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 nonreversible nerve transection and sub-optimal intermittent stimulation methods to reduce dyssynergia.

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 spinal cord injury (SCI) transection model accurately represents traumatic laceration and has been widely used to study the natural history and reorganization of neuropathways and plasticity in the central nervous system (CNS). This model is highly reproducible, which makes it ideal for studying the progression of injury as well as endogenous recovery and plasticity in the CNS. Five experimental groups of transection injury were designed: left hemitransection; right hemitransection; double hemitransection; complete transection injuries; and laminectomy-only control. We used somatosensory evoked potentials (SSEPs) as an objective electrophysiological assessment tool and motor behavior testing (Basso, Beattie, and Bresnahan [BBB] scoring) to functionally assess the neural pathways post-injury. Histological examinations were carried out to investigate the extent of injury and spinal cord morphological changes. Significant (p < 0.05) electrophysiological changes were observed and were verified by an increase in SSEP amplitude in somatosensory cortices for all four injury groups during days 4 and 7 post-injury. Degree of plasticity among the groups was distinguished by changes in SSEP amplitude and BBB scores. Our results support our previous published findings (using a contusive model of SCI), which shows that the reorganization of neuropathways and plasticity persist in time and are not transient phenomena. SSEPs are a reliable tool to assess the functionality of neural pathways and their projections to higher CNS structures such as the cortices. They enable us to determine residual function and the changes within the CNS post-injury and consistently track these events over time. The results from our study provide supporting evidence for the presence of neuronal network reorganization and plasticity in the CNS after transection SCI.

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Electrical excitation of neural tissue has wide applications, but how electrical stimulation interacts with neural tissue remains to be elucidated. Here, we propose a new theory, named the Circuit-Probability theory, to reveal how this physical interaction happen. The relation between the electrical stimulation input and the neural response can be theoretically calculated. We show that many empirical models, including strengthduration relationship and linear-non-linear-Poisson model, can be theoretically explained, derived, and amended using our theory. Furthermore, this theory can explain the complex non-linear and resonant phenomena and fit in vivo experiment data. In this letter, we validated an entirely new framework to study electrical stimulation on neural tissue, which is to simulate voltage waveforms using a parallel RLC circuit first, and then calculate the excitation probability stochastically.

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.

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.

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