Real‐time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in learning success and treatment response have been observed, yet the neural substrates underlying the learning of self‐regulation remain unclear. Against this background, we explored potential brain structural predictors for learning success with pooled data from three real‐time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback learning success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with learning success independent of specific aspects of the experimental design. Given the role of the putamen in associative learning this finding may reflect an important role of instrumental learning processes and brain structural variations in associated brain regions for successful acquisition of fMRI neurofeedback‐guided self‐regulation.

中文翻译：

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壳核体积预测跨范式和神经反馈目标区域的实时 fMRI 神经反馈学习成功

实时 fMRI 引导的神经反馈训练作为一种非侵入性大脑调节技术，具有在治疗环境中调节功能性大脑改变的潜力，越来越受到关注。已经观察到学习成功和治疗反应的个体差异，但自我调节学习背后的神经基质仍不清楚。在此背景下，我们利用来自三个实时 fMRI 数据集的汇总数据探索了潜在的大脑结构预测因素，以促进学习成功。我们的分析表明，右侧壳核的灰质体积可以预测三个数据集（n= 总共 66 个）。重要的是，原始研究采用了不同的神经反馈范式，在此期间训练不同的大脑区域，指出与实验设计的特定方面无关的与学习成功的一般关联。鉴于壳核在联想学习中的作用，这一发现可能反映了工具学习过程和相关大脑区域的大脑结构变化对于成功获得 fMRI 神经反馈引导的自我调节的重要作用。