The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Physiological observations validate finite element models for estimating subject-specific electric field distributions induced by transcranial magnetic stimulation of the human motor cortex
Open accessAbstract
Recent evidence indicates subject-specific gyral folding patterns and white matter anisotropy uniquely shape electric fields generated by TMS. Current methods for predicting the brain regions influenced by TMS involve projecting the TMS coil position or center of gravity onto realistic head models derived from structural and functional imaging data. Similarly, spherical models have been used to estimate electric field distributions generated by TMS pulses delivered from a particular coil location and position. In the present paper we inspect differences between electric field computations estimated using the finite element method (FEM) and projection-based approaches described above. We then more specifically examined an approach for estimating cortical excitation volumes based on individualistic FEM simulations of electric fields. We evaluated this approach by performing neurophysiological recordings during MR-navigated motormapping experiments. We recorded motor evoked potentials (MEPs) in response to single pulse TMS using two different coil orientations (45° and 90° to midline) at 25 different locations (5×5 grid, 1cm spacing) centered on the hotspot of the right first dorsal interosseous (FDI) muscle in left motor cortex. We observed that motor excitability maps varied within and between subjects as a function of TMS coil position and orientation. For each coil position and orientation tested, simulations of the TMS-induced electric field were computed using individualistic FEM models and compared to MEP amplitudes obtained during our motormapping experiments. We found FEM simulations of electric field strength, which take into account subject-specific gyral geometry and tissue conductivity anisotropy, significantly correlated with physiologically observed MEP amplitudes (rmax=0.91, p=1.8×10(-5) rmean=0.81, p=0.01). These observations validate the implementation of individualistic FEM models to account for variations in gyral folding patterns and tissue conductivity anisotropy, which should help improve the targeting accuracy of TMS in the mapping or modulation of human brain circuits.
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Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002) · NeuroImage · doi:10.1006/nimg.2002.1132 · Cited by 11,888
Depression of motor cortex excitability by low-frequency transcranial magnetic stimulation
Chen, R., Classen, J., Gerloff, C., Celnik, P., Wassermann, E. M., Hallett, M., & Cohen, L. G. (1997) · Neurology · doi:10.1212/wnl.48.5.1398 · Cited by 2,128 · cited 1×
“Since TMS-evokedMEP amplitudes have been described to be affected to varying degrees when using an inter-trials b 10 s (Chen et al., 1997; Julkunen et al., 2012; Pascual-Leone et al., 1994), we cannot exclude the possibility that short-term plasticity may have influenced some of our observations.”
ResultPorro, C. A., Francescato, M. P., Cettolo, V., Diamond, M. E., Baraldi, P., Zuiani, C., Bazzocchi, M., & di Prampero, P. E. (1996) · The Journal of Neuroscience · doi:10.1523/jneurosci.16-23-07688.1996 · Cited by 924
A new method for improving functional-to-structural MRI alignment using local Pearson correlation
Saad, Z. S., Glen, D. R., Chen, G., Beauchamp, M. S., Desai, R., & Cox, R. W. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.037 · Cited by 405
Transcranial magnetic brain stimulation: Therapeutic promises and scientific gaps
Wassermann, E. M., & Zimmermann, T. (2012) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2011.09.003 · Cited by 243
Cited by
Rossini, P. M., Burke, D., Chen, R., Cohen, L. G., Daskalakis, Z., Di Iorio, R., Di Lazzaro, V., Ferreri, F., Fitzgerald, P. B., George, M. S., et al. (2015) · Clinical Neurophysiology · doi:10.1016/j.clinph.2015.02.001 · Cited by 2,753
Self-citationMoseley, P., Fernyhough, C., & Ellison, A. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.10.001 · Cited by 113
Metadata
- Authors
- Opitz, A., Legon, W., Rowlands, A., Bickel, W. K., Paulus, W., & Tyler, W. J.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-11
- Volume
- 81
- Pages
- 253-264
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2068638051
- Cited by
- 198
- References
- 6
- FWCI
- 8.52
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Opitz, A., Legon, W., Rowlands, A., Bickel, W. K., Paulus, W., & Tyler, W. J. (2013). Physiological observations validate finite element models for estimating subject-specific electric field distributions induced by transcranial magnetic stimulation of the human motor cortex. NeuroImage. https://doi.org/10.1016/j.neuroimage.2013.04.067
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