Sustained and potent analgesia with negligible side effects enabled by adaptive individualized granular stimulation in rat brainstem.

To clarify if an adaptive current stimulation protocol, in which current amplitude is modulated during continuous stimulation, provides better efficacy than constant current stimulation protocol with respect to analgesia caused by individualized stimulation in rat periaqueductal gray matter (PAG) /dorsal raphe nuclei (DRN).Ultrathin microelectrodes adapted for recording (= 6) and stimulation (= 16) were implanted in rat primary somatosensory cortex and PAG/DRN, respectively. In each animal included (= 12), a subset of PAG/DRN microelectrodes (= 1-3 per animal) was selected that on simultaneous stimulation blocked nociceptive withdrawal reflexes in awake unrestrained animals without noticeable side effects.

Microelectrode clusters enable therapeutic deep brain stimulation without noticeable side-effects in a rodent model of Parkinson's disease.

Background: Deep Brain Stimulation (DBS) is an established treatment for motor symptoms in Parkinson's disease (PD). However, side effects often limit the usefulness of the treatment.

New Method: To mitigate this problem, we developed a novel cluster of ultrathin platinum-iridium microelectrodes (n = 16) embedded in a needle shaped gelatin vehicle.

3D microelectrode cluster and stimulation paradigm yield powerful analgesia without noticeable adverse effects.

The lack of satisfactory treatment for persistent pain profoundly impairs the quality of life for many patients. Stimulation of brainstem pain control systems can trigger powerful analgesia, but their complex network organization frequently prevents separation of analgesia from side effects. To overcome this long-standing challenge, we developed a biocompatible gelatin-embedded cluster of ultrathin microelectrodes that enables fine-tuned, high-definition three-dimensional stimulation in periaqueductal gray/dorsal raphe nucleus in awake rats.

Ice coating -A new method of brain device insertion to mitigate acute injuries.

Background: Reduction of insertion injury is likely important to approach physiological conditions in the vicinity of implanted devices intended to interface with the surrounding brain.

New Methods: We have developed a novel, low-friction coating around frozen, gelatin embedded needles. By introducing a layer of thawing ice onto the gelatin, decreasing surface friction, we mitigate damage caused by the implantation.

Embedded Ultrathin Cluster Electrodes for Long-Term Recordings in Deep Brain Centers.

Neural interfaces which allow long-term recordings in deep brain structures in awake freely moving animals have the potential of becoming highly valuable tools in neuroscience. However, the recording quality usually deteriorates over time, probably at least partly due to tissue reactions caused by injuries during implantation, and subsequently micro-forces due to a lack of mechanical compliance between the tissue and neural interface. To address this challenge, we developed a gelatin embedded neural interface comprising highly flexible electrodes and evaluated its long term recording properties.

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

Background: 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.

Strategies for high-performance resource-efficient compression of neural spike recordings.

Brain-machine interfaces (BMIs) based on extracellular recordings with microelectrodes provide means of observing the activities of neurons that orchestrate fundamental brain function, and are therefore powerful tools for exploring the function of the brain. Due to physical restrictions and risks for post-surgical complications, wired BMIs are not suitable for long-term studies in freely behaving animals. Wireless BMIs ideally solve these problems, but they call for low-complexity techniques for data compression that ensure maximum utilization of the wireless link and energy resources, as well as minimum heat dissipation in the surrounding tissues.

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.

Minimizing data transfer with sustained performance in wireless brain-machine interfaces.

Brain-machine interfaces (BMIs) may be used to investigate neural mechanisms or to treat the symptoms of neurological disease and are hence powerful tools in research and clinical practice. Wireless BMIs add flexibility to both types of applications by reducing movement restrictions and risks associated with transcutaneous leads. However, since wireless implementations are typically limited in terms of transmission capacity and energy resources, the major challenge faced by their designers is to combine high performance with adaptations to limited resources.