Thrilled to be at #ohbm presenting my latest work with @FlorAssaneo @davidpoeppel and F.Mantegna as well as our youngest lab member! Drop by poster #1055 to chat. Plus my new lab at @Georgetown is currently offering two fully funded postdoc positions🔥Come see me or message me
Joan Orpella retweeted
"Syllabic rhythm and prior linguistic knowledge interact with individual differences to modulate phonological statistical learning" sciencedirect.com/science/ar… New Cognition paper from @FlorAssaneo lab, with Ireri Gomez Varela @JOGBCN @PabloRiVi and me
Joan Orpella retweeted
Get in touch if you want to do a PhD with me!
Potential projects include (but not limited to):
- Individual differences in brain plasticity (in blindness and deafness)
- Cognitive and motor representations of actions (in people born without hands)
Joan Orpella retweeted
The robot wakes up and takes a deep breath - imagine this technology in 10 years teapawt.net/terrill/status/1466383…
Joan Orpella retweeted
Neuron
In vitro neurons learn and exhibit sentience when embodied in a simulated game-world
sciencedirect.com/science/ar…
Joan Orpella retweeted
The US high school graduating class of 2022 had the lowest average ACT score in more than three decades, marking the fifth year in a row that scores have been going down
cnn.it/3Vtr1wN
And very pleased to see the Poeppel Lab so well represented @SNLmtg!! Congrats @PhoebeHChen, @EchoLi1054, and @AriannaZuannazzi too! #SNL2022 @davidpoeppel
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Also super grateful for the opportunity to share our work on global motor inhibition responses preceding stuttered speech, wonderfully presented by Dr. Eric Jackson! Way to go @DrJacksonNYU! #SNL2022
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I *promise* to make a (short) thread asap about our very soon-to-be submitted speech imagery paper #SNL2022
Excited to share our latest preprint on the neural bases of stuttered speech! Thanks @GrahamFlick @FlorAssaneo @liinapy @davidpoeppel and @DrJacksonNYU for the great work! Short 🧵doi.org/10.1101/2022.08.02.5…
9. Remarkably, whether speech will be stuttered or fluent could be predicted from participants' beta power in the R-preSMA on a trial-by-trial basis.
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