Ultrasound Neuromodulation

Performance site: Campus Biotech, Geneva

Background

Ultrasound stimulation (US) has recently emerged as a promising technology to achieve reliable, selective and noninvasive neuromodulation of various targets of the central nervous system of rodents, non-human primates and humans. A myriad of applications can therefore be envisaged in which US would replace the standard and invasive electrical stimulation.

However, despite the growing emergence of this scientific field, to date, the fundamental mechanism(s) by which ultrasonic waves can modulate neural activity are still unknown. This is a limiting factor hindering the maturation of US as a reliable neuromodulation technology.

We are currently developing computational modeling framework to decipher the mechanisms of US-neuron interactions and formulate predictions of US neuromodulatory effects for different targets in the central and peripheral nervous systems. The projects presented below include the development of various branches of this computational framework, as well as its validation against experimental data.

Projects

 

Project description: Based on the SONIC model of ultrasound–membrane interaction that we recently proposed (Lemaire et al. 2019), we have developed a computational framework allowing to simulate the response of myelinated and unmyelinated peripheral axons to ultrasound stimuli (Lemaire et al. 2020) and predict the response of a simplified heterogeneous nerve bundle. We are now seeking to validate these predictions in ex vivo preparations, using a microfluidic platform to record compound action potentials travelling along fiber bundles (explanted from rat dorsal roots) upon ultrasound stimulation.

The goal of this project is to extend our computational framework and implement a more realistic model accounting for the specificities of this ex vivo experimental setting, in order to formulate predictions that can be directly compared to experimental data. The work will combine various modeling, experimental and analysis tasks including modeling of the experimental platform, acoustic and electromagnetic simulations, integration into the existing pipeline and validation of the results against experimental data collected during experiments. 

Activities:

Modeling

  • Familiarize with the SONIC model and the morphoSONIC simulation framework for ultrasound-evoked neural responses
  • Construct a 3D model of our microfluidic platform based on technical specifications
  • Construct a parametrized 3D model of our ultrasound transducer based on geometry and material specifications)
  • Use existing Python software perform acoustic simulations and characterize the acoustic field inside the platform upon stimulation by the transducer
  • Use existing Python software to perform electromagnetic simulations and extract electric field distributions within the platform-bundle environment
  • Integrate these modules with our morphoSONIC framework to predict ultrasound-evoked compound action potentials recorded throughout the acquisition channels of the platform.
  • Predict the compound bundle responses under different stimulation conditions

Experiments

  • Assist during ex vivo experiments of acoustic stimulation of dorsal spinal rootlets

Analysis

  • Validation of the simulation results against the collected experimental data

Requirements:

  • Basic knowledge of Hodgkin-Huxley models / differential equations
  • Basic programming skills
  • Experience with Git, Python, NEURON and C is a plus

Best for: master project

Contact:  [email protected]

References:

  • Lemaire, T., Neufeld, E., Kuster, N., and Micera, S. (2019). Understanding ultrasound neuromodulation using a computationally efficient and interpretable model of intramembrane cavitation. J. Neural Eng.
  • Lemaire, T., Vicari, E., Neufeld, E., Kuster, N., and Micera, S. (2020). Mechanistic modeling suggests that low-intensity focused ultrasound can selectively recruit myelinated or unmyelinated nerve fibers. BioRxiv 2020.11.19.390070.

Project description: Based on the SONIC model of ultrasound–membrane interaction that we recently proposed (Lemaire et al. 2019), we have developed a computational framework allowing to simulate ultrasound-evoked responses in myelinated and unmyelinated peripheral axons (Lemaire et al. 2020), and ultimately predict the response of a simplified heterogeneous nerve bundle to an ultrasound stimulus. We are now seeking to validate these predictions in vivo, using cuff electrodes to record compound action potentials travelling along the rat sciatic nerve upon ultrasound stimulation.

The goal of this project is to extend our computational framework and implement a more realistic model accounting for the specificities of this in vivo experimental setting, in order to formulate predictions that can be directly compared to experimental data. The project will combine various modeling, experimental and analysis tasks including histology, development of realistic nerve models from histological data, parametrized design of the ultrasonic source and recording electrode, integration into existing modeling pipelines and validation of the results against experimental data collected during in vivo experiments. 

Activities:

Modeling

  • Familiarize with the SONIC model and the morphoSONIC simulation framework for ultrasound-evoked neural responses
  • Use existing Python software to extract fascicles and nerve boundaries from cross section images and generate 3D compartmentalized nerve models
  • Construct a parametrized 3D model of our cuff electrode (based on geometry and electrical properties)
  • Use existing Python software to perform electromagnetic simulations and extract electric field distributions within the nerve-cuff environment
  • Integrate these modules with our morphoSONIC framework to predict ultrasound-evoked compound action potentials recorded by the cuff electrode
  • Predict the compound nerve response under different stimulation parameters

Experiments

  • Perform histology and acquire digital images of nerve cross sections
  • Assist during in vivo experiments of acoustic stimulation of rat sciatic nerves

Analysis

  • Validation of the simulation results against the collected experimental data

Requirements:

  • Basic knowledge of Hodgkin-Huxley models / differential equations
  • Basic programming skills
  • Experience with Git, Python, NEURON and C is a plus

Best for: master project

Contact:  [email protected]

References:

  • Lemaire, T., Neufeld, E., Kuster, N., and Micera, S. (2019). Understanding ultrasound neuromodulation using a computationally efficient and interpretable model of intramembrane cavitation. J. Neural Eng.
  • Lemaire, T., Vicari, E., Neufeld, E., Kuster, N., and Micera, S. (2020). Mechanistic modeling suggests that low-intensity focused ultrasound can selectively recruit myelinated or unmyelinated nerve fibers. BioRxiv 2020.11.19.390070.

Contact


If none of the projects suit you but you are interested in Ultrasound Neuromodulation or computational models in general, please feel free to contact us to discuss potential opportunities.

Elena Vicari ([email protected])


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