@KK The titration procedure provides a scaling factor that must be applied to the stimulation source (incident E-field, input current, or voltage applied at electrode pairs) in order to initiate an action potential in a fiber or neuron. Here are some examples depending on the stimulation source: Source: Incident E-field (e.g., induced by TMS) Assume the incident electric field is 1 V/m, and the titration procedure yields a titration factor, tf. The threshold E-field is therefore tf [V/m]. If this 1 V/m field results from a coil current rate of change dI/dt = A [A/s], then the threshold dI/dt required is A × tf [A/s]. Source: Applied voltage Let the applied voltage across an electrode pair be V = V₀. This value is also used as the Dirichlet boundary condition in low-frequency (LF) simulations. If the titration factor is tf, the threshold voltage becomes V₀ × tf [V]. Source: Applied current Let the applied current to an electrode pair be I = I₀, typically derived from LF simulations via a current flux integrator. With a titration factor tf, the threshold current is I₀ × tf [A]. The titration factor tf is a dimensionless number that gains physical meaning when applied to the relevant stimulation quantity (electric field, voltage, or current). @LJ was suggesting the correct course of action. I hope this clarification is helpful!

Hi @Habib -thank you! that makes sense. I think I missed that bit of the documentation. I thought section 2.12.1.5.1 is all the documentation available but now I found what you're talking about. I will give this a go- thanks again.

Removing neuron from the path file solved the issue but I don't know if there is a better solution.

@kj Here there is the equivalent Python code. Sometimes it is easier to have all code produced within Sim4Life. import numpy as np ## Waveform Parameters t=np.linspace(0,1,60000); # Creates Time Vector f=1000 # Frequency Carrier [Hz] df=10; # Frequency Modulation [Hz] ## Create the Waveform v=0.5*np.sin(2*np.pi*f*t)+0.5*np.sin(2*np.pi*(f+df)*t); # Creates The Data Structure data=np.array([t*1000, v]) ## Write as txt file to be imported in Sim4Life np.savetxt(filename, data, delimiter=' ',fmt='%1.4f')

That is exactly same as I suffered before. Check the "neurons4l" folder is installed in Sim4Life folder. For example, "C:\Program Files\Sim4Life_6.0.0.3176\neurons4l"

@JKM, I know the issue, however we prefer not to change the visualization method, as the data in the line sensors can be extracted to calculate other quantities of interest. The issue that you experience is for the myelinated fibers using any MRG parameterization (Motor, Small and Motor and Sensor MRG fibers). For Sweeney, Rat, Senn and the unmyelinated Sundt fiber model, the issue does not exist. All the best!

Dear @JKM , Sorry for the late answer. Yes, there are several ways. The first is to create a Point Sensor: after dragging and dropping the axonal entity, a list containing the name of all the sections will appear. E.g. for a myelinated SENN model, the list will show names such as node1[0],internode1[0],node1[1],internode1[1]... A second way, via Python is to run the following code that provide a list containing all the section names: import s4l_v1 as s4l sim=s4l.document.AllSimulations[simulationname] sections=sim.GetSectionNames()