🚨 New Preprint Alert 🚨Non-Human Recognition of Orthography: How is it implemented and how does it differ from Human orthographic processing https://www.biorxiv.org/content/10.1101/2024.06.25.600635v1 Combining behavioral data from Humans/Baboons/Pigeons with a computational model for neuro-cognitive phenotyping

The German Word Nerd 🤓Network got DFG funding! 🎉 We plan to build a Transparent, Transferable, and Sustainable Foundation for Psycholinguistic Reading Studies in German (TRUST). More info here: https://sites.google.com/view/gewonn/home If you want to get involved, get in contact!

The German Word Nerd 🤓Network got DFG funding! 🎉 We plan to build a Transparent, Transferable, and Sustainable Foundation for Psycholinguistic Reading Studies in German (TRUST). More info here: https://sites.google.com/view/gewonn/home If you are interested, get in contact!

Remember, if you want to join, there are only a few days left to register for the International Meeting on Quantifying Semantic-Orthographic Regularities Across Languages. Spots are filling up fast! https://sites.google.com/view/gewonn/events/quasemo-2024

Our International Meeting on Quantifying Semantic-Orthographic Regularities Across Languages (QuaSemO), happening from 7th-9th October 2024 in Munich, is open for registration! We have an amazing line-up of speakers! Check out our webpage: https://sites.google.com/view/gewonn/events/quasemo-2024

Das Training von Gehirnprozessen macht Lesen effizienter
Studie zeigt, dass eine Kombination von Computermodellierung und Künstlicher Intelligenz die Leseleistung beim Erlernen von Sprachen verbessert / Veröffentlichung in „npj Science of Learning“...
https://nachrichten.idw-online.de/2024/04/18/das-training-von-gehirnprozessen-macht-lesen-effizienter

🧠📚 Neue Studie: Gehirntraining verbessert Lesefähigkeit!
💬 Aktuelle Forschung der Uni Würzburg und @bg #UniKoeln zeigt, wie Kombinationen von Computermodellierung und KI das Sprachenlernen revolutionieren 🚀
Die Unterscheidung von bekannten und unbekannten Wörtern kann trainiert werden, was zu effizienterem Lesen führt.

Mehr dazu ➡️ https://uni.koeln/YCHPU

🧠📚 New Study: Brain Training Enhances Reading Ability!
Recent research from @bg #UniCologne and the University of Würzburg reveals how combinations of computer modelling and AI are revolutionizing language learning. 🚀 Distinguishing between familiar and unfamiliar words can be trained, leading to more efficient reading.

Read more ➡️ https://uni.koeln/QFFER

It's out now—so much work combining years of work! The project started with a hunch and grew into a huge project, including multiple training studies and a diagnostic approach that is likely applicable in the real world. Thanks to Klara and everyone else involved.

#reading #langage #learning

https://link.springer.com/article/10.1038/s41539-024-00237-7?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20240410&utm_content=10.1038/s41539-024-00237-7

@ShravanVasishth of course ... thanks for pointing out

this one should work: https://link.springer.com/article/10.1038/s41539-024-00237-7?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20240410&utm_content=10.1038/s41539-024-00237-7

🚨🚨NEW PREPRINT 🚨🚨 "Investigating lexical categorization in visual word recognition based on a joint diagnostic and training approach for language learners." https://psyarxiv.com/rs6gy/
We designed a training program including a machine learning-based diagnostic approach to train lexical categorization optimally, i.e., the process most likely implemented in the visual word form area (https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009995). 1/N

SAVE THE DATE!
We’re organizing an international meeting on quantifying #orthographic-#semantic regularities across #languages! More details to follow, but we already know the dates (7th-9th of October), location (#Munich, Germany), and have a line-up of amazing guest speakers, including Simona Amenta, Kevin Brown, Dave Kenneth Cayado, Davide Crepaldi, Katrina Dulay, Fritz Günther, Jay Rueckl, Olivera Savic, and Noam Siegelman.

🚨New Preprint🚨 We developed a new version of the orthographic prediction error (oPE) and found that the representation increases in precision over time. We found that the newly developed oPE representation better explained late EEG time windows and behavior. Also, allowed better ResNet18 performance. https://www.biorxiv.org/content/10.1101/2024.02.29.582776v1.full.pdf

🚨New Preprint🚨 We developed a new version of the orthographic prediction error (oPE) and found that the representation increases in precision over time. We found that the newly developed oPE representation better explained late EEG time windows and behavior. Also, allowed better ResNet18 performance. https://www.biorxiv.org/content/10.1101/2024.02.29.582776v1.full.pdf

This https://scholar.social/@bg/110751498157147277 just got accepted in npj Science of Learning!

Der neue DEAL mit Elsevier ist opt-in: wenn nicht genügend Institutionen zeichnen, kommt er nicht zustande.

Das bedeutet, dass wir am 15. Januar wissen, ob sich unsere wissenschaftlichen Institutionen auf die Seite der Konzerne, oder auf die Seite der Wissenschaft schlagen:

https://www.faz.net/aktuell/wissen/forschung-politik/wissenschaftliche-grossverlage-wissenschaftliche-grossverlage-19344181.html

Die Datenlage und daher auch die Expertenmeinung ist eindeutig: das ist kein guter DEAL für die Wissenschaft, Elsevier ist der Hauptprofiteur von diesem Vertrag.

#openaccess #openscience

Want to work with me? We just got a DFG Project funded in which we build and evaluate transparent Computer vision models for reading and visual word recognition. If you are interested or you know someone that might, write me a note!!!

New #preprint about our experiences offering 'reproducibility as a service' for a six month period: https://psyarxiv.com/k8d4u/

We made 10 papers #reproducible from @YorkPsychology covering a wide range of study designs, supported by funding from Research England 1/6

Each scientific paper should come with a special section “all that failed beforehand”.

Sometimes I think about all the knowledge lost and the time wasted because we are not doing that… (yet) 😣

#Academia #Neuroscience but also all other types of #Research

New preprint: Can we utilize Large Language Models (LLMs) to generate useful linguistic corpora? A case study of the word frequency effect in young German readers

DOI: https://doi.org/10.31234/osf.io/gm9b6 (open access preprint on PsArXiv)

Together with Benjamin Gagl (https://scholar.social/@bg, ORCID: https://orcid.org/0000-0002-2339-6293)
Nicole Marx (ORCID https://orcid.org/0000-0002-7027-0618)