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Growing Cells AtopMicroelectronic Chips:Interfacing Electrogenic CellsIn Vitro With CMOS-BasedMicroelectrode ArraysThis paper offers an overview of the fundamentals of bioelectronic measurements,

as well as the design, system integration, and application of CMOS-based microarrays

for recording from and for stimulating electrogenic cells from the brain and heart.

By Andreas Hierlemann, Member IEEE, Urs Frey,

Sadik Hafizovic, and Flavio Heer, Member IEEE

ABSTRACT | Complementary semiconductor–metal–oxide

(CMOS) technology is a very powerful technology that can be

more or less directly interfaced to electrogenic cells, like heart

or brain cells in vitro. To this end, the cells are cultured directly

atop the CMOS chips, which usually undergo dedicated post-

processing to obtain a reliable bidirectional interface via noble-

metal microelectrodes or high-k dielectrics. The big advantages

of using CMOS integrated circuits (ICs) include connectivity, the

possibility to address a large number of microelectrodes on a

tiny chip, and signal quality, the possibility to condition small

signals right at the spot of their generation. CMOS will be de-

monstrated to constitute an enabling technology that opens a

route to high-spatio–temporal-resolution and low-noise elec-

trophysiological recordings from a variety of biological pre-

parations, such as brain slices, or cultured cardiac and brain

cells. The recording technique is extracellular and noninvasive,

and the CMOS chips do not leak out any toxic compounds, so

that the cells remain viable for extended times. In turn, the

CMOS chips have been demonstrated to survive several months

of culturing while being fully immersed in saline solution and

being exposed to cellular metabolic products. The latter re-

quires dedicated passivation and packaging techniques as will

be shown. Fully integrated, monolithic microelectrode systems,

which feature large numbers of tightly spaced microelectrodes

and the associated circuitry units for bidirectional interaction

(stimulation and recording), will be in the focus of this review.

The respective dense microelectrode arrays (MEAs) with small

pixels enable subcellular-resolution investigation of regions of

interest in, e.g., neurobiological preparations, and, at the same

time, the large number of electrodes allows for studying the

activity of entire neuronal networks. Application areas include

neuroscience, as the devices enable fundamental neurophys-

iological insights at the cellular and circuit level, as well as

medical diagnostics and pharmacology.

KEYWORDS | Biomedical electronics; biological neural net-

works; bioelectric phenomena; complementary metal–oxide–

semiconductor (CMOS) integrated circuits; CMOS technology;

microelectrodes; mixed analog digital integrated circuits;

monolithic integrated circuits

Manuscript received December 2, 2009; accepted July 7, 2010. Date of publication

October 7, 2010; date of current version January 19, 2011. This work was supported

by ETH under the Internal Grant TH-00108, and by the Information Societies

Technology (IST) Future and Emerging Technologies program of the European

Union and the Swiss Bundesamt fur Bildung und Wissenschaft (BBW) under Contract

IST-2000-26463.

A. Hierlemann and F. Heer are with the Bio Engineering Laboratory, Department of

Biosystems Science and Engineering, ETH Zurich, CH-4058 Basel, Switzerland

(e-mail: [emailprotected]; [emailprotected]).

U. Frey was with the Bio Engineering Laboratory, Department of Biosystems Science

and Engineering, ETH Zurich, CH-4058 Basel, Switzerland. He is now with IBM Research

Zurich, 8803 Ruschlikon, Switzerland (e-mail: [emailprotected]).

S. Hafizovic was with the Bio Engineering Laboratory, Department of Biosystems

Science and Engineering, ETH Zurich, CH-4058 Basel, Switzerland. He is now with

Zurich Instruments, 8005 Zurich, Switzerland (e-mail: [emailprotected]).

Digital Object Identifier: 10.1109/JPROC.2010.2066532

252 Proceedings of the IEEE | Vol. 99, No. 2, February 2011 0018-9219/$26.00 �2010 IEEE

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I . INTRODUCTION

A high degree of connectivity and the coordinated elec-trical activity of neural cells or networks are believed to bereasons why the brain is capable of highly sophisticatedinformation processing. Likewise, the effectiveness of ananimal’s heart also largely depends on such coordinatedcell activity. To advance our understanding of these com-plex biological systems, high-spatio–temporal-resolutiontechniques to monitor cell electrical activity and an ideallyseamless interaction between cells and recording devicesat both, single-cell and network levels are desired.

Methods to directly measure the electrical activity ofcultured electrogenic cells (e.g., neurons, heart cells,retina cells, or muscle cells) include two fundamentallydifferent techniques: 1) transmembrane measurements byaccessing the cell interior or cytosol with one of the elec-trodes, the so-called Bpatch clamp[ technique [1], [2], and2) extracellular recordings, e.g., by means of externalmicrotransducers [3]–[14]. Additionally, there are indirectmethods like optical measurements using voltage-sensitiveor fluorescent dyes [15]–[17]. The patch clamp techniqueyields very accurate information on the electrophysiolog-ical properties of entire cells, or, alternatively, on currentsflowing through single ion channels. However, it is aninvasive method and is limited in the cell viability time(usually hours) and in the overall number of cells that canbe simultaneously investigated.

For extracellular recordings, the cells are cultured orplaced directly atop the sensors or electrodes [Fig. 1(a)].When electrical activity occurs in a cell, ions flow acrossthe cell membrane within milliseconds. These moving ionsgenerate an electric field, which can directly influence theopen-gate region of a field-effect transistor (FET) [18]–[22], or which can be recorded by means of metalmicroelectrodes [23]–[31]. Extracellular recordings arenoninvasive (no puncturing of the cell membrane), which

enables long-term measurements. Multisite measurements

are possible by arranging many sensors in an array. For

stimulation, voltage transients can be applied by means of

electrodes or stimulation spots, which then evoke a depo-

larization of the nearby cell membrane and solicit

subsequent electrical cell activity. A stimulation spot is a

several-micrometer-diameter spot of either metal or di-

electric materials with high dielectric constant, such as

TiO2 ð" ¼ 34Þ and HfO2 ð" ¼ 15:4Þ, connected to an elec-

trical supply, through which stimulation signals are

applied [32]–[34].The most common biological preparations studied

using microelectrode arrays (MEAs) are divided into two

main categories: acute tissue preparations (e.g., slices),

which are recorded from immediately after they have been

removed from the animal [Fig. 1(b)]; cell cultures, which

can be further divided into dissociated cell cultures and

organotypic tissue cultures. Dissociated cultures are cells

whose relative in vivo positions are no longer preserved[see, e.g., Fig. 19(b)], whereas organotypic tissue cultures

are slices that are maintained in vitro over a period of time.

These variations encompass the spectrum from short-term,

functionally preserved tissue slices to long-term organo-

typic or cell culture preparations.

Several parameters must be taken into consideration

when using MEA chips as a tool for recording from cells.

Most importantly, the cell–electrode interface must beoptimized so that tight coupling between the cells and

electrodes is established, maximizing the signal-to-noise

ratio. The high-density microelectrode arrays (HD-MEAs)

described later (Section IV-E2) are capable of recording

from as deep in the tissue as 100 �m, but the signal-to-

noise ratio drops off rapidly with distance [35]. Acute

slices, for example, have a layer of dead cells that are

damaged during the cutting of the tissue, which introducesa degree of isolation between the active cells and the

Fig. 1. (a) Schematic of a cell attached to a sensor surface. A cell featuring ion channels sits on a planar microsensor (open-gate transistor or

electrode). Moving ions in the electrode vicinity generate an electric field or voltage that is recorded by the microsensor. (b) Micrograph of an

acute cerebellar brain slice (parasagittal cut) placed on a CMOS high-density electrode chip for measurements. The white regions of the slice

constitute myelinated areas, where no electrical activity can be recorded.

