Nature Portfolio aims to enhance the reproducibility of published research through structured reporting. This section outlines specific guidelines for statistical analyses, software and code availability, data availability, and field-specific reporting. For statistical analyses, authors must provide details such as sample size, statistical tests used, and assumptions or corrections. Software and code must be made available to editors and reviewers, preferably in community repositories. Data availability statements should include access codes, identifiers, and any restrictions. The section also covers reporting for specific materials, systems, and methods, including antibodies, cell lines, animals, human participants, and clinical data. For behavioral and social sciences, studies must disclose relevant information, even if negative. The document provides detailed guidelines for magnetic resonance imaging, normalization, noise and artifact removal, volume censoring, and statistical modeling. It emphasizes the importance of reproducibility in brain-phenotype association studies, using methods like support vector regression and canonical correlation analysis.Nature Portfolio aims to enhance the reproducibility of published research through structured reporting. This section outlines specific guidelines for statistical analyses, software and code availability, data availability, and field-specific reporting. For statistical analyses, authors must provide details such as sample size, statistical tests used, and assumptions or corrections. Software and code must be made available to editors and reviewers, preferably in community repositories. Data availability statements should include access codes, identifiers, and any restrictions. The section also covers reporting for specific materials, systems, and methods, including antibodies, cell lines, animals, human participants, and clinical data. For behavioral and social sciences, studies must disclose relevant information, even if negative. The document provides detailed guidelines for magnetic resonance imaging, normalization, noise and artifact removal, volume censoring, and statistical modeling. It emphasizes the importance of reproducibility in brain-phenotype association studies, using methods like support vector regression and canonical correlation analysis.