Brain receives far more manuscript submissions than can reasonably be sent for formal peer review. Although the reasons for editorial rejection are diverse and include such factors as under-powered study design, limited conceptual novelty or remoteness from clinical translation, the motivation behind the authors’ work is rarely in doubt. Nevertheless, there remains a small number of submissions where the route to clinical application or to improved understanding of disease mechanisms is very difficult to infer, leaving one asking, ‘Why did the authors undertake this work in the first place?’ Such manuscripts disproportionately report on functional MRI in groups of patients without a discernible hypothesis. Showing that activation patterns or functional connectivity motifs differ significantly is, on its own, insufficient justification to occupy space in Brain. Given that functional MRI is ∼30 years old and continues to divert many talented young researchers from careers in other fields of translational neuroscience, it is worth reiterating two of the most troubling limitations of the method (and these are not the notorious pitfalls such as failure to correct for multiple comparisons or circular inference). First, the fundamental relationship between the blood oxygenation level-dependent (BOLD) signal and neuronal computations remains a complete mystery. As a direct consequence, it is extremely difficult to conclude that functional connectivity as measured by functional MRI genuinely measures information exchange between brain regions. Second, effect sizes are quasi-impossible to infer, leading to an anomaly in science where statistical significance remains the only metric reported. A puzzling phenomenon that should perhaps ring alarm bells is that the situation is not improved by increasing the spatial resolution using higher field strengths, where the confounding effect of blood vessels increases. This is not to dismiss the potential importance of the method when used with care and with a priori hypotheses, and in rare cases functional MRI has found a clinical role. One such application is in diagnosing consciousness in patients with cognitive-motor dissociation. A Scientific Commentary by Adrian Owen, who has pioneered the use of functional MRI in this setting, features in this issue, and highlights an article by Jiahui Pan, Qiuyou Xie, Pengmin Qin and colleagues, who use a machine-learning classifier to decode evoked EEG patterns to improve the ability to detect covert consciousness.

中文翻译：

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人脑区域或方法伪像之间的抑制作用？

脑收到的稿件数量远远超出了正式同行评审所需的稿件数量。尽管拒绝编辑的原因多种多样，包括诸如研究设计能力不足，概念上的新颖性有限或远离临床翻译之类的因素，但作者工作背后的动机很少受到质疑。然而，仍然有少数意见很难推论到临床应用或对疾病机理的更好理解的途径，而有人问：“为什么作者首先从事这项工作？” 在没有可辨别假设的患者群体中，此类手稿不成比例地报告了功能MRI。单独表明，激活模式或功能连接性主题存在显着差异，脑。鉴于功能性MRI已有30岁左右的历史，并且继续使许多才华横溢的年轻研究人员脱离翻译神经科学其他领域的职业，因此值得重申该方法的两个最令人困扰的局限性（而且这些都不是失败之类的臭名昭著的陷阱）更正多个比较或循环推断）。首先，血液氧合水平依赖性（BOLD）信号与神经元计算之间的基本关系仍然是一个谜。直接的结果是，很难得出结论，即通过功能性MRI测量的功能连通性能够真正测量大脑区域之间的信息交换。其次，效应大小是不可能推断的，这导致了科学中的异常，在统计学中统计意义仍然是唯一报告的指标。一个令人费解的现象可能会敲响警钟，那就是使用较高的场强无法通过提高空间分辨率来改善这种情况，因为在这种情况下，血管的混杂效应会增加。当谨慎使用时，这并不是要忽略该方法的潜在重要性。先验假设，在极少数情况下功能性MRI已发现临床作用。一种这样的应用是在认知运动分离患者中的意识诊断。在此环境中率先使用功能MRI的Adrian Owen的科学评论在本期中进行了介绍，并重点介绍了潘佳慧，谢秋友，秦鹏敏及其同事使用机器学习分类器解码诱发的文章。脑电图模式可提高发现秘密意识的能力。