Effects of Electric Field Direction on TMS-based Motor Cortex Mapping
Jing, Y.; Numssen, O.; Hartwigsen, G.; Knoesche, T.; Weise, K.
Show abstract
BackgroundTranscranial magnetic stimulation (TMS) modulates brain activity by inducing electric fields (E-fields) that can elicit action potentials in cortical neurons. Neuronal responses to TMS depend not only on the magnitude of the induced E-field but also on various physiological factors. In this study, we incorporated a novel average response model that efficiently estimates the firing threshold of neurons based on their orientation relative to the applied E-field, thereby advancing TMS mapping for motor function. MethodsWe conducted a regression-based TMS mapping experiment with fourteen subjects to localize cortical origins of motor evoked potential (MEP) on the first dorsal interosseous (FDI) muscle. Firing thresholds were estimated for excitatory neurons in cortical layers 2/3 and 5 via an average response model. Regression was performed between MEPs and three E-field quantities: the magnitude (magnitude model), the normal component (cosine model), and the effective E-field, which scales the E-field magnitude based on the firing thresholds specific to the neuronal orientation (neuron model). To validate, we applied TMS to ten subjects with optimized coil placements based on these three models to determine which model could yield the highest MEPs. ResultsThe magnitude and neuron models performed similarly, while the cosine model showed lower explained variance in regression results, required more TMS trials for stable mapping, and yielded the lowest MEP in the validation. ConclusionThis study is the first to advance TMS modeling by incorporating neuron-specific factors at the individual level. Results show that on the motor cortex, the magnitude model is-as expected-a good approximation of cortical TMS effects as it shows similar results as the neuron model. In contrast, the classic cosine model exhibited lower performance and required more TMS trials for stable results, and is not recommended for future studies.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Personalized whole-brain activity patterns predict human corticospinal tract activation in real-time 96%
- The phase of sensorimotor mu and beta oscillations has the opposite effect on corticospinal excitability 96%
- TMS with fast and accurate electronic control: measuring the orientation sensitivity of corticomotor pathways 96%
Similar papers in this journal
- Kilohertz Transcranial Magnetic Perturbation (kTMP): A New Non-invasive Method to Modulate Cortical Excitability 96%
- Spatially bivariate EEG-neurofeedback can manipulate interhemispheric rebalancing of M1 excitability 95%
- Transcranial focused ultrasound to rIFG improves response inhibition through modulation of the P300 onset latency 94%
Similar papers in this journal
- Transcranial Random Noise Stimulation acutely lowers the response threshold of human motor circuits 96%
- Dissociation of direct and peripheral transcranial magnetic stimulation effects in nonhuman primates 96%
- Electrical stimulation of temporal and limbic circuitry produces distinct responses in human ventral temporal cortex 95%
Similar papers in this journal
- Responses of Model Cortical Neurons to Temporal Interference Stimulation and Related Transcranial Alternating Current Stimulation Modalities 95%
- Optimal placement of high-channel visual prostheses in human retinotopic visual cortex 95%
- TAP: Targeting and analysis pipeline for optimization and verification of coil placement in transcranial magnetic stimulation 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.