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Development of a computational model of the human somatosensory nerves for stimulation and recording
Our previous studies has identified that the nature of signals recorded with electrodes implanted in the peripheral nervous system strongly depends on the type of electrode and the degree of activity inside the nerve. For this project your aim will be to further explore which dimension of a population activity a given type of electrode can identify. Based on the literature you will identify discharge patterns combination permitting to recreate the main different classes of bio-plausible population activity. You will also complete the existing hybrid model to integrate the main kinds of electrodes used with neural interfaces (use of Solidworks, Matlab, and Comsol).
You will then implement your bio-mimetic population activity in the full model and study each electrode’s dynamic selectivity. Your final goal would be to establish rules permitting to classify from the recording alone what “family” of activity is happening in the nerve.
Neuroprostheses based on electrical stimulation
are becoming a therapeutic reality, dramatically improving
the life of disabled people. They are based on
neural interfaces that are designed to create an intimate
contact with neural cells. These devices speak the language
of electron currents, while the human nervous system uses
ionic currents to communicate. A deep understanding of
the complex interplay between these currents, during the
electrical stimulation, is essential for the development of
optimized neuroprostheses. Neural electrodes can have
different geometries, placement within the nervous system,
and the stimulation protocols (paradigms of use). This
high-dimensional problem is not tractable by an empiric,
brute-force approach and should be tackled by exact
computational models, making use of our accumulated
knowledge. In pursuit of this goal, a hybrid finite element
method—NEURON modeling—is used for a solution of electrical
field generated by stimulation, within the different neural
structures having anisotropic conductivity, and a corresponding
neural response computation.
Neuroprostheses based on electrical stimulation are becoming a therapeutic reality, dramatically improving the life of disabled people. They are based on neural interfaces that are designed to create an intimate contact with neural cells. These devices speak the language of electron currents, while the human nervous system uses ionic currents to communicate. A deep understanding of the complex interplay between these currents, during the electrical stimulation, is essential for the development of optimized neuroprostheses. Neural electrodes can have different geometries, placement within the nervous system, and the stimulation protocols (paradigms of use). This high-dimensional problem is not tractable by an empiric, brute-force approach and should be tackled by exact computational models, making use of our accumulated knowledge. In pursuit of this goal, a hybrid finite element method—NEURON modeling—is used for a solution of electrical field generated by stimulation, within the different neural structures having anisotropic conductivity, and a corresponding neural response computation.
Recommendable Skills: MATLAB, Solidworks and COMSOL, NEURON.
Time effort required: Master project full time
Recommendable Skills: MATLAB, Solidworks and COMSOL, NEURON. Time effort required: Master project full time
Dr. Giacomo Valle, Assistant Professor, Head of Neural Bionics laboratory, Chalmers University of Technology, Goteborg Sweden
Email: valleg@chalmers.se
Dr. Giacomo Valle, Assistant Professor, Head of Neural Bionics laboratory, Chalmers University of Technology, Goteborg Sweden Email: valleg@chalmers.se
