# AUTHOR GUIDELINES Authors should refer to the author guidelines for navigating the peer review platform here. Reviewers should refer to the reviewer guidelines for navigating the peer review platform here. # Journal Description Aperture Neuro was created through the Organization for Human Brain Mapping to address the growing need among the international brain imaging and neuroscience community for an exceptional non-profit, open access, and community guided publishing platform that offers a wide range of options for publication. Aperture Neuro publishes traditional HTML and PDF objects and offers opportunities to link these to notebooks, data, code, and videos. # Scope The focus of Aperture Neuro is original basic or clincal research and novel methods that increase our understanding of the structure, function, and organizational principles of the human brain. We also aim to advance the utility, transparency, and replicability of all findings through catalyzing dissemination of high quality new approaches, useful data, and basic concepts and approaches. Aperture Neuro publishes original research, review articles, tutorials, book reviews, editorials, conference and workshop summaries, replication studies, registered reports, as well as papers describing code, data, notebooks, and videos. # Publication Fees Aperture Neuro as well as the Organization for Human Brain Mapping are non-profit, therefore the Author Processing Charge (APC) is set for sustainability. There are no submission fees. Authors that have their work accepted for publication are required to pay an APC of $1000 for non-OHBM members, and $800 for members. Aperture Neuro will allow the APC to be waived for: * Authors who reside and work in countries where the expenditure on research and development is below $200 USD per capita * Authors of invited submissions * Authors reporting on events of specific interest to the OHBM community (e.g., conference or workshop summaries) If you feel that you qualify for a fee waiver, please contact the Journal Manager . Each request will be evaluated by the Editor-in-Chief and Associate Editor-in-Chief on a case-by-case basis. # Submission Process All papers should be formatted in the AMA style. ## Language We ask that you use either American English or British English and remain consistent. Please note that Aperture Neuro does not currently offer copyediting services. Authors are responsible for ensuring correct and clear expression of English in submitted content. ## Authorship Aperture Neuro defines authors and contributors according to the recommendations outlined by the [Committee on Publication Ethics (COPE)](https://publicationethics.org/files/COPE_DD_A4_Authorship_SEPT19_SCREEN_AW.pdf) and the [International Committee of Medical Journal Editors (ICMJE)](https://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html). For more information, see the [Editorial Policies webpage](https://apertureneuro.org/pages/588-editorial-policies#authorship). ## Title Titles are limited to 300 characters. Please do not use subscript, superscript, boldface and/or italics in your title. # Submission Materials ## Cover Letter Please include a cover letter with your submission. You will be asked to upload your cover letter as a separate document in the submission platform. This letter should be addressed to Aperture Neuro’s Editorial Team and include any relevant information you feel will aid the Editors in the consideration of your work. In addition, you may include up to five suggested reviewers with their corresponding emails. You may also include reviewers that you wish to be excluded. Please note that the Editors use this information at their discretion. ## Main Text The main text document should be double spaced and uploaded as a Word or LaTeK (PDF) document in AMA citation style. Publication quality figures are submitted separately; however, please include figures, tables, and figure captions within the text for ease of review. Make every effort to keep the text within 12,000 words. ## Methods Reporting **Reporting Guidelines**: To promote transparent and reproducible research, authors should ensure that methodological reporting follows best practice standards appropriate for the study design of their submission. For example, systematic reviews and meta-analyses should refer to [PRISMA](http://www.prisma-statement.org/?AspxAutoDetectCookieSupport=1) for minimum criteria and case reports to [CARE](https://www.care-statement.org/). For an extensive list of resources, please visit the National Library of Medicine’s [Research Reporting Guidelines and Initiatives](https://www.nlm.nih.gov/services/research_report_guide.html) or the EQUATOR Network's [Reporting Guidelines](https://www.equator-network.org/). Original research articles should contain the following sections: Title Page (including title, authors, affiliations, corresponding author information), Abstract, Introduction, Methods, Results, Discussion, and References. See ICMJE [recommendations](https://www.icmje.org/recommendations/browse/manuscript-preparation/preparing-for-submission.html) for more details. Aperture Neuro encourages the documentation of data/code/methods according to the following community standards: * For data documentation, it is advised to use the BIDS format (https://bids.neuroimaging.io/). It is recommended that the authors: 1) check the respective box in the submission form, 2) use ‘BIDS’ as one of the key-words of the manuscript, and 3) mention the version of the BIDS validator (e.g. this [online tool](https://bids-standard.github.io/bids-validator/)) that was used to ensure BIDS compatibility. Reviewers are encouraged to check if the data are indeed following the BIDS format. * For reporting of acquisition methods, authors are advised to follow the COBIDAS standard. An interactive eCOBIDAS checklist is available here: [https://ohbm.github.io/eCOBIDAS/#/](https://ohbm.github.io/eCOBIDAS/#/) * If the data/code/methods have been downloaded from the public domain, the source and means of obtaining the data/code/method should be stated with links and versions. **Data/code availability**: Papers containing original data and/or code should incorporate a statement addressing the accessibility of all data utilized in the submission. In cases where data cannot be openly shared, a valid justification should be provided, which could relate to ethical concerns or privacy issues related to clinical data or constraints imposed by the institution overseeing the study. If the data will only be accessible upon request from the authors, the terms of such a request and any associated restrictions should be explicitly outlined. These conditions might encompass the necessity for a formal data sharing agreement, approval from the requesting researcher's local ethics committee, submission of a formal project outline, or stipulations for co-authorship or inclusion in the authorship credit. A vague "Available upon request" is unacceptable without specifying potential requirements. ## Ethics in Publishing Authors must include statements about the ethical collection of human or animal data (if applicable), as well as disclosure of financial support and any conflicts of interest. For more information, please see the [Editorial Policies webpage](https://apertureneuro.org/pages/588-editorial-policies#ethics-in-publishing). ## Figures High quality .jpg or .jpeg files identified accordingly as "Figure 1, Figure 2.." ## Tables Tables should be embedded in a Word or LaTeK document and must have an accompanying title that is descriptive (for example "Table 1. The effect of percent change on correlation"). If the table is overly complex in structure, the best option is to convert it to a Figure and submit it as such. ## Header Image for Website Display This will be displayed on the website with the text of the title, authors, and a lede. A simple figure with minimal text is desired. The image must be a .jpg or .jpeg of least 1000 pixels x 500 pixels and have an aspect ratio of between 1 and 2.5. ## Supplementary Material Format supplementary material similarly to that of the main text.

Improving the Interpretability of fMRI Decoding Using Deep Neural Networks and Adversarial Robustness