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electrodes. To promote the adhesion of cells or the tissuemass, the MEA chips are usually coated with cell-adhesion

substrates such as poly-D-lysine, laminin, collagen, and

fibronectin [36], [37]. Successful tactics for making

recordings from tissue sections utilize, for example,

cellulose nitrate or a coagulated plasma/thrombin clots

to stabilize the slices on the chip surface [38]. Further-

more, a perfusion system usually is necessary for the

delivery of carbogen gas (95% O2/5% CO2) and nutrients,which are required to sustain the physiologic processes of

the cells. Chip-through-holes have been realized on

circuitless chips to further improve nutrient access to the

bottom slice face on the chip and to thus enhance the

viability time [39]. This is very difficult if not impossible to

realize in high spatio–temporal resolution arrays due to

the densely packed circuitry and connection lines in the

chip as will be evidenced in Section IV.Substrate-integrated MEAs enable the study of neuro-

nal information processing [40]–[44] or the characteriza-

tion of cellular responses upon dosing biologically active

agents [25], [45]–[47]. Studying electrogenic cells in vitroprovides different experimental conditions in comparison

to investigating cells in vivo or in intact organisms: Most

animal and plant tissues comprise a variety of different cell

types, whereas a single specific cell type of interest orassemblies of selected different cell types can be grown in

culture. Moreover, the experimental parameters, such as

temperature or concentration of a chemical compound,

can be controlled much more rigorously in cell cultures as

compared to an organism. However, inferences from

in vitro-experiments to the in vivo behavior of cells have to

be experimentally verified. The investigation of acute or

organotypic slices, such as brain or other tissue slices[Fig. 1(b)] may help to bridge the gap between in vitro and

in vivo experiments to some extent [48], [49].

II . WHY USE IC OR CMOS TECHNOLOGY?

This review covers the application of complementary

semiconductor–metal–oxide (CMOS)-based, active micro-

arrays for recording from and stimulation of electrogeniccells in vitro. BActive[ array means that circuitry compo-

nents, such as amplifiers or filter units, are integrated with

the electrodes on the same substrate. The focus will be on

in vitro applications so that needle arrays carrying electrodes

and the respective in vivo applications will be omitted, as they

have been reviewed before in this journal [4], [50].

The three main advantages in using integrated circuit

(IC) or CMOS technology include most importantly1) connectivity; large numbers of transducers or electrodes

can be addressed by on-chip multiplexing architectures;

then 2) signal quality; the signal is conditioned right at the

electrode by means of dedicated circuitry units (filters,

amplifiers); and, less significantly, 3) ease of handling anduse; the devices and signals are robust (no Faraday cages,

digital signals, see below); many functions can be prog-

rammed or automated via user-friendly software anddigital interfaces that directly address digital registers

and logic or memory units on the chip side. Examples of

automation include self-identification of the chip, storage

of calibration or operation parameters, and the execution

of self-test functions. The presence of user-friendly fea-

tures is a crucial issue to encourage neuroscientists and

biologists to adopt such systems.

Traditional MEAs without multiplexers usually offer64 electrodes, with each electrode needing a connection to

external circuitry, which adds parasitic capacitance and

attenuates the small signals. CMOS-based MEAs, however,

comprise up to 16 384 electrodes with the necessary ad-

dressing circuitry on the same chip [49], [51]–[54]. The

high transducer density is an important asset, which

cannot be realized without on-chip multiplexers and ad-

dressing, simply since incorporating thousands of physicalor electrical connections on a millimeter-size chip is

impossible.

On-chip microelectronics provided by IC or CMOS

technology translate into improved system capability. For

example, signal conditioning can be performed on-chip,

ensuring that weak neural signals are faithfully recorded. It

is mandatory to not only amplify the signals but to also

limit the signal bandwidth to avoid noise aliasing in thesubsequent multiplexing. There are only very short

connection lines (a few micrometers) between electrode

and signal conditioning circuitry, and there are no long

lead lines running close to saline or the electrically active

culture under a thin layer of insulation. Therefore, any

interference with the target signals is largely obviated so

that Faraday cages and electrical shielding are not needed.

CMOS systems provide bidirectional communication viathe electrodes as they feature stimulation and recording

units. Active circuitry allows the stimulation of cells via

single or multiple electrodes in arbitrary configurations

from the set of densely packed electrodes, all while re-

cording from other electrodes without interruption. On-

chip analog-to-digital conversion (ADC) means that the

chip produces signals that may be easily manipulated and

transferred without compromising its information content.There is no influence of mechanical and electrical con-

nections (spring contacts) that cause problems for small

analog signals. Finally, the complete system can be mono-

lithically integrated on a single chip, which features an

area on the order of 20–40 mm2. The resulting measure-

ment setups are small, easily transportable and can be used

on a lab bench, or several of the devices can be placed in an

incubator with only a flat-band cable making connection tothe rest of the setup (see Section IV-E3).

As yet, the detailed structure of the extracellular-

potential landscape of a neuron and its dynamics are still

mostly unknown, since the signal-to-noise ratio and the

spatial resolution in the recordings of extracellular poten-

tials are, in most cases, low. This prevents a clear sepa-

ration of individual signal sources and an unambiguous

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reconstruction of the neuronal networks derived from fieldpotentials or multiunit recordings [55]. HD-MEAs, real-

ized in standard CMOS technology, offer the potential to

perform recordings at single-cell or even subcellular reso-

lution [53]. The devices, however, have to meet two re-

quirements. They have to provide 1) high signal-to-noiseratio in the recordings of very small signals and, at the

same time, they have to enable 2) high spatial and temporalresolution measurements. The dilemma is that the two re-quirements are diametrically opposed in a technical reali-

zation. High spatial resolution entails the use of small

electrodes featuring higher thermal noise and that only

very few and small circuitry elements for addressing and

signal amplification can be realized per electrode. The

smaller the available space for electrodes and circuitry is,

however, the larger the noise is, since the noise of a tran-

sistor scales inversely with size, and since filters or am-plifiers requiring large capacitors cannot be realized. This

means that the signal quality is compromised by the cir-

cuitry generally needed to readout such high-density

arrays. Therefore, several devices to date feature a com-

parably high noise level that prevents the revelation of

electrophysiological details. There are, however, work-

arounds as will be shown in Section IV-E2.

A disadvantage of CMOS chips is that silicon is nottransparent to visible light in contrast to standard cell

culture substrates used in biology. Additionally, the chip or

its components may corrode upon operation and long-term

exposure. This holds particularly true as CMOS chips are

usually not made for being immersed in salt water over

extended times (weeks and months). Moreover, as soon as

stimulation features are implemented on-chip, severe

problems may arise from electrochemistry upon deliveringcurrent or voltage pulses and from the different redox

potentials of the variety of exposed materials, which may

generate local electrochemical elements and cause massive

corrosion (e.g., complete dissolution of CMOS metal alu-

minum). Therefore, a good packaging solution is needed,

on the one hand, to protect the chip against metabolic

products and chemicals of the cell culture, and, on the

other hand, to prevent the cells from being poisoned ordisturbed by toxic materials released by the chip, such as

the CMOS metal aluminum (also copper in modern pro-

cesses) that dissolves in saline solution. Viable solutions

will be presented in Section IV.

