Models of Ultrasound Neurostimulation

Performance site: Campus Biotech, Geneva

Develop morphologically realistic computational models of ultrasound neurostimulation in NEURON

Background: Ultrasonic 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 (King et al., 2013; Legon et al., 2014). A myriad of applications can therefore be envisaged in which US would replace the standard and invasive electrical stimulation. However in order for US to become a reliable neuromodulation technology, we need a deeper understanding of the fundamental mechanism(s) by which ultrasonic waves can modulate neural activity.

Project description: we are currently developing a computational modeling framework of ultrasound neurostimulation, using the recently proposed biophysical mechanism of “intramembrane cavitation” (Krasovitski et al., 2011; Plaksin et al., 2014). A “point-neuron” model (i.e. no spatial extent) has been implemented using the NEURON simulation environment in combination with Python. The student’s main task will be to extend this point-neuron model to multi-compartmental, morphologically realistic neuron representations.

Activities:

  • Familiarize with the point-neuron model, underlying differential equations, and the current Python+NEURON modeling pipeline
  • Develop innovative strategies to build and connect multiple compartments in NEURON within the very singular frame of our “intramembrane cavitation” based model
  • Implement and validate a generic model consisting of one soma connected to multiple axons and dendrites
  • Adapt the generic model to specific neuron types

Requirements:

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

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

Contact: theo.lemaire@epfl.ch

References:

King, R.L., Brown, J.R., Newsome, W.T., and Pauly, K.B. (2013). Effective parameters for ultrasound-induced in vivo neurostimulation. Ultrasound Med. Biol. 39, 312–331.

Krasovitski, B., Frenkel, V., Shoham, S., and Kimmel, E. (2011). Intramembrane cavitation as a unifying mechanism for ultrasound-induced bioeffects. Proc. Natl. Acad. Sci. U. S. A. 108, 3258–3263.

Legon, W., Sato, T.F., Opitz, A., Mueller, J., Barbour, A., Williams, A., and Tyler, W.J. (2014). Transcranial focused ultrasound modulates the activity of primary somatosensory cortex in humans. Nat. Neurosci. 17, 322–329.

Plaksin, M., Shoham, S., and Kimmel, E. (2014). Intramembrane Cavitation as a Predictive Bio-Piezoelectric Mechanism for Ultrasonic Brain Stimulation. Phys. Rev. X 4.

Develop and validate specific computational models of leech sensory neurons responding to ultrasound neurostimulation

Background: Ultrasonic 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 (King et al., 2013; Legon et al., 2014). A myriad of applications can therefore be envisaged in which US would replace the standard and invasive electrical stimulation. However in order for US to become a reliable neuromodulation technology, we need a deeper understanding of the fundamental mechanism(s) by which ultrasonic waves can modulate neural activity.

Project description: we are currently developing a computational modeling framework of ultrasound neurostimulation, using the recently proposed biophysical mechanism of “intramembrane cavitation” (Krasovitski et al., 2011; Plaksin et al., 2014). “Point-neuron” models (i.e. no spatial extent) of several generic cortical neuron types have been implemented in Python. The student’s main task will be to adapt these point-neuron models to specific models of sensory neurons of the medicinal leech, and then to conduct a thorough quantitative comparison between model predictions and experimental data (already) acquired on those neurons.

Activities:

  • Familiarize with the point-neuron model, underlying differential equations, and the current Python implementation
  • Search the literature to identify a clear nomenclature of key ion channel populations present in the targeted cell types (touch, pressure and nociceptive cells), along with the underlying gating dynamics of these ion channels (Hodgkin-Huxley equations)
  • Implement those point-neuron models and validate them against observations from the literature (spontaneous activity, response to electrical stimulation, …)
  • Establish key features of neural responses to ultrasound stimulation predicted by these models
  • Conduct a thorough comparison of model predictions with experimental data, using relevant metrics
  • Write a report with presentation and discussion of results

Requirements:

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

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

Contact: theo.lemaire@epfl.ch

References:

King, R.L., Brown, J.R., Newsome, W.T., and Pauly, K.B. (2013). Effective parameters for ultrasound-induced in vivo neurostimulation. Ultrasound Med. Biol. 39, 312–331.

Krasovitski, B., Frenkel, V., Shoham, S., and Kimmel, E. (2011). Intramembrane cavitation as a unifying mechanism for ultrasound-induced bioeffects. Proc. Natl. Acad. Sci. U. S. A. 108, 3258–3263.

Legon, W., Sato, T.F., Opitz, A., Mueller, J., Barbour, A., Williams, A., and Tyler, W.J. (2014). Transcranial focused ultrasound modulates the activity of primary somatosensory cortex in humans. Nat. Neurosci. 17, 322–329.

Plaksin, M., Shoham, S., and Kimmel, E. (2014). Intramembrane Cavitation as a Predictive Bio-Piezoelectric Mechanism for Ultrasonic Brain Stimulation. Phys. Rev. X 4.

Johansen, J. (1991). Ion conductances in identified leech neurons. Comp Biochem Physiol A Comp Physiol 100, 33–40.

Develop models of acoustic propagation with a peripheral nerve and its anatomical environment

Background: Ultrasonic 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 (King et al., 2013; Legon et al., 2014). A myriad of applications can therefore be envisaged in which US would replace the standard and invasive electrical stimulation. However in order for US to become a reliable neuromodulation technology, we need a deeper understanding of the fundamental mechanism(s) by which ultrasonic waves can modulate neural activity.

Project description: we are currently developing a multi-scale modeling framework of ultrasound neurostimulation, by coupling (1) morphologically detailed, biophysical neuron models and (2) models of acoustic propagation within realistic neural structures (brain, spinal cord, peripheral nerves) and their anatomical environment. The student’s main task will be to develop a model of acoustic propagation within the peripheral nerve and its anatomical environment, from a distant ultrasound transducer, using the Sim4Life simulation platform (https://zmt.swiss/sim4life/).

Activities:

  • Familiarize with the different bioeffects of ultrasound, the theory of acoustic propagation and the main existing mathematical models (Kyriakou, 2015)
  • Search the relevant literature for acoustic propagation properties of different nerve tissues
  • Familiarize with the Sim4Life simulation platform and the main modeling workflow
    • Nerve segmentation from imaging data
    • Definition of the model geometry
    • Assignment of material properties
    • Mesh creation, model discretization
    • Simulation
    • Results analysis
    • Automation using Python scripts
  • Develop and validate a model of acoustic propagation within a peripheral nerve and its environment
  • Define and implement metrics to quantify the distribution of acoustic intensity within the nerve
  • Compare the performances of different transducer types and geometries

Requirements:

  • Basic knowledge of Finite Element Models (FEM) / Finite Element Analysis (FEA)
  • Basic programming skills
  • Experience with Python is a plus

Best for: master project

Contact: theo.lemaire@epfl.ch

References:

King, R.L., Brown, J.R., Newsome, W.T., and Pauly, K.B. (2013). Effective parameters for ultrasound-induced in vivo neurostimulation. Ultrasound Med. Biol. 39, 312–331.

Kyriakou (2015). Multi-Physics Computational Modeling of Focused Ultrasound Therapies.

Legon, W., Sato, T.F., Opitz, A., Mueller, J., Barbour, A., Williams, A., and Tyler, W.J. (2014). Transcranial focused ultrasound modulates the activity of primary somatosensory cortex in humans. Nat. Neurosci. 17, 322–329.

If none of the projects suit you but you are interested in Ultrasound Neuromodulation or computational models in general, please feel free to contact the person in charge (theo.lemaire@epfl.ch) to discuss potential opportunities.