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Although, at first sight, one might assume that the human brain is constructed in a roughly symmetric fashion, at closer investigation it becomes apparent that it is inherently asymmetric, i.e., that homotopic brain regions show structural and functional differences [1]. This applies on a structural/anatomical level with, e.g., the right frontal lobe and left occipital lobe tending to protrude over the centerline in a counterclockwise manner called the Yakovlevian torque, but also on the level of brain activity, with certain functions being linked to asymmetric areas of brain activity, such as language which is mainly (but not exclusively) located in the left hemisphere. However, it has been demonstrated that with advancing age, this functional asymmetry of the brain undergoes plastic changes [1]. Over the years, several models have been developed to explain age-related changes in brain asymmetry, such as the Hemispheric Asymmetry Reduction in Older Adults (HAROLD), the right-hemisphere aging, and the Scaffolding Theory of Aging and Cognition (STAC) model ([2] for review). Even though each model succeeds in explaining a subset of brain changes, none accomplishes to serve as an all-encompassing explanation. Therefore, another more recent attempt categorizes the existing evidence on brain aging into three main lines of interpretation, also applicable to brain lateralization: dedifferentiation, neural inefficiency, and compensatory plasticity [3, 4]. In brief, the dedifferentiation model assumes an age-related reduction in the signal-to-noise ratio and specialization of brain regions, resulting in an over-recruitment of task-specific and-unspecific brain regions in older versus younger adults; the neural inefficiency model hypothesizes a diminished signal processing efficiency of the aging brain, leading to a compensatory over-recruitment of task-specific brain regions; and the compensatory neural plasticity model describes (like the dedifferentiation model) an increased task-specific and-unspecific over-recruitment of brain regions with advancing age, however not as the result of malfunctioning but rather of compensatory functional reorganization [4]. As previously stated, advancing age simultaneously impacts lateralization structurally and functionally and a multitude of techniques are employed to study these changes. Structural changes in brain lateralization can be examined using neuroimaging. For example, alterations in the ratio between the two hemispheres' local cortical thickness, gray matter volume (e.g., using voxel-based morphometry analysis) or white matter connectivity (e.g., as assessed with diffusion-weighted imaging) of homologous brain regions can yield information about the brain's structural aging process [4]. At the intersection of brain structure and function, non-invasive brain stimulation techniques such as transcranial magnetic stimulation (TMS) are powerful tools to examine the cortex's lateralization. For example, single-pulse (sp)TMS can be used for investigating cortico-spinal excitability (CSE) and the spatial extent and localization of a muscle's cortical motor representation (i.e., motor map) at the primary motor cortex (M1). In addition, dual-site (ds)TMS can be applied to study the interaction of a motor-related brain region and M1 [5]. This can be done at rest or during a task for investigating the chronometry of CSE or an interaction on a temporal scale of milliseconds. While evidence on the lateralization of the brain's motor function using TMS is scarce, our recent work indicated no evidence for age-related differences in lateralization, i.e., in the ratio of the two hemispheres' CSE, motor map size and volume [6]. Lastly, repetitive (r)TMS can temporarily interfere with a brain region's function, resulting in a measurable change of behavior. For example, repetitive stimulation of Broca's area on the left hemisphere interferes with speech, while stimulating the anatomical homologue has no language-related effect. This allows us to study the laterality of a broader set of brain functions such as cognitive tasks [1]. When focusing on brain activation, functional magnetic resonance imaging (fMRI) is a prominent tool to capture the fluctuations in the blood-oxygen-level-dependent (BOLD) signal over time during a task or at rest. Studying task-induced hemodynamic changes in specific brain regions helps to infer their function. More specifically, brain regions engaging synchronously in response to stimuli suggest shared functionality and, altogether, form a connection or network. In the absence of stimuli, i.e., at rest, brain activity is translated into Editorial www.aging-us.com

