A dynamical model for generating synthetic data to quantify active tactile sensing behavior in the rat

Nadina O. Zweifel, Nicholas E. Bush, Ian Abraham, Todd D. Murphey, Mitra J.Z. Hartmann*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


As it becomes possible to simulate increasingly complex neural networks, it becomes correspondingly important to model the sensory information that animals actively acquire: the biomechanics of sensory acquisition directly determines the sensory input and therefore neural processing. Here, we exploit the tractable mechanics of the well-studied rodent vibrissal (“whisker”) system to present a model that can simulate the signals acquired by a full sensor array actively sampling the environment. Rodents actively “whisk” ∼60 vibrissae (whiskers) to obtain tactile information, and this system is therefore ideal to study closed-loop sensorimotor processing. The simulation framework presented here, WHISKiT Physics, incorporates realistic morphology of the rat whisker array to predict the time-varying mechanical signals generated at each whisker base during sensory acquisition. Single-whisker dynamics were optimized based on experimental data and then validated against free tip oscillations and dynamic responses to collisions. The model is then extrapolated to include all whiskers in the array, incorporating each whisker's individual geometry. Simulation examples in laboratory and natural environments demonstrate that WHISKiT Physics can predict input signals during various behaviors, currently impossible in the biological animal. In one exemplary use of the model, the results suggest that active whisking increases in-plane whisker bending compared to passive stimulation and that principal component analysis can reveal the relative contributions of whisker identity and mechanics at each whisker base to the vibrissotactile response. These results highlight how interactions between array morphology and individual whisker geometry and dynamics shape the signals that the brain must process.

Original languageEnglish (US)
Article numbere2011905118
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number27
StatePublished - Jul 6 2021


  • Neuromechanics
  • Sensorimotor systems
  • Synthetic data
  • Touch
  • Vibrissae

ASJC Scopus subject areas

  • General


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