Biomechanical texture coding in rat whiskers
Abstract
Classically, texture discrimination has been thought to be based on ‘global’ codes, i.e. frequency (signal analysis based on Fourier analysis) or intensity (signal analysis based on averaging), which both rely on integration of the vibrotactile signal across time and/or space. Recently, a novel ‘local’ coding scheme based on the waveform of frictional movements, discrete short lasting kinematic events (i.e. stick-slip movements called slips) has been formulated. We performed biomechanical measurements of relative movements of a rat vibrissa across sandpapers of different roughness. We find that the classic global codes convey some information about texture identity, but are consistently outperformed by the slip-based local code. Moreover, the slip code also surpasses the global ones in coding for active scanning parameters. This is remarkable as it suggests that the slip code would explicitly allow the whisking rat to …
Wieland Brendel
Principal Investigator (PI)
Wieland Brendel received his Diploma in physics from the University of Regensburg (2010) and his Ph.D. in computational neuroscience from the École normale supérieure in Paris (2014). He joined the University of Tübingen as a postdoctoral researcher in the group of Matthias Bethge, became a Principal Investigator and Team Lead in the Tübingen AI Center (2018) and an Emmy Noether Group Leader for Robust Machine Learning (2020). In May 2022, Wieland joined the Max-Planck Institute for Intelligent Systems as an independent Group Leader and is now a Hector-endowed Fellow at the ELLIS Institute Tübingen (since September 2023). He received the 2023 German Pattern Recognition Award for his substantial contributions on robust, generalisable and interpretable machine vision. Aside of his research, Wieland co-founded a nationwide school competition (bw-ki.de) and a machine learning startup focused on visual quality control.