Modeling Fast-scan Cyclic Voltammetry Data from Electrically Stimulated Dopamine Neurotransmission Data Using QNsim1.0

The overall goal of this software program is to estimate the kinetics of electrically stimulated dopamine neurotransmission from the experimental fast-scan cyclic voltammetry data. This method can facilitate study designs to help answer key questions about dopamine neurotransmission, such as how electrically evoked striatal dopamine neurotransmission is altered by the drugs and disease states. The main advantage of this software is that it provides a user-friendly platform to model experimental voltammetry data using a quantitative neurobiological framework.

In this procedure, download QNsim1.0. zip and extract it to a desired directory. Next, prepare the stimulated dopamine response data for modeling by organizing a spreadsheet in which each column contains a temporal dopamine response converted to micromolar dopamine concentration, and save this file to the same directory as the program files.

After that, open the programming software, navigate to the QNsim1.0 directory in the current folder window and open the file entitled Initialization.m. Then click Run to launch the Initialization screen. To begin a new project, under the New Project section type the name of the spreadsheet file that contains the dopamine response data for the project in the dopamine data file text box.

This spreadsheet contains three responses from two studies, one collected in the dorsal striatum, and one collected in the nucleus accumbens. Next to Simulation Time input the time points corresponding to the start and end of data collection relative to the start of the stimulation. For the sample data, there are responses with a 5-second prestimulation interval and 35 seconds of data collection after the start of the stimulation.

Following that, input the number of responses in each study next to the corresponding text box. Next to Sampling Interval, input the experimental data sampling interval in seconds, which was every 0.1 seconds for our data. Then, next to Save As, designate the file name, including the file type where the project is to be saved.

Click Create New Project to launch the simulator window. Alternatively, to continue a previous project, in the Continue Previous Project section of the initialization window, enter the dot mat file name of a previously begun project. Afterward, click Load Existing Project to launch the simulator window.

In this procedure, select the experimental dopamine response to simulate by inputting the study number, response number, and duration of the stimulation in the corresponding text boxes. Press the Enter key or click Simulate to begin the simulation process, which creates three graphs containing experimental data, simulated data, and simulated data that does not account for post stimulation dopamine release. To model the experimental dopamine responses, adjust the delta DAR, delta DAR tau, and dar steady state parameters associated with dopamine release to match the amplitude of the stimulation.

Then adjust the VMAX, KM initial, delta KM, KM inflection. Then adjust the VMAX, KM initial, delta KM, KM inflection, and K parameters associated to dopamine reuptake such that in Panel A the simulated data approximates the shape of the rising phase of the experimental data and the simulation without post stim release trace is less than the experimental data trace for all post stimulation time points. This modeling approach is an iterative process of adjusting model parameters.

Thus, it will likely be necessary to modify DA release parameters to match the shape of the rising phase. Then adjust XR, tau R, and M parameters associated with post stimulation dopamine release such that the simulated data approximates the experimental data in the Dopamine versus Time graph. In order to validate the accuracy of simulation parameters it is critical to ascertain that the same set of stimulated release and reuptake parameters can approximate experimental responses to different durations of stimulation from the same sampling site.

Once a set of parameters closely models the experimental data, click Save Parameters, which will save that set of parameters for the given response to the dot mat file for the project. If required, load previously saved parameters for a particular response by clicking Load Parameters. Ensure that the appropriate study number and response number are entered in the corresponding text boxes.

To export the saved parameters, in the text box next to the Export Parameters button type in the file name and click Export Parameters to export a text file with all the parameters of the simulations. Delimit the cells in Excel by spaces to view this data in a table format. The left and right graph shown here depict the simulations in experimental data collected in the dorsal striatum and nucleus accumbens respectively.

The two regions generally exhibit different response shapes with concave rising shapes in the dorsal striatum and convex rising shapes in the nucleus accumbens. Although there is variability in response shapes and amplitudes, even within a given region, both response shapes could be modeled with a few notable differences and parameterizations. Generally, VMAX is lower, and KM inflection is much lower in the nucleus accumbens, compared to the dorsal striatum.

While attempting this procedure, it's important to remember to be systematic in your approach by minimizing estimates of dopamine release and reuptake parameters and validating parameters on multiple experimental responses from the same sampling site. After watching this video, you should have a good understanding of how to model the stimulated dopamine responses in order to estimate the kinetics of electrically stimulated dopamine neurotransmission in the striatum.