Neuroscience is a field most obviously associated with medicine and/or psychology. However, my background in physics and computer science enables me to explore, and further understand, how the brain computes and stores information, identifying the underlying physical mechanisms and the interplay between them.
My longstanding work with Professor Friedemann Pulvermüller from the Freie Universität Berlin seeks to answer a number of questions, primarily how are little children able to quickly interlink signs with meanings while our closest relatives in the animal kingdom struggle to do so? In order to find answers, we work with neural network models that we compare with brain-imaging experiments.
These neural models are potential tools for improving our understanding of complex brain functions, and it is a main argument in our new Nature Reviews Neuroscience paper that they need to be neurobiologically realistic to cover the complexity of brain function; models too simple may miss relevant aspects and mechanisms.
Neural network models of the future – the key to unlocking how our brain works
Dr Thomas Wennekers has co-authored a perspectives paper for ‘Nature Reviews Neuroscience’ on the future of neural network models