In the following, this review will first provide a short

introduction to the fundamentals of bioelectronics and

bioelectronic measurements (Section III), and then, an

overview on the design and application of CMOS-basedMEAs for interacting with electrogenic cells in vitro(Section IV). All systems feature the sensors or transducers

and the circuitry components on the same chip (monolithic

design). CMOS circuitry-only chips featuring recording

and/or stimulation units (see, e.g., [56] and [57]), which

are then connected to separate circuitless electrode array

chips (mostly on glass substrates), will not be covered here.

III . FUNDAMENTALS OF RECORDING OFELECTRICAL CELL ACTIVITY

A. Electrogenic CellsMany types of cells in the body have the ability to

undergo a transient electrical depolarization and repo-

larization that is either triggered by external mechanisms

(e.g., motor-nerve stimulation of skeletal muscle, or cell-

to-cell depolarization in the heart) or by intracellular,spontaneous mechanisms (e.g., cardiac pacemaker cells)

[58]. Cells that exhibit the ability to generate electrical

signals are called electrogenic cells, the most prominent of

which include brain cells or neurons and heart cells or

cardiomyocytes. Only a brief description of the biology of

electrogenic cells will be given in this section; for more

details the reader is directed to various books on this topic

[58]–[60].A huge number of neuronal cells form the nervous sys-

tem that regulates all aspects of body functions. The hu-

man brain contains about 1012 neurons (nerve cells) with

each neuron forming thousands of connections to other

neurons so that a large network of electrical connections

with massively parallel information processing character-

istics results. The output of a nervous system is the result

of its inputs and its circuit properties, that is, of the wiringor interconnections (synapses) between the single neu-

rons, and of the strength of these interconnections. The

synaptic connections between neurons can be reorganized,

which is known as synaptic plasticity, and is believed to be

a mechanism of learning in our brain. Different types of

neurons can be distinguished according to their physiology

and function in the body [58], [60].

Neurons exhibit four distinct regions with differentfunctions: the cell body, the dendrites, the axon, and the

axon terminals (Fig. 2). The cell body or soma with a dia-

meter of 10–30 �m contains the nucleus and is the pro-

duction site of most neuronal proteins. The majority of

neurons have a single axon, whose diameter varies from a

micrometer in the human brain to a millimeter in the giant

squid. Axons are specialized for the conduction of elec-

trical pulses, termed action potentials, away from the cellbody towards the axon terminals. Most of the neurons are

polarized: They receive synaptic input at the dendritic end

and provide output through synapses at the axonal end

(Fig. 2) [58].

Fig. 2. Schematic view of a neuron. Modified from [58].

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Neurons communicate with other neurons through

specialized contact zones, which are called synapses. Sy-napses generally transmit signals in only one direction,

from the axon terminal of the presynaptic cell to the den-

drites of the postsynaptic cell. Synapses can be either

electrical or chemical [58], [60]. Electrical synapses are

normally located at the gap junctions, which consist of

specialized proteins that form channels bridging the in-

teriors of two neurons and allow current flow from one

neuron to the other. In a chemical synapse, action po-tentials trigger the secretion of neurotransmitters in the

presynaptic neuron. The neurotransmitters then diffuse

across the synaptic cleft (20–25-nm width), and bind to a

receptor site on the postsynaptic membrane and cause

electrical signals there. The time required for this process,

the so-called synaptic delay, is typically 0.3–0.5 ms. The

synapse is an important feature for neural networks to

learn and to perform computation.Different ion concentrations inside and outside the

neuronal cell lead to an electric potential across the plasma

membrane (Fig. 3). In virtually all cases, the inside of the

cell membrane is negatively charged relative to the outside

[58], [60], i.e., a concentration gradient of ions between

the extracellular and the intracellular space (cytosol)

exists. Ion channels are embedded transmembrane proteins

that allow for the selective passage of certain ions. Ionchannels are termed gated if they can be opened or closed.

There are three types of gated ion channels: ligand-gated,

mechanically gated, and voltage-gated channels. The con-

centration of Kþ ions inside typical metazoan cells is about

ten times larger than that in the extracellular fluid, where-

as the concentrations of Naþ and Cl� ions are much higher

outside the cell than inside (Fig. 3). These concentration

gradients are maintained by membrane proteins that are

capable of pumping ions from one side of the membrane tothe other, often against their concentration gradients,

which consumes energy. There are additional types of ion

channels involved, but the membrane potential of most

electrically active cells is primarily affected by the opening

and closing of ion channels for Kþ, Naþ, Cl�, and

sometimes Ca2þ [58], [60].

The concentration gradient across the cell membrane

leads to an electrical potential, which is called restingpotential. The resting potential is mainly a consequence of

the membrane permeability to Kþ ions. The plasma mem-

brane contains resting Kþ ion channels, which are open in

the resting state and allow the passage of only Kþ ions. The

Kþ ions move across the membrane down their concen-

tration gradient, which leaves an excess negative charge on

the cytosolic face and deposits positive charge on the

exoplasmic face

Ex ¼RT

zxFln

cox

� �

dcixe: (1)

A variant of the Nernst equation (1) allows us to calcu-

late the maximum potential difference across a membrane

Ex (electromotive force), for any ion x at concentration cx.

Ex is given by the product of the thermal voltage RT=zxFand the concentration difference. R is the molar gas

constant, T is the temperature in Kelvin, zx is the number

of exchanged charges (1 for Kþ, Naþ, and Cl�), and F is theFaraday constant. The superscripts Bi[ and Bo[ denote the

ion concentration inside and outside the cell, respectively

[see (1)]

VM ¼RT

F� ln ½Ko�PK þ ½Nao�PNa þ ½Cli�PCl

½Ki�PK þ ½Nai�PNa þ ½Clo�PCl: (2)

The electric potential VM across a cell membrane can

be calculated by the Goldman–Hodgkin–Katz voltageequation (2), a more complex variant of the Nernst

equation, in which the concentrations of the ions are

weighted in proportion to the magnitudes of their trans-

membrane permeability constants P. P is a measure of the

ease with which an ion can cross a unit area of a membrane

driven by a one-molar difference in concentration; it is

proportional to the number of open ion channels and the

number of ions that each channel can conduct per second.Thus, PNa, PK, and PCl are measures of the Bleakiness[ of a

unit area of the membrane to these ions. The permeability

of the membrane to Naþ and Cl� ions is about one tenth

of that for Kþ, since there are about ten times more open

Kþ channels than open channels for Naþ or Cl�. In

theory, the resting membrane potential may be anywhere

between EK (�90 mV), the potassium equilibrium

Fig. 3. Intra- and extracellular ion concentrations for the species

primarily involved in the electrogenic properties of the neuronal

membrane, Naþ, Kþ, and Cl�. Redrawn according to [58]. Note that the

outside cell membrane is considered to be positively charged.

A� denotes all nonchloride anions (phosphates, etc.).

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potential, and ENa (55 mV), the sodium equilibrium po-

tential. By inserting the typical ion concentrations into (2),

the potential of the resting membrane amounts to, e.g.,

�62 mV for the squid giant axon. Most neurons feature

resting potentials around �60 mV.

