Multielectrode Arrays

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Curator: Guenter W. Gross

Figure 1: Nerve cell network derived from dissociated murine spinal tissue growing on a 64-electrode recording matrix. Electrodes are spaced 40 µm laterally and 200 µm between rows. Transparent indium-tin oxide conductors are 10 µm wide. Recording sites are laser de-insulated followed by electrolytic gold deposition to reduce impedances at 1 kHz to approximately 1 megohm.

MEAs are fixed geometry arrangements of microelectrodes for the purpose of multisite, parallel electrophysiological recording. The large number of MEA designs that have been generated and used cannot be summarized in a short article. Our experience has been limited to simple, two-dimensional electrode array plates, devoid of active circuitry, for in vitro investigations in the domain of neuroscience. This article focuses on planar, passive arrays with substrate-integrated microelectrodes for use in neuronal cell cultures.



Figure 2: (A) The CNNS MMEP-4 showing the 50 x 50 x 1 mm glass plate with 32 amplifier contacts at either side. (B) 1 mm2 recording area with 8 x 8 electrode matrix, equal distance separation of 150 µm. Electrolytic gold plating of the exposed transparent indium-tin oxide in shallow craters reduces the interface impedance to 800 kohms. (C) MMEP-5 featuring two separate recording islands with 32 microelectrodes each. The center-to-center distance between the recording areas is 2.24 cm. Amplifier contacts are the same as for MMEP-4. (D) Cruciform electrode design used or MMEP-5B to enhance probability of cell-electrode coupling in low-density cultures. (E) Micrograph of two adjacent electrodes from a MMEP-5B recording matrix. Laser de-insulation allows selection of the number of sites that are opened and avoids a second chemical etching step. (F) Single electrode in culture with a large multipolar neuron (live culture, phase contrast microscopy).

The concept of using groups of microelectrodes for recording from or stimulating neural tissue is as old as the realization that the monitoring of dynamic neural systems requires the simultaneous capture of multiple electrophysiological events. However, the lack of appropriate microelectronic techniques and the large data streams prevented systematic fabrication and application until the second half of the 20th century. By the end of this century, technology had caught up with the demands of neuroscientists resulting in an explosion of designs, applications, and concomitant novel neurophysiological data. The domain of microelectrode arrays is broad and encompasses sets of movable microelectrodes (Crain, 1976), bundles of wire electrodes and fixed array needle electrodes (Schmidt, 1999), and microelectronic multisite recording “daggers” (Wise et al., 1970). These categories are further complicated by devices with on-board electronics (BeMent et al., 1986), or arrays with FETs that are often classified as “active arrays” (Fromherz, et al., 1991). Such arrays must be discussed separately from this article. The review article by Pine provides more detail of early developments (Pine, 2006). Theory, design, and modeling of thin film electrodes also are well represented in a review article by Kovacs (1994).

The first functional planar array using photolithographed thin film conductors was conceived and fabricated by Thomas et al. (1972) with gold/nickel conductors on glass and used successfully for recording of action potentials from cardiac myocytes. The first recordings of action potentials from individual neurons was reported in 1977 using spontaneously active Helix pomatia (snail) ganglia (Gross et al., 1977, Gross, 1979). These experiments used a glass plate decorated with 36 thin film gold conductors on titanium, 12 um wide, insulated with a polysiloxane and de-insulated with single laser shots (pulsed nitrogen laser, 337 nm). The next major step forward was achieved by J. Pine (1980) when the first signals from mammalian central nervous system cultures were obtained with a 16-electrode array. This was quickly followed by recording from murine spinal neuronal networks (Gross et al., 1982; Gross and Lucas, 1982, Droge et al., 1986) and the introduction of transparent indium tin oxide as an electrode material (Gross et al., 1985) to minimize the optical loss induced by opaque electrode materials.

Figure 3: Example of conformal MEA for use with hippocampal slices featuring recording and stimulating columns (R and S in inset, respectively). Reproduced from Gholmie et al. (2006) with permission.

In addition to the early developments of passive planar arrays and subsequent participation of commercial enterprises such as Multichannel Systems in Reutlingen, Germany, Panasonic USA, and Ayanda in Switzerland, the simplicity of photolithography has allowed various research groups to fabricate custom arrays suited to their research purposes. This is especially true for slice recording where specific array geometries were introduced to optimize monitoring of activity from different brain regions with specific geometries: retina (Grumet et al., 2000; Meister et al., 1991), spinal cord (Borkholder et al., 1997; Streit et al., 2006), and hippocampus (Boppart et al., 1992; Egert et al., 1998; Novak and Wheeler, 1988; Thiebaud et al., 1997, Oka et al., 1999; Gholmieh et al. 2006). 3-D arrays with tip-shaped electrodes to penetrate the dead cell layer of slices have also been introduced (Heuschkel et al., 2006).

