André Garenne

Borna Disease Virus Infection Impairs Synaptic Plasticity

ABSTRACT The mechanisms whereby Borna disease virus (BDV) can impair neuronal function and lead to neurobehavioral disease are not well understood. To analyze the electrophysiological properties of neurons infected with BDV, we used cultures of neurons grown on multielectrode arrays, allowing a real-time monitoring of the electrical activity across the network shaped by synaptic transmission. Although infection did not affect spontaneous neuronal activity, it selectively blocked activity-dependent enhancement of neuronal network activity, one form of synaptic plasticity thought to be important for learning and memory. These findings highlight the original mechanism of the neuronal dysfunction caused by noncytolytic infection with BDV.

A Real-Time Closed-Loop Setup for Hybrid Neural Networks

Hybrid living-artificial neural networks are an efficient and adaptable experimental support to explore the dynamics and the adaptation process of biological neural systems. We present in this paper an innovative platform performing a real-time closed-loop between a cultured neural network and an artificial processing unit like a robotic interface. The system gathers bioware, hardware, and software components and ensures the closed-loop data processing in less than 50 mus. We detail here the system components and compare its performances to a recent commercial platform.

State-Dependent, Bidirectional Modulation of Neural Network Activity by Endocannabinoids

The endocannabinoid (eCB) system and the cannabinoid CB1 receptor (CB1R) play key roles in the modulation of brain functions. Although actions of eCBs and CB1Rs are well described at the synaptic level, little is known of their modulation of neural activity at the network level. Using microelectrode arrays, we have examined the role of CB1R activation in the modulation of the electrical activity of rat and mice cortical neural networks in vitro. We find that exogenous activation of CB1Rs expressed on glutamatergic neurons decreases the spontaneous activity of cortical neural networks. Moreover, we observe that the net effect of the CB1R antagonist AM251 inversely correlates with the initial level of activity in the network: blocking CB1Rs increases network activity when basal network activity is low, whereas it depresses spontaneous activity when its initial level is high. Our results reveal a complex role of CB1Rs in shaping spontaneous network activity, and suggest that the outcome of endogenous neuromodulation on network function might be state dependent.

In-vitro exposure of neuronal networks to the GSM-1800 signal.

The central nervous system is the most likely target of mobile telephony radiofrequency (RF) field exposure in terms of biological effects. Several electroencephalography (EEG) studies have reported variations in the alpha-band power spectrum during and/or after RF exposure, in resting EEG and during sleep. In this context, the observation of the spontaneous electrical activity of neuronal networks under RF exposure can be an efficient tool to detect the occurrence of low-level RF effects on the nervous system. Our research group has developed a dedicated experimental setup in the GHz range for the simultaneous exposure of neuronal networks and monitoring of electrical activity. A transverse electromagnetic (TEM) cell was used to expose the neuronal networks to GSM-1800 signals at a SAR level of 3.2 W/kg. Recording of the neuronal electrical activity and detection of the extracellular spikes and bursts under exposure were performed using microelectrode arrays (MEAs). This work provides the proof of feasibility and preliminary results of the integrated investigation regarding exposure setup, culture of the neuronal network, recording of the electrical activity, and analysis of the signals obtained under RF exposure. In this pilot study on 16 cultures, there was a 30% reversible decrease in firing rate (FR) and bursting rate (BR) during a 3 min exposure to RF. Additional experiments are needed to further characterize this effect.

Design of a Bioelectronics Hybrid System in Real Time and in Closed Loop

Hynets, for Hybrid (living-artificial) Networks, are an efficient and adaptable experimental support to explore the dynamics and the adaptation process of biological systems. We present in this paper an innovative platform performing a real-time closed-loop between a cultured network (e.g. neurons) and an artificial processing (e.g. software processing or a robotic interface). The system gathers bioware, hardware, and software components and ensures the closed-loop data processing in less than 50 µs. We describe also a methodology that may help to standardize the description of some experiments. This method is associated to a full custom Graphical User Interface. We detail here the system choices, components, and performances.