An action potential event is largely the result of

voltage-gated ion-channel conductances that cause a depo-

larization and repolarization of the neuronal plasma mem-brane within 2–3 ms [Fig. 4(a)]. The resting potential

across the membrane is, as already mentioned, maintained

by large transmembrane proteins that pump ions, against

their electrochemical gradient, in and out of the cell. The

action potential is triggered when the membrane is depo-

larized to a threshold value causing voltage-gated ion

channels to open. Naþ ions then flow down their elec-

trochemical gradient across the cell membrane (inwardcurrent, INa), further depolarizing the membrane. Depo-

larization causes Kþ ion channels to open, causing a cur-

rent flow in the opposite direction (outward current, IK)

that repolarizes the membrane [see Fig. 4(a)]. Finally, all

ion channels relax to their original state, and the mem-

brane returns, often after a brief hyperpolarization (mem-

brane potential more negative than resting potential), to

its resting potential. It has to be noted that the occurrenceof an action potential is an electrical event generated by a

change in the distribution of charge across the membrane

and not by a marked change in the overall intracellular or

extracellular concentration of Naþ or Kþ ions (ion con-

centration change of less than 1 per mill inside the cell).

Action potentials propagate unidirectional from the

axon hillock down the axon to the axon terminals (Fig. 2).

This is due to the fact that the voltage-gated Naþ channels

remain inactive for several milliseconds after opening, a

time span called the refractory period [58], [60]. The

inability of Naþ channels to reopen during the refractory

period also limits the number of action potentials per

second that a neuron can conduct.

Cardiac muscle cells, also denoted cardiac myocytes (or

cardiomyocytes), share similarities with skeletal muscle

cells with regard to their striated appearance and contrac-tion. A coordinated and synchronous activity of the cardio-

myocytes is necessary to effectively pump blood through

the vessels. Therefore, there is a direct connection be-

tween the cytoplasms of cardiac cells, called gap junctions,

which allows various molecules and ions to pass freely and

without attenuation. Accordingly, a depolarization wave

rapidly spreads through those direct connections without

characteristic temporal delay, which is observed forneuronal chemical synapses [58]. This direct cell-to-cell

connection means that one usually does not observe single-

cell action potentials, but so-called Bfield potentials[ upon

using extracellular electrodes to record from cell ensem-

bles. Field potentials are comparably large-amplitude

signals that result from simultaneous, collective electrical

activity of patches of electrogenic cells.

There are two general types of cardiac action poten-tials: 1) nonpacemaker action potentials, which are found

throughout the heart, and 2) spontaneous action potentials

of pacemaker cells. The latter are found in the sinoatrial

and atrioventricular nodes of the heart [6], [58]. Both

types of action potentials in the heart differ considerably

from those of neuronal cells in the duration of the action

potentials [neuronal cell about 1 ms; see Fig. 4(a); cardiac

action potential from 200 to 400 ms; see Fig. 4(b) and (c)]

Fig. 4. Schematic, time course, and current contributions of action potentials of different electrogenic cells as measured intracellularly.

Arrows pointing to the right represent ion currents flowing into the cell, arrows pointing to the left represent outward currents. (a) Neuron: Onset

of the action potential at 0.5 ms; the membrane potential becomes more positive (depolarization) through Naþ influx. After 1 ms return via

hyperpolarization state (potential more negative than resting potential) to resting potential through opening of Kþ channels: Kþ efflux.

Adapted from [58]. (b) Cardiomyocytes (ventricular myocyte): The numbers 0–4 mark the initial rapid depolarization phase (0), an initial

repolarization phase (1), a plateau phase (2), a rapid repolarization phase (3), and the membrane resting potential (4); for more information,

see text. (c) Action potential of a cardiac pacemaker cell: The numbers here mark the depolarization phase of the action potential (0),

a repolarization phase (3), and a spontaneous depolarization phase (4); for more information, see text.

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and the involved ion channels. In neuronal and nonpace-maker cardiac cells, the depolarization phase of the action

potential is caused by an opening of sodium channels,

whereas in cardiac pacemaker cells, calcium ions are in-

volved in the initial depolarization.

Nonpacemaker cardiac cells have a true resting mem-

brane potential [phase 4, Fig. 4(b)] that remains near the

equilibrium potential for Kþ ðEKÞ. When these cells are

rapidly depolarized to a threshold voltage of about�70 mVby another conducted action potential (phase 0), a fast

Naþ-current INa flows into the cell. At the same time, the

outward Kþ current IK is interrupted. These two changes

in ionic currents move the membrane potential farther

away from the resting potential and closer toward the

sodium potential. Phase 1 then represents an initial repo-

larization caused by the opening of a special type of Kþ

channel producing a transient outward Kþ current, IKðtoÞ.However, due to the large increase in the slow inward

Ca2þ current ICaðlÞ, the repolarization is delayed, and there

is a plateau phase in the action potential (phase 2). This

inward calcium movement is through long-lasting (l-type)

calcium channels that open up when the membrane

potential depolarizes to about �40 mV. Repolarization

(phase 3) occurs, when the outward Kþ current IK in-

creases again, and the Ca2þ current ICaðlÞ decreases.Therefore, the action potential in nonpacemaker cells is

primarily determined by changes in fast Naþ, slow Ca2þ,

and Kþ currents. During phases 0, 1, 2, and a part of

phase 3, the cell is refractory to the initiation of new action

potentials, i.e., the cell does not show any electrical

response.

Pacemaker cells are characterized as having no true

resting potential, but instead generate regular, spontane-ous action potentials [58]. There are, in fact, no fast Naþ

currents operating in those cells [Fig. 4(c)]. At phase 0, the

depolarization is primarily due to increased inward Ca2þ

currents ICaðlÞ. As the movement (or conductance) of Ca2þ

through the channels is not rapid, the rate of depolariza-

tion (slope of phase 0) is much slower than in other cardiac

cells. Repolarization occurs (phase 3) as the outward Kþ

current IK increases and the Ca2þ current ICaðlÞ decreases.Spontaneous depolarization (phase 4) is due to a fall in the

Kþ current IK and a small increase in the Ca2þ current

ICaðtÞ. A slow inward Naþ current also contributes to

phase 4, and is thought to be responsible for what is

termed the pacemaker or Bfunny current[ If . Once this

spontaneous depolarization reaches threshold (approxi-

mately �40 mV), a new action potential is triggered.

Although pacemaker activity is spontaneously generated,the rate of this activity can be modified significantly by

external factors such as autonomic nerves, hormones,

ions, and ischemia/hypoxia.

The rhythm of the heart is normally generated and

regulated by pacemaker cells within the sinoatrial (SA)

node, which is located within the wall of the right atrium.

SA nodal pacemaker activity normally governs the rhythm

of the atria and ventricles [6]. When this rhythm becomesirregular, too fast (tachycardia) or too slow (bradycardia),

or the frequency of the atrial and ventricular beats are

different, then this is called an arrhythmia [6]. Arrhyth-

mias can develop from either altered impulse formation or

altered impulse conduction. The former concerns changes

in rhythm that are caused by changes in the automaticity of

the pacemaker cells or by abnormal generation of action

potentials at sites other than the SA node. Altered impulseconduction is usually associated with a complete or partial

block of electrical conduction within the heart and

commonly results in reentry, which can lead to tachyar-

rhythmias. Many origins of arrhythmia, e.g., the so-called

QT-prolongation (Q and T denote specific features in the

waveform of an electrocardiogram), a delayed repolariza-

tion following the depolarization or excitation of the heart

[47], can be also observed in cell cultures, which opens alarge field of applications for MEAs in the pharmaceutical

industry (see also Section IV-E4) [25], [61].

