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. T-NEURO now also permits to accurately and efficiently deal with neural sensing – the simulation of measurable electric signals resulting from neural activity.
  • Embedded geometrical and dynamical representation of neurons (soma, axon, and dendritic tree) generate physiologically functionalized anatomical models.
  • 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 andex vivo and in vivo measurements, and is continually advanced and validated.
  • MRgFUS Neurosurgery Applications: Tumor Ablation, Neuropathic Pain Treatment, Movement Disorders
  • FUS-Based Neural Stimulation
  • EM Neuro-Stimulation
  • Neural sensing: Compound action potential (CAP), electroencephalogram (EEG), and electrocorticogram (ECoG) recordings
  • Neuro-Prosthetics (retina, cochlea, vestibular, motor)
  • High LF-EM Field Safety Assessment (e.g., MR Gradient Coils)
  • Pacemaker
  • Temperature Impact on Neuronal Dynamics
  • Neuro-Motoric Incapacitation
  • Dynamic modeling of EM-induced neuronal activation inhibition & synchronization
  • Unidirectional coupling with the EM-QS and Thermal solver
  • Accurately and efficiently dealing with neural sensing sensing
  • Powerful Hessian Calculator for the investigation of electrical neuro-stimulation within the complexity of the human anatomy
  • 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
  • SENN model can be applied inside whole body models
  • 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
  • Applicable to heterogeneous, anisotropic dielectric environment model, including the most complex anatomical representations

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