 Aperture Neuro (previously Aperture) is excited to announce its first published Research Object and the launch of a new open-source publishing platform, Kotahi (a Coko Community product).
It has been one year since Aperture Neuro, the new open-access publishing platform powered by the Organization for Human Brain Mapping, officially opened for submissions. In that time, 20 Research Objects have been submitted and reviewed, and four of those have already been accepted for publication. More Research Objects are currently being revised and reviewed and we look forward to announcing more published Research Objects in the near future. With this launch, we wanted to highlight the first Aperture Neuro publication, share some of the exciting features of the new platform, review the types of Research Objects authors can submit, and discuss the ways OHBM members can support this exciting initiative.
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By Peter Bandettini
Episode produced by Kevin Sitek and Rachael Stickland
S2 Ep5: Jack Gallant, Strong opinions about fMRI analysis
MRI is ultimately about separating a known but variable signal from highly variable noise. How one does this makes all the difference, and fMRI is particularly challenging since what is signal and what is noise is not always clear as they both vary in time and space. Jack is a huge proponent of fMRI encoding or, more generally, careful model building to probe the time series, and he thinks that more model-free approaches and paradigm-free methods are ultimately limited. The discussion gets technical as well as intense at times. The points he makes are important. While we agreed most of the time, there were some nuanced differences of opinion - mostly when it came to discussing alternative methods for probing fMRI data. Overall, it was a fun and hopefully useful discussion! What does come through is his passion for what he does. Given that we only barely got into my questions, we scheduled a follow-up conversation with him.
S2 Ep6: Jack Gallant, Deriving fundamentals of brain organization with fMRI
The first podcast with Jack delved so deeply into his approach to assessing fMRI data and his philosophy of doing good science that we really didn’t get a chance to talk about either his groundbreaking results or what questions they open up. In this episode, we cover both of these topics in-depth. First, we discuss his fascinating and potentially paradigm shifting results on widely-distributed, semantic maps in the brain that shift and warp depending on the task itself. These results, at least in my opinion, open up new avenues for insight into fundamentals of brain organization. The brain is not just a conglomeration of distinct and static modules, but a shifting landscape of representation, much of which may be shaped primarily by our experience in the world. How our attention shifts these landscapes is an open and potentially profound question. Here we also discuss prospects for layer fMRI as well as the challenges of clinical MRI. It was a rich and engaging discussion with one of the true luminaries in the field.
About the guest:
Jack Gallant, Ph.D. is a neuroscientist and engineer at heart who trained with David Van Essen at Wash U. He is currently a Chancellor’s Professor of Psychology and Class of 1940 Endowed Chair at UC Berkeley and is affiliated with the Department of Electrical Engineering and Computer Science. He is also affiliated with the graduate programs in Bioengineering, Biophysics, Neuroscience and Vision Science. His work spans from single unit recordings, to whole brain fMRI, embracing the whole of computational neuroscience, setting extremely high standards, technical rigor, creativity, and insight.
By Peter Bandettini
Episode produced by Rachael Stickland and Anastasia Brovkin
AFNI is a major processing package used by brain mapping groups all over the world. It is nearly as old as fMRI itself and has been steadily growing in functionality as the field has evolved. Here we discuss how it all started as well as a few of the challenges of fMRI processing that have arisen over the years. Importantly, we explore the philosophy underlying a key tenet of AFNI development: the ability for researchers to drill down and look directly at the data. This emphasis on flexibly and efficiently visualizing the data at all processing steps not only guards against problematic data and hidden artifacts but is also a catalyst for new analysis ideas. We discuss a bit of the future of analysis and the bottleneck for clinical implementations.
It’s happened again. Summer (in the Northern hemisphere) has left us, and now we’re left with just memories of the balmier days of 2021. And with that, it’s a good time to reflect on the events of summer—and in particular OHBM2021. This was the second virtual edition of the annual OHBM meeting, with the online-only format offering unique challenges and opportunities. Considerable planning and effort from many teams of volunteers and OHBM staff members went into the development of the new platform—affectionately dubbed “Planet Brain” by past Chair Aina Puce. Leadership took the higher-risk path to work with a new-to-the-market and, critically, open-source vendor, Sparkle, in hopes of achieving a much more engaging virtual experience that captured more of the true OHBM meeting spirit. But how did you think it went? Here we summarize some results from the two surveys that were sent out, one to annual meeting attendees to gather information about their experience and another to OHBM members, whether they registered for the meeting or not, to find out their views on future meetings. We provide anonymized responses to the Annual Meeting Feedback survey, alternative visualizations, and an environment for their re-analysis at https://emdupre.github.io/ohbm2021-survey-feedback/
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