The Effect of Sub-Threshold Pre-Pulses on Neural Activation Depends on Electrode Configuration

Abstract

Objective: Published research on nerve stimulation with sub-threshold conditioning pre-pulses is contradictory. Like most early research on electrical stimulation (ES), the pioneer work on the use of pre-pulses was modelled and measured only for monopolar electrodes. However, many contemporary ES applications, including miniaturized neuromodulation implants, known as electroceuticals, operate in bipolar mode. Methods: We compared depolarizing (DPPs) and hyperpolarizing (HPPs) prepulses on neural excitability in rat nerve with monopolar and bipolar electrodes. The rat common peroneal nerve was stimulated with biphasic stimuli with and without ramp and square DPPs or HPPs of 1, 5 and 10ms duration and 10% -20% of the amplitude of the following pulse. Results: The effects were opposite for the monopolar and bipolar configurations. With monopolar electrodes DPPs increased the amplitude required to activate 50% of the motoneuron pool (between 0.7% and 10.3%) and HPPs decreased the threshold (between 1.7% and 4.7%). With bipolar electrodes both pre-pulse types had the opposite effect: DPPs decreased thresholds (between 1.8% and 5.5%) whereas HPPs increased thresholds (between 0.5% and 4.1%). Electroneurograms from the stimulated nerve revealed spatial and temporal differences in action potential generation for monopolar and bipolar electrodes. In bipolar biphasic stimulation, excitation first occurred at the return electrode as a response to the transition between the cathodic and anodic phase. Conclusion: These data help to resolve the contradictions in the published data over two decades. Significance: They also show that fundamental research carried out in monopolar configuration is not directly applicable to contemporary bipolar ES applications.

Optimized Monophasic Pulses with Equivalent Electric Field for Rapid-Rate Transcranial Magnetic Stimulation

“…The second optimization step adjusted the waveforms’ amplitude based on stimulation thresholds obtained from neural simulations. The linear membrane model, while useful for estimation of time constants [43,46,48], produced significantly higher amplitude adjustment values than the non-linear models since the linear model did not capture the known lowering of threshold by hyperpolarizing negative prepulses due to dis-inhibition of the sodium ion channels [67–71]. The threshold-based scaling factors were consistent across models and cell types that include non-linear ion channels, demonstrating robustness of the amplitude adjustment step.…”

“…The second optimization step adjusted the amplitude of the waveform based on stimulation thresholds obtained from simulations with a range of model neurons. The linear membrane model required substantially higher amplitude adjustments than the nonlinear models since the linear model did not capture the reduction of threshold by hyperpolarizing leading phase due to deinactivation of the sodium channels [68][69][70][71][72]. The threshold-based scaling factors were consistent across nonlinear models and cell types, demonstrating robustness of the amplitude adjustment step.…”

AI-Controlled Closed-Loop Electrical Stimulation Implants: A Feasibility Study

“…Although the maximal feasible pulse rate depends on safety considerations [14,15], the fatigue resistance of the stimulation target structure is more likely to be the limiting factor. Even with the low pulse rate of one stimulation every 3 seconds that we used in the terminal rat electrophysiology experiments to minimize neuromuscular fatigue [16,17], a 200-pulse calibration phase would only require 10 minutes.…”

“…A further element potentially limiting both benefit and applicability of AI methods for predicting ES input-output functions for closed-loop neuromodulation implants is the typically high degree of difficulty of measuring and normalizing neural activation. In our particular experimental setup we used normalized muscle twitch force as indication of neural activation, which has been verified to be positively correlated with the root mean square (RMS) of the electrically evoked compound action potential (eCAP) in the stimulated CPN [17]. However, systems that directly receive feedback from the stimulated nerve through an ENG, as would likely be necessary for miniaturized neurostimulation implants placed in direct proximity to the target nerve, will need to incorporate algorithms to analyse the ENG, increasing both computational complexity and overhead.…”

“…Experiments were conducted in 11 adult Wistar rats under adherence to the Animals (Scientific Procedures) Act of 1986 and approval by the Home Office under the project licence (PPL 40/3743) and are described in detail in [16,17]. This study was approved by the Liverpool John Moores University Research Ethics Committee.…”