Authors: Faruk Gulban |  Published: June 2025

Scientific publishing is evolving, but the PDF endures as the gold standard: static, formal, and supposedly unimpeachable.  In this satirical commentary, I examine the widening gap between traditional publication norms, and emerging channels of science communication, including blogs, podcasts, social media threads, and video tutorials. While critiquing institutional inertia, and performative rigor, I also caution against mistaking popularity for impact. I argue for a broader, more accessible model of scientific exchange, one that respects methodological integrity while embracing clarity, conversation, and reach. PDFs are not obsolete, but they are no longer enough. In an age of hypercommunication, perhaps the greatest risk is being understood.

Long before journals, and DOIs (digital object identifiers), science was shared in ink, and wax. Letters were the vessels of discovery between natural philosophers. Galileo writing to Kepler, Darwin sending drafts to Hooker, Émilie du Châtelet debating Newtonian physics with Voltaire, or Marie Curie exchanging ideas with Albert Einstein. The 17th-century Philosophical Transactions wasn’t just a repository of findings; it was the latest evolution of a timeless question: how should scientists communicate?

From handwritten correspondence to conferences, from lab notebooks to preprints, scientific publishing has never been static. It has always evolved with the communication technologies of its time (see Figure 1). Today, we find ourselves in a new transition. Podcasts, blogs, open code repositories, online video tutorials, social media threads, and collaborative documents offer us tools to share science faster, more broadly, and often more effectively. And yet, many of us cling, often out of habit or institutional inertia, to the PDF as our sacred format of choice.

Interlude: A 10 point guide for publishing like a proper scientist today

1. Everyone loves a 12-month publishing cycle. The anticipation! Submit, wait four months, get cryptic reviewer comments, revise, wait again. By the time it’s published, you’ve changed institutions, and forgotten half the project. Nothing builds character like slow feedback.
2. The gospel of the immutable PDF. Sure, your methods section might have unintentionally left out half the pipeline. But that’s the beauty of a PDF, it freezes your work in time, imperfections and all. It will never update, never improve. Ideal.
3. Why make your work reproducible when you can make it mysterious? Sharing your talk recordings, conference presentations, and analysis code are fine in theory. But if a colleague can actually replicate your analyses without emailing you… What is left of the scientific mystique?
4. Blogs are for people with hobbies. You might be tempted to write a short, clear explanation of your latest model. Maybe even highlight its limitations, and use cases. Resist. A true scientist knows that insights belong in 10-point font, two-column PDFs behind journal paywalls.
5. Video tutorials might help people. But helping people doesn’t earn citations. Making a clear, narrated walkthrough of your pipeline could save hundreds of hours for others. But is it indexed on PubMed? Will your tenure committee ever watch it? Exactly.
6. Podcasts are dangerously human. They reveal things like: how ideas were formed, where you struggled, what you’re curious about. These things don’t fit neatly into an abstract, and they might even make science feel accessible. Best avoided.
7. Preprints are anarchic. Why share your work before it’s been anointed by Reviewer 2? Imagine publishing without waiting 10 months, or receiving open feedback from multiple colleagues. Chaos.
8. Social media threads let you explain your work too quickly. And worse, people might actually read them. The brevity, the visualizations, the conversational tone… these are dangerous tools in the wrong hands. Some people even use them to summarize entire conferences in real time. Scandalous.
9. Visibility is a dangerous thing. People who communicate well across platforms often gain visibility. And visibility can lead to collaboration, funding, and recognition… but not necessarily the “right kind.” A real scientist measures success with impact factors, not impact.
10. You might enjoy it. Writing a blog post, recording a video, responding to a comment on your tutorial… These are activities that can feel energizing, engaging, and rewarding. This sets a dangerous precedent.

Breaking the rules is how we got here

When scientists started mailing letters across the world, it was not official publishing. When journals went online, people doubted the legitimacy of digital peer review. When preprints first appeared, they weren’t respected. Each of these shifts felt uncomfortable, even inappropriate, at first. But they shaped what we now consider standard. So maybe a video tutorial is today’s Darwin’s letter to Hooker. Maybe your blog post is the Philosophical Transactions of your circle. Maybe the tools we’re hesitant to legitimize are exactly the ones the next generation will take for granted.