DECREASED SPONTANEOUS ELECTRICAL ACTIVITY IN NEURONAL NETWORKS EXPOSED TO RADIOFREQUENCY 1800 MHZ SIGNALS

The rapid development of wireless communications has raised questions about their potential health risks. So far, the only identified biological effects of radiofrequency fields (RF) are known to be caused by heating, but the issue of potential nonthermal biological effects, especially on the central nervous system (CNS), remains open. We previously reported a decrease in the firing and bursting rates of neuronal cultures exposed to a Global System for Mobile (GSM) RF field at 1,800 MHz for 3 min (Moretti D, Garenne A, Haro E, Poulleier de Gannes F, Lagroye I, Lévêque P, Veyret B, Lewis N. Bioelectromagnetics 34: 571-578, 2013). The aim of the present work was to assess the dose-response relationship for this effect and also to identify a potential differential response elicited by pulse-modulated GSM and continuous-wave (CW) RF fields. Spontaneous bursting activity of neuronal cultures from rat embryonic cortices was recorded using 60-electrode multielectrode arrays (MEAs). At 17-28 days in vitro, the neuronal cultures were subjected to 15-min RF exposures, at specific absorption rates (SAR) ranging from 0.01 to 9.2 W/kg. Both GSM and CW signals elicited a clear decrease in bursting rate during the RF exposure phase. This effect became more marked with increasing SAR and lasted even beyond the end of exposure for the highest SAR levels. Moreover, the amplitude of the effect was greater with the GSM signal. Altogether, our experimental findings provide evidence for dose-dependent effects of RF signals on the bursting rate of neuronal cultures and suggest that part of the mechanism is nonthermal. NEW & NOTEWORTHY In this study, we investigated the effects of some radiofrequency (RF) exposure parameters on the electrical activity of neuronal cultures. We detected a clear decrease in bursting activity, dependent on exposure duration. The amplitude of this effect increased with the specific absorption rate (SAR) level and was greater with Global System for Mobile signal than with continuous-wave signal, at the same average SAR. Our experiment provides unique evidence of a decrease in electrical activity of cortical neuronal cultures during RF exposure.

Modeling large-scale neural network culture interface on very-high density multi-electrode arrays

The use of multi-electrode arrays (MEA) technology is developing in neuroscience fields like neuro-pharmacology [1,2], network plasticity investigation [3-5] or neurological diseases [6] and disorders [7]. Dissociated cultures or slices are now often employed on 60–100 multi-site arrays. Recently, matrixes of several thousands of microelectrodes have been developed in order to gain higher spatial resolution from the cell scale up to large network scale. With the framework of a European Consortium (IDEA Project) we developed a 4096 electrode MEA using the Active Pixel Sensor APS technology as well as a computer model of cortical dissociated cultures grown on this device including the neuron-to-electrode interface. Our goal is to better understand the network mechanisms responsible for recorded activity, and to provide integrated software for Computer Aided Design (CAD) of neural engineering devices. Since it was computationally too heavy to work with thousands of interconnected Hodgkin-Huxley cell models, we chose to implement the Izhikevich model which is known as a good compromise between realistic cellular properties and computation time [8]. Indeed, the classical standard leaky integrate-and-fire cellular model can hardly mimic the rich repertoire of intrinsic cellular properties that can be found in biological substrates. We present here the first recordings of high-density MEAs together with dedicated software which can simulate the complete system composed of the electrode matrix and the biological network grown on top. The first results of these large-scale interconnected networks simulations (size and number of cells similar to those recorded in vitro) are consistent with the first recorded data using our prototype of high-density MEAs: (i) the bursts initiation location varies randomly from one place to another, (ii) their propagation varies with the connectivity and the level of presynaptic firing, (iii) the average bursting frequency with no inhibitory connections is close to 1 Hz and similar activity is obtained with bicucculin treated dissociated culture activity. Finally, (iv) the model burst propagation speed is about 100 mm/s and this value has also been computed on real cultures in our lab. This tool is currently used to optimize the design and to investigate the properties of large-scale MEA devices under development and constitutes an innovative neuro-engineering CAD environment.