Xin Yuan Thow

The effect of anaesthesia on somatosensory evoked potential measurement in a rat model

Somatosensory evoked potentials (SEPs) are widely used to study the functional integrity of ascending sensory pathways. For animal studies, SEPs provide a convenient method to quantitatively assess the functionality of the nervous system with low invasiveness. Even though they are frequently used in animal models, little attention is paid to the fact that SEPs are vulnerable to contamination from experimental factors such as anaesthetic delivery. In this study, the effect of isoflurane on SEP measurement was investigated in a rat model. The aim was to find out the adjustments for anaesthetic delivery optimizing the quality of the recordings. Two aspects were studied: the effect of isoflurane dosage on the SEP parameters and on the repeatability of the measurements. The SEP quality was found to be best when 1.5% isoflurane concentration was used. This dosage resulted in the best signal-to-noise ratio and equal repeatability of the measurements compared with the others. Our findings can help in refining the anaesthetic protocols related to SEP recordings in a rat model and, by improving the quality of the measurements, potentially reducing the number of subjects needed to carry out studies.

Automatic Parametrization of Somatosensory Evoked Potentials With Chirp Modeling

In this paper, an approach using polynomial phase chirp signals to model somatosensory evoked potentials (SEPs) is proposed. SEP waveforms are assumed as impulses undergoing group velocity dispersion while propagating along a multipath neural connection. Mathematical analysis of pulse dispersion resulting in chirp signals is performed. An automatic parameterization of SEPs is proposed using chirp models. A Particle Swarm Optimization algorithm is used to optimize the model parameters. Features describing the latencies and amplitudes of SEPs are automatically derived. A rat model is then used to evaluate the automatic parameterization of SEPs in two experimental cases, i.e., anesthesia level and spinal cord injury (SCI). Experimental results show that chirp-based model parameters and the derived SEP features are significant in describing both anesthesia level and SCI changes. The proposed automatic optimization based approach for extracting chirp parameters offers potential for detailed SEP analysis in future studies. The method implementation in Matlab technical computing language is provided online.

A Highly Selective 3D Spiked Ultraflexible Neural (SUN) Interface for Decoding Peripheral Nerve Sensory Information

Artificial sensors on the skin are proposed as a way to capture information that can be used in intracortical microstimulation or peripheral intraneural stimulation to restore sensory feedback to persons with tetraplegia. However, the ability of these artificial sensors to replicate the density and complexity of the natural mechanoreceptors is limited. One relatively unexplored approach is to make use of the signals from surviving tactile and proprioceptive receptors in existing limbs by recording from their transmitting axons within the primary sensory nerves. Here, a novel spiked ultraflexible neural (SUN) interface that is implanted into the peripheral nervous system to capture sensory information from these mechanoreceptors in acute rat experiments is described. The novel 3D design, which integrates spiked structures for intrafascicular nerve recording with an ultraflexible substrate, enables a unique conformal interface to the target nerve. With the high-quality recording (average signal-to-noise-ratio of 1.4) provided by the electrode, tactile from proprioceptive stimuli can be differentiated in terms of the firing rate. In toe pinching experiments, high spatial resolution classification can be achieved with support vector machine classifier. Further work remains to be done to assess the chronic recording capability of the SUN interface.

The first principle of neural circuit and the general Circuit-Probability theory.

A new neural circuit is proposed by considering the myelin as an inductor. This new neural circuit can explain why the lump-parameter circuit used in previous C-P theory is valid. Meanwhile, it provides a new explanation of the biological function of myelin for neural signal propagation. Furthermore, a new model for magnetic nerve stimulation is built and all phenomena in magnetic nerve stimulation can be well explained. Based on this model, the coil structure can be optimized.A neural circuit model involving inductance is established to explain the neural networks’ behavior. A parallel resistor-inductor-capacitor (RLC) circuit was used to fit the stimulus artifacts in the electromyography (EMG) recording of cortical and pelvic electrical nerve stimulations. This parallel RLC circuit model also predicts the resonance effect in both stimulus artifacts and EMG signals. Moreover, the well-known strength-duration relationship was directly derived to be a precise format with this parallel RLC circuit model. A theoretical explanation is provided to show the inductance is generated by the coil structure of the myelin sheath and the piezoelectric effect of the plasma membrane. One Sentence Summary: The inductance in the neural systems is generated by the coil structure of the myelin sheath and the piezoelectric effect of the plasma membrane.Abstract A five-anchor model is provided to describe the physical working procedure of an individual ion channel. It provide the first principle for ion channel behavior: which is the polarity change of each anchor is induced by electron transition independently. Thus, the long off kenetics of neural stimulation by optogenetics, the stochastic gating pattern of single ion channel under DC voltage, the refractory period of action potential and the nerve conductance block, which are well observed for years in many studies, can [17], be directly explained by this model. Meanwhile, as one part of the general Circuit-Probability theory this model expand the probability calculation from a single equation, which is applied for the Circuit-Probability theory in our previous study, to a general form, which is a set of quantized operation.

Novel neurostimulation of autonomic pelvic nerves overcomes Bladder-sphincter dyssynergia

The disruption of coordination between smooth muscle contraction in the bladder and the relaxation of the external urethral sphincter (EUS) striated muscle is a common issue in dysfunctional bladders. It is a significant challenge to overcome for neuromodulation approaches to restore bladder control. Bladder-sphincter dyssynergia leads to undesirably high bladder pressures, and poor voiding outcomes, which can pose life-threatening secondary complications. Mixed pelvic nerves are potential peripheral targets for stimulation to treat dysfunctional bladders, but typical electrical stimulation of pelvic nerves activates both the parasympathetic efferent pathway to excite the bladder, as well as the sensory afferent pathway that causes unwanted sphincter contractions. Thus, a novel pelvic nerve stimulation paradigm is required. In anesthetized female rats, we combined a low frequency (10 Hz) stimulation to evoke bladder contraction, and a more proximal 20 kHz stimulation of the pelvic nerve to block afferent activation, in order to produce micturition with reduced bladder-sphincter dyssynergia. Increasing the phase width of low frequency stimulation from 150 to 300 μs alone was able to improve voiding outcome significantly. However, low frequency stimulation of pelvic nerves alone evoked short latency (19.9–20.5 ms) dyssynergic EUS responses, which were abolished with a non-reversible proximal central pelvic nerve cut. We demonstrated that a proximal 20 kHz stimulation of pelvic nerves generated brief onset effects at lower current amplitudes, and was able to either partially or fully block the short latency EUS responses depending on the ratio of the blocking to stimulation current. Our results indicate that ratios >10 increased the efficacy of blocking EUS contractions. Importantly, we also demonstrated for the first time that this combined low and high frequency stimulation approach produced graded control of the bladder, while reversibly blocking afferent signals that elicited dyssynergic EUS contractions, thus improving voiding by 40.5 ± 12.3%. Our findings support advancing pelvic nerves as a suitable neuromodulation target for treating bladder dysfunction, and demonstrate the feasibility of an alternative method to non-reversible nerve transection and sub-optimal intermittent stimulation methods to reduce dyssynergia.