The long game of modern science communication

I’ve personally found that the time I have “lost” engaging in modern forms of communication has repaid me in unexpected but meaningful, and quantifiable ways. For instance:

• During my PhD, a spontaneous exchange in the OHBM Open Science Room led to a collaboration that became one of my most impactful projects. What started as a casual conversation evolved into a multi-institutional publication with a PhD student in another continent working on auditory brainstem nuclei (Sitek & Gulban et al, 2018). Together, Kevin, and I produced something far greater than either of us could have achieved independently. It remains my second most cited manuscript to date.
• Around the same time, I became a co-author on a multi-species brain imaging paper after a series of conversations on social media evolved into a full collaboration (Heuer et al., 2019). This experience expanded my perspective, showing me that the segmentation method I had developed for human imaging (Gulban & Schneider et al., 2018) could be applied to non-human data as well. I assisted Katja, and Roberto in expediting their segmentation work in time for a submission deadline, and in turn, this cross-species application strengthened the societal impact section of my PhD thesis (Gulban, 2020).
• After reading blog posts on LayerfMRI.com, I reached out to Renzo Huber to contribute to the open-source LayNii software suite. What began as an informal connection through shared online resources led to a deep technical collaboration, and eventually my first last-author paper (Huber et al., 2021). By 2024, LayNii had become the most widely used software in its niche, surpassing even established tools like FreeSurfer, and BrainVoyager in this very specific domain (see Huber & Gulban, 2024, Figure 1). To date, this has also become my most cited publication, reflecting not just academic attention but real-world utility, and widespread adoption in the field.
• I also received an unexpected invitation to publish a deeply niche, “non-publishable” side project: an English translation, and contextual commentary on a scientific paper from the 1880s. The editor, Dr. Maria Holland, who had read my social media posts offered the perfect venue for it (Heynckes et al., 2021).
• Long-haul flights became opportunities for discovery. While listening to a podcast episode featuring Audrey Fan on Neurosalience, I was inspired to adapt my high-resolution, limited-coverage imaging methods (Gulban et al., 2022) toward clinically relevant applications (Gulban et al., 2025). I’ve never met Dr. Fan beyond sending her a single email of thanks, she likely has no idea how influential that podcast was on my work.
• Finally, thanks to a mix of writing scientific blog posts, recording video tutorials, dabbling in podcast production, and the occasional social media thread, in addition to regularly publishing fully peer-reviewed, traditional scientific papers, I somehow ended up being invited to write this very commentary on a , ironically, on modern scientific publishing.

These moments were not born in formal review processes or indexed journals, they emerged from being open, visible, and curious in public scientific spaces. They were not distractions from “real” science; they were how real science happened.

But not without risks

This modern publication ecosystem is not without its shadows. The line between authentic engagement, and performative self-promotion can blur easily. It’s tempting to chase followers, impressions, and visibility to become an “academic influencer” chasing metrics, rather than a scientist pursuing insight. Just because someone produces slick videos, engaging posts, or charming podcasts doesn’t mean their science is stronger, or even sound. A good thumbnail is not a good hypothesis.

Michael Strevens (2020), in The Knowledge Machine, describes science’s strength as its “Iron Rule”: an obsessive commitment to empirical argument, method, and rigor. This rule demands that, regardless of how science is communicated, its foundation must remain intellectually dry, and methodologically sound. Communicating well should never replace writing excellent papers, it should amplify them.

Conclusions

Still, in a world where science is increasingly politicized, misunderstood, or actively undermined, those of us who have the privilege, and skill to speak across platforms may carry a new kind of responsibility. If a tutorial video, a podcast, or a social media thread can clarify science to someone outside our echo chamber, or inside it, then perhaps we owe it to the discipline to keep pressing “record.”

The landscape has changed. Today’s early-career scientists are not just navigating research, they’re navigating a social, digital, political, and economic environment vastly different from the one their mentors came up in. Gatekeeping old channels won’t preserve science, it might instead paralyze it. Maybe it is time to accept that progress might come one video tutorial at a time.

