Biology subjects

Graham, R. D.

Publications and source records attributed to Graham, R. D..

3 recordsLinked to original sources

bioRxiv2023

Multiformity of extracellular microelectrode recordings from Aδ neurons in the dorsal root ganglia: A computational modeling study

Microelectrodes serve as a fundamental tool in electrophysiology research throughout the nervous system, providing a means of exploring neural function with a high resolution of neural firing information. We constructed a hybrid computational model using the finite element method and multi-compartment cable models to explore factors that contribute to extracellular voltage waveforms that are produced by sensory pseudounipolar neurons -- specifically, smaller A-type neurons -- and that are recorded by microelectrodes in dorsal root ganglia. The finite element method model included a dorsal root ganglion, surrounding tissues, and a planar microelectrode array. We built a multi-compartment neuron model with multiple trajectories of the glomerular initial segment found in many A-type sensory neurons. Our model replicated both the somatic intracellular voltage profile of A{delta} low-threshold mechanoreceptor neurons and the unique extracellular voltage waveform shapes that are observed in experimental settings. Results from this model indicated that tortuous glomerular initial segment geometries can introduce distinct multiphasic properties into a neurons recorded waveform. Our model also demonstrated how recording location relative to specific microanatomical components of these neurons, and recording distance from these components, can contribute to additional changes in the multiphasic characteristics and peak-to-peak voltage amplitude of the waveform. This knowledge may provide context for research employing microelectrode recordings of pseudounipolar neurons in sensory ganglia, including functional mapping and closed-loop neuromodulation. Further, our simulations gave insight into the neurophysiology of pseudounipolar neurons by demonstrating how the glomerular initial segment aids in increasing the resistance of the stem axon and mitigating rebounding somatic action potentials.

neuroscience↗

bioRxiv2023

Computational modeling of dorsal root ganglion stimulation using an Injectrode

ObjectiveMinimally invasive neuromodulation therapies like the Injectrode, which is composed of a tightly wound polymer-coated platinum/iridium microcoil, offer a low-risk approach for administering electrical stimulation to the dorsal root ganglion (DRG). This flexible electrode is aimed to conform to the DRG. The stimulation occurs through a transcutaneous electrical stimulation (TES) patch, which subsequently transmits the stimulation to the Injectrode via a subcutaneous metal collector. However, effectiveness of stimulation relies on the specific geometrical configurations of the Injectrode-collector-patch system. Hence, there is a need to investigate which design parameters influence the activation of targeted neural structures. ApproachWe employed a hybrid computational modeling approach to analyze the impact of the Injectrode system design parameters on charge delivery and the neural response to stimulation. We constructed multiple finite element method models of DRG stimulation and multi-compartment models of DRG neurons. We simulated the neural responses using parameters based on prior acute preclinical experiments. Additionally, we developed multiple human-scale computational models of DRG stimulation to investigate how design parameters like Injectrode size and orientation influenced neural activation thresholds. Main resultsOur findings were in accordance with acute experimental measurements and indicated that the Injectrode system predominantly engages large-diameter afferents (A{beta}-fibers). These activation thresholds were contingent upon the surface area of the Injectrode. As the charge density decreased due to increasing surface area, there was a corresponding expansion in the stimulation amplitude range before triggering any pain-related mechanoreceptor (A{delta}-fibers) activity. SignificanceThe Injectrode demonstrates potential as a viable technology for minimally invasive stimulation of the DRG. Our findings indicate that utilizing a larger surface area Injectrode enhances the therapeutic margin, effectively distinguishing the desired A{beta} activation from the undesired A{delta}-fiber activation.

bioengineering↗

bioRxiv2021

Augmented Transcutaneous Stimulation Using an Injectable Electrode

Minimally invasive neuromodulation technologies seek to marry the neural selectivity of implantable devices with the low-cost and non-invasive nature of transcutaneous electrical stimulation (TES). The Injectrode(R) is a needle-delivered electrode that is injected onto neural structures under image guidance. Power is then transcutaneously delivered to the Injectrode using surface electrodes. The Injectrode serves as a low-impedance conduit to guide current to the deep on-target nerve, reducing activation thresholds by an order of magnitude compared to using only surface stimulation electrodes. To minimize off-target recruitment of cutaneous fibers, the energy transfer efficiency from the surface electrodes to the Injectrode must be optimized. TES energy is transferred to the Injectrode through both capacitive and resistive mechanisms. Electrostatic finite element models generally used in TES research consider only the resistive means of energy transfer by defining tissue conductivities. Here, we present an electroquasistatic model, taking into consideration both the conductivity and permittivity of tissue, to understand transcutaneous power delivery to the Injectrode. The model was validated with measurements taken from (n=4) swine cadavers. We used the validated model to investigate system and anatomic parameters that influence the coupling efficiency of the Injectrode energy delivery system. Our work suggests the relevance of electroquasistatic models to account for capacitive charge transfer mechanisms when studying TES, particularly when high-frequency voltage components are present, such as those used for voltage-controlled pulses and sinusoidal nerve blocks.

bioengineering↗