Modelling and innovative optimization methods for sensory restoration

Performance site: Campus Biotech, Geneva

Possibility of remote projects

Background

Hybrid modeling (HM) is a modeling technique that aims at computing the response of a given population of neural cells subject to the forcing action of a field. We perform HM for peripheral nerve stimulation (PNS) computing the electric field imposed extracellularly to nerve fibers via finite element modeling (FEM) and then solving for fiber spiking via a dedicated neural simulator (e.g., NEURON). HM can serve both to optimize neuroprosthetic devices and stimulation routines and to understand basic phenomena relevant to peripheral nerve stimulation.

References:
– Raspopovic S., Capogrosso M., and Micera S., A computational model for the stimulation of rat sciatic nerve using a transverse intrafascicular multichannel electrode. IEEE Trans. Neural. Syst. Rehabil. Eng. 19(4), 2011.
– Raspopovic S., Petrini F. M., Zelechowski M., and Valle G., Framework for the Development of Neuroprostheses: From Basic Understanding by Sciatic and Median Nerves Models to Bionic Legs and Hands. Proceedings of the IEEE 105, 2017.
– McIntyre C. C., Richardson A. G., Grill W. M., Modeling the excitability of mammalian nerve fibers: influence of afterpotentials on the recovery cycle. Neurophysiol. 87(2), 2002.


General requirements:
– Basic programming in MATLAB;
– Basic programming in Python;
– Experience with NEURON is a plus;
– Experience with FEM software (e.g. COMSOL) is a plus;
– Experience with Jupyter Notebooks, Git and LaTeX is a plus.

Projects

Project description: C fibers play a key role both in tactile sensory feedback (they mediate thermo- and nociception) and in bioelectronic medicine (they constitute the majority of vagus nerve fibers). No mechanism exists for their selective stimulation because of them being small-caliber unmyelinated fibers. A compartmental model for C fibers exists, but extensive analyses about its characteristic response and appropriateness should be performed. Sympathetic nerve stimulation could consequently be studied computationally, and compared to somatic nerves. The possibility of selective stimulation of C fibers with ad-hoc stimulation waveforms should also be investigated. Such a stimulation paradigm could pave the way to a better embodiment of neuroprostheses.

Requirements:

  • Knowledge of Hodgkin-Huxley-like conductance-based neural models
  • Experience with NMODL is a plus.

Best for: Semester / master project (to be discussed)

Contact: [email protected]

References:

  • Sundt D., Gamper N., and Jaffe D. B., Spike propagation through the dorsal root ganglia in an unmyelinated sensory neuron: a modeling study. Neurophysiol. 114(6), 2015
  • Lubba C. H., Le Guen Y., Jarvis S., Jones N. S., Cork S. C., Eftekhar A., and Schultz S. R., PyPNS: Multiscale Simulation of a Peripheral Nerve in Python. Neuroinformatics 17(1), 2019

Project description: The generation of ad-hoc electric fields via multisite and multielectrode stimulation should be investigated. The number of electrodes to be implanted to achieve given selectivity specifications and their required relative position could be obtained. Furthermore, guidelines could be drawn to deal with the uncertainty intrinsic to surgical implantation and active site malfunctioning. Additionally, the application of different time-varying waveforms that exploit the time behavior of nerve fibers to obtain steering and selective activation of specific fiber subpopulations can be investigated.

Requirements:

  • Experience with non-convex optimization routines is a plus.

Best for: Semester / master project (to be discussed)

Contact: [email protected]

References:

  • Schiefer M. A., Triolo R. J., and Tyler D. J., A model of selective activation of the femoral nerve with a flat interface nerve electrode for a lower extremity neuroprosthesis. IEEE Trans. Neural. Syst. Rehabil. Eng. 16(2), 2008

Project description: Invasive neuroprosthetic devices cause intraneural geometry to change because of external mechanical stress (e.g., FINE) or tissue swelling (e.g., TIME). Additionally, the mechanical stress induced by an external device generates a cascade of immunohistochemical reactions leading to the formation of a gliotic scar, which modifies the shape of the stimulating electric fields in the intraneural environment. Thus affecting the selectivity properties of neuroprosthetic devices. Models for all of these effects should be studied, which describe reasonably well qualitative and quantitative observations about different foreign body reactions.

Requirements:

  • Experience with function fit routines is a plus;
  • Experience with dynamic systems is a plus.

Best for: Semester / master project (to be discussed)

Contact: [email protected]

References:

  • Schiefer M. A., Triolo R. J., and Tyler D. J., A model of selective activation of the femoral nerve with a flat interface nerve electrode for a lower extremity neuroprosthesis. IEEE Trans. Neural. Syst. Rehabil. Eng. 16(2), 2008
  • Wurth S., Capogrosso M., Raspopovic S., Gandar J., Federici G., Kinany N., Cutrone A., Piersigilli A., Pavlova N., Guiet R., Taverni G., Rigosa J., Shkorbatova P., Navarro X., Barraud Q., Courtine G., and Micera S., Long-term usability and bio-integration of polyimide-based intra-neural stimulating electrodes. Biomaterials 122, 2017.

Project description: Helmholtz reciprocity theorem can be employed to adapt the framework of HM for peripheral nerve stimulation to peripheral nerve recording. HM is used to weight the contribution of each fiber node to the total potential recorded from an electrode active site. The development of a point of conjunction of biomimetic fiber activity simulators and this abstract framework will pave the way for the optimization of recording neuroprosthetic devices (similarly to what has been done for stimulation). Additionally, it could even help to answer some fundamental questions on functional segregation and somatotopy in peripheral nerves. The model will be validated via microneurographic multi-unit recordings.

Requirements:

  • Experience with NEURON extracellular and xtra mechanisms is a plus;
  • Experience with Bensmaia’s TouchSim is a plus.

Best for: Semester / master project (to be discussed)

Contact: [email protected]

References:

  • Saal H. P., Delhaye B. P., Rayhaun B. C., and Bensmaia S. J., Simulating tactile signals from the whole hand with millisecond precision. PNAS 14(28), 2017.
  • Jehenne B., Raspopovic S., Capogrosso M., Arleo A., and Micera S., Recording properties of an electrode implanted in the peripheral nervous system: A human computational model. 7th International IEEE/EMBS Conference on Neural Engineering (NER), 2015.

Project description: The development of nerve geometry simplification routines allows in principle to automatically solve for a high number of different nerve sections to study the influence of intersubject variability on HM results. This requires to possess the segmentation of many nerve sections, which must be automatically segmented. Once a proper routine has been developed, it can also be employed to study the anatomy of nerves that have not currently fully described (e.g., the vagus nerve) and its variations among species, which will give a measure of translatability. The study of internal fascicle displacements could be carried on by comparing adjacent nerve sections via probabilistic model, and simplified and ex-novo geometries could be generated, which replicate the tortuosity and intermingling extent of natural nerves.

Requirements:

  • Experience with mathematical morphology and convolutional neural networks is a plus.

Best for: Semester / master project (to be discussed)

Contact: [email protected]

References:

  • Zhong Y., Wang L., Dong J., Zhang Y., Luo P., Qi J., Liu X., and Xian C. J., Three-dimensional Reconstruction of Peripheral Nerve Internal Fascicular Groups. Scientific Reports, 2015.

Contact

If none of the projects suit you but you are interested in hybrid modeling for peripheral nerve stimulation in general, please feel free to contact us to discuss potential opportunities.

Simone Romeni ([email protected])


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