Evaluation of an elastomer based gold microelectrode array for neural recording applications

We are reporting on the fabrication and electrical characterization of a novel elastomer based micro-cuff neural interface. Electrodes are gold (Au) tracks of sub-100nm thickness and are thermally evaporated on a 0.5 mm thick polydimethylsiloxane (PDMS) substrate. We investigate how electrode area and immersion in phosphate buffered saline (PBS) at 37°C influence electrode impedance. A microfluidic channel is bonded to the electrode array to form the cuff. In an acute, in-vivo, proof-of-principle recording, the device is capable of detecting light stroking and pinch of a hind leg of an anaesthetized rat.

Compliant Multi-electrode Micro-channel Array for Recording Afferent Nerve Activity

We have fabricated a compliant neural interface to record afferent nerve activity. Stretchable gold electrodes were evaporated on a polydimethylsiloxane (PDMS) substrate and were encapsulated using photo-patternable PDMS. The built-in microstructure of the gold film on PDMS allows the electrodes to twist and flex repeatedly, without loss of electrical conductivity. PDMS microchannels (5mm long, 100μm wide, 100μm deep) were then plasma bonded irreversibly on top of the electrode array to define five parallel-conduit implants. The soft gold microelectrodes have a low impedance of ~200kΩ at the 1kHz frequency range. Teased nerves from the L6 dorsal root of an anaesthetized Sprague Dawley rat were threaded through the microchannels. Acute tripolar recordings of cutaneous activity are demonstrated, from multiple nerve rootlets simultaneously. Confinement of the axons within narrow microchannels allows for reliable recordings of low amplitude afferents. This electrode technology promises exciting applications in neuroprosthetic devices including bladder fullness monitors and peripheral nervous system implants.

A microchannel neuroprosthesis for bladder control after spinal cord injury in rat

A severe complication of spinal cord injury is loss of bladder function (neurogenic bladder), which is characterized by loss of bladder sensation and voluntary control of micturition (urination), and spontaneous hyperreflexive voiding against a closed sphincter (detrusor-sphincter dyssynergia). A sacral anterior root stimulator at low frequency can drive volitional bladder voiding, but surgical rhizotomy of the lumbosacral dorsal roots is needed to prevent spontaneous voiding and dyssynergia. However, rhizotomy is irreversible and eliminates sexual function, and the stimulator gives no information on bladder fullness. We designed a closed-loop neuroprosthetic interface that measures bladder fullness and prevents spontaneous voiding episodes without the need for dorsal rhizotomy in a rat model. To obtain bladder sensory information, we implanted teased dorsal roots (rootlets) within the rat vertebral column into microchannel electrodes, which provided signal amplification and noise suppression. As long as they were attached to the spinal cord, these rootlets survived for up to 3 months and contained axons and blood vessels. Electrophysiological recordings showed that half of the rootlets propagated action potentials, with firing frequency correlated to bladder fullness. When the bladder became full enough to initiate spontaneous voiding, high-frequency/amplitude sensory activity was detected. Voiding was abolished using a high-frequency depolarizing block to the ventral roots. A ventral root stimulator initiated bladder emptying at low frequency and prevented unwanted contraction at high frequency. These data suggest that sensory information from the dorsal root together with a ventral root stimulator could form the basis for a closed-loop bladder neuroprosthetic. Copyright © 2013, American Association for the Advancement of Science

Characterization and antimicrobial efficacy against E. coli of a helium/air plasma at atmospheric pressure created in a plastic package

A plasma source, sustained by the application of a floating high voltage (±15 kV) to parallel-plate electrodes at 50 Hz, has been achieved in a helium/air mixture at atmospheric pressure (P = 105 Pa) contained in a zip-locked plastic package placed in the electrode gap. Some of the physical and antimicrobial properties of this apparatus were established with a view to ascertain its performance as a prototype for the disinfection of fresh produce. The current–voltage (I–V) and charge–voltage (Q–V) characteristics of the system were measured as a function of gap distance d, in the range (3 × 103 ≤ Pd ≤ 1.0 × 104 Pa m). The electrical measurements showed this plasma source to exhibit the characteristic behaviour of a dielectric barrier discharge in the filamentary mode and its properties could be accurately interpreted by the two-capacitance in series model. The power consumed by the discharge and the reduced field strength were found to decrease quadratically from 12.0 W to 4.5 W and linearly from 140 Td to 50 Td, respectively, in the range studied. Emission spectra of the discharge were recorded on a relative intensity scale and the dominant spectral features could be assigned to strong vibrational bands in the 2+ and 1− systems of N2 and ${\rm N}_2^+$ , respectively, with other weak signatures from the NO and OH radicals and the N+, He and O atomic species. Absolute spectral intensities were also recorded and interpreted by comparison with the non-equilibrium synthetic spectra generated by the computer code SPECAIR. At an inter-electrode gap of 0.04 m, this comparison yielded typical values for the electron, vibrational and translational (gas) temperatures of (4980 ± 100) K, (2700 ± 200) K and (300 ± 100) K, respectively and an electron density of 1.0 × 1017 m−3. A Boltzmann plot also provided a value of (3200 ± 200 K) for the vibrational temperature. The antimicrobial efficacy was assessed by studying the resistance of both Escherichia coli K12 its isogenic mutants in soxR, soxS, oxyR, rpoS and dnaK selected to identify possible cellular responses and targets related with 5 min exposure to the active gas in proximity of, but not directly in, the path of the discharge filaments. Both the parent strain and mutants populations were significantly reduced by more than 1.5 log cycles in these conditions, showing the potential of the system. Post-treatment storage studies showed that some transcription regulators and specific genes related to oxidative stress play an important role in the E. coli repair mechanism and that plasma exposure affects specific cell regulator systems.

