Transcranial electrical stimulation (tES), including transcranial direct and alternating current stimulation (tDCS, tACS) are non-invasive brain stimulation techniques increasingly used for modulation of central nervous system excitability in humans. Here we address methodological issues required for tES application. This review covers technical aspects of tES, as well as applications like exploration of brain physiology, modelling approaches, tES in cognitive neurosciences, and interventional approaches. It aims to help the reader to appropriately design and conduct studies involving these brain stimulation techniques, understand limitations and avoid shortcomings, which might hamper the scientific rigor and potential applications in the clinical domain.

Electromagnetic data collected using electroencephalography (EEG) and magnetoencephalography (MEG) are of central importance for psychophysiological research. The scope of concepts, methods, and instruments used by EEG/MEG researchers has dramatically increased and is expected to further increase in the future. Building on existing guideline publications, the goal of the present paper is to contribute to the effective documentation and communication of such advances by providing updated guidelines for conducting and reporting EEG/MEG studies. The guidelines also include a checklist of key information recommended for inclusion in research reports on EEG/MEG measures.

To determine whether data quality is meaningfully reduced by high electrode impedance, EEG was recorded simultaneously from low-and high-impedance electrode sites during an oddball task. Low-frequency noise was found to be increased at high-impedance sites relative to lowimpedance sites, especially when the recording environment was warm and humid. The increased noise at the high-impedance sites caused an increase in the number of trials needed to obtain statistical significance in analyses of P3 amplitude, but this could be partially mitigated by highpass filtering and artifact rejection. High electrode impedance did not reduce statistical power for the N1 wave unless the recording environment was warm and humid. Thus, high electrode impedance may increase noise and decrease statistical power under some conditions, but these effects can be reduced by using a cool and dry recording environment and appropriate signal processing methods.In event-related potential (ERP) studies, researchers have traditionally minimized noise in the recordings by reducing the impedance between the recording electrodes and the living skin tissue (Luck, 2005;Picton et al., 2000). When large numbers of electrodes are used, however, the process of reducing the impedances becomes very time consuming, and this has led manufacturers of electroencephalogram (EEG) recording systems to develop systems that can tolerate high electrode impedances. These systems have become quite popular, but many researchers are concerned that the quality of the EEG will be poorer with high electrode impedances than with low electrode impedances. High electrode impedances do not meaningfully reduce the size of the EEG signal (Johnson et al., 2001), but they might increase the noise level, resulting in a lower signal-to-noise (S/N) ratio. The goal of the present study was to determine whether the S/N ratio is meaningfully reduced when the EEG is recorded with high compared to low electrode impedances.If the S/N ratio of the EEG is lower, more trials will need to be averaged together to obtain a given S/N ratio in the averaged ERPs. That is, a decline in the S/N ratio of the EEG recordings will necessitate an increase in the number of trials tested in each subject or an increase in the number of subjects tested in an experiment to achieve a given S/N ratio in the averaged ERPs. To put this in terms that reflect the "bottom line" for most ERP researchers, recording the EEG under conditions that yield a lower S/N ratio will either decrease the probability of obtaining a statistically significant experimental effect (if the number of trials is held constant) or increase the amount of recording time necessary to obtain a significant effect (if the statistical power is held constant). In most cases, researchers would like to maintain the probability of obtaining a significant effect. However, the increased number of trials required for this is often higher than one might expect, because the S/N ratio of an

The dot-probe task is often considered a gold standard in the field for investigating attentional bias to threat. However, serious issues with the task have been raised. Specifically, a number of studies have demonstrated that the traditional reaction time (RT) measure of attentional bias to threat in the dot-probe task has poor internal reliability and poor test-retest reliability. In addition, although threatening stimuli capture attention in other paradigms, attentional bias to threat has not usually been found in typical research participants in the dot-probe task. However, when attention is measured in the dot-probe task with the N2pc component of the event-related potential waveform, substantial attentional orienting to threat is observed, and the internal reliability is moderate. To provide a rigorous comparison of the reliability of this N2pc measure and the conventional behavioral measure, as well as to examine the relationship of these measures to anxiety, the present study examined the N2pc in conjunction with RT in the dot-probe task in a large sample of participants (N = 96). As in previous studies, RT showed no bias to threatening images across the sample and exhibited poor internal reliability. Moreover, this measure did not relate to trait anxiety. By contrast, the N2pc revealed a significant initial shift of attention to threat, and this measure was internally reliable. However, the N2pc was not correlated with trait anxiety, indicating that it does not provide a meaningful index of individual differences in anxiety in the dot-probe task. Together, these results indicate a serious need to develop new tasks and methods to more reliably investigate attentional bias to threat and its relationship to anxiety in both clinical and non-clinical populations.

In designing an ERP study, researchers must choose how many trials to include, balancing the desire to maximize statistical power and the need to minimize the length of the recording session. Recent studies have attempted to quantify the minimum number of trials needed to obtain reliable measures for a variety of ERP components. However, these studies have largely ignored other variables that affect statistical power in ERP studies, including sample size and effect magnitude. The goal of the present study was to determine whether and how the number of trials, number of participants, and effect magnitude interact to influence statistical power, thus providing a better guide for selecting an appropriate number of trials. We used a Monte Carlo approach to measure the probability of obtaining a statistically significant result when testing for (a) the presence of an ERP effect, (b) within-participant condition differences in an ERP effect, and (c) between-participants group differences in an ERP effect. Each of these issues was examined in the context of the error-related negativity and the lateralized readiness potential. We found that doubling the number of trials recommended by previous studies led to more than a doubling of statistical power under many conditions. Thus, when determining the number of trials that should be included in a given study, researchers must consider the sample size, the anticipated effect magnitude, and the noise level, rather than relying solely on general recommendations about the number of trials needed to obtain a "stable" ERP waveform.