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When you provide multiple EM-LF simulations as sources to the Neuron solver, the neuron effectively receives the sum of the extracellular fields/potentials generated by the individual simulations (assuming the same modulation pulse is used). This is expected behavior because EM-LF simulations are linear, and therefore their solutions can be superimposed. To verify this behavior, you can use the Field Combiner tool in Sim4Life: First, combine the EM-LF results using the Field Combiner, which applies linear superposition of the fields. Then, use the combined field as a single source for the Neuron simulation. If you compare this setup to a Neuron simulation where the individual EM-LF results are used as separate sources (with the same modulation pulse), the neuron response will be identical. This confirms that, internally, the Neuron solver is operating on the sum of the fields from the different EM-LF simulations. If additional verification is desired, the EM-LF fields can also be interpolated along the neuron spline (for each simulation individually and for the Field Combiner result) to explicitly confirm that the combined field corresponds to the pointwise sum of the individual fields. Note: the field combiner expects the fields to be at the same frequency. If you would like more information about a specific application, or if you would like to share your project with us to receive more targeted feedback, please do not hesitate to contact us at s4l-support@zmt.swiss.

Thanks for the suggestion. I will contact the licensing team at s4l-license@zmt.swiss with the relevant details and will update this thread once I receive their guidance.

When you use the normalization option, Sim4Life: Computes the current flux through an automatically generated iso-potential surface Scales all output quantities so that the resulting current matches the value specified in the Normalize Frequency-Domain Results field The current value you enter represents the phasor amplitude, i.e. the baseline-to-peak current. For more information, please refer to the Sim4Life Manual Section 2.13.7.3.3 Normalization -- Normalization to Current.

Hi, there aren't any known issues with the Multiplier tool that would prevent you from scaling your field by any arbitrary value. Is it possible that in your script, you are using the same variable 'output1' for each case and as such are calculating the same value each time? If you are still having issues, could you share your project and script with the support team via s4l-support@zmt.swiss?

@halder Thanks do much, the call was really very useful.

This is nice. Thanks @Robin-Wydaeghe

Dear Geremia, Here is the procedure I use for S4L: Prerequisites: The Yale Neuron compiler 8.2.6 for Windows https://github.com/neuronsimulator/nrn/releases/tag/8.2.6 You can use newer versions, but this one works best with S4L. Create a directory for a particular neuron structure, at root level: hoc files, asc, etc. a subdirectory called 'mechanisms': all your mod files. From a console, run the Yale Compiler on your 'mechanisms' directory: > nrnivmodl if it succeeds, it will create a nrnmech.dll file. move the nrnmech.dll file to root level (where your hoc files are) and clean the 'mechanisms' directory - all the .c and .o files. Compress into a zip file the main directory (that contains the hoc files, nrnmech.dll and 'mechanisms' dir). Change the extension to .hocz Now, in S4L use the import button to import your new neuron model, your newly created hocz file. Regards, Guillermo

@halder I hope this message finds you well. I am currently conducting a temporal interference (TI) simulation using the LF Electro Ohmic Quasi-Static solver in Sim4Life, and I have encountered an issue regarding the electric field distribution at the electrode–skin interface. Here are the specific settings I used: There are four electrodes in total. For the first pair of stimulating electrodes, I assigned PEC material type to the other two electrodes (which are not used for stimulation). The stimulating electrodes were not assigned a material type; instead, I only applied Dirichlet boundary conditions to them. In the voxel settings, the four electrodes were set with priority = 1, and the Duke model with priority = 0. For the second pair of electrodes, I applied the same procedure accordingly. However, during post-processing, I noticed that the region where the electrodes overlap with the skin shows no electric field distribution, which seems physically unreasonable. Could you please advise if there might be an issue with my setup or if there are additional steps required to properly model the electrode–skin contact in TI simulations? Thank you very much for your time and support. I truly appreciate your help.

Thank you for your response. Additionally, I would appreciate it if you could tell me how to output the temperatures from the thermal simulation results to text files, spreadsheets, Excel, etc. Ideally, I would like to be able to extract the temperatures at specified coordinates or average values for each model (Lung, Spleen, etc.). If specifying the model is difficult, it would also be acceptable to obtain the post-simulation temperature at specified coordinates.

Hi Sylvain, thanks again for your detailed answer. I also talked with Arjama; I guess the best solution is to import both Huygens sources (Even if this means loosing the information about the input power) and to simulate the exposure field not with the BC coil, but with the two imported sources. Then, the other simulations (as in the youtube tutorial) can be linked to the field sensor used when simulating the two Huygens-imported sources.

Hi @Kihyun, To create an acoustic simulation, click on “Sources”, then change the excitation signal from “Sinusoidal” to “User Defined.” This will provide an “Expression” field that you can edit as needed. I also recommend checking the Acoustic Tutorial in Section 3.7 of the Sim4Life Manual, which you can access from the top ribbon under “Help.” [image: 1761036820889-sim4life_jvkul06rui.png] [image: 1761036826795-sim4life_q3dc6omg4u.png]

Hi @MB, The solution would be to export a separate Huygens source for each port individually (i.e., without using the Simulation Combiner). You can then set the amplitudes and phases of each Huygens source when you use them. This approach is quite powerful if you need to simulate multiple amplitude/phase configurations. However, we understand this might be a concern if you have a large number of ports involved. That said, we’re aware of this limitation and are working on adding this feature in an upcoming release.

@bryn Thank you very much for your reply. Both the visualization of the electric field in the nerve region and the extraction of the field data as a .mat file have been successfully resolved. I really appreciate your kind support and clear explanations.

Solved it - Model the electrode as PEC and use the voltage reader

Hi everyone, I'm using Sim4Life and currently working with the Optimizer tool. I would like to run the optimization algorithm on a network server using ARES instead of executing it on my local machine. However, I can't seem to find an option in the simulation settings that allows me to select the server as the execution target — the optimizer always defaults to running locally. Is it now possible to run parameter sweeps and optimization tasks on a remote machine in the network (without using a remote desktop session)? If so, how can I configure this in Sim4Life? Thanks in advance!

Btw, this topic is quite similar https://forum.zmt.swiss/topic/735/the-shape-of-the-t1-image-and-the-shape-of-the-electric-field-are-different

to get the current density in Python you could use a script like import s4l_v1.document as document try: # add a SimulationExtractor for the simulation call "LF" simulation = document.AllSimulations["LF"] simulation_extractor = simulation.Results() # create an EmSensorExtractor em_sensor_extractor = simulation_extractor["Overall Field"] em_sensor_extractor.FrequencySettings.ExtractedFrequency = u"All" document.AllAlgorithms.Add(em_sensor_extractor) # update the pipeline, make sure current density is extracted em_sensor_extractor.Outputs["J(x,y,z,f0)"].Update() # get data current_density_field = em_sensor_extractor.Outputs["J(x,y,z,f0)"].Data except Exception as exc: import traceback traceback.print_exc()

Dear, @AntoninoMC Thank you very much for your detailed clarification. I now understand the fundamental difference between the Ohmic solver and the QS solver, and I have also tried some test runs with the QS solver, which helped me to grasp the impact of frequency dependence more clearly. In my current application, I am applying a voltage to the human body and measuring the potential difference between two points on the head. I am particularly interested in how the measured potential difference changes with the frequency of the applied current. The frequency range I am considering is typically from about 10 kHz up to 100 kHz, but I am also exploring much lower frequencies, down to around 100 Hz. If you could kindly point me to relevant references or scientific literature that discuss similar applications or provide guidance on which dielectric properties are most suitable in this frequency range, it would be extremely helpful. Thank you again for your support.