B. Electrical Interface and Signal RecordingThe electrical interface includes the cell membrane in

physiological solution on the one hand and the transducer

on the chip on the other hand. The electrical properties of

the cell membrane are usually described by the gate model

of Hodgkin and Huxley [62]. The gate model has been

developed studying the squid axon and proposes that ion

currents are flowing through transmembrane channelsdown their concentration gradients. The channels feature

voltage-sensitive gating or gating particles. Fig. 5 shows the

equivalent circuit of the neuronal membrane according to

the gate model of Hodgkin and Huxley. The equivalent

circuit consists of parallel branches for the different ionic

contributions and the membrane capacitance. The tunable

resistors represent voltage-gated ion channels, and gx and

Ix denote the specific voltage- and time-dependent con-ductance for ion x and the current carried by ion x (e.g.,

Naþ, Kþ, and Cl�). The voltage sources arise from ionic

concentration gradients across the cell membrane, and the

Nernst potential Ex represents the equilibrium potential of

ion x according to (1). The main ionic currents include the

potassium current IK, the sodium current INa, and some

smaller currents summarized in a leakage current IL:. The

resulting total membrane current is then described by

IM ¼ CMdVM

dtþX

x

Ix

¼ CMdVM

dtþX

x

gxðVM; tÞðVM � ExÞ (3)

where IM is the total membrane current, CM is the mem-

brane capacitance, and VM is the membrane potential. For

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more information on this model, the interested reader isdirected to [59] or, for cardiac cells, to [6].

As an example, neuronal electrical signals or action

potentials are shown for intracellular patch clamp mea-

surements (compare Fig. 4) and extracellular measure-

ments on the right-hand side of Fig. 5. The signals have

been recorded from the cell soma. The extracellularly

recorded signals feature an amplitude that is three orders

of magnitude lower than that of intracellular signals and abipolar shape with first a negative and then a positive peak

with respect to the baseline. The bipolar signal is similar to

that of lose patch clamp and can be explained with the

position of the electrode outside the cell: First, fast Naþ

current flows away from the electrode into the cell (nega-

tive peak), and, later, a somewhat slower current of Kþ

ions flows out of the cell towards the electrode (positive

peak). The intracellularly measured signals (Figs. 4 and 5)show almost opposite characteristics: A positive peak upon

the fast inward Naþ current and a small swing through

negative territory upon the outward Kþ current. In gene-

ral, there is a large variety of signal shapes and amplitudes

in extracellular recordings; examples will be shown in

Section IV-E4. These depend on the relative position of the

electrode with respect to the signal generating entity

(cluster of cells, single cell, soma, axon, dendrites), thenature of the cells under investigation, and the direction of

signal propagation. The analytical methods of electrical

cable theory are usually applied to investigate and explain

neuronal signal propagation [59]. For details on modeling

extracellular potentials and correlations between extracel-

lular and intracellular waveforms, the reader is referred to

[63] and [64].

The signal amplitude also depends on the cell size.Larger cells tend to yield higher signals, as the transmem-

brane currents that are needed to depolarize the cell arelarger in comparison to small cells. These currents depend

on the type and the number of contributing ion channels

and on the spatial distribution of the ion channels. Another

important issue is the distance between the transducer and

the neuron: the closer the cell is to the transducer, the

larger is the recorded signal. A third aspect includes the

resistance of the extracellular space to the different cur-

rents. A large resistance to spreading currents, or largesealing resistance, will entail high signals. The sealing

resistance Rseal in Fig. 5 can assume values between 1 and

10 M� [65]–[67]. The resistance to currents from the cell

to the electrode, i.e., the resistance of the gap between cell

and transducer Rgap, should be as low as possible and is a

function of the contact area, of the width of the gap, and of

the electrolyte resistance. In most dissociated cell cultures,

Rgap is much smaller than Rseal and can be neglected.Also important is the sensor/transducer size. Ideally,

the transducers should be as small as possible, since large

transducers will measure a potential averaged over a large

area, which reduces the peak signal amplitudes. On the

other hand, the use of smaller transducers may entail

higher noise levels in the signals, which may counterbal-

ance or even outbalance the small-size advantage. In dis-

sociated cultures, the cells are usually very close to theelectrodes, yielding large signals. Moreover, when large

neurons, such as snail neurons [68], are used, the signals

can reach up to tens of mV; in the case of cultures of

smaller mammalian neurons, they still can reach several

mV [69]. High-density cultures provide larger signals in

comparison to low-density cultures, as the sealing resis-

tance in the extracellular space is larger due to many

tightly spaced cells (ions have to move in the space belowthe cells along the transducer surface and cannot escape

Fig. 5. Electrical equivalent circuit of a cell membrane adjacent to a sensor, in this case, a metal electrode. The equivalent model of the

membrane relies on the Hodgkin–Huxley model of the squid axon [62]. The electrode is represented by a capacitor and resistor in parallel.

For details, see text. On the right-hand side, an intracellular neuronal signal recorded by using the patch clamp technique and an extracellular

signal recorded by means of a metal electrode are displayed for comparison, along with the involved ion currents. The Naþ-current flows into

the cell, and the Kþ-current flows outward. Note the three-orders-of-magnitude difference in signal amplitudes.

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into the open solution). Slices generally produce consid-

erably smaller signals, as a layer of cell debris is between

the intact cells and the electrodes.

The extracellular transducer or sensor, which records

the electrical signals, i.e., the potential changes upon ion

movement, is, in most cases, a metal electrode or an open-

gate field-effect transistor (OGFET); see Fig. 6 [70]. Thecell preparation is usually placed or cultured directly atop

the transducer element (Figs. 5 and 6), i.e., the transducer

is immersed in the physiological culture solution for days,

weeks, or months. The first extracellular recordings using

arrays of microelectrodes or OGFETs were performed in

the 1970s [20], [21], [30], [71].

Metal electrodes and OGFETs can be arranged in 2-D

arrays for in vitro applications. The same metal electrodescan be used for recording and for stimulation, since the

metal electrode/electrolyte impedance can be very low

(metal electrodes are not suitable for the measurement of

dc potentials due to electrode polarization [72]). An open

FET used for recording is, in most cases, accompanied by a

capacitive-type stimulation spot that then triggers electri-

cal cell activity [32]–[34]. In the case of the OGFET, firing

electrogenic cells change the extracellular potential in thegap between cell and the exposed gate oxide of the tran-

sistor (Fig. 6), which directly modulates the source-drain

current [Fig. 6(a)]. In common metal–oxide silicon (MOS)

FETs, the low-frequency noise is caused by electrons tun-

neling between silicon and traps in the gate oxide. This

noise is reduced when the electron channel of the tran-

sistor is buried in the silicon substrate, a few nanometers

away from the interface.The interface capacitance of an open-gate transistor

(electrolyte–oxide–silicon capacitance: 1.48 �F/cm2 for

TiO2 or 0.22 �F/cm2 for SiO2 [34]) is small in comparison

to that of a metal electrode (electrolyte–metal capacitance:

20–50 �F/cm2 depending on metal; see, e.g., [73]), which

renders stimulation more difficult due to the low charge

transfer capability. It also has to be noted that many of the

traditional OGFET devices need a strong biasing (positivebias with respect to the ionic solution) to avoid the pene-

tration of sodium and other ions in the open gate region,

which will diffuse into the device and alter the transistor

characteristics [74]–[78]. This problem has been alleviated

through the use of passivation layers and so-calledBextended-gate[ architectures as will be described below.

