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      Outcome measures for electric field modeling in tES and TMS: A systematic review and large-scale modeling study

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          Abstract

          Background:

          Electric field (E-field) modeling is a potent tool to estimate the amount of transcranial magnetic and electrical stimulation (TMS and tES, respectively) that reaches the cortex and to address the variable behavioral effects observed in the field. However, outcome measures used to quantify E-fields vary considerably and a thorough comparison is missing.

          Objectives:

          This two-part study aimed to examine the different outcome measures used to report on tES and TMS induced E-fields, including volume- and surface-level gray matter, region of interest (ROI), whole brain, geometrical, structural, and percentile-based approaches. The study aimed to guide future research in informed selection of appropriate outcome measures.

          Methods:

          Three electronic databases were searched for tES and/or TMS studies quantifying E-fields. The identified outcome measures were compared across volume- and surface-level E-field data in ten tES and TMS modalities targeting two common targets in 100 healthy individuals.

          Results:

          In the systematic review, we extracted 308 outcome measures from 202 studies that adopted either a gray matter volume-level ( n = 197) or surface-level ( n = 111) approach. Volume-level results focused on E-field magnitude, while surface-level data encompassed E-field magnitude ( n = 64) and normal/tangential E-field components ( n = 47). E-fields were extracted in ROIs, such as brain structures and shapes (spheres, hexahedra and cylinders), or the whole brain. Percentiles or mean values were mostly used to quantify E-fields. Our modeling study, which involved 1,000 E-field models and > 1,000,000 extracted E-field values, revealed that different outcome measures yielded distinct E-field values, analyzed different brain regions, and did not always exhibit strong correlations in the same within-subject E-field model.

          Conclusions:

          Outcome measure selection significantly impacts the locations and intensities of extracted E-field data in both tES and TMS E-field models. The suitability of different outcome measures depends on the target region, TMS/tES modality, individual anatomy, the analyzed E-field component and the research question. To enhance the quality, rigor, and reproducibility in the E-field modeling domain, we suggest standard reporting practices across studies and provide four recommendations.

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          Most cited references252

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          A multi-modal parcellation of human cerebral cortex

          Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal ‘fingerprint’ of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.
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            The Human Connectome Project: a data acquisition perspective.

            The Human Connectome Project (HCP) is an ambitious 5-year effort to characterize brain connectivity and function and their variability in healthy adults. This review summarizes the data acquisition plans being implemented by a consortium of HCP investigators who will study a population of 1200 subjects (twins and their non-twin siblings) using multiple imaging modalities along with extensive behavioral and genetic data. The imaging modalities will include diffusion imaging (dMRI), resting-state fMRI (R-fMRI), task-evoked fMRI (T-fMRI), T1- and T2-weighted MRI for structural and myelin mapping, plus combined magnetoencephalography and electroencephalography (MEG/EEG). Given the importance of obtaining the best possible data quality, we discuss the efforts underway during the first two years of the grant (Phase I) to refine and optimize many aspects of HCP data acquisition, including a new 7T scanner, a customized 3T scanner, and improved MR pulse sequences. Copyright © 2012 Elsevier Inc. All rights reserved.
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              Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping.

              The recent advent of multichannel near-infrared spectroscopy (NIRS) has expanded its technical potential for human brain mapping. However, NIRS measurement has a technical drawback in that it measures cortical activities from the head surface without anatomical information of the object to be measured. This problem is also found in transcranial magnetic stimulation (TMS) that transcranially activates or inactivates the cortical surface. To overcome this drawback, we examined cranio-cerebral correlation using magnetic resonance imaging (MRI) via the guidance of the international 10-20 system for electrode placement, which had originally been developed for electroencephalography. We projected the 10-20 standard cranial positions over the cerebral cortical surface. After examining the cranio-cerebral correspondence for 17 healthy adults, we normalized the 10-20 cortical projection points of the subjects to the standard Montreal Neurological Institute (MNI) and Talairach stereotactic coordinates and obtained their probabilistic distributions. We also expressed the anatomical structures for the 10-20 cortical projection points probabilistically. Next, we examined the distance between the cortical surface and the head surface along the scalp and created a cortical surface depth map. We found that the locations of 10-20 cortical projection points in the standard MNI or Talairach space could be estimated with an average standard deviation of 8 mm. This study provided an initial step toward establishing a three-dimensional probabilistic anatomical platform that enables intra- and intermodal comparisons of NIRS and TMS brain imaging data.
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                Author and article information

                Journal
                9215515
                20498
                Neuroimage
                Neuroimage
                NeuroImage
                1053-8119
                1095-9572
                1 April 2024
                01 November 2023
                15 September 2023
                11 April 2024
                : 281
                : 120379
                Affiliations
                [a ]REVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium
                [b ]Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
                [c ]Brain Stimulation Laboratory, Department of Psychiatry, Medical University of South Carolina, Charleston, SC, United States
                Author notes
                [* ]Corresponding author: Hasselt University, Faculty of Rehabilitation Sciences, Agoralaan, Building A, 3590 Diepenbeek, Belgium.
                [** ]Corresponding author: Department of Psychiatry, Medical University of South Carolina, 67 President Street, 504 N, Charleston, SC, USA. sybren.vanhoornweder@ 123456uhasselt.be (S. Van Hoornweder), caulfiel@ 123456musc.edu (K.A. Caulfield).
                [#]

                These authors share last-authorship

                Article
                NIHMS1936453
                10.1016/j.neuroimage.2023.120379
                11008458
                37716590
                bedbeea9-bfb1-4fd8-b2c8-e96f21442063

                This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/).

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                Neurosciences
                electric field (e-field) modeling,transcranial electrical stimulation (tes),transcranial direct current stimulation (tdcs),finite element method (fem),region of interest (roi) analyses,whole brain analyses

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