Here’s a brand new PhD training opportunity, @dfg_public-funded, joint project of @ObleserLab at @UniLuebeck Germany, supervised by me, with star collaborator @GesaHartwigsen (@MPI_CBS) — starting next spring. Please be in touch. Please distribute widely. https://t.co/oTUEVVgQSG pic.twitter.com/L4DtFaqRJl
— Jonas Obleser (@jonasobleser) October 19, 2021
Very excited to announce that former Obleser lab PhD student Lea-Maria Schmitt with her co-authors *) is now out in the Journal Science Advances with her new work, fusing artifical neural networks and functional MRI data, on timescales of prediction in natural language comprehension:
*) Lea-Maria Schmitt, Julia Erb, Sarah Tune, and Jonas Obleser from the Obleser lab / Lübeck side, and our collaborators Anna Rysop and Gesa Hartwigsen from Gesa’s Lise Meitner group at the Max Planck Institute in Leipzig. This research was made possible by the ERC and the DFG.
Santa struck early this year: The Deutsche Forschungsgemeinschaft (DFG) has just granted AC head Jonas (University of Lübeck) and brain-stimulation wiz Gesa Hartwigsen (now a group leader at AC’s former institution, the MPI in Leipzig) a joint 3‑year grant, worth 371,000 € in total, on “Modulating neural network dynamics of speech comprehension: The role of the angular gyrus”. This project will build on Gesa and Jonas’ recent paper in Cortex on the topic. Thanks again to the funding body and the helpful reviewers!
Our newest member of the lab, post-doc Sarah Tune, just published a review article in the Journal of Neuroscience. The article appeared in the “Journal Club” section, where graduate students or post-docs are given the chance to write short review pieces.
Sarah and former UCI Brain Circuits colleague Salomi Asaridou comment on a recent TMS study by Davey et al. (2015) who investigated the role(s) of the middle temporal gyrus and angular gyrus in the encoding and retrieval of semantic information. Sarah and Salomi review and discuss some of the factors that limit the interpretation of rTMS-induced behavioral changes in semantic judgement tasks. Concluding, they argue that a focus on neural networks and mechanistic principles is key to understanding the neural implementation of semantic cognition.