Research Assistant Professor at the University of Minnesota 🧠
Minneapolis, MN
Joined April 2007
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Emily J. Allen, PhD retweeted
Scientific publishing norms were built for a world that no longer exists.
In this commentary, I argue that the future of scientific exchange may benefit from new channels of interaction and dissemination.
In a satirical commentary, @ofgulban examines the widening gap between traditional publication norms and emerging channels of science communication: doi.org/10.52294/001c.147146
@OHBM
#FutureofPublishing #SpecialIssue
Emily J. Allen, PhD retweeted
Congratulations to @Emsquem for receiving an Early Career Research Grant from NIDCD aiming to develop a reliable method for defining and parcellating auditory cortex in humans using cutting-edge techniques. buff.ly/47v5eed #UMNCLA #UMNProud
ALT Headshot of Dr. Emily Allen
This is the start of something big...
All NeuroImage and NeuroImage:Reports editors have resigned over the high publication fee, and are starting a new non-profit journal
imaging-neuroscience.org
This comes with great regret, and a huge amount of thought and discussion- please read announcement to get more details.
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Emily J. Allen, PhD retweeted
Had fun writing this News & Views piece for @NatureNeuro with @tommy_botch and @RobertsonNeuro on the Natural Scenes Dataset, a deep and rich new high-res fMRI resource from @cvnlab for studying the cognitive neuroscience of vision and memory nature.com/articles/s41593-0…
Emily J. Allen, PhD retweeted
Latest lab work in @NatureNeuro. The Natural Scenes Dataset, a deep (large-data-per-subject) 7T fMRI neuroimaging resource for vision and memory, coupled with optimized single-trial estimation methods. For people who are good with data. nature.com/articles/s41593-0…
It's here, it's finally here! Our Natural Scenes Dataset article is out in Nature Neuroscience today!! 🖼️👀🧠 🎉
The Natural Scenes Dataset (NSD), in which high-resolution (7T) #fMRI responses to tens of thousands of richly annotated natural scenes were measured while participants performed a continuous recognition task
New from @cvnlab @Emsquem @umnmedschool
go.nature.com/327oX6C
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Emily J. Allen, PhD retweeted
The Natural Scenes Dataset (NSD), in which high-resolution (7T) #fMRI responses to tens of thousands of richly annotated natural scenes were measured while participants performed a continuous recognition task
New from @cvnlab @Emsquem @umnmedschool
go.nature.com/327oX6C
jneurosci.org/content/featur…
Check out our featured article in the Journal of Neuroscience looking at representations of tonotopy and pitch in human auditory cortex using ultra-high field 7T fMRI 🧠🎶🌈
Emily J. Allen, PhD retweeted
#JNeurosci: Using 7T fMRI and a variety of sounds, Allen et al. @UMNews find evidence for tuning to simple frequency but also specific tuning for pitch, shedding new light on how higher-order sound features like pitch may be represented in the brain. jneurosci.org/lookup/DOI/10.…
ALT Feature maps reveal gradient reversals in all three dimensions. Unthresholded CF maps for the Feature Tuning Model for three individual participants and averaged across all participants (bottom right quadrant). Maps are shown on spherical cortical surfaces of the left and right hemispheres, respectively. Each row is the CF map for a given condition (pure tones, timbre, and pitch, respectively). White and black arrows indicate high (blue) and low (red) frequency regions, respectively, in the pure-tone conditions. Arrows are shown in the same anatomical locations for the timbre and pitch conditions for ease of reference.
Emily J. Allen, PhD retweeted
NSD is here. The massive 7T fMRI dataset is now freely available on Amazon S3. Published paper to come soon. Pre-print: biorxiv.org/content/10.1101/… More info: naturalscenesdataset.org
Emily J. Allen, PhD retweeted
Well, you know what? Wherever we are going, it is going to be amazing as long as we do it together! ✨ Thanks @OhbmOpen, @CNeuromod, @brainhackorg, @OHBM & all our wonderful community members! 💙
Join us today at 10am EST! Where is neuroimaging going: deeper, broader, or longer? And what is (should be) the role of the Community in shaping its future? 👇🏼 #ohbm2021 #brainhack
Just posted a photo @ St Paul, Minesota instagram.com/p/COjmuVBnB8j/…
I love this idea. teapawt.net/neuralreckoning/status…
Frustrated with journals, I've been tinkering with ideas for a better way to read papers than static/linear. I have a v0.1 demo - would be great to get feedback. Would you find something like this useful? What else should be included? More details in 🧵👇
thesamovar.github.io/notpape…
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Emily J. Allen, PhD retweeted
Getting data is one thing, analyzing data is another. The Naselaris Lab (naselarislab.net) and @cvnlab are looking for a postdoc to play with NSD. Computational modeling + big data. Contact us if interested.
I am thrilled to announce that a preprint for our extensive, high-quality, high-resolution, machine learning-friendly, 7T fMRI Natural Scenes Dataset (NSD) is now available! 🥳
NSD is coming. Massive 7T fMRI dataset (70,000+ COCO images shown to 8 humans) + resting-state and diffusion + new single-trial GLM methods + extensive data preparation = data mining and machine learning happiness. biorxiv.org/content/10.1101/…
New opinion piece with Thomas Naselaris and Kendrick Kay, "Extensive sampling for complete models of individual brains" is out now in Current Opinion in Behavioral Sciences! authors.elsevier.com/c/1cSvO…
For my birthday, I'm raising money for the American Indian Science And Engineering Society. Every little bit helps! facebook.com/donate/27327513…
