Objective Our goal is to develop an interface that integrates chronic monitoring of lower urinary tract (LUT) activity with stimulation of peripheral pathways. Approach Penetrating microelectrodes were implanted in sacral dorsal root ganglia (DRG) of adult male felines. Peripheral electrodes were placed on or in the pudendal nerve, bladder neck and near the external urethral sphincter. Supra-pubic bladder catheters were implanted for saline infusion and pressure monitoring. Electrode and catheter leads were enclosed in an external housing on the back. Neural signals from microelectrodes and bladder pressure of sedated or awake-behaving felines were recorded under various test conditions in weekly sessions. Electrodes were also stimulated to drive activity. Main results LUT single- and multi-unit activity was recorded for 4 to 11 weeks in four felines. As many as 18 unique bladder pressure single-units were identified in each experiment. Some channels consistently recorded bladder afferent activity for up to 41 days, and we tracked individual single-units for up to 23 days continuously. Distension-evoked and stimulation-driven (DRG and pudendal) bladder emptying was observed, during which LUT sensory activity was recorded. Significance This chronic implant animal model allows for behavioral studies of LUT neurophysiology and will allow for continued development of a closed-loop neuroprosthesis for bladder control.

A closed-loop device for bladder control may offer greater clinical benefit compared to current open-loop stimulation devices. Previous studies have demonstrated the feasibility of using single-unit recordings from sacral-level dorsal root ganglia (DRG) for decoding bladder pressure. Automatic online sorting, to differentiate single units, can be computationally heavy and unreliable, in contrast to simple multi-unit thresholded activity. In this study, the feasibility of using DRG multi-unit recordings to decode bladder pressure was examined. A broad range of feature selection methods and three algorithms (multivariate linear regression, basic Kalman filter, and a nonlinear autoregressive moving average model) were used to create training models and provide validation fits to bladder pressure for data collected in seven anesthetized feline experiments. A non-linear autoregressive moving average (NARMA) model with regularization provided the most accurate bladder pressure estimate, based on normalized root-mean-squared error, NRMSE, (17 ± 7%). A basic Kalman filter yielded the highest similarity to the bladder pressure with an average correlation coefficient, CC, of 0.81 ± 0.13. The best algorithm set (based on NRMSE) was further evaluated on data obtained from a chronic feline experiment. Testing results yielded a NRMSE and CC of 10.7% and 0.61, respectively from a model that was trained on data recorded 2 weeks prior. From offline analysis, implementation of NARMA in a closed-loop scheme for detecting bladder contractions would provide a robust control signal. Ultimate integration of closed-loop algorithms in bladder neuroprostheses will require evaluations of parameter and signal stability over time.

BackgroundMechanosensitive afferents innervating the bladder increase their firing rate as the bladder fills and pressure rises. However, the relationship between afferent firing rates and intravesical pressure is not a simple linear one. Firing rate responses to pressure can differ depending on prior activity, demonstrating hysteresis in the system. Though this hysteresis has been commented on in published literature, it has not been quantified.ResultsSixty-six bladder afferents recorded from sacral dorsal root ganglia in five alpha-chloralose anesthetized felines were identified based on their characteristic responses to pressure (correlation coefficient ≥ 0.2) during saline infusion (2 ml/min). For saline infusion trials, we calculated a maximum hysteresis ratio between the firing rate difference at each pressure and the overall firing rate range (or Hmax) of 0.86 ± 0.09 (mean ± standard deviation) and mean hysteresis ratio (or Hmean) of 0.52 ± 0.13 (n = 46 afferents). For isovolumetric trials in two experiments (n = 33 afferents) Hmax was 0.72 ± 0.14 and Hmean was 0.40 ± 0.14.ConclusionsA comprehensive state model that integrates these hysteresis parameters to determine the bladder state may improve upon existing neuroprostheses for bladder control.

Repeated or extended-duration pudendal nerve stimulation can elicit maintained increases in vaginal blood perfusion. This work indicates the potential for pudendal neuromodulation as a method for increasing genital arousal as a potential treatment for FSD.

We investigated the potential of deep brain stimulation (DBS) in the central nucleus of the amygdala (CeA) in rats to modulate functional reward mechanisms. The CeA is the major output of the amygdala with direct connections to the hypothalamus and gustatory brainstem, and indirect connections with the nucleus accumbens. Further, CeA has been shown to be involved in learning, emotional integration, reward processing, and regulation of feeding. We hypothesized that DBS, which is used to treat movement disorders and other brain dysfunctions, might block reward motivation. In rats performing a lever pressing task to obtain sugar pellet rewards, we stimulated the CeA and control structures, and compared stimulation parameters. During CeA stimulation, animals stopped working for rewards and rejected freely available rewards. Taste reactivity testing during DBS exposed aversive reactions to normally liked sucrose tastes and even more aversive taste reactions to normally disliked quinine tastes. Interestingly, given the opportunity, animals implanted in the CeA would self-stimulate with 500 ms trains of stimulation at the same frequency and current parameters as continuous stimulation that would stop reward acquisition. Neural recordings during DBS showed that CeA neurons were still active and uncovered inhibitory-excitatory patterns after each stimulus pulse indicating possible entrainment of the neural firing with DBS. In summary, DBS modulation of CeA may effectively usurp normal neural activity patterns to create an “information lesion” that not only decreased motivational “wanting” of food rewards, but also blocked “liking” of rewards.

Tablet PC-based engineering software can be used as an effective teaching tool for core engineering courses such as electronics, signal and systems, and digital systems. Wireless connection between Tablet PCs of students and the teaching professor will substantially improve students' involvement during the course. Circuit drawing is an important task especially in undergraduate courses such as electronics and digital systems. Most existing software tools for circuit drawing use a toolbox where symbols for all circuit components are prepared and ready for pick up. A user has to go through a number of layers of menus each time he/she wants to use a circuit symbols. To improve human computer interaction, we have developed an online recognition system on a Tablet PC using C# for the handwritten circuit and its components. The system can recognize and redraw many circuits and their components such as resistors, capacitors, ground and various voltage power supplies, which are drawn with a stylus pen on a Tablet PC. We present details of our approach and preliminary results of an experimental system.

Local field potentials (LFPs) have been proposed for use in controlling neural prosthetic devices because they can provide reliable motor and sensory-related information, and can easily be recorded over long periods of time. While studies have shown that directional information about motor movements can be inferred from LFPs, it is not known at what depth these signals should be recorded from in order to maximize the amount of movement information. Towards this end, we used a directional motor task in Long Evans rats, while sampling LFPs with an electrode consisting of 16 vertical recording sites that were evenly-spaced 100 microm apart. This allowed for simultaneous recording of all layers of the motor cortex. The frequency components of LFPs were then analyzed using k-means clustering to determine directional information as a function of depth. Here we report our initial findings that superficial layers (II/III) of motor cortex may provide more information about movement directions then deeper layers (V).

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