Recent advances and reflections on reproducible human neuroscience, especially brain-wide association studies (BWAS) leveraging large datasets, have led to divergent and sometimes opposing views on research practices and priorities. The debates span multiple dimensions. Shifts along these axes have fractured consensus and further fragmented an already heterogeneous field of cognitive neuroscience. Here, we sketch a holistic and integrative response grounded in population neuroscience, organized around a closed-loop "design-analysis-interpretation" research cycle that aims to build consensus while bridging these divides. Our central claim is that population neuroscience offers a unique population-level vantage point for identifying general principles, characterizing inter-individual variabilities, and benchmarking intra-individual changes, thereby providing a supportive framework for small-scale, mechanism-focused studies at the individual level and allowing them to co-evolve with population-level studies. Population neuroscience is not simply about providing larger N for BWAS; its deeper goal is to accumulate a family of cross-scale priors and shared infrastructures that can support design, analysis, and interpretation of human neuroscience for decades to come. In this sense, we outline a "third-generation" view of population neuroscience that reorients the field from amassing isolated associations toward building integrative reference frameworks for future mechanistic and translational work.
翻译:近期关于可重复性人类神经科学(特别是利用大规模数据集的脑全关联研究)的进展与反思,已导致对研究实践和优先事项产生分歧乃至对立的观点。相关争论涉及多个维度。这些轴向上的转变已打破既有共识,进一步分化了本就异质性的认知神经科学领域。本文基于群体神经科学提出一种整体性整合应对框架,围绕"设计-分析-解释"的闭环研究循环展开,旨在建立共识的同时弥合领域分歧。我们的核心论点是:群体神经科学为识别普遍规律、表征个体间差异及标定个体内变化提供了独特的群体层面观测视角,从而为个体层面聚焦机制的小规模研究提供支撑性框架,并使其能与群体层面研究协同演进。群体神经科学不仅是为脑全关联研究提供更大样本量;其深层目标在于积累跨尺度先验知识家族与共享基础设施,以支持未来数十年人类神经科学的设计、分析与解释工作。在此意义上,我们勾勒出群体神经科学的"第三代"发展图景,将领域重心从积累孤立关联转向构建面向未来机制研究与转化应用的整合性参考框架。