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Emulating skin biomechanics through GelSight: neural mechanisms of tactile texture perception
The project consists in assessing the degree to which our perception of natural texture is shaped by the mechanics of the skin. We have implemented an approach, developed by Ted Adelson at MIT (GelSight), that consists of fabricating a gel whose material properties match those of the skin and then imaging (using a laser profilometer) the pattern of deformation on the surface of the gel that is produced when pressed against the surface. We can then estimate how the skin would be deformed by any given texture using this approach and assess whether we can better predict from these patterns of skin deformation the responses of tactile nerve fibers to that texture and the perception thereof.
We showed that the high-frequency components of a texture are preferentially filtered out by the skin. Furthermore, the pattern of skin deformation produced by some textures, particularly textures with highly compliant elements, is almost completely unpredictable from the profile of the texture itself. We are now comparing the predictions of our in-silico model (TouchSim) and Gelsight with nerve recording during realistic texture scans in primates. These preliminary findings are very promising and likely to lead to important insights into tactile texture perception.
We showed that the high-frequency components of a texture are preferentially filtered out by the skin. Furthermore, the pattern of skin deformation produced by some textures, particularly textures with highly compliant elements, is almost completely unpredictable from the profile of the texture itself. We are now comparing the predictions of our in-silico model (TouchSim) and Gelsight with nerve recording during realistic texture scans in primates. These preliminary findings are very promising and likely to lead to important insights into tactile texture perception.
The major goals for the student will be:
- Is touch shaped by the biomechanics of the skin?
- Frequency components of textures in skin deformation (spatial/frequency filter?)
- Does the skin transform textures?
- How involved is skin biomechanics in neural encoding patterns?
- Compare simulated (TouchSim) neural response with nerve recordings.
- How are textures perceived? Predict from the textures the perception.
Recommendable skills: Signal processing, MATLAB, C++, C, peripheral nervous system neurophysiology and anatomy.
Extra skills: Computational neuroscience.
Time effort required: Master project full time.
The major goals for the student will be: - Is touch shaped by the biomechanics of the skin? - Frequency components of textures in skin deformation (spatial/frequency filter?) - Does the skin transform textures? - How involved is skin biomechanics in neural encoding patterns? - Compare simulated (TouchSim) neural response with nerve recordings. - How are textures perceived? Predict from the textures the perception. Recommendable skills: Signal processing, MATLAB, C++, C, peripheral nervous system neurophysiology and anatomy. Extra skills: Computational neuroscience.
Time effort required: Master project full time.
Dr. Giacomo Valle, Assistant Professor, Head of Neural Bionics laboratory, Chalmers University of Technology, Department of Electrical Eng., Life Bionics, Goteborg Sweden
Email: valleg@uchalmers.se
Dr. Giacomo Valle, Assistant Professor, Head of Neural Bionics laboratory, Chalmers University of Technology, Department of Electrical Eng., Life Bionics, Goteborg Sweden
