Dataset for: Systematic review and network meta-analysis of anodal tDCS effects on verbal episodic memory: Modelling heterogeneity of stimulation locations

Dataset for: Bartl, G. J., Blackshaw, E., Crossman, M., Allen, P., & Sandrini, M. (2020). Systematic review and network meta-analysis of anodal tDCS effects on verbal episodic memory: Modeling heterogeneity of stimulation locations. Zeitschrift für Psychologie, 228(1), 3–13. https://doi.org/10.1027/2151-2604/a000396 Dataset for metaregression containing pooled effect sizes for metaregression; contains the following information: study label, Hedges' g, SE, blinding status (1-double, 0-single), current density, arm 1, arm 2, sample size 1, sample size 2, notes. Dataset for network meta-analysis containing pooled effect sizes for network meta-analysis; contains the following information: study label, Hedges' g, SE, arm 1, arm 2, sample size 1, sample size 2. There is growing interest in the study of transcranial direct current stimulation (tDCS), a non-invasive brain stimulation technique, as an effective intervention to improve memory. In order to evaluate the relative efficacy of tDCS based on the location of anodal electrode sites, we conducted a systematic review examining the effect of stimulation applied during encoding on subsequent verbal episodic memory in healthy adults. We performed a network meta-analysis of 20 studies (23 experiments) with N = 978 participants. Left ventrolateral prefrontal and temporo-parietal sites appeared most likely to enhance episodic memory, although any significant effects were based on findings from single studies only. We did not find evidence for verbal retrieval enhancement of tDCS versus sham stimulation where the effect was based on more than one experimental paper. More frequent replication efforts and stricter reporting standards may improve the quality of evidence and allow more precise estimation of population-level effects of tDCS. GB received project-specific funding from Santander UK. GB and EB are supported by the Vice-Chancellor’s Scholarship from the University of Roehampton. Dataset for metaregression; Dataset for network meta-analysis