Towards a Material Basis for Symbols
Cluster Members and Researchers at University of Plymouth Use Novel Network Models for Understanding the Human Ability to Manipulate Symbols and Language
The paper »Biological Constraints on Neural Network Models of Cognitive Function« is one of the first key outputs from a recently initiated Advanced Grant funded by the European Research Council called Material Constraints Enabling Human Cognition (MatCo, ERC-2019-ADG 883811). In this project and in the Cluster of Excellence »Matters of Activity. Image Space Material«, Pulvermüller and his team are now systematically approaching material-based answers to questions such as the following: How can humans learn a vocabulary of 10,000s of words whereas our closest relatives are normally stuck with 10s? How is it possible that little children quickly interlink signs with meanings, upon only one experience in the extreme, although our closest relatives have great difficulty building such links and neural networks require excessive time for learning them? By which mechanisms can we build abstract concepts and what contribution (if any) makes language to this process? (… and many others)
Contact
Prof. Dr. Dr. Friedemann Pulvermüller
Dr. Rosario Tomasello
Links
Brain Language Laboratory at the Freie Universität: https://www.geisteswissenschaften.fu-berlin.de/v/brainlang/research/Current-Research/MatCo-Project/index.html
Pulvermüller, F., Tomasello, R., Henningsen-Schomers, M. R., & Wennekers, T. (2021). Biological constraints on neural network models of cognitive function. Nature Reviews Neuroscience, doi: 10.1038/s41583-021-00473-5.
https://www.nature.com/articles/s41583-021-00473-5