A hippocampal conformal MEA (cMEA) fabricated by the Berger research group at USC is shown in Figure 3 (Gholmieh et al, 2006). Other interesting new developments include multiwell plastic dishes with small inter-well conduits that allow passage of neurites, providing excellent recording across the high resistance conduits with single electrodes (Claverol-Tinture, 2009).

Cell-electrode coupling in primary cell cultures

Dissociate embryonic tissue forms intimate contact with a hydrophilic insulation surface. However, adhesion-enhancing molecules are generally applied to improve adhesion and long-term stability. A large number of adhesion-promoting materials have been tried among which polylysine or polyornithine (McKeehan and Ham, 1976), and laminin (Hunter et al., 1991) are the most common. Hydrophobic surfaces can be “activated” by plasma etching or flaming before they accept decoration with polylysine. The latter procedure involves a one second exposure to a butane flame and is simple and economic (Lucas et al., 1986). It has the additional advantage of direct generation of adhesion islands by flaming through masks.

Figure 4: Three microelectrodes spaced 40 um laterally with adhered axons. Over 70% of the recordings are obtained from axons (based on triphasic waveshapes). Horizontal conductors of this particular MEA version are 12 um wide. Glia are difficult to see but exist both below and above the neuronal circuitry. Bodian stain, interference contrast microscopy.
Figure 5: Waveshape profiles generated by the Plexon Inc. Rasputin software. Digital signal processors (DSPs) sample at 40kHz and display smooth waveforms of which four can be discriminated in real time on one electrode, assuming sufficient differences in size and shape (left panel). The right panel shows a yield of 50 discriminated units from manual assignment of 32 DSPs to a field of 64 electrodes.

The adhered ”monolayer” is actually a shallow 3-dimensional volume with neurons residing on top of a glial carpet and neurites both on top and below the carpet. Vertical distances range from 3 um over glia to more than 10 um over neuronal perikarya. Regardless of the covalent surface decoration selected, the use of polylysine or polyornithine, as well as the unavoidable cell debris introduced during cell seeding, masks the chemical characteristics of the original surface, and generates a rather complex non-specific adhesion milieu. Very high signal-to-noise ratios (SNRs) are obtained when an active process crosses a recording crater and is capped by glia ( Figure 4 and Figure 5). In the early stages of network development, it has been observed that glia climb over adhered neurites, that neurites climb onto and over glia, but that adhered neuronal cell bodies are lifted by approaching glia that grow between the substrate and the membrane of the soma. Complete control over this stratification and the glial capping has not yet been achieved, but would yield very large signals (of the order of 1 mV) and a high electrode yield. It should also be noted that optimal crater geometry is not well understood, except for the repeatedly demonstrated fact that recessed electrodes provide higher SNRs due to the increased spreading resistance to ground and the quasi isolation of the electrode by glia.

It is important to recognize that the ratio of cell mass to adhesion area cannot be too large, as it leads to regional or global retraction of network components. Large fascicles, if allowed or even encouraged to form in networks (as in “ordered networks”), develop tension and usually lift off the substrate. The best stability is obtained from quasi monolayers of neurons and glia with neuronal densities not exceeding 500 per mm2 and glia growth controlled by antimitotics such as fluoro-2’-deoxyuridine (Ransom et al., 1977). However, antimitotics are not essential. Excessive glial growth obscures network morphology and often contributes to tissue retractions at the edges of the network but does not interfere with recording.

Maturation, survival and self-organization

Figure 6: Neuronal cell count stabilization after 20 days in vitro. Identification was based on neurofilament antibody, immunocytochemistry and a Loots-modified Bodian stain. The linear regression is based on the Bodian stain data and reflects a 3% neuronal loss per month.

After an initial loss of neurons in the first 10 to 15 days after seeding, cultures stabilize with minimal reduction in neuronal counts ( Figure 6). With present culture maintenance protocols, survival of primary cultures for 6 to 12 months is possible (Gross, 1994; Potter and DeMarse, 2001). For practical reasons, most experiments use 4 to 8 week old cultures. Morphological and electrophysiological stability is generally attained by 3 - 4 weeks of growth in vitro. After this time, only minimal cell movement occurs and unique tissue-specific activity patterns have a high probability of being expressed (see below).

