BACKGROUND After two decades of transcranial direct current stimulation (tDCS) research, it is still unclear which applications benefit most from which tDCS protocols. One prospect is the acceleration of learning, where previous work has demonstrated that anodal tDCS applied to the right ventrolateral prefrontal cortex (rVLPFC) is capable of doubling the rate of learning in a visual camouflaged threat detection and category learning task. GOALS Questions remain as to the specific cognitive mechanisms underlying this learning enhancement, and whether it generalizes to other tasks. The goal of the current project was to expand previous findings by employing a novel category learning task. METHODS Participants learned to classify pictures of European streets within a discovery learning paradigm. In a double-blind design, 54 participants were randomly assigned to 30 min of tDCS using either 2.0 mA anodal (n = 18), cathodal (n = 18), or 0.1 mA sham (n = 18) tDCS over the rVLPFC. RESULTS A linear mixed-model revealed a significant effect of tDCS condition on classification accuracy across training (p = 0.001). Compared to a 4.2% increase in sham participants, anodal tDCS over F10 increased performance by 20.6% (d = 1.71) and cathodal tDCS by 14.4% (d = 1.16). CONCLUSIONS These results provide further evidence for the capacity of tDCS applied to rVLPFC to enhance learning, showing a greater than quadrupling of test performance after training (491% of sham) in a difficult category learning task. Combined with our previous studies, these results suggest a generalized performance enhancement. Other tasks requiring sustained attention, insight and/or category learning may also benefit from this protocol.

中文翻译：

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经颅直流电刺激促进洞察力学习

背景 经过二十年的经颅直流电刺激 (tDCS) 研究，目前仍不清楚哪些应用程序从哪些 tDCS 协议中获益最多。一个前景是加速学习，之前的工作表明，应用于右腹外侧前额叶皮层 (rVLPFC) 的阳极 tDCS 能够使视觉伪装威胁检测和类别学习任务中的学习速度加倍。目标问题仍然是关于这种学习增强背后的特定认知机制，以及它是否可以推广到其他任务。当前项目的目标是通过采用新的类别学习任务来扩展先前的发现。方法 参与者学习在发现学习范式中对欧洲街道的图片进行分类。在双盲设计中，在 rVLPFC 上使用 2.0 mA 阳极（n = 18）、阴极（n = 18）或 0.1 mA 假（n = 18）tDCS 将 54 名参与者随机分配到 30 分钟的 tDCS。结果 线性混合模型揭示了 tDCS 条件对整个训练的分类准确度的显着影响 (p = 0.001)。与假参与者增加 4.2% 相比，F10 的阳极 tDCS 性能提高了 20.6% (d = 1.71)，阴极 tDCS 提高了 14.4% (d = 1.16)。结论这些结果为 tDCS 应用于 rVLPFC 增强学习的能力提供了进一步的证据，显示在困难的类别学习任务中训练后的测试性能增加了四倍以上（491% 的假）。结合我们之前的研究，这些结果表明了普遍的性能增强。其他需要持续关注的任务，