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Field-stimulation theory paper published in Physical Review Letters

2012-09-14 11:05 by Philip Bittihn

Finding the most sensitive locations for electric-field stimulation of biological tissue

Numerical simulation on a cross-section of a rabbit ventricle revealing field-strength dependent recruitment of wave sources (electric field strength increasing from left to right). Negative curvature boundaries are activated at the lowest field strengths.<br /> Excerpt of figure 4 from Bittihn, Hörning, Luther, <em>Physical Review Letters</em><strong> 109</strong>, 118106 (2012)
Numerical simulation on a cross-section of a rabbit ventricle revealing field-strength dependent recruitment of wave sources (electric field strength increasing from left to right). Negative curvature boundaries are activated at the lowest field strengths.
Excerpt of figure 4 from Bittihn, Hörning, Luther, Physical Review Letters 109, 118106 (2012)

Low-energy electric field stimulation is a novel approach to control life-threatening cardiac arrhythmias (S. Luther, F.H. Fenton et al., Nature 2011). How electric fields interact with excitable biological substrates is an important and challenging question. In our work (P. Bittihn, M. Hörning, S. Luther, PRL 2012), we develop a theory that predicts how sensitive different parts of the tissue boundary are to stimulation by a uniform electric field.

Electric field stimulation can activate excitable tissue at heterogeneities in electrical conductance, such as at tissue boundaries. However, the phenomenon’s dependence on the anatomical structure has not yet been determined. Our results show that the sensitivity is closely related to the shape of these boundaries. In a biological substrate of complex shape, such as the heart, this leads to a specific and predictable spatial arrangement of “sweet spots” that are most susceptible to electric-field stimulation within a given field orientation. We anticipate that our finding may help to develop and improve novel therapies based on electric field stimulation that combine the spatial information about potential activation sites and dynamical properties of malign activity to control the dynamics in the tissue.

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