Action Potential Analysis

Note: This package does not yet contain functions to analyze and plot action potential data. However, I am including this vignette here to show you how to perform raw data analysis in Clampfit. The resulting data will be ready to use in future versions of patchclampplotteR.

This vignette will demonstrate how to analyze action potential properties using a raw .abf file. You will identify the first current injection that resulted in action potentials and then select the first action potential within this sweep for further analyses.

The box outlines the first action potential on the first sweep with action potentials.

You will identify the threshold using the first derivative method. This means that the threshold corresponds to the membrane potential where the action potential velocity is 10 mV/ms or greater (Farries et al., 2010).

Set up data sheet

Before you begin, you should set up a .csv file. I would suggest using a consistent naming scheme that includes the date. I use the YYYYMMDD-title.csv format, such as 20250113-AP-analysis.csv. This makes it easy to identify when I last analyzed my data, and the files sort easily.

In your .csv file, fill row 1 with the following column titles. Notice that all (except for ID are in lowercase.

• letter The unique letter identifier of a single cell. You can use this to link data from different recordings taken from the same cell.
• state A character value. In this example, the values are Baseline and Insulin, indicating a current clamp protocol taken after the cell had been exposed to 500 nM insulin for 25 minutes.
• time_of_threshold A numerical value (in ms) used to determine properties like the latency to fire.
• t_x The membrane potential at the moment that an action potential is initiated, also known as the threshold.
• t11 The derivative of the trace you are analyzing. Must be 10 mV/ms or greater to properly identify the threshold.
• ID A character value indicating the recording number. This corresponds to the File Name column that is automatically generated in the Results sheet in Clampfit.
• first_sweep_with_APs A number representing the earliest sweep number where action potentials first appeared.
• trace_start This is an automatic value calculated by Clampfit, and it corresponds to the sweep number. It is not used in any analyses, but it will automatically be included in the Results sheet in Clampfit. It’s faster to just copy all the data rather than try to exclude this value.
• peak_amplitude The membrane potential (in mV) during maximum depolarization.
• time_to_peak The time of the peak amplitude (in ms), which should also be relative to the time_of_threshold if you have repositioned Cursor 1 to the time_of_threshold.
• antipeak_amplitude The afterhyperpolarization amplitude (in mV)
• time_of_antipeak The time of the after-hyperpolarization (in ms), which should be relative to the time_of_threshold.
• half-width The width of the action potential when the membrane potential is half of the peak_amplitude.

Get derivative

1. Open the .abf file containing the current clamp step protocol in Clampfit. Ensure that the x-axis shows time in milliseconds. If it shows seconds, double-click the x-axis, and change the Elapsed Time from Automatic to Milliseconds.

Warning! The y-axis values should generally be around -70 mV during the flat regions outside of the current injection. Sometimes the scaling factor in Clampfit is distorted (for unknown reasons) and the y-axis may be in the thousands range. If this happens, follow step 1b).

1b. If the y-axis scale is off (see the warning box above), double-click on the y-axis to open the Modify Signal Parameters box. Change the V/pA ratio to 0.01, and click “OK”. This will re-scale the y-axis to the correct units relative to the current injections. Double-check that the x-axis is in milliseconds!

Sometimes the V/pA ratio is altered, so you may need to change it to 0.01.

2. Press the “Enter” key to show just one sweep at a time. It will begin at the sweep corresponding to the lowest current injection. Use greater than symbol (>) to cycle up through the sweeps.

3. Move up to sweeps corresponding to higher current injections until you identify the first sweep that contains an action potential. I will call this t_x, since it may be t5 in one recording, or t6 in another, etc.

4. Position Cursors 1 and 2 around the first action potential in t_x. Cursor 1 should be before the threshold (aim for the area before the slope of the curve increases steeply). Cursor 2 should be in the after-hyperpolarization region.

The ideal placement of Cursor 1 should be in the middle of the curve. Left: Cursor 1 is placed where the curve is very steep, and it is likely that you will miss the threshold. Middle: Cursor 1 is very low, so Clampfit may identify this as the after-hyperpolarization. Right: This is the ideal spot, where the cursor is early enough to capture the threshold in the search region.

Warning! It is important that Cursor 2 touches the curve at a value that is lower than the voltage value for Cursor 1. If Cursor 1 is lower, then Clampfit may identify the location at Cursor 1 as the after-hyperpolarization region if you forget to move the cursor to the threshold (see step 11).

5. Click on the arithmetic button (it is the button with basic math symbols), then Add Traces. Write “1” and click OK. This will add a new empty trace, called t11.

6. t11 should be the derivative of t_x. In the Expression box, write t11=diff(t6) (replace t6 with your value for t_x).

Find threshold

7. Click on Edit -> Transfer Traces and set the Region to transfer as Cursors 1..2. In the Trace Selection category, choose only Vm_primary () as the signal. Select t_x and t11 for the traces, then click OK.