Metal electrode arrays have been used by several labo-

ratories to perform extracellular recordings [3], [9], [46],

[79]–[84], and electrode-based systems are commercially

available.1 These commercial systems mostly include passive

metal electrode arrays on glass or silicon substrates with

external signal conditioning and recording components.

The metal electrode/electrolyte interface is character-ized by a capacitive process resulting from redistribution of

charged and polar particles in the electrode vicinity with

no charge transfer between the solution and the electrode,

and a component resulting from the electron exchange

between the electrode and a redox species in the solution,

termed Faradaic process (Fig. 7). In a non-Faradaic scena-

rio, the electrode is typically highly polarized and behaves

almost as an ideal capacitor. For any electrode/electrolyteinterface, however, there is a range of potentials, in which

charged particles such as electrons are able to pass across

the interface. Charge transfer typically involves oxidation

or reduction reactions.

Platinum electrodes in physiological saline are gener-

ally modeled using both Faradaic and non-Faradaic pro-

cesses. The immersion of a metal in an electrolyte results

in the formation of space charge layers near the electrodesurface, the so-called Stern layer [85], which includes

layers of water dipoles or opposite-charge ions and their

hydration shells. These layers entail capacitive contribu-

tions to the overall electrode/electrolyte interface char-

acteristics. The distribution of the charges within a certain

distance from the electrode is taken into account using the

Gouy–Chapman model [85]. Fig. 7 shows the resulting,

commonly used equivalent-circuit model of the electrode/electrolyte interface. The model consists of a constant-

phase-angle impedance ZCPA, a charge-transfer resistance

RCT, the Warburg impedance ZW, and a serial resistance

Fig. 6. (a) Open-gate field-effect transistor (OGFET). (b) Extended-gate

field-effect transistor (EGFET) in CMOS implementation. Reprinted

from [70] and adapted from [51] with permission.

1Multi Channel Systems GmbH, Reutlingen, Germany (www.multi-channelsystems.com); Alpha MED Scientific Inc., Osaka, Japan(www.med64.com); Plexon Inc., Dallas, TX (www.plexon.com); AlphaOmega Co., Alpharetta, GA (www.alphaomega-eng.com); Bionas GmbH,Rostock, Germany (www.bionas.de).

Fig. 7. (a) Commonly used equivalent circuit model of the electrode/

electrolyte interface. (b) Simplified model, which is a suitable

approximation for extracellular recordings.

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RS [86]–[88]. The empirical non-Faradaic constant phase-angle-impedance is given by ZCPA ¼ Kði!Þ�� where K is a

measure of the magnitude and � is a measure of the de-

viation from purely capacitive behavior ð� ¼ 1Þ. Typically,

� is between 0.7 and 0.9 [73], [86]–[89]. RCT is the

Faradaic charge transfer resistance. For platinum, the

charge-transfer resistance is in the range of several hun-

dred megaohms [73]. The Warburg impedance ZW takes

into account that ions, produced on the surface of theelectrode, need to diffuse away. This impedance is negli-

gible for large charge-transfer resistances, which produce

only small Faradaic currents. RS is the electrical resistance

between measuring electrode and counter electrode. This

resistance is on the order of kiloohms and can be neg-

lected. A simplified model version is given in Fig. 7(b),

which is also used as transducer or sensor equivalent cir-

cuit in Fig. 5. It includes a capacitor CE, in parallel to aresistor RCT. The time constant of this structure is given by

RCT � CE (on the order of 1 Hz or lower) and is below the

signal band of typical cellular signals (kilohertz range), so

that the electrode/electrolyte interface can be approxi-

mated by a capacitor.

The impedance of the microelectrode is an important

parameter for extracellular recording, since it determines

the noise of the electrode and the signal attenuation.Commonly used electrode materials include platinum

black [89]–[91], titanium nitride [26], [92], indium tin

oxide (ITO) [45], and iridium oxide [93]. Platinum black

and titanium nitride (regular columnar structure) form

high-surface area coatings with low electrode impedance,

which is beneficial with regard to noise performance.

Titanium nitride and iridium oxide feature comparably

high specific charge transfer capability, so that thesematerials are frequently used for stimulation electrodes

[92]. ITO is transparent so that the cells can be observed

from the bottom with standard microscopy tools for

biology. More recently, carbon nanotubes have also been

used as electrode material [94]–[97].

In addition to planar electrodes, 3-D designs have been

developed, such as pyramid-shape electrodes to achieve

better quality recording from slices as they may penetratethrough the outermost layer of dead cells [26], [27], or,

more recently, nail-shape electrodes, which are intended

to be internalized and overgrown by neurons or neurites

(see Fig. 8) [98], [99]. The nail-shape electrodes have been

applied to cell lines, but not yet to wild-type cells. It will be

very interesting to see which information can be extracted

from an array of nail-type electrodes, as the recording

scenario resembles that of multilocation patch clamp ex-periments [98] rather than that of planar multielectrode

arrays, where many neurons contribute to the signals

recorded from the respective electrodes.

Finally, it has to be noted that there is not a large

difference between the two transducer types, OGFET and

metal electrode, and the respective front-end readout

schemes in CMOS implementations. The transistor gates

are located at the bottom of the CMOS layer stack, assource and drain are diffused into the monocrystalline

silicon before the deposition of the dielectrics and metal

layers. To enable access to those transistor gates in order to

realize OGFETs, one would have to etch away all the layers

above the gate, which is occasionally done for chemical

sensors [100]–[102]. However, it is much easier to imple-

ment the so-called Bextended-gate[ FETs (EGFETs). In

EGFETs metal wiring through CMOS vias and the metallayers is used to electrically connect a metal electrode at

the surface of the CMOS layer stack down to the transistor

gate [Fig. 6(b)] [51]. To ensure a capacitive interface and

an Bopen-gate-like[ electrochemical situation, a dielectric

with high dielectric coefficient (TiO2, HfO2, ZrO2 [34]) is

afterwards deposited on the metal electrode. This dielec-

tric material is then in contact with the electrolyte solution

[Fig. 6(b)] [51], [68], [103]. For metal electrodes, inreturn, usually a filter capacitor (high-pass filter, compa-

rably large capacitance) is implemented in between the

metal electrode, which directly contacts the electrolyte

solution, and the first amplifying transistor (see Fig. 18 in

Section IV-E1) [104], [105]. So for both transducers, a

largely capacitive recording situation can be assumed, be it

through a layer of dielectric material at the interface

(EGFET), or through a CMOS filter capacitor (metalelectrode).

C. Extracellular StimulationStimulation capability is a crucial feature, especially in

the field of neuroscience, to expose the neuronal culture to

certain stimulus patterns, to repeatedly apply identical

patterns to achieve a Btraining[ of the neuronal colonies,

or to do closed-loop experiments [106]. To advance theunderstanding of network dynamics, a large number of

bidirectional electrical interfaces to the neuronal network,

i.e., stimulation and recording sites are needed. An ideal

system for stimulation includes the following features:

• possibility to stimulate any subset of electrodes;

• flexibility in the stimulation waveform;

• current and voltage stimulation capability;

Fig. 8. (a) Schematic representation of a neuron engulfing a

micronail-structured electrode. The tight junction between the cell

membrane and the sensor surface increases the sealing resistance

between cells and electrodes as compared to planar electrodes.

