Scholar
Michael Wibral
Google Scholar ID: XjZ0RzMAAAAJ
Professor for Data Driven Analysis of Biological Networks, Georg-August University, Göttingen
Citations & Impact
Citations
8,178
H-index
45
i10-index
78
Publications
20
Co-authors
104
list available
Publications
Resume (English only)
Academic Achievements
- Successfully used measures of local information dynamics such as local active information storage and transfer to test predictive coding theories, to investigate altered information processing in schizophrenia and autism, and to obtain a better understanding of the information processing changes underlying the loss of consciousness in anesthesia.
Research Experience
- Currently, his group works on more advanced information measures that are tailored to detect predictive processing in an hypothesis-free way from neural data, on novel types of cortex-inspired deep neural networks with local information theoretic goal functions, and on the development and application of partial information decomposition to neural data.
Background
- A physicist working on solving neuroscience puzzles using information theoretic methods. Fascinated by information processing in the neocortex, where one highly conserved circuit scheme can support a variety of functions like signal detection, object perception, various forms of short and long term memory, executive functions, and motor control.
Miscellany
- Blog: https://mwibral.github.io