8. Click on the Results sheet (Window -> Results1). The Results page will display three columns: Time (ms), Trace #6 (or #5, #7, etc.), and Trace #11. Trace #x is the membrane potential in mV, and Trace #11 is the derivative of Trace #x.

Warning! The Results page of the transferred traces does not delete data between files. If you are doing several analyses in one session, ensure that you are looking at the correct columns corresponding to the active recording.

9. Scroll down the Trace #11 column (the derivative column) until you see a series of positive values with increasing magnitude (e.g. > 100 or more). This is where the derivative is increasing. Select the first value within this series that is greater than or equal to 10 mV/ms. Copy the value of all three columns in this row.

Note There may be isolated peaks within the derivative that are greater than 10 mV/ms. Only select this value if it is part of a series of increasingly larger positive values, followed by a series of negative values.

10. If the scaling is correct, the threshold (t_x) should be around -30 mV for a healthy cell. Your .csv file should now look like this:

Measure action potential properties

11. Double-click on Cursor 1 and change its x-position value (time) to match the time_of_threshold.

Note how Cursor 1 is shifted to the right relative to the earlier cursor image. It is now located at the x-value where the membrane potential crosses the threshold.

Warning! If you do not reposition Cursor 1 to be at the time of threshold, the values for time_of_peak and time_of_antipeak will be incorrect!

12. Click on the Statistics button (a small icon with a summation symbol on top of it) or press Alt+s.

13. Set the following settings:

• Trace Selection: Choose Vm_primary () and t_x (in this case, t6) ONLY. Do NOT include t11.
• Peak Polarity: Vm_primary, Positive-going
• Baseline Region: Fixed at [paste in the threshold value (column t_x in your sheet) here]
• Search Region 1: Range: Cursors 1..2
• Destination Option: Replace results in sheet (prevents you from accidentally copying old data
• Column Order: Measurement, Region, Signal
• Measurements: peak_amplitude, time of peak, antipeak amplitude, time of antipeak, half-width

Click OK and then Window -> Results1 to see the Results page.

14. Select all data except for the File Path column (unless you think you will need it later) and paste it into the .csv file. You’ll notice that the .csv column names are different than the column names in the Results sheet. I changed these column names to make them easier to use in R code.

15. Your .csv file should now look like this.

16. While you still have this file open, you may want to count action potentials (see the section on counting action potentials below).

17. A completed dataset should look something like the spreadsheet below.

Note If there are no action potentials in the later recording, insert the values for the columns letter and state and leave all the others blank.

Count action potentials

The next step is to count the number of action potentials in each sweep. This will allow you to later make a plot of action potential frequency vs. current injection and see how a treatment affect action potential frequency.

18. Create a separate .csv file (for example 20250113-AP-count-data.csv). This file should have four columns:

• letter The unique letter identifier of a single cell.
• state A character value (“Baseline” or “Insulin” in this example)
• sweep A number from 1 to 10 (see step 18a to generate this)
• no_of_APs a numerical value indicating the number of action potentials

18a. To generate a repeated sequence from 1-10 quickly, type the number 1 in cell C2. Then, type the number 2 in cell C3.

18b. Select C2 and C3 together, then hover your mouse over the bottom right corner of the group until you see a small black plus symbol.

18c. Click and hold down the mouse key and drag the selection down to C11 to generate a sequence from 1 to 10.

18d. The entire range from C2 to C11 should be selected. Move your mouse to the bottom right corner of the cell until you see the + symbol again. Hold down the Ctrl key and drag this selection down. This will generate the sequence from 1-10 repeatedly (e.g. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 1, 2, 3…)

18e. You can then copy and paste this range repeatedly to fill your column.

19. Open a current clamp steps recording in Clampfit (you may be coming directly from step 16 when you measured action potential properties).

20. Press the Enter key to view one sweep at a time, and use < and > to cycle through the sweeps. Count the number of action potentials in each sweep, and record them in the no_of_APs column.

Yes, this step may seem super simple, but that’s because it is - look at each sweep and count the number of action potentials present!

21. Here is an example of what one recording could look like:

FAQ

What do I do if there are no action potentials following treatment?

Do not discard this cell; this is important and meaningful data! Fill in only the letter and state, and leave all other columns blank. R will fill this with NA values, since there are no action potential properties to measure. However, for your AP count data, please just indicate 0 for all current injections.

What do I do if there are action potentials outside of the time when a current injection was applied?

This can happen with very excitable cells. Only count the action potentials that occurred within the injection period.

Should I count an action potential that looks very wavy?

Only include the action potential if it clearly crosses the threshold, comes to a sharp peak, and has an after-hyperpolarization period.

References

Farries, M. A., Kita, H., & Wilson, C. J. (2010). Dynamic Spike Threshold and Zero Membrane Slope Conductance Shape the Response of Subthalamic Neurons to Cortical Input. Journal of Neuroscience, 30(39), 13180–13191. https://doi.org/10.1523/JNEUROSCI.1909-10.2010