Therefore, no, I’m not going to stop publishing PDFs. Peer review, archiving, and formal structure are still extremely critical for science. But I am going to keep supplementing my PDFs with videos, blogs, threads, and conversations, before, during, and after publication. Not to replace scientific rigor, but to enrich the ecosystem around it. To make science more visible, more alive, and above all, more human.

References

• Sitek, K.R., Gulban, O.F., Calabrese, E., Johnson, G.A., Lage-Castellanos, A., Moerel, M., Ghosh, S.S., De Martino, F., 2019. Mapping the human subcortical auditory system using histology, postmortem MRI and in vivo MRI at 7T. eLife 8, 1–36. https://doi.org/10.7554/eLife.48932
• Heuer, K., Gulban, O.F., Bazin, P.-L., Osoianu, A., Valabregue, R., Santin, M., Herbin, M., Toro, R., 2019. Evolution of neocortical folding: A phylogenetic comparative analysis of MRI from 34 primate species. Cortex 1–26. https://doi.org/10.1016/j.cortex.2019.04.011
• Gulban, O.F., 2020. Imaging the human auditory system at ultrahigh magnetic fields. Maastricht University. https://doi.org/10.26481/dis.20201006og
• Heynckes, M., Gulban, O.F., De Martino, F., 2022. On the superior temporal gyrus by R.L. Heschl: English translation of “Über Die Vordere Quere Schläfenwindung Des Menschlichen Großhirns.” Brain Multiphysics 100055. https://doi.org/10.1016/j.brain.2022.100055
• Huber, L., Poser, B.A., Bandettini, P.A., Arora, K., Wagstyl, K., Cho, S., Goense, J., Nothnagel, N., Morgan, A.T., van den Hurk, J., Müller, A.K., Reynolds, R.C., Glen, D.R., Goebel, R., Gulban, O.F., 2021. LayNii: A software suite for layer-fMRI. NeuroImage 237, 118091. https://doi.org/10.1016/j.neuroimage.2021.118091
• Gulban, O.F., Huber, R., 2024. Computing geometric layers and columns on continuously improving human (f)MRI data, in: Encyclopedia of the Human Brain (Second Edition). Elsevier. https://doi.org/10.1016/B978-0-12-820480-1.00188-1
• Gulban, O.F., Bollmann, S., Huber, L., Wagstyl, K., Goebel, R., Poser, B.A., Kay, K., Ivanov, D., 2022. Mesoscopic in vivo human T2* dataset acquired using quantitative MRI at 7 Tesla. NeuroImage 264, 119733. https://doi.org/10.1016/j.neuroimage.2022.119733
• Gulban, O.F., Schneider, M., Marquardt, I., Haast, R.A.M., De Martino, F., 2018. A scalable method to improve gray matter segmentation at ultra high field MRI. PloS one 13, e0198335. https://doi.org/10.1371/journal.pone.0198335
• Gulban, O.F., Stirnberg, R., Tse, D.H.Y., Pizzuti, A., Koiso, K., Archila-Melendez, M.E., Huber, L., Bollmann, S., Goebel, R., Kay, K., Ivanov, D., 2025. In vivo reconstruction of Duvernoy’s postmortem vasculature images. https://doi.org/10.1101/2025.03.23.644588
• Strevens, M., 2020. The Knowledge Machine: How Irrationality Created Modern Science, 1st ed. ed. Liveright Publishing Corporation, Erscheinungsort nicht ermittelbar.

Thanks

I thank Satrajit Ghosh, Peter Bandettini, and Mallar Chakravarty for inviting and encouraging me to write this article for Aperture Neuro “The Future of Scientific Publishing” special issue. In addition, I thank to Justine Ziolkowski and Renzo Huber for guiding me with the submission procedure. I also thank Felix Duecker for organizing the ABCN meetings at the Cognitive Neuroscience Department of Maastricht University, where my early ideas behind this piece first took shape and received valuable feedback on February 2025.

Visuals

• Wiliam Caxton showing specimens of his printing to King Edward IV and his Queen

Visuals that are not referenced above have been created by the author and licensed under CC BY 4.0.