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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., Competing Interests: Declaration of Competing Interest none., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

It has been argued that age-related changes in the neurochemical and neurophysiological properties of the GABAergic system may underlie increases in reaction time (RT) in older adults. However, the role of GABA levels within the sensorimotor cortices (SMC) in mediating interhemispheric interactions (IHi) during the processing stage of a fast motor response, as well as how both properties explain interindividual differences in RT, are not yet fully understood. In this study, edited magnetic resonance spectroscopy (MRS) was combined with dual-site transcranial magnetic stimulation (dsTMS) for probing GABA+ levels in bilateral SMC and task-related neurophysiological modulations in corticospinal excitability (CSE), and primary motor cortex (M1)-M1 and dorsal premotor cortex (PMd)-M1 IHi, respectively. Both CSE and IHi were assessed during the preparatory and premotor period of a delayed choice RT task. Data were collected from 25 young (aged 18-33 years) and 28 older (aged 60-74 years) healthy adults. Our results demonstrated that older as compared to younger adults exhibited a reduced bilateral CSE suppression, as well as a reduced magnitude of long latency M1-M1 and PMd-M1 disinhibition during the preparatory period, irrespective of the direction of the IHi. Importantly, in older adults, the GABA+ levels in bilateral SMC partially accounted for task-related neurophysiological modulations as well as individual differences in RT. In contrast, in young adults, neither task-related neurophysiological modulations, nor individual differences in RT were associated with SMC GABA+ levels. In conclusion, this study contributes to a comprehensive initial understanding of how age-related differences in neurochemical properties and neurophysiological processes are related to increases in RT., (Copyright © 2021. Published by Elsevier Inc.)