Sina Shirinpour1, Nicholas Hananeia2, James Rosado3, Harry Tran4, Christos Galanis5, Andreas Vlachos6, Peter Jedlicka2, Gillian Queisser3, Alexander Opitz7. 1. Department of Biomedical Engineering, University of Minnesota, Minneapolis, USA. Electronic address: shiri008@umn.edu. 2. Faculty of Medicine, ICAR3R - Interdisciplinary Centre for 3Rs in Animal Research, Justus-Liebig-University, Giessen, Germany. 3. Department of Mathematics, Temple University, Philadelphia, USA. 4. Department of Biomedical Engineering, University of Minnesota, Minneapolis, USA. 5. Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany. 6. Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany; Center Brain Links Brain Tools, University of Freiburg, Freiburg, Germany; Center for Basics in Neuromodulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany. 7. Department of Biomedical Engineering, University of Minnesota, Minneapolis, USA. Electronic address: aopitz@umn.edu.
Abstract
BACKGROUND: Transcranial Magnetic Stimulation (TMS) is a widely used non-invasive brain stimulation method. However, its mechanism of action and the neural response to TMS are still poorly understood. Multi-scale modeling can complement experimental research to study the subcellular neural effects of TMS. At the macroscopic level, sophisticated numerical models exist to estimate the induced electric fields. However, multi-scale computational modeling approaches to predict TMS cellular and subcellular responses, crucial to understanding TMS plasticity inducing protocols, are not available so far. OBJECTIVE: We develop an open-source multi-scale toolbox Neuron Modeling for TMS (NeMo-TMS) to address this problem. METHODS: NeMo-TMS generates accurate neuron models from morphological reconstructions, couples them to the external electric fields induced by TMS, and simulates the cellular and subcellular responses of single-pulse and repetitive TMS. RESULTS: We provide examples showing some of the capabilities of the toolbox. CONCLUSION: NeMo-TMS toolbox allows researchers a previously not available level of detail and precision in realistically modeling the physical and physiological effects of TMS.
BACKGROUND: Transcranial Magnetic Stimulation (TMS) is a widely used non-invasive brain stimulation method. However, its mechanism of action and the neural response to TMS are still poorly understood. Multi-scale modeling can complement experimental research to study the subcellular neural effects of TMS. At the macroscopic level, sophisticated numerical models exist to estimate the induced electric fields. However, multi-scale computational modeling approaches to predict TMS cellular and subcellular responses, crucial to understanding TMS plasticity inducing protocols, are not available so far. OBJECTIVE: We develop an open-source multi-scale toolbox Neuron Modeling for TMS (NeMo-TMS) to address this problem. METHODS: NeMo-TMS generates accurate neuron models from morphological reconstructions, couples them to the external electric fields induced by TMS, and simulates the cellular and subcellular responses of single-pulse and repetitive TMS. RESULTS: We provide examples showing some of the capabilities of the toolbox. CONCLUSION: NeMo-TMS toolbox allows researchers a previously not available level of detail and precision in realistically modeling the physical and physiological effects of TMS.
Authors: Jerel K Mueller; Erinn M Grigsby; Vincent Prevosto; Frank W Petraglia; Hrishikesh Rao; Zhi-De Deng; Angel V Peterchev; Marc A Sommer; Tobias Egner; Michael L Platt; Warren M Grill Journal: Nat Neurosci Date: 2014-06-29 Impact factor: 24.884
Authors: Zsolt Turi; Nicholas Hananeia; Sina Shirinpour; Alexander Opitz; Peter Jedlicka; Andreas Vlachos Journal: Front Neurosci Date: 2022-07-08 Impact factor: 5.152
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