Nociceptive transmission to rat primary somatosensory cortex - comparison of sedative and analgesic effects.

CO(2)-laser C-fibre evoked cortical potentials (LCEPs) is a potentially useful animal model for studies of pain mechanisms. A potential confounding factor when assessing analgesic effects of systemically administered drugs using LCEP is sedation. This study aims to clarify: 1) the relation between level of anaesthesia and magnitude of LCEP, 2) the effects of a sedative and an analgesic on LCEP and dominant EEG frequency 3) the effects of a sedative and analgesic on LCEP when dominant EEG frequency is kept stable. LCEP and EEG were recorded in isoflurane/nitrous-oxide anaesthetized rats. Increasing isoflurane level gradually reduced LCEPs and lowered dominant EEG frequencies. Systemic midazolam (10 μmol/kg) profoundly reduced LCEP (19% of control) and lowered dominant EEG frequency. Similarly, morphine 1 and 3 mg/kg reduced LCEP (39%, 12% of control, respectively) and decreased EEG frequency. When keeping the dominant EEG frequency stable, midazolam caused no significant change of LCEP. Under these premises, morphine at 3 mg/kg, but not 1 mg/kg, caused a significant LCEP reduction (26% of control). In conclusion, the present data indicate that the sedative effects should be accounted for when assessing the analgesic effects of drug. Furthermore, it is suggested that LCEP, given that changes in EEG induced by sedation are compensated for, can provide information about the analgesic properties of systemically administrated drugs

The density difference between tissue and neural probes is a key factor for glial scarring.

A key to successful chronic neural interfacing is to achieve minimal glial scarring surrounding the implants, as the astrocytes and microglia may functionally insulate the interface. A possible explanation for the development of these reactions is mechanical forces arising between the implants and the brain. Here, we show that the difference between the density of neural probes and that of the tissue, and the resulting inertial forces, are key factors for the development of the glial scar. Two probes of similar size, shape, surface structure and elastic modulus but differing greatly in density were implanted into the rat brain. After six weeks, significantly lower astrocytic and microglial reactions were found surrounding the low-density probes, approaching no reaction at all. This provides a major key to design fully biocompatible neural interfaces and a new platform for in vivo assays of tissue reactions to probes with differing materials, surface structures, and shapes

Computationally efficient simulation of extracellular recordings with multielectrode arrays

In this paper we present a novel, computationally and memory efficient way of modeling the spatial dependency of measured spike waveforms in extracellular recordings of neuronal activity. We use compartment models to simulate action potentials in neurons and then apply linear source approximation to calculate the resulting extracellular spike waveform on a three dimensional grid of measurement points surrounding the neurons. We then apply traditional compression techniques and polynomial fitting to obtain a compact mathematical description of the spatial dependency of the spike waveform. We show how the compressed models can be used to efficiently calculate the spike waveform from a neuron in a large set of measurement points simultaneously and how the same procedure can be inversed to calculate the spike waveforms from a large set of neurons at a single electrode position. The compressed models have been implemented into an object oriented simulation tool that allows the simulation of multielectrode recordings that capture the variations in spike waveforms that are expected to arise between the different recording channels. The computational simplicity of our approach allows the simulation of a multi-channel recording of signals from large populations of neurons while simulating the activity of every neuron with a high level of detail. We have validated our compressed models against the original data obtained from the compartment models and we have shown, by example, how the simulation approach presented here can be used to quantify the performance in spike sorting as a function of electrode position

Profound inhibition of chronic itch induced by stimulation of thin cutaneous nerve fibres.

