Important paper from Tsvetanov, Cam-CAN et al. on vascular effects in aging in a sample of 335 subjects.
The scaling analysis revealed that much of the effects of age on task-based activation studies with fMRI do not survive correction for changes in vascular reactivity, and are likely to have been overestimated in previous fMRI studies of ageing.
New paper from Kenny Vaden and the Eckert lab on spoken word recognition in older adults implicating the cingulo-opercular network in correct recognition.
Great introduction to the Unix/OS X $PATH variable (and the command line) from A List Apart.
The command line is inherently spooky to many people—it’s the arcane technology wielded by “hackers” and “computer wizards” in popular culture. In reality, though, it isn’t that cool. It’s a set of ridiculously simple tools created by Bell (now AT&T) employees to accomplish mostly simple tasks in the 1970s. It’s about as “space-age” as your microwave oven.
It’s also extremely useful—like going from building a house by hand to using power tools. And through a few concepts and metaphors, we can shine a light on the darkest corners of this command line.
Semantic associations affect MMN responses to consolidated newly-learned words.
Review on the application of graph theory and connectivity in the context of brain disease. I'm not yet convinced but it's an interesting idea.
Lots of great advice in the form of reflections—these ring true to me.
7 Be willing to take on tasks you’re not sure you’re completely qualified to do.
If you never do this, not only will you not discover what your strengths are but you also won’t ever acquire these additional skills. Should I be apologetic that the first Research Council committee I chaired I didn’t know what a lot of the acronyms meant when I first sat down to read the applications? No, I don’t think so.
There are more issues at stake than "just" senior vs. junior researchers.
What they are not-proposing here is to create a mechanism aimed at the most demographically homogenous group of researchers...[S]uddenly we may have a very direct new mechanism that, regardless of the underlying logic, is essentially un-diversity.
Is laminar imaging the next frontier in human neuroimaging?
The Enigma machine and de Bruijn sequences inform neuroscience analyses, including quotes from Josh Gold and Geoff Aguirre.
The Penn scientists have taken their cues from a 73-year-old algorithm that British code-breaker Alan Turing used to read secret German messages during World War II, and a mathematical sequence more famously used to break into digital keypad locks on cars.
Link is to the 2014 schedule, but presumably similar this year. Looks like a great lineup.
Commentary from Datahound.
(1) This problem already has a solution. An investigator can (with approval from the relevant IC) name a new Principal Investigator for a grant. Assuming the PI is qualified and NIH approves, this is an effective transition strategy that has been used many times.
(2) For most research programs, is "succession planning" something that NIH staff are worried about? Given that many investigators train numerous younger scientists over the course of their careers and that the system is currently flooded with accomplished younger scientists, the solution to this problem without any mechanism seems to be at hand.
(3) Even proposing such a mechanism seems quite inappropriate and tone deaf at this juncture when so many younger scientists are struggling to establish and maintain their careers.
If money were flowing freely, there may be some positive things coming out of this iniative. But in the "current funding climate" I don't see how this is helpful.
This is a great course, and Edinburgh is a great city.
New this year: There is a first day for "absolute beginners" that includes introduction to what MRI measures, and Matlab basics. I've always thought that every brain imaging course should be couple with intro to programming.
Helpful visualization from Felix Schönbrodt.
To summarize: Whether a strong evidence “hits you between the eyes” depends on many things – the kind of test, the kind of visualization, the sample size. Sometimes a BF of 2.5 seems obvious, and sometimes it is hard to spot a BF>100 by eyeballing only. Overall, I’m glad that we have a numeric measure of strength of evidence and do not have to rely on eyeballing only.
Great information here.
Statistical methods have been under increasing scrutiny in the past few years. I encourage the field to put the acquisition and pre-processing steps under the same microscope. If that means you make your MRI physicist squeal, so be it.
Alpha oscillations, listening effort, and age from the Obleser lab.
Negative Results: Research papers from authors who tried to test important hypotheses but did not get the outcome they expected. Failed preclinical tests are particularly welcome. These manuscripts must include testing the hypothesis by multiple experimental approaches, rigorously reproducing the experimental models of others that you claim to refute, and meticulous use of both positive and negative controls.
Failure to Replicate: Research papers from authors who could not reproduce someone else’s work of significant importance despite using the same methodology (explaining why the reproduction failed is not mandatory).
Refreshing.
(I'm not a big fan of media-specific journal titles like eLife or eNeuro—it's not like we have printJournal of Neuroscience—but I do like some of the changes they are instituting.)
UPDATE: Greg Hickok confirms that Psychonomic Bulletin and Review also encourages negative results (although this isn't spelled out on their website). Is there a central list of "journals that are happy to publish your negative results"?
A good list here spanning many areas of neuroscience. Add yourself if you are a female neuroscientist, and use as a resource if you are putting together a symposium or speaker series and find yourself with fewer than 50% females on your list.
In this sample, several women were labeled "abrasive". Surprisingly the number of abrasive men was 0.
Compares various automated TIV-calculation routines to the "gold standard" of manual tracing. Freesurfer and SPM12 do well; SPM8 does poorly. Although the paper focuses on TIV, the results suggest SPM12 segmentation is better overall.
Put together by Greg Hickok for a graduate seminar - lots of excellent articles here.
Jonathan Peelle, PhD
CV: PeelleCV.pdf | Google Scholar profile
Lab: peellelab.org
Office: ISEC 320
E-mail: j.peelle123@northeastern.edu(without the 123)
Mastodon: @jpeelle@neuromatch.social
("Peelle" sounds like "peel". I blame my ancestors for the extra letters.)