Impact of brain tissue filtering on neurostimulation fields: A modeling study

Abstract

Electrical neurostimulation techniques, such as deep brain stimulation (DBS) and transcranial magnetic stimulation (TMS), are increasingly used in the neurosciences, e.g., for studying brain function, and for neurotherapeutics, e.g., for treating depression, epilepsy, and Parkinson’s disease. The characterization of electrical properties of brain tissue has guided our fundamental understanding and application of these methods, from electrophysiologic theory to clinical dosing-metrics. Nonetheless, prior computational models have primarily relied on ex-vivo impedance measurements. We recorded the in-vivo impedances of brain tissues during neurosurgical procedures and used these results to construct MRI guided computational models of TMS and DBS neurostimulatory fields and conductance-based models of neurons exposed to stimulation. We demonstrated that tissues carry neurostimulation currents through frequency dependent resistive and capacitive properties not typically accounted for by past neurostimulation modeling work. We show that these fundamental brain tissue properties can have significant effects on the neurostimulatory-fields (capacitive and resistive current composition and spatial/temporal dynamics) and neural responses (stimulation threshold, ionic currents, and membrane dynamics). These findings highlight the importance of tissue impedance properties on neurostimulation and impact our understanding of the biological mechanisms and technological potential of neurostimulatory methods.

Motor Cortex Neurostimulation Technologies for Chronic Post-stroke Pain: Implications of Tissue Damage on Stimulation Currents

“…The models were generated following methods previously outlined (Wagner et al, 2004, 2007b), and following foundational physics reviewed in the appendix of Wagner et al (2014).…”

“…While, we used a 1 mA source magnitude for EBS, it should be noted that the EBS solutions are linear in the region of interest and simple multiplicative scaling can be used to account for varied source magnitudes (Woodson and Melcher, 1968; Zahn, 2003; Wagner et al, 2014). Furthermore, as the EBS electrostatic solutions are addressable by superposition, we focused on one bipolar section at a time (Woodson and Melcher, 1968; Zahn, 2003; Wagner et al, 2014).…”

Modeling sequence and quasi-uniform assumption in computational neurostimulation

“…Here, the framework is well agreed-upon, if not the specific tissue parameters that should be used in any given case Opitz et al, 2011;Schmidt et al, 2015;Wagner et al, 2014). The tissue properties are generated in forward models by first dividing the anatomy into individual masks, such as gray and white matter.…”

In vitro Magnetic Stimulation: A Simple Stimulation Device to Deliver Defined Low Intensity Electromagnetic Fields

“…Although, a few studies have profited from indwelling electrodes to measure TMS-induced electric fields in the brain (macaque, Lisanby et al, 2001; human, Wagner et al, 2004), the currents actually generated will vary according to the cellular components involved, specifically cell membrane resistance and capacitance, which in turn vary with the presence/absence of myelin and/or the distribution of ion channels (Chan and Nicholson, 1986; Wagner et al, 2014). However, in human patients/subjects without such electrodes, modeling or calculation is needed to define the electric field (Deng et al, 2013; Lu and Ueno, 2013; Janssen et al, 2015).…”