Dual-site transcranial magnetic stimulation (ds-TMS) is well suited to investigate the causal effect of distant brain regions on the primary motor cortex, both at rest and during motor performance and learning. However, given the broad set of stimulation parameters, clarity about which parameters are most effective for identifying particular interactions is lacking. Here, evidence describing inter-and intra-hemispheric interactions during rest and in the context of motor tasks is reviewed. Our aims are threefold: (1) provide a detailed overview of ds-TMS literature regarding inter-and intra-hemispheric connectivity; (2) describe the applicability and contributions of these interactions to motor control, and; (3) discuss the practical implications and future directions. Of the 3659 studies screened, 109 were included and discussed. Overall, there is remarkable variability in the experimental context for assessing ds-TMS interactions, as well as in the use and reporting of stimulation parameters, hindering a quantitative comparison of results across studies. Further studies examining ds-TMS interactions in a systematic manner, and in which all critical parameters are carefully reported, are needed. This work was supported by the KULeuven Special Research Fund grant (C16/15/070), Research Foundation Flanders grant (G089818N and G039821N), and the Excellence of Science grant (EOS 30446199, MEMODYN). SVM (11L9322N) and MH (11F6921N) are funded by a grant from the Research Foundation Flanders. SVM is supported by the UHasselt Special Research Fund grant (BOF21INCENT15).

in the brain from MR-measurements of the current-induced magnetic field B z. Aim: We test the performance of a standard reconstruction algorithm ("projected current density algorithm", PCD, Jeong et al. 2014) for human brain data. We compare it with current flow simulations using personal-ized head models. Methods: 1. We generated ground-truth data for the TES current flow and Bz-field using a detailed head model and SimNIBS (www.simnibs.org). We applied the PCD algorithm to the B z-field and quantified the reconstruction performance by comparison with the ground-truth current flow. We additionally compared the PCD results with simulations using a simple head model ("3c" with scalp, bone and a homogeneous intracranial compartment). 2. We reconstructed the current flow from in-vivo MRCDI data (G€ oksu et al, 2018) with the PCD algorithm. We also used head models of different complexities ("3c" and "4c": scalp, skull, CSF & brain) and optimized their conductivities to minimize the root-mean-square difference between the measured and simulated B z. Results: 1. For simulated B z data, the PCD algorithm only coarsely reconstructed the true current flow. Even the simple head model performed better. 2. For measured B z data, current flows obtained with personalized head models and fitted conductivities explained the measurements better than the current flow reconstructed with the PCD algorithm. This was already the case for the simple head model (3c). The more detailed model (4c) resulted in further statistically significant improvements. However, for all models, the unexplained variance stayed above the noise floor, indicating remaining differences to unknown true current flow. Conclusions: The PCD algorithm has low accuracy for MRCDI data of the brain. However, MRCDI is useful for evaluations and improvements of current flow simulations with anatomically detailed personalized head models.

The net output of the primary motor cortex (M1) is shaped by several (non-)motor brain regions including the dorsal premotor cortex (PMd) which is playing an important role in sensorimotor integration, response selection, bimanual motor control, and motor learning. Previous dual-site transcranial magnetic stimulation (dsTMS) setups mainly investigated the interhemispheric PMd – M1 interactions, as testing the intrahemispheric PMd – M1 interactions yield technical difficulties due to the vicinity of both regions. A novel dsTMS setup was used in a sample of 23 young healthy right-handed adults to probe intrahemispheric left PMd – M1 interactions at rest. Biphasic stimuli were applied to M1 to elicit an MEP of at least 1 mV peak-to-peak amplitude (testing stimulus, TS) in the resting first dorsal interosseus (FDI). The conditioning stimulus (CS) was applied ∼2 cm anterior to M1 at an interstimulus interval (ISI) of 6 ms and an intensity of 75% of the resting motor threshold (rMT). To physiologically test this setup, short-interval intra-cortical inhibition (SICI) was measured with the same coil arrangement, using two coils targeted at M1 (ISI = 3 ms, CS intensity = 75% rMT, TS intensity = 1 mV). First, SICI could robustly be elicited using the novel coil setup. Second, conditioning left PMd lead to a robust modulation of left M1 output when using a CS intensity of 75% rMT. This interaction was mostly found to be inhibitory. However, in some subjects (∼15%) a facilitatory PMd – M1 interaction was seen. This novel coil setup opens new opportunities to measure intrahemispheric PMd – M1 interactions at rest and in different task-related contexts without facing technical difficulties such as large stimulation distances due to coil size or coil heating (particularly in small coils).