.. _publications:

Publications
=============
The main publications documenting SimNIBS development are


Version 4.0
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:ref:`charm_docs` segmentation pipeline
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* `Puonti O, Van Leemput K, Saturnino GB, Siebner HR, Madsen KH, Thielscher A. (2020). Accurate and robust whole-head segmentation from magnetic resonance images for individualized head modeling. Neuroimage, 219:117044. <https://doi.org/10.1016/j.neuroimage.2020.117044>`_

.. _coilmodels:

TMS coil models
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* `Drakaki M, Mathiesen C, Siebner HR, Madsen KH, Thielscher A. (2022). Database of 25 validated coil models for electric field simulations for TMS. Brain Stimulation. <https://doi.org/10.1016/j.brs.2022.04.017>`_


Version 3.2
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TMS Optimiztion (ADM method)
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* `Gomez, L. J., Dannhauer, M., & Peterchev, A. V. (2020). Fast computational optimization of TMS coil placement for individualized electric field targeting. NeuroImage 2021; 228: 117696. <https://doi.org/10.1016/j.neuroimage.2020.117696>`_


Magnetic Field Calculations
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* `Yazdanian, H., Saturnino, G. B., Thielscher, A., & Knudsen, K. (2020). Fast evaluation of the Biot-Savart integral using FFT for electrical conductivity imaging. Journal of Computational Physics, 109408. <https://doi.org/10.1016/j.jcp.2020.109408>`_
 

Electric Field Strength Optimization
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* `Saturnino, G. B., Madsen, K. H., & Thielscher, A. (2020). Optimizing the Electric Field Strength in Multiple Targets for Multichannel Transcranial Electric Stimulation. bioRxiv. <https://doi.org/10.1101/2020.05.27.118422>`_


Version 3.1
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TDCS Optimization
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* `Saturnino, G. B., Siebner, H. R., Thielscher, A., & Madsen, K. H. (2019). Accessibility of cortical regions to focal TES: Dependence on spatial position, safety, and practical constraints. NeuroImage, 203, 116183. <https://doi.org/10.1016/j.neuroimage.2019.116183>`_


TMS Optimization
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* `Weise, K., Numssen, O., Thielscher, A., Hartwigsen, G., & Knösche, T. R. (2020). A novel approach to localize cortical TMS effects. Neuroimage, 209, 116486. <https://doi.org/10.1016/j.neuroimage.2019.116486>`_



Version 3.0
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Assessement of accuracy and speed of new solver
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* `Saturnino, Guilherme B., Kristoffer H. Madsen, and Axel Thielscher. (2019). "Electric field
  simulations for transcranial brain stimulation using FEM: an efficient implementation and error analysis." Journal of neural engineering 16.6 066032. <https://doi.org/10.1088/1741-2552/ab41ba>`_


Uncertainty Quantification
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* `Saturnino, G. B., Thielscher, A., Madsen, K. H., Knösche, T. R., & Weise, K. (2019). A principled approach to conductivity uncertainty analysis in electric field calculations. NeuroImage, 188, 821-834. <https://doi.org/10.1016/j.neuroimage.2018.12.053>`_

* `Weise, K., Poßner, L., Müller, E., Gast, R., & Knösche, T. R. (2020). Pygpc: A sensitivity and uncertainty analysis toolbox for Python. SoftwareX, 11, 100450 <https://doi.org/10.1016/j.softx.2020.100450>`_


Version 2.1
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Validation 
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* `Puonti, O., Saturnino, G. B., Madsen, K. H., & Thielscher, A. (2020). Value and limitations of intracranial recordings for validating electric field modeling for transcranial brain stimulation. Neuroimage, 208, 116431. <https://doi.org/10.1016/j.neuroimage.2019.116431>`_

Tutorial paper
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* `Saturnino, G. B., Puonti, O., Nielsen, J. D., Antonenko, D., Madsen, K. H., & Thielscher, A. (2019). Simnibs 2.1: A comprehensive pipeline for individualized electric field modelling for transcranial brain stimulation. In Brain and Human Body Modeling (pp. 3-25). Springer, Cham. <https://link.springer.com/chapter/10.1007/978-3-030-21293-3_1>`_

:ref:`headreco_docs` pipeline and assessement of skull segmentation accuracy
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* `Nielsen, J. D., Madsen, K. H., Puonti, O., Siebner, H. R., Bauer, C., Madsen, C. G., ..., and Thielscher, A. (2018). Automatic skull segmentation from MR images for realistic volume conductor models of the head: Assessment of the state-of-the-art. NeuroImage, 174, 587-598. <https://doi.org/10.1016/j.neuroimage.2018.03.001>`_

Version 2.0
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Overview
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* `Thielscher, A., Antunes, A. and Saturnino, G.B. (2015), Field modeling for transcranial magnetic stimulation: a useful tool to understand the physiological effects of TMS? IEEE EMBS 2015, Milano, Italy <http://dx.doi.org/10.1109/EMBC.2015.7318340>`_

:ref:`mri2mesh_docs` pipeline and Version 1.0
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* `Windhoff, M., Opitz, A., and Thielscher, A. (2013). Electric field calculations in brain stimulation based on finite elements: an optimized processing pipeline for the generation and usage of accurate individual head models. Human brain mapping, 34(4), 923-935. <https://doi.org/10.1002/hbm.21479>`_