Figure 7: Simultaneous recording of native activity from multiple channels from three different CNS tissues: (A) spinal cord, (B) midbrain, and (C) cortex. Panels represent 40 sec of activity in the form of raster plots where time stamps from threshold crossing of action potentials are represented as vertical tick marks. The time stamp resolution is 25 μs. Each tissue has a characteristic native activity that is found in almost all cultures.

Networks in culture are not random systems, but represent self-organized dynamic ensembles (Bettencourt et al., 2007), and native, spontaneous activity patterns are unique for networks formed from tissue of different brain regions. Whereas the cortical networks show highly coordinated bursting, midbrain tissue expresses high spike rates with embedded, minimally coordinated bursts, and spinal cord networks display multiple, simultaneous patterns with strong bursts of relatively long duration ( Figure 7). Such tissue-specific patterns have been observed by many laboratories using different species of mice, different culture protocols, and different MEAs. The observations demonstrate powerful inherent self-organizational principles based presumably on different cell types and relatively unique interconnections. The reader is cautioned that such patterns are influenced by medium biochemistry, pH, and medium osmolarity. Attention to such environmental factors is essential.


In addition to the obvious quest for understanding how neuronal ensembles function and how they generate or process spatio-temporal action potential patterns (cf Taketani and Baudry, 2006), primary networks in culture have shown a surprising histiotypic (like the parent tissue) pharmacologic behavior, if prepared to contain ratios of neuronal and glial components similar to those found in the parent tissue (Gross and Gopal, 2006). Consequently, it has been proposed that such networks on MEAs can be used as effective and rapid screening platforms in pharmacology, toxicology, for drug testing, and even tissue-based biosensors (Gross and Pancrazio, 2006). The MEA approach is crucial for obtaining average system information, fault tolerant read-out based on many cells, individual neuron response profiles, and action potential wave shape data.

Given the histiotypic nature of pharmacological and toxicological network responses, the application of these platforms to rapid screening of compounds represents a natural next step. Such platforms provide the following specific advantages:

  1. Long-term (days to weeks) multisite action potential readout with cell identification based on wave shape templates.
  2. Control over the biochemical environment.
  3. Determination of functional changes (in the absence of cell death).
  4. Quantification of cytotoxicity using activity decay as the primary measure.
  5. Close correlation between electrophysiological and morphological changes.
  6. Combined electrophysiological and fluorescence readout.

In addition, one mouse with 12 embryos can provide enough central nervous system tissue to seed up to 1000 networks. This represents a very high tissue utilization efficiency that, however, cannot be put to practice until the technology for massively parallel multi-array platforms is developed.

Although cultures can be maintained in incubators for many months. Effective survival times in external recording platforms varies depending on sterility conditions, life support stability, and experimental manipulations. Five to ten days on such platforms with continuous recording can be routinely achieved.

Pharmacology and Toxicology

Figure 8: Sequential pharmacological simplification of synaptic driving forces in a spinal cord network using mean burst rate and burst duration as the activity variables. Each data point represents averaged values in one-minute bins. After addition of NBQX the network enters a highly regular and stable bursting state at 20 bpm (period: 2.9+/-0.3 sec).

Figure 8 shows the response of a spinal cord network in terms of mean burst duration plotted against mean burst rate to a sequential addition of different compounds designed to block inhibitory and, partially excitatory, synapses culminating in a network driven almost exclusively by NMDA synapses (Keefer et al, 2001). Starting with native activity, the culture received 40 uM bicuculline to block GABAA inhibition, followed by 1 uM strychnine to remove glycinergic inhibitory influences, 50 uM SCH50119, a GABAB antagonist, and 20 uM NBQX to block AMPA/kainate receptors. Charybdotoxin (15 nM) and apamin (1 uM) antagonize, respectively, the large and small conductance Ca++ activated K+ channels and were used to explore the effect of the Ca++ activated BK channel on activity patterns. A surprising result was the rapid development of a highly regular burst pattern after addition of NBQX at burst periods of 2.9+/-0.3 sec (18 – 23 bursts per min). Subsequent additions of cholinergic and dopaminergic blockers had no measurable effect on the final “NMDA-only” state.

Figure 9: Global network activity plot constructed from average activity in one-minute (or larger) bins. Analyses require zero slope activity plateaus from which normalized, percent decreases are determined. Such basic network performance plots can then be supplemented with analyses of burst structure and a variety of emerging non-linear analyses tools.

