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Ilya Tarotin

Publications and source records attributed to Ilya Tarotin.

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Model-based geometrical optimisation and in vivo validation of a spatially selective multielectrode cuff array for vagus nerve neuromodulation

Background. Neuromodulation by electrical stimulation of the human cervical vagus nerve may be limited by adverse side effects due to stimulation of off-target organs. It may be possible to overcome this by spatially selective stimulation of peripheral nerves. Preliminary studies have shown this is possible using a cylindrical multielectrode human-sized nerve cuff in vagus nerve selective neuromodulation. New method. The model-based optimisation method for multi-electrode geometric design is presented. The method was applied for vagus nerve cuff array and suggested two rings of 14 electrodes, 3 mm apart, with 0.4 mm electrode width and separation and length 0.5-3 mm, with stimulation through a pair in the same radial position on the two rings. The electrodes were fabricated using PDMS-embedded stainless steel foil and PEDOT: pTS coating. Results. In the cervical vagus nerve in anaesthetised sheep, it was possible to selectively reduce the respiratory breath rate (RBR) by 85 +/- 5% without affecting heart rate, or selectively reduce heart rate (HR) by 20 +/- 7% without affecting respiratory rate. The cardiac- and pulmonary-specific sites on the nerve cross-sectional perimeter were localised with a radial separation of 105 +/- 5 degrees (P < 0.01, N = 24 in 12 sheep). Conclusions. Results suggest organotopic or function-specific organisation of neural fibres in the cervical vagus nerve. The optimised electrode array demonstrated selective electrical neuromodulation without adverse side effects. It may be possible to translate this to improved treatment by electrical autonomic neuromodulation for currently intractable conditions.

physics.med-ph

Simulation of impedance changes with a FEM model of a myelinated nerve fibre

Objective: Fast neural Electrical Impedance Tomography (EIT) is a method which permits imaging of neuronal activity in nerves by measuring the associated impedance changes (dZ). Due to the small magnitudes of dZ signals, EIT parameters require optimization, which can be done using in silico modelling: apart from predicting the best parameters for imaging, it can also help to validate experimental data and explain the nature of the observed dZ. This has previously been completed for unmyelinated fibres, but an extension to myelinated fibres is required for the development of a full nerve model which could aid imaging neuronal traffic at the fascicular level and optimise neuromodulation of the supplied internal organs to treat various diseases. Methods: An active FEM model of a myelinated fibre coupled with external space was developed. A spatial dimension was added to the experimentally validated space-clamped model of a human sensory fibre using the double cable paradigm. Electrical parameters of the model were changed so that nodal and internodal membrane potential as well as propagation velocity agreed with experimental values. dZ was simulated during activity under various conditions and the optimal parameters for imaging were determined. Main Results: When using AC, dZ could be recorded only at frequencies above 4 kHz, which is supported by experimental data. Optimal bandwidths for dZ measurement were found to increase with AC frequency. Conclusion and significance: The novel fully bi-directionally coupled FEM model of a myelinated fibre was able to optimize EIT for myelinated fibres and explain the biophysical basis of the measured signals.

physics.med-ph