Effect on signal-to-noise ratio of splitting the continuous contacts of cuff electrodes into smaller recording areas.

BackgroundCuff electrodes have been widely used chronically in different clinical applications. This neural interface has been dominantly used for nerve stimulation while interfering noise is the major issue when employed for recording purposes. Advancements have been made in rejecting extra-neural interference by using continuous ring contacts in tripolar topologies. Ring contacts provide an average of the neural activity, and thus reduce the information retrieved. Splitting these contacts into smaller recording areas could potentially increase the information content. In this study, we investigate the impact of such discretization on the Signal-to-Noise Ratio (SNR). The effect of contacts positioning and an additional short circuited pair of electrodes were also addressed.MethodsDifferent recording configurations using ring, dot, and a mixed of both contacts were studied in vitro in a frog model. An interfering signal was induced in the medium to simulate myoelectric noise. The experimental setup was design in such a way that the only difference between recordings was the configuration used. The inter-session experimental differences were taken care of by a common configuration that allowed normalization between electrode designs.ResultsIt was found that splitting all contacts into small recording areas had negative effects on noise rejection. However, if this is only applied to the central contact creating a mixed tripole configuration, a considerable and statistically significant improvement was observed. Moreover, the signal to noise ratio was equal or larger than what can be achieved with the best known configuration, namely the short circuited tripole. This suggests that for recording purposes, any tripole topology would benefit from splitting the central contact into one or more discrete contacts.ConclusionsOur results showed that a mixed tripole configuration performs better than the configuration including only ring contacts. Therefore, splitting the central ring contact of a cuff electrode into a number of dot contacts not only provides additional information but also an improved SNR. In addition, the effect of an additional pair of short circuited electrodes and the "end effect" observed with the presented method are in line with previous findings by other authors

On the viability of implantable electrodes for the natural control of artificial limbs: Review and discussion

The control of robotic prostheses based on pattern recognition algorithms is a widely studied subject that has shown promising results in acute experiments. The long-term implementation of this technology, however, has not yet been achieved due to practical issues that can be mainly attributed to the use of surface electrodes and their highly environmental dependency. This paper describes several implantable electrodes and discusses them as a solution for the natural control of artificial limbs. In this context "natural" is defined as producing control over limb movement analogous to that of an intact physiological system. This includes coordinated and simultaneous movements of different degrees of freedom. It also implies that the input signals must come from nerves or muscles that were originally meant to produce the intended movement and that feedback is perceived as originating in the missing limb without requiring burdensome levels of concentration. After scrutinizing different electrode designs and their clinical implementation, we concluded that the epimysial and cuff electrodes are currently promising candidates to achieving a long-term stable and natural control of robotic prosthetics, provided that communication from the electrodes to the outside of the body is guaranteed

Attenuation of Hippocampal Evoked Potentials in vivo by Activation of GtACR2, an Optogenetic Chloride Channel

Aim GtACR2, a light-activated chloride channel, is an attractive tool for neural inhibition as it can shunt membrane depolarizations. In this study, we assessed the effect of activating GtACR2 on in vivo hippocampal CA1 activity evoked by Schaffer collateral (SC) stimulation. Methods Adult male Wistar rats were unilaterally injected with 0.5 mu L of adeno associated viral vector for induction of GtACR2-mCherry (n = 10, GtACR2 group) or mCherry (n = 4, Sham group) expression in CA1 pyramidal neurons of the hippocampus. Three weeks later, evoked potentials (EPs) were recorded from the CA1 subfield placing an optrode (bipolar recording electrode attached to an optic fiber) at the injection site and a stimulation electrode targeting SCs. Effects of illumination parameters required to activate GtACR2 such as light power densities (LPDs), illumination delays, and light-pulse durations were tested on CA1 EP parameters [population spike (PS) amplitude and field excitatory postsynaptic potential (fEPSP) slope]. Results In the GtACR2 group, delivery of a 10 ms light-pulse induced a negative deflection in the local field potential which increased with increasing LPD. When combined with electrical stimulation of the SCs, light-induced activation of GtACR2 had potent inhibitory effects on CA1 EPs. An LPD of 160 mW/mm(2) was sufficient to obtain maximal inhibition CA1 EPs. To quantify the duration of the inhibitory effect, a 10 ms light-pulse of 160 mW/mm(2) was delivered at increasing delays before the CA1 EPs. Inhibition of EPs was found to last up to 9 ms after the cessation of the light-pulse. Increasing light-pulse durations beyond 10 ms did not result in larger inhibitory effects. Conclusion Precisely timed activation of GtACR2 potently blocks evoked activity of CA1 neurons. The strength of inhibition depends on LPD, lasts up to 9 ms after a light-pulse of 10 ms, and is independent of the duration of the light-pulse given

Electrical stimulation of the human optic nerve

Thèse de doctorat en sciences médicales (neuroscience) (MED 3)--UCL, 200

Classification of Visual Sensations Generated Electrically in the Visual Field of the Blind

Within the framework of the OPTIVIP project, an optic nerve based visual prosthesis is being developed in order to restore partial vision to the blind. In this paper, we concentrate on the classification problem of visual sensations generated by multiple electrical stimulations. We propose to use probabilistic neural networks in order to perform Bayesian classification. Statistical sampling techniques are utilized in order to reduce the bias on the estimated performances and assess the sensitivity of the method. In noisy environment the Parzen window estimator seems more reliable than finite Gaussian mixtures. Copyright 2003 IFAC Keywords: probabilistic neural networks, probabilistic models, probability density function, classification, parameter estimation, cross-validation, electrical stimulation, optic nerve * Michel Verleysen is a Senior Research Associate of the Belgian F.N.R.S. (National Fund for Scientific Research)