The complexity of the activity and the variability of spontaneous activity among network often lead to comments that “data management and analysis over long time periods is impossible”. In the domains of pharmacology and toxicology this is simply not the case. Here, the responses are slow and the necessity to wait for equilibrium after test compound application requires observation periods of 20 to 30 min. It is possible to condense one minute of activity across all channels into one data point and express global network activity as a “minute mean” ( Figure 9). From these binned population means the entire history of the network before, during, and after compound application, can be observed and quantified.

Figure 10: Electrophysiological quantification of zinc acetate toxicity with simultaneous morphological observations. Data points represent average network spike (left ordinate) and burst (right ordinate) activity in one-minute bins. Diagonal conductor is 8 um in width. Osmotic swelling kills all neurons and glia in a concentration specific time period. Lower panel: log/log representation of time required for 50% activity loss as a function of zinc acetate concentration in media with and without serum. 5% serum protects at low concentrations. (from Parviz and Gross, 2007)

The global activity plots allow the calculation of a variety of pharmacological parameters such as concentration response curves, EC50(EC50 : effective concentration for a 50% change in activity) or ET50 values(ET50(C): effective time required for a 50% change in activity at a constant test compound concentration), reversibility, and even dissociation constants. Figure 10 demonstrates a combined electrophysiological and optical monitoring of network responses to 200 uM zinc acetate, revealing the correlation between activity decay and morphological signatures of cell stress and death. A quantification of network spike production decay is more quantifiable than using morphological features.

Figure 11 and Figure 12 show results from more quantitative pharmacological investigations. Relatively subtle shifts in EC50 values can be demonstrated by comparing fluoxetine dose responses with those of fluoxetine and ethanol (Xia and Gross, 2003). Dissociation constants have also been determined with MEA technology. Figure 12 shows the shift of GABA agonist muscimol dose response curves in the presence of the competitive antagonist bicuculline. A Schild plot then allows extrapolation of dissociation constants. Figure 9B shows such a plot for the antagonists bicuculline, gabazine, and trimethylol-popane phosphate (Rijal-Oli and Gross, 2008).

Figure 11: Systematic shift of fluoxetine IC50 (red) from 4.3+/-0.2 to 2.7+/- 0.2 in the presence of 20 mM ethanol (black curves). Redrawn from Xia and Gross, 2003.
Figure 12: (A) Shift of muscimol dose response curves to higher concentrations in the presence of increasing concentrations of bicuculline. (B) Schild plot for three antagonists resulting in dissociation constants (x-intercepts) of 0.23, 0.61, and 3.98 uM for gabazine, bicuculline, and TMPP, respectively.


Neuronal networks on microelectrode arrays are physiological sensors and not “olfactory systems”. They report effects of neuroactive and toxic substances at the concentrations that affect physiological functions. Hence they may be considered “broad band biosensors” as they respond to known and unknown compounds (Gross and Pancrazio, 2006). Unknown compounds may be classified by comparing response patterns to a library of recorded responses (Gramowski et al., 2004). Prototypes of remote stations have been developed (Pancrazio et al. 2003). However, the problem of sensor (i.e. the network) replacement has not been worked out and required automated data analysis programs still need to be developed. Figure 13 shows a simple analysis protocol that can provide useful data, especially if a novel substance is encountered.

Figure 13: Substance evaluation flowchart for network responses to unknown compounds. It is important to realize that the cultures contain neurons and glia and are able to report functional toxicity (loss of activity in the absence of cytotoxicity), neurotoxicity (loss of neurons), and general cytotoxicity.

How many electrodes are sufficient?

The number of microelectrodes required for analysis depends on the complexity of the pattern to be analyzed. There is no simple formula for this query. The population response must be representative of the induced dynamical changes. Not every cell responds in exactly the same manner. Even the relatively slow pharmacological responses show subpopulations, a phenomenon that has not yet received sufficient experimental attention. For example, Xia and Gross reported in 2003 that the application of 40 mM ethanol to 14 frontal cortex cultures (200 recorded units) decreased spiking in 71% of the neurons, increased firing in 20%, and generated no effects in 9%. Similar ethanol effects were seen in the locus coeruleus (Pohorecky and Brick, 1977), and with CA1 and CA3 pyramidal neurons in hippocampal slices (Siggins et al., 1987). The sampling becomes even more complicated if we try to separate axonal, somal, and dendritic signatures based on wave shapes. The information traffic in a network is probably best represented by axonal action potential patterns. Although the triphasic wave shape of a traveling action potential is relatively easy to recognize, it is presently general practice to accept any signal that can be recorded reliably. Given these challenges, it is prudent to keep the number of electrodes as high as practicable.

