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Enabling electric field model of microscopically realistic brain

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Weise,  Konstantin       
Methods and Development Group Brain Networks, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Faculty of Electrical Engineering and Information Technology, University of Applied Sciences, Leipzig, Germany;

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Knösche,  Thomas R.       
Methods and Development Group Brain Networks, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Qi, Z., Noetscher, G. M., Miles, A., Weise, K., Knösche, T. R., Cadman, C. R., et al. (2025). Enabling electric field model of microscopically realistic brain. Brain Stimulation, 18(1), 77-93. doi:10.1016/j.brs.2024.12.1192.


Cite as: https://hdl.handle.net/21.11116/0000-000F-2C7B-7
Abstract
Background: Modeling brain stimulation at the microscopic scale may reveal new paradigms for various stimulation modalities.

Objective: We present the largest map to date of extracellular electric field distributions within a layer L2/L3 mouse primary visual cortex brain sample. This was enabled by the automated analysis of serial section electron microscopy images with improved handling of image defects, covering a volume of 250 × 140 × 90 μm³.

Methods: The map was obtained by applying a uniform brain stimulation electric field at three different polarizations and accurately computing microscopic field perturbations using the boundary element fast multipole method. We used the map to identify the effect of microscopic field perturbations on the activation thresholds of individual neurons. Previous relevant studies modeled a macroscopically homogeneous cortical volume.

Result: Our result shows that the microscopic field perturbations - an 'electric field spatial noise' with a mean value of zero - only modestly influence the macroscopically predicted stimulation field strengths necessary for neuronal activation. The thresholds do not change by more than 10 % on average.

Conclusion: Under the stated limitations and assumptions of our method, this result essentially justifies the conventional theory of "invisible" neurons embedded in a macroscopic brain model for transcranial magnetic and transcranial electrical stimulation. However, our result is solely sample-specific and is only relevant to this relatively small sample with 396 neurons. It largely neglects the effect of the microcapillary network. Furthermore, we only considered the uniform impressed field and a single-pulse stimulation time course.