs extends the applicability of the method to in vivo synapses with the physiological inputs. The parameter estimation was also possible under the time-variant, but slowly changing, conditions as well as for open systems that are part of larger vesicular storage systems but whose parameters can either not be reliably determined or are of no interest. The quality of parameter estimation was monitored continuously by comparing the observed and predicted output and/or estimated parameters with the true values. Finally, the method was tested experimentally using the rat phrenic-diaphragm neuromuscular junction.

Synaptic activity slows vesicular replenishment at excitatory synapses of rat hippocampus

“…The model used here not only provides the 'derived' parameters (fractional release and replenishment), but also the underlying 'basic' parameters (release coupling, replenishment coupling and RRP size) that are more directly related to the vesicular storage and release processes and thus can provide additional insight (Goda and Stevens 1998;Aristizabal and Glavinovic 2004;Kruckenberg and Sandweg 1968). To illustrate the point, an increase in the replenishment rate may be due to an increase in replenishment coupling (1/R 1 ), decrease in RRP size (C 1 ), or both.…”

“…Random stimulation was used for testing the accuracy of the estimated parameters. It provides more accurate parameter values, as it covers all, and not just two, stimulation frequencies (Aristizabal and Glavinovic 2004). Nonetheless, using either type of stimulation yielded similar parameters, and random stimulation does not allow for direct visual assessment of the changes to the vesicular dynamics from the EPSC amplitudes.…”

“…an action potential) causes the vesicles to release their content and produce a post-synaptic response (1 ms). We used Simulink to simulate the circuit model (Aristizabal and Glavinovic 2004). An important advantage of this method is that its modular design provides information about the system's topology that is not easily accessible from differential equations.…”

Augmentation Increases Vesicular Release Probability in the Presence of Masking Depression at the Frog Neuromuscular Junction

“…7D), suggesting an additional faster depression (Dobrunz et al, 1997;Varela et al, 1997), or that factors in addition to depletion may be contributing to depression (Zucker and Regehr, 2002). A third approach that will be important to quantify dynamic changes in the components is modeling of the release process Sen et al, 1996;Varela et al, 1997;Dittman et al, 2000;Matveev et al, 2002;Aristizabal and Glavinovic, 2003).…”

Numerical simulation for a neurotransmitter transport model in the axon terminal of a presynaptic neuron

“…It is assumed that this process is a simple diffusion-vesicles diffuse in the cytoplasm and dock in specific regions of the cell membrane. The process of release takes place on a time scale of 1 ms, whereas the depletion of the vesicle pool that takes place after the repeated simulation has a time scale of 1 s. The biological assumptions, both mentioned above and specified in the sequel, are based on the work of Aristizabal and Glavinovic (2004), Parsons et al (1995), Squire et al (2008), Steyer et al (1997, Vitale et al (1995), and Oheim et al (1999).…”