SIM4LIFE » Tissue Models » T-NEURO
T-NEURO

 Tissue Models: T-NEURO

Neuronal Tissue Models

The Neuronal Tissue Models (T-NEURO) enable the dynamic modeling of EM-induced neuronal activation, inhibition, and synchronization using either complex, multi-compartmental representations of axons, neurons, and neuronal networks with varying channel dynamics, or generic models. Sim4Life uses the NEURON solver developed at the Yale University which is ideal for studying interaction mechanisms, evaluating and optimizing neurostimulating devices, and assessing safety issues.

 

DTI-based fiber tracking for the optimized placement of dynamic neuron models.

Embedded geometrical and dynamical representation of neurons (soma, axon, and dendritic tree) generate physiologically functionalized anatomical models. (coming soon)

The SENN model (safety standards) and more complex  models can be applied inside whole-body models. The graphics user interface (GUI) facilitates the integration of other neuronal models from commonly used databases or independently derived models.

T-NEURO has been validated against published data and
ex vivo and in vivo measurements, and is continually advanced and validated.

 
 

 Application Areas

  • MRgFUS Neurosurgery Applications: Tumor Ablation, Neuropathic Pain Treatment, Movement Disorders
  • FUS-Based Neural Stimulation

 

  • Neuro-Prosthetics (retina, cochlea, vestibular, motor)
  • EM Neuro-Stimulation
  • Neuro-Motoric Incapacitation

 

  • High LF-EM Field Safety Assessment (e.g., MR Gradient Coils)
  • Pacemaker
  • Temperature Impact on Neuronal Dynamics
 

 Key Features

  • Dynamic modeling of EM-induced neuronal activation inhibition & synchronization
  • Unidirectional coupling with the EM-QS and Thermal solver
  • SENN model can be applied inside whole body models

 

  • Interface allows integration of other neuronal models from commonly used databases
  • User-friendly import & visualization of nerve geometries from commonly used databases
  • Determining thresholds through titration procedure
  • Detection of neuronal spikes and their occurence times

 

  • Novel spatially varying temperature dependence impact on the neuronal dynamics
  • Capturing & plotting membrane dynamics over time
  • Easily define pulse sources that correspond to gradient switching fields
 

Neuronal response modeling in MRI gradient switching fields considering RF induced local temperature increases.

Improved DBS treatment analysis facilitated by the head model incorporating the Morel stereotactic atlas of the thalamus.

Propagation of the transmembrane voltage in a rat hippocampus neuron with a detailed dendritic tree.