Biosensors and Bioelectronics 25 (2010) 1889–1896 Contents lists available at ScienceDirect Biosensors and Bioelectronics journal homepage: www.elsevier.com/locate/bios BioMEA TM : A versatile high-density 3D microelectrode array system using integrated electronics Guillaume Charvet a , Lionel Rousseau b , Olivier Billoint a , Sadok Gharbi a , Jean-Pierre Rostaing a , Sébastien Joucla e,f , Michel Trevisiol a , Alain Bourgerette a , Philippe Chauvet e,f , Céline Moulin a , Franc ¸ ois Goy c , Bruno Mercier b , Mikael Colin d , Serge Spirkovitch d , Hervé Fanet a , Pierre Meyrand e,f , Régis Guillemaud a , Blaise Yvert e,f,∗ a CEA-LETI, Grenoble, France b ESIEE-Paris, Noisy-le-Grand, France c Bio-Logic SAS, Claix, France d Memscap, Crolles, France e CNRS, UMR5228, Bordeaux, F-33000, France f Université de Bordeaux, UMR5228, Bordeaux, F-33000, France article info Article history: Received 24 June 2009 Received in revised form 13 October 2009 Accepted 5 January 2010 Available online 13 January 2010 Keywords: Neural networks Extracellular electrophysiological recording Electrical microstimulation ASIC Implants Neural prosthesis abstract Microelectrode arrays (MEAs) offer a powerful tool to both record activity and deliver electrical micros- timulations to neural networks either in vitro or in vivo. Microelectronics microfabrication technologies now allow building high-density MEAs containing several hundreds of microelectrodes. However, dense arrays of 3D micro-needle electrodes, providing closer contact with the neural tissue than planar elec- trodes, are not achievable using conventional isotropic etching processes. Moreover, increasing the number of electrodes using conventional electronics is difficult to achieve into compact devices address- ing all channels independently for simultaneous recording and stimulation. Here, we present a full modular and versatile 256-channel MEA system based on integrated electronics. First, transparent high- density arrays of 3D-shaped microelectrodes were realized by deep reactive ion etching techniques of a silicon substrate reported on glass. This approach allowed achieving high electrode aspect ratios, and different shapes of tip electrodes. Next, we developed a dedicated analog 64-channel Application Specific Integrated Circuit (ASIC) including one amplification stage and one current generator per channel, and analog output multiplexing. A full modular system, called BIOMEA TM , has been designed, allowing con- necting different types of MEAs (64, 128, or 256 electrodes) to different numbers of ASICs for simultaneous recording and/or stimulation on all channels. Finally, this system has been validated experimentally by recording and electrically eliciting low-amplitude spontaneous rhythmic activity (both LFPs and spikes) in the developing mouse CNS. The availability of high-density MEA systems with integrated electronics will offer new possibilities for both in vitro and in vivo studies of large neural networks. © 2010 Elsevier B.V. All rights reserved. 1. Introduction Advances of microtechnologies in the past decades have opened the way to massive recordings of large neural networks using microelectrode arrays (MEAs). These approaches have been gaining increasing interest in neuroscience because they provide an easy way to probe neural activity distributed over multiple populations of neurons either in vitro (Gross et al., 1982) or in vivo (Maynard ∗ Corresponding author at: CNRS and Université de Bordeaux, Centre Neuro- sciences Intégratives et Cognitives, UMR 5228 Bâtiment B2, Avenue des facultés, 33405 Talence cedex, France. Tel.: +33 5 40 00 25 73; fax: +33 5 40 00 25 61. E-mail address: b.yvert@cnic.u-bordeaux1.fr (B. Yvert). et al., 1997; Nicolelis and Ribeiro, 2002; Buzsaki, 2004). MEAs have thus found a wide variety of applications, including the exploration of large-scale neuronal coding (Nicolelis et al., 1997), properties of immature (Meister et al., 1991; Demas et al., 2003; Yvert et al., 2007) or mature neural network activity (Beggs and Plenz, 2003), activity-dependent adaptation and learning (Shahaf and Marom, 2001; Eytan et al., 2003; Wagenaar et al., 2005), and the devel- opment of neural prosthesis (Klinke et al., 1999; Rauschecker and Shannon, 2002; Weiland et al., 2005; Rizk et al., 2009) and brain- machine interfaces (Chapin et al., 1999; Wessberg et al., 2000; Taylor et al., 2002; Hochberg et al., 2006). These approaches make use of arrays of metal microelectrodes contacting the neural tis- sue and interconnected to a dedicated electronics ensuring signal amplification, acquisition, and stimulation. 0956-5663/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.bios.2010.01.001