Enhancing neuroprosthetics and neurorobotics with insights from touch mechanoreceptor encoding in humans.

The NeuroSchool PhD Program of Aix-Marseille University (France) has launched its annual calls for international co-supervised PhDs.

The call for international co-supervised PhDs aims to provide an exceptional opportunity for talented young researchers to have an international doctoral training. The candidates may be local (AMU master’s student) or external (from other French or foreign universities). 

This project is one of the two proposed projects. Check our website for details.

State of the art: Touch feedback from the hands is vital for object manipulation and texture perception, playing a central role in our everyday lives. In hand amputation, individuals lose an important means of interaction, where research is critical to understand fundamental touch function and apply this in prosthetics.

Objectives: The PhD aims to develop advanced neural decoding algorithms and feedback systems, bridging the gap between biological touch perception and artificial systems, to enhance the usability of neuroprosthetics and dexterity in robotics. We will develop decoding algorithms to interpret spiking patterns from single human mechanoreceptors. From this, we will implement real-time feedback systems that translate the tactile information into sensations, such as vibration or force, enhancing precision and usability by simulating natural touch.

Methods: Single unit recordings of mechanoreceptors from the median nerve of the hand, via microneurography in humans, will be obtained and modeled by adaptive machine learning. We will use different vibration frequencies and forces to modulate mechanoreceptor firing and relate this to intensity perception of the stimulation, to link neuronal firing with the judgement of the sensation.

Expected results: The data from modulating mechanoreceptor firing will give insights into how the main four types of touch receptor encode a range of vibration and pressure stimuli, which will be modeled to output standardized algorithms that represent such feedback. The developed neural decoding models will establish a new standard for real-time tactile feedback systems. This will enhance neuroprosthetics, where improved feedback will enable users to perform tasks with greater precision and naturalness, via electrical stimulation or mechanical stimulation of the stump. Robotic system improvements will allow human-like dexterity, to adapt robot grip and movements based on tactile data.

Feasibility: The project focuses solely on humans, where ethical approval is in place to via CPP ID-RCB: 2021-A01604-37 for microneurography and perception experiments (valid until 2033).

Complementarity of the two laboratories: The CRPN in Marseille is centered on fundamental and applied research in neuroscience and psychology, where the Somatosense team works on human touch encoding and perception. The Bristol Robotics Lab at the University of Bristol is focused on the application of robotics, such as advancing dexterity with robotic hands. The two labs are highly complementary, where human neurophysiology meets robotic engineering, to create new fundamental touch knowledge, as well as innovative and advanced solutions in neuroprosthetics.

Within Aix Marseille Université, NeuroMarseille brings together 8 research laboratories and NeuroSchool, a graduate school in neuroscience, to increase the attractiveness of the university, international collaborations, interdisciplinarity, links with the clinical and industrial worlds and the integration of students into professional life. 

Launched in July 2018, NeuroSchool unifies and harmonizes the training of the third year of the Bachelor of Life Sciences (Neuroscience track), the Master's and the PhD in Neuroscience. 

• Master's degree from a non-French university in neuroscience or related field
• Fluent in English

The candidate should have a strong background in (1) computer programming (e.g. Python), (2) signal processing, (3) data science (e.g. machine learning), and (4) an understanding of neuroscience (e.g. touch system).