N1 enhancement in synesthesia during visual and audio-visual perception in semantic cross-modal conflict situations: an ERP study

Synesthesia entails a special kind of sensory perception, where stimulation in one sensory modality leads to an internally generated perceptual experience of another, not stimulated sensory modality. This phenomenon can be viewed as an abnormal multisensory integration process as here the synesthetic percept is aberrantly fused with the stimulated modality. Indeed, recent synesthesia research has focused on multimodal processing even outside of the specific synesthesia-inducing context and has revealed changed multimodal integration, thus suggesting perceptual alterations at a global level. Here, we focused on audio-visual processing in synesthesia using a semantic classification task in combination with visually or auditory-visually presented animated and in animated objects in an audio-visual congruent and incongruent manner. Fourteen subjects with auditory-visual and/or grapheme-color synesthesia and 14 control subjects participated in the experiment. During presentation of the stimuli, event-related potentials were recorded from 32 electrodes. The analysis of reaction times and error rates revealed no group differences with best performance for audio-visually congruent stimulation indicating the well-known multimodal facilitation effect. We found enhanced amplitude of the N1 component over occipital electrode sites for synesthetes compared to controls. The differences occurred irrespective of the experimental condition and therefore suggest a global influence on early sensory processing in synesthetes.

Simulation of a diffusion driven mobile robot

In this paper, we investigate the possibility to control a mobile robot via a sensory-motory coupling utilizing diffusion system. For this purpose, we implemented a simulation of the diffusion process of chemicals and the kinematics of the mobile robot. In comparison to the original Braitenberg vehicle in which sensorymotor coupling is tightly realised by hardwiring, our system employs the soft coupling. The mobile robot has two sets of independent sensory-motor unit, two sensors are implemented in front and two motors on each side of the robot. The framework used for the sensory-motor coupling was such that 1) Place two electrodes in the medium 2) Drop a certain amount of Chemical U and V related to the distance to the walls and the intensity of the light 3) Place other two electrodes in the medium 4) Measure the concentration of Chemical U and V to actuate the motors on both sides of the robot. The environment was constructed with four surrounding walls and a light source located at the center. Depending on the design parameters and initial conditions, the robot was able to successfully avoid the wall and light. More interestingly, the diffusion process in the sensory-motor coupling provided the robot with a simple form of memory which would not have been possible with a control framework based on a hard-wired electric circuit.

Decomposition of surface electromyographic signal using Hidden Markov Model

The detection of physiological signals from the motor system (electromyographic signals) is being utilized in the practice clinic to guide the therapist in a more precise and accurate diagnosis of motor disorders. In this context, the process of decomposition of EMG (electromyographic) signals that includes the identification and classification of MUAP (Motor Unit Action Potential) of a EMG signal, is very important to help the therapist in the evaluation of motor disorders. The EMG decomposition is a complex task due to EMG features depend on the electrode type (needle or surface), its placement related to the muscle, the contraction level and the health of the Neuromuscular System. To date, the majority of researches on EMG decomposition utilize EMG signals acquired by needle electrodes, due to their advantages in processing this type of signal. However, relatively few researches have been conducted using surface EMG signals. Thus, this article aims to contribute to the clinical practice by presenting a technique that permit the decomposition of surface EMG signal via the use of Hidden Markov Models. This process is supported by the use of differential evolution and spectral clustering techniques. The developed system presented coherent results in: (1) identification of the number of Motor Units actives in the EMG signal; (2) presentation of the morphological patterns of MUAPs in the EMG signal; (3) identification of the firing sequence of the Motor Units. The model proposed in this work is an advance in the research area of decomposition of surface EMG signals.

Resting tremor classification and detection in Parkinson's disease patients

Parkinson is a neurodegenerative disease, in which tremor is the main symptom. This paper investigates the use of different classification methods to identify tremors experienced by Parkinsonian patients.Some previous research has focussed tremor analysis on external body signals (e.g., electromyography, accelerometer signals, etc.). Our advantage is that we have access to sub-cortical data, which facilitates the applicability of the obtained results into real medical devices since we are dealing with brain signals directly. Local field potentials (LFP) were recorded in the subthalamic nucleus of 7 Parkinsonian patients through the implanted electrodes of a deep brain stimulation (DBS) device prior to its internalization. Measured LFP signals were preprocessed by means of splinting, down sampling, filtering, normalization and rec-tification. Then, feature extraction was conducted through a multi-level decomposition via a wavelettrans form. Finally, artificial intelligence techniques were applied to feature selection, clustering of tremor types, and tremor detection.The key contribution of this paper is to present initial results which indicate, to a high degree of certainty, that there appear to be two distinct subgroups of patients within the group-1 of patients according to the Consensus Statement of the Movement Disorder Society on Tremor. Such results may well lead to different resultant treatments for the patients involved, depending on how their tremor has been classified. Moreover, we propose a new approach for demand driven stimulation, in which tremor detection is also based on the subtype of tremor the patient has. Applying this knowledge to the tremor detection problem, it can be concluded that the results improve when patient clustering is applied prior to detection.