(b) Electron micrograph depicting a cross section through a PC12 cell

(neuronal cell line) engulfing three functionalized gold micronails.

The gold micronail in the center of the image was cut only through the

head, and the other two were cut along the micronail’s head and stalk.

Reprinted with permission from [98].

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• capability to do a fast switching from stimulation torecording even on the same electrode.

The so-called real-time all-channel stimulator (RACS)

by Wagenaar and Potter [107] based on discrete off-chip

components meets these requirements. The stimulation of

neuronal cells can be performed by means of current or

voltage pulses. Intracellular stimulation during patch

clamp measurements is usually done in the current

mode, since the stimulation of neurons in their naturalenvironment also occurs through current inputs to their

dendritic tree. For extracellular stimulation, both voltage

stimulation [13], [108], [109] and current stimulation [13],

[105], [110]–[112] methods are widely used.

For current stimulation, a voltage-limiting element is

required in order to prevent electrolysis, which may

change the local pH, produce undesired electrochemistry,

or damage the electrode. The applied current and, conse-quently, the number of charges released into the culture

can be controlled. However, beyond the electrode, the

exact current paths and the current density that arrives at a

targeted cell are not known. It has been found that in most

cases negative current pulses are very effective to excite

neurons to fire action potentials [107], [110]. In case of

voltage stimulation, the applied voltage at the electrode

during stimulation can be controlled so that no electrolysiscan occur as long as the voltage is small enough, but the

current flowing into the preparation is unknown. Biphasic

voltage-controlled pulses with the first part of the pulse

having a positive voltage sign constitute most effective

stimuli, since the sharp downward voltage transient be-

tween the positive phase and the negative phase corre-

sponds to a strong negative current pulse.

The pulse amplitude and its duration determine thestimulus efficacy [107], [111]. The number of cells that are

directly stimulated through a defined, voltage-controlled

pulse grows with the amplitude of the respective pulse

[107], [113]. The pulse must be strong and long enough to

allow the cell membrane and all parasitic capacitances in

the system to charge. Normally, the pulse amplitude is in

the range of hundred to several hundred microvolts, al-

though pulse trains of weak capacitive stimuli can also beused as has been published recently [32], [33]. Another

important parameter is the electrode impedance, since it

determines the current for a given voltage transient and

the voltage on the electrode for a given current transient,

respectively.

Electrical stimulation pulses are on the order of 1 V,

whereas the cell signals are typically on the order of

100 �V. The large disparity between the voltage ranges forstimulation and recording leads to artifacts in the recorded

signals, which can easily interfere with or completely mask

action potentials, even on electrodes that are rather distant

from the stimulation site. This stimulation artifact can be

removed by using software approaches [114], [115], which

are computationally expensive and often require real-time

processing. Moreover, hardware approaches, based on

active suppression circuits, have been successfully devel-oped (see also Section IV-E4b) [81], [104].

In a practical application, effective stimuli need to be

found that do not damage electrodes or cells and minimize

stimulation artifacts that interfere with the recording of

responses. For long-term experiments, it is crucial to pre-

vent damage to the electrodes and damage to the cells. The

latter may result from high charge injection or high charge

densities [116]. There is a couple of choices that have to bemade, which include 1) the electrode material; 2) the

electrode configuration, i.e., the selection of a specific

electrode or a set of electrodes to stimulate a target neuron

or neuronal colony; 3) the decision to use voltage or cur-

rent control; and 4) the selection of a stimulus waveform

and pulse duration (monophasic, biphasic, multiphasic or

asymmetric, etc.). For more details, see [111]–[119]. Any

stimulation will, however, affect the electrochemical equi-librium or, at least, the ionic distribution in the vicinity of

the stimulating transducer.

IV. INTEGRATED CMOS-BASEDSYSTEMS FOR IN VITRO APPLICATIONS

OGFETs in semiconductor technology have been devel-

oped in the group of P. Fromherz, Martinsried, Germany[3], [18], [120], and by Offenhausser et al. [121], [122]. A

CMOS-based approach making use of palladium (Pd) elec-

trodes has been reported on by Baumann et al. [123]. None

of these initial semiconductor-based devices exhibit any

on-chip circuitry or electronic components other than the

transducers themselves (FETs, electrodes).

As discussed in the introduction, the use of on-chip

microelectronics is imperative for the realization of largeror high-density multitransducer or multielectrode arrays

with stimulation and recording capabilities. High-density

multielectrode arrays, designed according to the pixel

concept (repetition of circuitry unit with each electrode),

which feature integrated multiplexers and in-pixel ampli-

fiers, have been presented by Berdondini et al. [91],

[124], [125]. Using the chip, one can simultaneously

record from 4096 electrodes featuring a 42-�m pitch. AnOGFET- or EGFET-based multitransducer design featur-

ing 16 384 transducers at 7.8-�m pitch was developed by

Eversmann et al. [49], [51]. This system features only a

single EGFET and two switching transistors per recording

site. Both high-density approaches exhibit limited area for

the in-pixel circuitry, and stimulation capability has not yet

been included. A variant of the OGFET-based chip with

stimulation features is under development. A CMOS chipwith on-chip stimulation capability, realized as an integ-

rated stimulation electrode located outside but close to the

recording-electrode array, has been presented by the group

of Kovacs at Stanford University [126]. Finally, monolithic

CMOS MEAs featuring 128 bidirectional electrodes in a

low-density design (pixel concept), or 11 011 bidirec-

tional electrodes in a high-density design (switch-matrix

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approach as discussed in Section IV-E2) with full on-chipsignal conditioning and ADC have been presented by

Heer et al. [105], [127], [128] and Frey et al. [53], [129]. All

these systems will be detailed in the subsequent sections.

In general, high-density designs offer two major

benefits. 1) The number of successful cell-sensor contacts

is not influenced by cellular dynamics. Cells can be placed

randomly on the array and may move during a dynamic

network formation without escaping from the sensitivearea or electrodes. 2) Dense arrays with small pixels enable

subcellular-resolution investigation of regions of interest

in neurobiological preparations, and, at the same time, the

large number of electrodes allows for studying the activity

of entire neuronal networks.

A. 128 � 128 CMOS FET Array for ExtracellularRecording of Neural Activity

A CMOS-based array featuring 16 384 field-effect-

based sensors at a pitch of 7.8 �m has been developed by

the Max Planck Institute for Biochemistry, Martinsried,Germany, in collaboration with Infineon Technologies

Corporate Research, Munich, Germany [51], [68]. The

system setup and chip architecture are depicted in

Fig. 9(c).

The monolithically integrated sensor array includes

128 � 128 sensors or pixels. The column decoder period-

ically selects one of the 128 columns of the pixel array.

Moreover, control signals are provided by this decoder,which determine whether the pixels within the selected

column are operated in the readout mode or in a calibra-

tion mode [Fig. 9(a)]. Calibration of all pixels needs to be

performed before the pixels are operated in the readout

mode, and this calibration has to be periodically repeated

after a certain number of readout frames (typically 100).

This calibration procedure is needed as a consequence of

the mismatch of the transistor characteristics and of leak-age occurring at the gate of the transistors.

