We addressed this limitation by generating probabilistic maps of visual topographic areas in 2 standardized spaces suitable for use with adult human brains. Using standard fMRI paradigms, we identified 25 topographic maps in a large population of individual subjects (N = 53) and transformed them into either a surface- or volume-based standardized space. Here, we provide a quantitative characterization of the inter-subject variability within and across visual regions, including the likelihood that a given point would be classified as a part of any region (full probability map) and the most probable region for any given point (maximum probability map).
Early parallel activation of semantics and phonology in picture naming using multiple linear regression→
/Nice methods demonstration.
We here used a multiple linear regression approach to magnetoencephalography (MEG) analysis of picture naming in order to investigate early effects of variables specifically related to visual, semantic, and phonological processing. This was combined with distributed minimum-norm source estimation and region-of-interest analysis. Brain activation associated with visual image complexity appeared in occipital cortex at about 100 ms after picture presentation onset. At about 150 ms, semantic variables became physiologically manifest in left frontotemporal regions. In the same latency range, we found an effect of phonological variables in the left middle temporal gyrus. Our results demonstrate that multiple linear regression analysis is sensitive to early effects of multiple psycholinguistic variables in picture naming.
A voluntary commitment to research transparency→
/A great start.
Beyond these already beneficial changes, we asked ourself: What can we do on the personal and local department level to make more published research true?
Negotiating with publishers for immediate self-archiving→
/I'm surprised this was so easy.
After that everything was simple. I logged in to my zenodo.org account and uploaded the author’s copy of the manuscript. As a result, anyone searching for the article on google scholar will find the publisher’s version requesting 34.95 EUR for pdf access, and right next to it a link to exactly the same article freely available via Zenodo. That’s it! Nice and clean!
Comprehensive introductory R material by Paul Hiemstra→
/I've only had a quick peak but this looks great.
Interview with Jonathan Eisen on gender balance in science→
/In addition, there are a large number of ways implicit biases (i.e., those that are not necessarily purposefully trying to be biased against women) affect women’s careers in science. For example, since women on average tend to be more responsible for child care in families with children, lack of support for childcare in various venues has a disproportional effect on women. One classic example of implicit bias is in the discussion and recognition of scientists in the media, popular press, and in various related activities. For various reasons, the work on male scientists is overrepresented in such promotional actions.
Great post from Michael Frank on improving reproducibility in science →
/Hard to argue with any of these suggestios.
2. Everything open by default. There is a huge psychological effect to doing all your work knowing that everyone will see all your data, your experimental stimuli, and your analyses. When you're tempted to write sloppy, uncommented code, you think twice. Unprincipled exclusions look even more unprincipled when you have to justify each line of your analysis.** And there are incredible benefits of releasing raw stimuli and data – reanalysis, reuse, and error checking. It can make you feel very exposed to have all your experimental data subject to reanalysis by reviewers or random trolls on the internet. But if there is an obvious, justifiable reanalysis that A) you didn't catch and B) provides evidence against your interpretation, you should be very grateful if someone finds it (and even more so if it's before publication).
Awesome AMA from The Winnower from researchers living in Antarctica→
/Fascinating.
WHAT'S THE BACKUP PLAN FOR IF THE HEATER FAILS?
Dissociable roles for frontoparietal and cingulo-opercular networks in working memory→
/In our task, spatial cues indicating the relevant item in a WM array occurred either before the memory array or during the maintenance period, providing a direct comparison between prospective and retrospective control of WM. We found that in both cases a frontoparietal network activated following the cue, but following retrocues this activation was transient and was succeeded by a cingulo-opercular network activation.
fMRI activations in inferior temporal lobe during intelligible speech comprehension→
/The aim of this study was to use intelligible and unintelligible (spectrally rotated) sentences to determine if the vATL could be detected during a passive speech comprehension task using a dual-echo acquisition. A whole brain analysis for an intelligibility contrast showed bilateral superior temporal lobe activations and a cluster of activation within the left vATL.
In vivo mapping of human spinal cord microstructure at 300mT/m→
/Impressive technical demonstration of spinal cord imaging with MRI.
Measuring directionality between neuronal oscillations of different frequencies→
/This measure is based on the phase-slope index (PSI) between the phase of slower oscillations and the power envelope of faster oscillations. Further, we propose a randomization framework for statistically evaluating the coupling measures when controlling for multiple comparisons over the investigated frequency ranges. The method was firstly validated on simulated data and next applied to resting state electrocorticography (ECoG) data. These results demonstrate that the method works reliably. In particular, we found that the power envelope of gamma oscillations drives the phase of slower oscillations in the alpha band.