Studies of pattern generation and information processing

Whereas quantitative pharmacology and the determination of substance toxicity have proven to be relatively simple if stable life support is assured and appropriate application protocols are used, investigations of plasticity, learning, pattern processing, and fault tolerance have been found to be more difficult. It is assumed that the former domain is governed primarily by the pharmacological sensitivities of the cell types, receptors, and synapses found in the culture rather than by the detailed circuitry. However, information processing appears to be influenced at least to an equal degree by the circuitry that is established in vitro. Such circuitry, even in these highly simplified systems, is difficult to determine morphologically. However, progress is now being made in establishing functional connectivity (Eytan and Marom, 2006; Bettencourt et al., 2007; Eckmann et al., 2008; Ham et al. 2008). Subtle plasticity phenomena are also yielding to investigation (Jimbo et al, 1999; Shahaf and Marom, 2001) and dynamic attractors in activity patterns are being identified (Beggs and Plenz, 2004; Wagenaar et al., 2006).

Prototype multi-array platforms

Applications in research benefit from parallel recording arrays that allow simultaneous experimental and control studies and provide statistical results in a short period of time. For drug efficacy and toxicity screening these approaches to high throughput are essential and platforms must be scaled up to a maximum possible number of networks. These efforts present a significant technical and programming challenge in the areas of life support, pipetting accuracy, repeatability, and automated data analysis.

A prototype 8-network MEA has been developed by the CNNS and has shown promise in numerous experiments. Life support is provided by a 10% CO2 atmosphere and 30% humidity with robotic water additions, determined empirically, to maintain osmolarities. Both the robot (Biotek Precision 2000) and the Plexon VLSI, 32 channel preamplifiers function well in such an environment.

Figure 14: (A) 8-network array plate (90 x 56 x 1.1 mm) served by 32 cruciform microelectrodes per recording area (256 total). Amplifier contact fingers are 300 μm wide with a pitch of 300 μm. Large circles show contact position of chamber block ‘O’ rings; small circles depict seeding areas. (B) One of the 8 recording areas. (C) Assembled recording chamber with preamplifiers in an environmental chamber with robotic medium maintenance and test substance application.

Modification of electrodes with carbon nanotubes

A remarkable reduction of electrode impedances (up to a 23 –fold reduction) can be achieved by decorating the exposed metal recording sites with carbon nanotubes (CNTs) or organic conductive polymers (Keefer et al. 2008). This simple electrolytic modification allows further down sizing of conductor dimensions, recording site diameters, and a substantial increases in electrode densities without compromising optical access and signal-to-noise ratios. Especially the potential size reduction of the optically opaque recording site, which normally interferes with morphological determinations of cell-electrode coupling, can make important contributions to circuit tracing.

Figure 15: Carbon nanotube-modified indium tin oxide recording sites of a laser deinsulated MEA. (A) Bright field micrograph of the center region of an MEA with transparent ITO conductors with recording craters decorated with gold (left two columns; 1 kHz Z = 800 kOhm) and gold/carbon nanotubes (right two columns, Z = 40 kOhm). Bar: 150 μm. (B) Recording site (approx. 20 um in diameter; gold on ITO) after decoration with CNTs), Bar: 15 μm. (C and D) Higher magnifications of the microelectrode surface (x 7,360 and x 14,700) showing a unique organization of CNTs into relatively short, elliptical bundles. Irregular features in B and C resulted from laser de-insulation (pulsed nitrogen laser) that vaporizes some ITO and causes a pressure removal of the methyl-trimethoxysilane resin over the impact area.


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  • Xia, Y, Gross, GW (2003). Histiotypic electrophysiological responses of cultured neuronal networks to ethanol. Alcohol 30: 167-174.

Further reading

  • Johnstone, A.F.M., Gross G.W., Weiss, D.G., Schroeder, O., Gramowski, A. and Shafer, T.J. (2010). Micro-electrode Arrays: A Physiologically-based Neurotoxicity Testing Platform for the 21st Century. NeuroToxicology 31: 331–350.
  • Gandolfo, M., Maccione, A., Tedesco, M., Martinoia, S., Berdondini, L. (2010) Tracking burst patterns in hippocampal cultures with high-density CMOS-MEAs. J. Neural Engineering 7:1-16.

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