Introduction Transcranial Magnetic Stimulation (TMS) is a non-invasive method for neuromodulation, with a range of clinical and research applications including the treatment of depression and functional brain mapping. TMS works… Click to show full abstract
Introduction Transcranial Magnetic Stimulation (TMS) is a non-invasive method for neuromodulation, with a range of clinical and research applications including the treatment of depression and functional brain mapping. TMS works by generating a time-varying magnetic field which induces an electric field (E-field) in the brain. Despite its widespread use, understanding of the neural effects of TMS is limited, making it difficult to address issues like high subject-to-subject variability and optimization of stimulation protocols. Computational modeling offers the opportunity to unravel the mechanisms of TMS in ways that are infeasible experimentally. Objectives We used cortical neuron models to investigate which neural elements are activated by TMS and how the threshold for action potential (AP) initiation varies with field orientation. Materials & methods We adapted models from the experimentally validated library of rat cortical neurons developed by the Blue Brain Project. These are multi-compartment, conductance-based cable models with realistic 3D morphologies implemented in the NEURON modeling software. The models were coupled to extracellular potentials calculated in MATLAB. Since the neural processes in the cortex are short relative to the E-field spatial gradient, the E-field was approximated as uniform. Threshold “maps” for activation were determined using a binary search algorithm at field orientations sweeping the polar and azimuthal directions. Results The site of action potential (AP) initiation and maximum depolarization was nearly always an axonal termination parallel to the field, with the exception of some orientations maximally depolarizing bifurcations near pre-synaptic terminals. Due to the high degree of branching and spatial extent of the realistic axons included in these models, the threshold maps indicated relative insensitivity to orientation and exhibited numerous local minima of thresholds, dependent on the specific axon morphology. Conclusion Within the assumptions of these models, axon terminals are typically the lowest threshold elements of cortical neurons for E-fields with low spatial gradients, and morphological differences between cell-types directly affect threshold values.
               
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