Background Despite the fact that severe itch is common in many dermatological diseases, the therapeutic arsenal against itching is limited. From neurophysiological experiments, using a new technique termed cutaneous field stimulation, it is known that acute itch can be effectively relieved by stimulation of cutaneous nociceptors. Methods We tested the effects of cutaneous field stimulation (25 min, 16 electrodes, 4 Hz per electrode, up to 0.8 mA) on chronic itch due to atopic dermatitis. Transcutaneous electrical nerve stimulation (100 Hz, up to 26 mA) was used for comparison. In 27 patients, itch was measured just prior to, during and at regular intervals up to 12 h after either type of treatment. Results Both treatments augmented the itch sensation during ongoing stimulation, presumably reflecting an altered sensory processing in the somatosensory pathways of chronic itch patients. However, after cessation of cutaneous field stimulation, but not transcutaneous electrical nerve stimulation, the itch sensation was significantly depressed for up to 7 h. The peak inhibitory effect (about 25% of control) was reached between 1 and 5 h poststimulation. Neither treatment had any significant effect on alloknesis, as measured before and 10 min after stimulation. Conclusion It is concluded that cutaneous field stimulation strongly depresses chronic itch, and is a potentially useful symptomatic treatment of itch

Spike-Feature Based Estimation of Electrode Position in Extracellular Neural Recordings

Detecting and sorting spikes in extracellular neural recordings are common procedures in assessing the activity of individual neurons. In chronic recordings, passive electrode movements introduce changes in the shape of detected spike waveforms, and may thus lead to problems with identification and tracking of spikes recorded at separate instances in time, which is an important step in long-term monitoring of individual neurons. Information about electrode movements after implantation is crucial to the evaluation of mechanical stability of different electrode designs. In this paper, we present a preliminary study of the relationship between electrode movements and the resulting movements of spike-features in feature space. We show that there is a characteristic relationship between the two movements and that this relationship can be modeled as a linear transformation between two coordinate systems. Finally, we show how the relationship can be used for estimating electrode positions based on measured spike waveforms without any prior knowledge about the type of neuron by introducing a learning procedure during electrode insertion

Statistical modelling of spike libraries for simulation of extracellular recordings in the cerebellum

Brain machine interfaces with chronically implanted microelectrode arrays for signal acquisition require algorithms for successful detection and classification of neural spikes. During the design of such algorithms, signals with a priori known characteristics need to be present. A common way to establish such signals is to model the recording environment, simulate the recordings and store ground truth about spiking activity for later comparison. In this paper, we present a statistical method to expand the spike libraries that are used in a previously presented simulation tool for the purpose described above. The method has been implemented and shown to successfully provide quick access to a large assembly of synthetic extracellular spikes with realistic characteristics. Simulations of extracellular recordings using synthesized spikes have shown to possess characteristics similar to those of in-vivo recordings in the cat cerebellum

An array of highly flexible electrodes with a tailored configuration locked by gelatin during implantation-initial evaluation in cortex cerebri of awake rats.

A major challenge in the field of neural interfaces is to overcome the problem of poor stability of neuronal recordings, which impedes long-term studies of individual neurons in the brain. Conceivably, unstable recordings reflect relative movements between electrode and tissue. To address this challenge, we have developed a new ultra-flexible electrode array and evaluated its performance in awake non-restrained animals

Size-dependent long-term tissue response to biostable nanowires in the brain

AbstractNanostructured neural interfaces, comprising nanotubes or nanowires, have the potential to overcome the present hurdles of achieving stable communication with neuronal networks for long periods of time. This would have a strong impact on brain research. However, little information is available on the brain response to implanted high-aspect-ratio nanoparticles, which share morphological similarities with asbestos fibres. Here, we investigated the glial response and neuronal loss in the rat brain after implantation of biostable and structurally controlled nanowires of different lengths for a period up to one year post-surgery. Our results show that, as for lung and abdominal tissue, the brain is subject to a sustained, local inflammation when biostable and high-aspect-ratio nanoparticles of 5 μm or longer are present in the brain tissue. In addition, a significant loss of neurons was observed adjacent to the 10 μm nanowires after one year. Notably, the inflammatory response was restricted to a narrow zone around the nanowires and did not escalate between 12 weeks and one year. Furthermore, 2 μm nanowires did not cause significant inflammatory response nor significant loss of neurons nearby. The present results provide key information for the design of future neural implants based on nanomaterials