A cable theory based biophysical model of resistance change in crab peripheral nerve and human cerebral cortex during neuronal depolarisation: implications for electrical impedance tomography of fast neural activity in the brain

Medical & Biological Engineering & Computing
A D ListonD S Holder

Abstract

Electrical impedance tomography (EIT) is a medical imaging method with the potential to image resistance changes which occur during neuronal depolarisation in the brain with a resolution of milliseconds and millimetres. Most biomedical EIT is conducted with applied current over 10 kHz, as this reduces electrode impedance and so instrumentation artefact. However, impedance changes during neuronal depolarization are negligible at such frequencies. In order to estimate optimal recording frequency and specify instrumentation requirements, we have modelled their amplitude and frequency dependence during evoked activity using cable theory. Published values were used for the electrical properties and geometry of cell processes. The model was adjusted for the filtering effect of membrane capacitance and proportion of active neurons. At DC, resistance decreases by 2.8 % in crab nerve during the compound action potential and 0.6 % (range 0.06-1.7 %) locally in cerebral cortex during evoked physiological activity. Both predictions correlate well with independent experimental data. This encourages the view that true tomographic imaging of fast neural activity in the brain is possible, at least with epicortical electrodes in the first insta...Continue Reading

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Citations

Sep 9, 2015·NeuroImage·Kirill Y AristovichDavid S Holder
Apr 13, 2015·Medical & Biological Engineering & Computing·Seppo P Ahlfors, Christopher Wreh
Mar 5, 2016·The Journal of Physiology·Walter Paulus, John C Rothwell
Dec 25, 2013·The Journal of International Medical Research·Bin YangXiuzhen Dong
Mar 30, 2017·Physiological Measurement·Mayo FaulknerDavid Holder
Jun 2, 2018·Medical & Biological Engineering & Computing·Zhanxiong WuXiaohui Yu
Jun 27, 2019·Journal of Neural Engineering·Ilya TarotinDavid Holder

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