A modular 256-channel micro electrode array platform for in vitro and in vivo neural stimulation and recording: BioMEA.

In order to understand the dynamics of large neural networks, where information is widely distributed over thousands of cells, one of today's challenges is to successfully monitor the simultaneous activity of as many neurons as possible. This is made possible by using the Micro-Electrode Array (MEA) technology allowing neural cell culture and/or tissue slice experimentation in vitro. Thanks to development of microelectronics' technologies, a novel data acquisition system based on MEA technology has been developed, the BioMEA™. It combines the most advanced MEA biochips with integrated electronics, and a novel user-friendly software interface. To move from prototype (result of the RMNT research project NEUROCOM) to manufactured product, a number of changes have been made. Here, we present a 256-channel MEA data acquisition system with integrated electronics (BioMEA™) allowing simultaneous recording and stimulation of neural networks for in vitro and in vivo applications. This integration is a first step towards an implantable device for BCI (Brain Computer Interface) studies and neural prosthesis.

Dynamic, electronically switchable surfaces for membrane protein microarrays.

Microarray technology is a powerful tool that provides a high throughput of bioanalytical information within a single experiment. These miniaturized and parallelized binding assays are highly sensitive and have found widespread popularity especially during the genomic era. However, as drug diagnostics studies are often targeted at membrane proteins, the current arraying technologies are ill-equipped to handle the fragile nature of the protein molecules. In addition, to understand the complex structure and functions of proteins, different strategies to immobilize the probe molecules selectively onto a platform for protein microarray are required. We propose a novel approach to create a (membrane) protein microarray by using an indium tin oxide (ITO) microelectrode array with an electronic multiplexing capability. A polycationic, protein- and vesicle-resistant copolymer, poly(l-lysine)-grafted-poly(ethylene glycol) (PLL-g-PEG), is exposed to and adsorbed uniformly onto the microelectrode array, as a passivating adlayer. An electronic stimulation is then applied onto the individual ITO microelectrodes resulting in the localized release of the polymer thus revealing a bare ITO surface. Different polymer and biological moieties are specifically immobilized onto the activated ITO microelectrodes while the other regions remain protein-resistant as they are unaffected by the induced electrical potential. The desorption process of the PLL-g-PEG is observed to be highly selective, rapid, and reversible without compromising on the integrity and performance of the conductive ITO microelectrodes. As such, we have successfully created a stable and heterogeneous microarray of biomolecules by using selective electronic addressing on ITO microelectrodes. Both pharmaceutical diagnostics and biomedical technology are expected to benefit directly from this unique method.

Spatiotemporal characterization of rhythmic activity in rat spinal cord slice cultures.

Rat spinal networks generate a spontaneous rhythmic output directed to motoneurons under conditions of increased excitation or of disinhibition. It is not known whether these differently induced rhythms are produced by a common rhythm generator. To investigate the generation and the propagation of rhythmic activity in spinal networks, recordings need to be made from many neurons simultaneously. Therefore extracellular multisite recording was performed in slice cultures of embryonic rat spinal cords grown on multielectrode arrays. In these organotypic cultures most of the spontaneous neural activity was nearly synchronized. Waves of activity spread from a source to most of the network within 35-85 ms and died out after a further 30-400 ms. Such activity waves induced the contraction of cocultured muscle fibres. Several activity waves could be grouped into aperiodic bursts. Disinhibition with bicuculline and strychnine or increased excitability with high K(+) or low Mg(2+) solutions could induce periodic bursting with bursts consisting of one or several activity waves. Whilst the duration and period of activity waves were similar for all protocols, the duration and period of bursts were longer during disinhibition than during increased excitation. The sources of bursting activity were mainly situated ventrally on both sides of the central fissure. The pathways of network recruitment from one source were variable between bursts, but they showed on average no systematic differences between the protocols. These spatiotemporal similarities under conditions of increased excitation and of disinhibition suggest a common spinal network for both types of rhythmic activity.

The generation of rhythmic activity in dissociated cultures of rat spinal cord.

Locomotion in vertebrates is controlled by central pattern generators in the spinal cord. The roles of specific network architecture and neuronal properties in rhythm generation by such spinal networks are not fully understood. We have used multisite recording from dissociated cultures of embryonic rat spinal cord grown on multielectrode arrays to investigate the patterns of spontaneous activity in randomised spinal networks. We were able to induce similar patterns of rhythmic activity in dissociated cultures as in slice cultures, although not with the same reliability and not always with the same protocols. The most reliable rhythmic activity was induced when a partial disinhibition of the network was combined with an increase in neuronal excitability, suggesting that both recurrent synaptic excitation and neuronal excitability contribute to rhythmogenesis. During rhythmic activity, bursts started at several sites and propagated in variable ways. However, the predominant propagation patterns were independent of the protocol used to induce rhythmic activity. When synaptic transmission was blocked by CNQX, APV, strychnine and bicuculline, asynchronous low-rate activity persisted at approximately 50% of the electrodes and approximately 70% of the sites of burst initiation. Following the bursts, the activity in the interval was transiently suppressed below the level of intrinsic activity. The degree of suppression was proportional to the amount of activity in the preceding burst. From these findings we conclude that rhythmic activity in spinal cultures is controlled by the interplay of intrinsic neuronal activity and recurrent excitation in neuronal networks without the need for a specific architecture.

Power-law behavior of beat-rate variability in monolayer cultures of neonatal rat ventricular myocytes.

It is known that extracardiac factors (nervous, humoral, and hemodynamic) participate in the power-law behavior of heart-rate variability. To assess whether intrinsic properties of cardiac tissue might also be involved, beat-rate variability was studied in spontaneously beating cell cultures devoid of extracardiac influences. Extracellular electrograms were recorded from monolayer cultures of neonatal rat ventricular myocytes under stable incubating conditions for up to 9 hours. The beat-rate time series of these recordings were examined in terms of their Fourier spectra and their Hurst scaling exponents. A non-0 Hurst exponent was found in 21 of 22 preparations (0.29+/-0.09; range, 0.11 to 0.45), indicating the presence of fractal self-similarity in the beat-rate time series. The same preparations exhibited power-law behavior of the power spectra with a power-law exponent of -1.36+/-0.24 (range, -1.04 to -1.96) in the frequency range of 0.001 to 1 Hz. Furthermore, it was found that the power-law exponent was nonstationary over time. These results indicate that the power-law behavior of heart-rate variability is determined not only by extracardiac influences but also by components intrinsic to cardiac tissue. Furthermore, the presence of power-law behavior in monolayer cultures of cardiomyocytes suggests that beat-rate variability might be determined by the complex nonlinear dynamics of processes occurring at the level of the cellular network, eg, interactions among a large number of cell oscillators or metabolic regulatory systems.