Rapid and automatic speech-specific learning mechanism in human neocortex→
/We found a robust index of neurolexical memory-trace formation: a rapid enhancement of the brain's activation elicited by novel words during a short (~ 30 min) perceptual exposure, underpinned by fronto-temporal cortical networks, and, importantly, correlated with behavioural learning outcomes. Crucially, this neural memory trace build-up took place regardless of focused attention on the input or any pre-existing or learnt semantics.
Time-of-day effects in brain volume (brain volumes are larger in the morning) (!) →
/There was a statistically significant effect of time-of-day on the BPF change in MS clinical trial datasets (− 0.180 per day, that is, 0.180% of intracranial volume, p = 0.019) as well as the ADNI dataset (− 0.438 per day, that is, 0.438% of intracranial volume, p < 0.0001), showing that the brain volume is greater in the morning. Linearly correcting the BPF values with the time-of-day reduced the required sample size to detect a 25% treatment effect (80% power and 0.05 significance level) on change in brain volume from 2 time-points over a period of 1 year by 2.6%.
Identifying neuronal oscillations using rhythmicity→
/Here, we present lagged coherence, a frequency-indexed measure that quantifies the rhythmicity of neuronal activity. We use this method to identify the sensorimotor alpha and beta rhythms in ongoing magnetoencephalographic (MEG) data, and to study their attentional modulation. Using lagged coherence, the sensorimotor rhythms become visible in ongoing activity as local rhythmicity peaks that are separated from the strong posterior activity in the same frequency bands.
Inter-individual variability in cortical excitability and motor network connectivity following rTMS→
/We found that non-responders (subjects not showing an MEP increase of ≥ 10% after one iTBS block) featured stronger rsFC between the stimulated primary motor cortex (M1) and premotor areas before stimulation compared to responders. However, only the group of responders showed increases in rsFC and MEPs, while most non-responders remained close to baseline levels after all three blocks of iTBS. Importantly, there was still a large amount of variability in both groups.
The Bayesian Reproducibility Project→
/Alexander Etz on why we need a better metric for "success" in reproducibility.
Based on these two metrics, the headlines are accurate: Over half of the replications “failed”. But these two reproducibility metrics are either invalid (comparing significance levels across experiments) or very vague (confidence interval agreement). They also only offer binary answers: A replication either “succeeds” or “fails”, and this binary thinking leads to absurd conclusions in some cases like those mentioned above. Is replicability really so black and white? I will explain below how I think we should measure replicability in a Bayesian way, with a continuous measure that can find reasonable answers with replication effects near zero with wide CIs, effects near the original with tight CIs, effects near zero with tight CIs, replication effects that go in the opposite direction, and anything in between.
Daniel Lakens: Power of replications in the Reproducibility Project→
/Nice take.
For now, it means 35 out of 97 replicated effects have become quite a bit more likely to be true. We have learned something about what predicts replicability. For example, at least for some indicators of replication success, “Surprising effects were less reproducible” (take note, journalists and editors of Psychological Science!). For the studies that did not replicate, we have more data, which can inform not just our statistical inferences, but also our theoretical inferences. The Reproducibility Project demonstrates large scale collaborative efforts can work, so if you still believe in an effect that did not replicate, get some people together, collect enough data, and let me know what you find.
Working too hard is counterproductive→
/Interesting read, and I did not know that about Henry Ford.
Many people believe that weekends and the 40-hour workweek are some sort of great compromise between capitalism and hedonism, but that’s not historically accurate. They are actually the carefully considered outcome of profit-maximizing research by Henry Ford in the early part of the 20th century. He discovered that you could actually get more output out of people by having them work fewer days and fewer hours. Since then, other researchers have continued to study this phenomenon, including in more modern industries like game development.
The research is clear: beyond ~40–50 hours per week, the marginal returns from additional work decrease rapidly and quickly become negative. We have also demonstrated that though you can get more output for a few weeks during “crunch time” you still ultimately pay for it later when people inevitably need to recover. If you try to sustain crunch time for longer than that, you are merely creating the illusion of increased velocity. This is true at multiple levels of abstraction: the hours worked per week, the number of consecutive minutes of focus vs. rest time in a given session, and the amount of vacation days you take in a year.
