FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2068638051> ?p ?o ?g. }

• W2068638051 endingPage "264" @default.
• W2068638051 startingPage "253" @default.
• W2068638051 abstract "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, 1 cm 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 (r max = 0.91, p = 1.8 × 10 -5 r mean = 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. • Individual hand knob curvature influences TMS motormapping outcomes. • TMS coil orientation and gyral folding affect excitability in response to TMS. • Subject-specific conductivity anisotropy also influences TMS motormapping results. • FEM simulations of TMS-induced E-fields are compared against physiology results. • FEM simulations predict physiological outcomes better than projection approaches." @default.
• W2068638051 created "2016-06-24" @default.
• W2068638051 creator A5028123152 @default.
• W2068638051 creator A5047609364 @default.
• W2068638051 creator A5080015386 @default.
• W2068638051 creator A5081714379 @default.
• W2068638051 creator A5082720571 @default.
• W2068638051 creator A5090308856 @default.
• W2068638051 date "2013-11-01" @default.
• W2068638051 modified "2023-09-23" @default.
• W2068638051 title "Physiological observations validate finite element models for estimating subject-specific electric field distributions induced by transcranial magnetic stimulation of the human motor cortex" @default.
• W2068638051 cites W1967742020 @default.
• W2068638051 cites W1987061172 @default.
• W2068638051 cites W1994673993 @default.
• W2068638051 cites W1999761573 @default.
• W2068638051 cites W2006096283 @default.
• W2068638051 cites W2010156877 @default.
• W2068638051 cites W2016478370 @default.
• W2068638051 cites W2018731294 @default.
• W2068638051 cites W2022559191 @default.
• W2068638051 cites W2024832506 @default.
• W2068638051 cites W2025539634 @default.
• W2068638051 cites W2034753893 @default.
• W2068638051 cites W2044889549 @default.
• W2068638051 cites W2047126441 @default.
• W2068638051 cites W2052986508 @default.
• W2068638051 cites W2059606609 @default.
• W2068638051 cites W2061551969 @default.
• W2068638051 cites W2063841517 @default.
• W2068638051 cites W2065571228 @default.
• W2068638051 cites W2074813852 @default.
• W2068638051 cites W2078441972 @default.
• W2068638051 cites W2082526227 @default.
• W2068638051 cites W2087813588 @default.
• W2068638051 cites W2096892196 @default.
• W2068638051 cites W2097542629 @default.
• W2068638051 cites W2098406191 @default.
• W2068638051 cites W2098732363 @default.
• W2068638051 cites W2099385285 @default.
• W2068638051 cites W2112927743 @default.
• W2068638051 cites W2116423195 @default.
• W2068638051 cites W2117085951 @default.
• W2068638051 cites W2127919130 @default.
• W2068638051 cites W2136961426 @default.
• W2068638051 cites W2146712952 @default.
• W2068638051 cites W2149883075 @default.
• W2068638051 cites W2158425431 @default.
• W2068638051 cites W2164535356 @default.
• W2068638051 cites W2168512521 @default.
• W2068638051 cites W4235770099 @default.
• W2068638051 cites W4240721737 @default.
• W2068638051 doi "https://doi.org/10.1016/j.neuroimage.2013.04.067" @default.
• W2068638051 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/23644000" @default.
• W2068638051 hasPublicationYear "2013" @default.
• W2068638051 type Work @default.
• W2068638051 sameAs 2068638051 @default.
• W2068638051 citedByCount "162" @default.
• W2068638051 countsByYear W20686380512013 @default.
• W2068638051 countsByYear W20686380512014 @default.
• W2068638051 countsByYear W20686380512015 @default.
• W2068638051 countsByYear W20686380512016 @default.
• W2068638051 countsByYear W20686380512017 @default.
• W2068638051 countsByYear W20686380512018 @default.
• W2068638051 countsByYear W20686380512019 @default.
• W2068638051 countsByYear W20686380512020 @default.
• W2068638051 countsByYear W20686380512021 @default.
• W2068638051 countsByYear W20686380512022 @default.
• W2068638051 countsByYear W20686380512023 @default.
• W2068638051 crossrefType "journal-article" @default.
• W2068638051 hasAuthorship W2068638051A5028123152 @default.
• W2068638051 hasAuthorship W2068638051A5047609364 @default.
• W2068638051 hasAuthorship W2068638051A5080015386 @default.
• W2068638051 hasAuthorship W2068638051A5081714379 @default.
• W2068638051 hasAuthorship W2068638051A5082720571 @default.
• W2068638051 hasAuthorship W2068638051A5090308856 @default.
• W2068638051 hasBestOaLocation W20686380511 @default.
• W2068638051 hasConcept C115260700 @default.
• W2068638051 hasConcept C120665830 @default.
• W2068638051 hasConcept C121332964 @default.
• W2068638051 hasConcept C135628077 @default.
• W2068638051 hasConcept C15744967 @default.
• W2068638051 hasConcept C169760540 @default.
• W2068638051 hasConcept C180205008 @default.
• W2068638051 hasConcept C24890656 @default.
• W2068638051 hasConcept C24998067 @default.
• W2068638051 hasConcept C2778373776 @default.
• W2068638051 hasConcept C2778581513 @default.
• W2068638051 hasConcept C30403606 @default.
• W2068638051 hasConcept C46141821 @default.
• W2068638051 hasConcept C60799052 @default.
• W2068638051 hasConcept C62520636 @default.
• W2068638051 hasConcept C85725439 @default.
• W2068638051 hasConcept C97355855 @default.
• W2068638051 hasConceptScore W2068638051C115260700 @default.
• W2068638051 hasConceptScore W2068638051C120665830 @default.
• W2068638051 hasConceptScore W2068638051C121332964 @default.
• W2068638051 hasConceptScore W2068638051C135628077 @default.
• W2068638051 hasConceptScore W2068638051C15744967 @default.

• next