The full frame readout rate is 2 kf/s. Each of the

128 rows is connected to a separate readout amplifier

[Fig. 9(c)]. The outputs of these amplifiers are connected to

the chip output drivers or to dummy loads via sixteen 8-to-1multiplexers. The 16 output drivers provide an output

current to I/V converters arranged on an off-chip printed

circuit board. Finally, the buffered output voltages of the

I/V converters are processed by 16 ADCs with an effective

resolution higher than 8 b. Integrating larger analog signal

processing units in the pixel is not feasible if high spatial

resolution is required. Therefore, the pixel circuit shown in

Fig. 9(a) consists of only three transistors: One transistor isrequired for sensing the extracellular voltage, another one

for pixel selection. Due to the mismatch of the electrical

parameters of the relatively small sensor transistors, a cali-

bration transistor shorts the gate and drain of the sensor

transistors in the calibration mode of the pixel. The cali-

bration technique, which has to be continuously performed

during the measurements, is described in detail in [51]. The

disadvantage of this calibration procedure is that the re-sulting artifacts in the recording traces have to be sub-

tracted afterwards. The pixel requires 7.8 �m � 7.8 �m

area; the electrically sensitive area features a diameter of

4.5 �m so that an array of 128 � 128 pixels can be integ-

rated within an area of 1 mm� 1 mm as shown in Fig. 9(b).

In order to read out the 16 384 sensors of the array with a

reasonable number of lines, the column scanning is ex-

tended by a row multiplexing at a ratio of 1 : 8.Recording-site densities of conventional passive metal elec-

trode arrays (64 electrodes) amount to 25/mm2, whereas

this CMOS-based sensor array features 16 000/mm2.

The chips have been fabricated using a two-metal-layer,

n-well epi CMOS process, optimized for analog applica-

tions with a minimum gate length of 0.5 �m, a gate oxide

thickness of 15 nm, and a supply voltage of 5 V; for details,

see [51]. After this standard process (devices, two metallayers, nitride passivation, and tungsten vias) has been

completed, the specific postprocessing starts (compare also

Fig. 6 [51]). First, the surface is planarized by a chemical

mechanical polishing (CMP) step. An approximately

50-nm-thick Ti/Pt stack is then vapor-deposited and struc-

tured in a liftoff process. This metal stack is used to provide

the sensor electrodes and the adhesion layer for the contact

Fig. 9. High-density sensor array with 16 384 sensor pixels on 1 � 1 mm2. (a) Pixel circuit. (b) Blowup of the sensor array showing pixel

diameter and pitch. (c) Chip architecture. Reprinted from [51] with permission.

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pads. As sensor dielectric, a 40-nm-thick stack of 10-nm

TiO2, 5-nm ZrO2, 10-nm TiO2, 5-nm ZrO2, and 10-nm TiO2

layers is sputter-deposited at temperatures below 400 �C to

avoid damage to the CMOS metallization layers. The

measured effective relative dielectric constant of this stack

is approximately 45. The dielectric is removed by a reactive

ion etch on the bond pads, and a 400-nm-thick Au layer is

vapor deposited and structured using a liftoff process [51].The extracellular recording capabilities have been de-

monstrated, e.g., with neurons from a pond snail, lymnaea

stagnalis [51]. Fig. 10(b) shows the result of a neuron

contacted by an invasive microelectrode and stimulated by

the injection of a constant current of 0.1 nA for 500 ms [51].

The intracellular voltage is recorded with the same micro-

electrode as used for stimulation. Four action potentials

with amplitudes of 60 mV have been observed. The changeof the intracellular potential at the beginning and the end of

the current injection is a measurement artifact due to the

voltage drop, which occurs owing to the microelectrode

resistance. An area of 32� 40 pixels of the sensor array has

been selected for readout with a sample rate of 8 kHz. Data

of the extracellular potentials recorded from one pixel

underneath the neuron are shown in Fig. 10(b) [51]. Due to

the high-pass transfer function of the gap between cell andtransducer, the extracellular signal represents the deriva-

tive of the intracellular signal. The same chip has also been

used to record field potentials from cultured brain slices

[49]. The noise level has been found to range between 70

and 250 �VRMS [49], [51].

B. 64 � 64 High-Density Electrode Array forImaging Electrophysiological Activity

Another high-density array has been developed at the

University and the Centre Suisse d’Electronique et de

Microtechnique (CSEM), Neuchatel, Switzerland [54],

[91], [124], [125]. The CMOS design is based on a solid-

state active pixel sensor (APS) concept that was originally

developed for image sensors. The chip consists of an array

of 64 � 64 pixel elements on an overall active area of

2.5 mm� 2.5 mm. Each pixel occupies an area of 42 �m�42 �m and comprises a square-shape aluminum or gold

microelectrode of 21 �m � 21 �m as well as a pream-plifier. The center-to-center electrode pitch amounts to

42 �m. Based on image-video concepts, applied at the de-

vice and acquisition system level, full-frame data streams

from 4096 microelectrodes (�560 electrodes/mm2) are

acquired at 7.7 kHz. A subset of 64 electrodes can be read

out at up to 120 kHz. A dual-mode acquisition concept has

been implemented and enables to either acquire electro-

physiological activities from the full frame or to zoom onspecific region of interests (ROIs) at higher temporal

resolution [124], [125].

The in-pixel preamplifier has to fit into the small pixel

dimensions, so that only circuits with a low number of

transistors have been considered. A five-transistor opera-

tional transconductance amplifier [5-OTA in Fig. 11(b)],

optimized for low noise and small area, has been used for

the preamplifier in the first design [54], [130]. Three ad-ditional transistors (T1, T2, and T3) have been integrated

in addition to the 5-OTAs in each pixel as can be seen in

Fig. 11(c). The presence of these additional transistors

allows for operating the preamplifier in open- or closed-

loop mode. In the open-loop mode, the signal is directly

amplified by the open-loop gain, while in the closed-loop

mode, the gain is set to one, and the preamplifier acts as an

impedance transformer.The most recent architecture of the overall system in-

cludes 1) the 64 � 64 MEA, on-chip amplification and

Fig. 10. (a) Snail neuron on the sensor chip in culture. (b) Measured data from a snail neuron. The neuron is stimulated and monitored

for reference purposes with a micropipette. Stimulation current ISTIM, intracellular potential VINTRA, and extracellular potential VEXTRA,

as recorded with the sensor array. Reprinted from [51] with permission.

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filtering circuits as well as a high-speed random addressing

logic; 2) a field-programmable gate array (FPGA)-based in-terface providing analogue-to-digital converters (12-b reso-

lution), addressing control, real-time data preprocessing, and

a serializer for sending the data to a frame grabber through a

high-speed interface; and 3) a host computer equipped with a

frame grabber and running a custom software application

managing the platform control, data acquisition, and data

analysis on a multicore processor [54], [125].

Electrophysiological measurements have been per-formed by culturing dissociated hippocampal neuronal

cultures, prepared from embryonic E18 rats, on the alu-

minum electrodes of the chip. In the most recent gene-

ration of the chips [54], there is no noble metal layer on

the electrodes, whereas, in previous versions, gold has

been used as electrode material [130]. The CMOS

passivation has been opened and the topmost CMOS

aluminum layer is directly exposed to the cell culture. It isremarkable that, according to the authors, the CMOS

aluminum withstands the culturing and the cell metabolic

activity, and, on the other hand, that the cells tolerate the

presence of the aluminum for extended time [54].

Measurements have been conducted between day 14 and

day 30 in vitro. The cells showed spontaneous electrical

activity featuring amplitudes (extracellular potentials)

between 100 and 400 �VPP. Fig. 12 shows the recordedspontaneous neuronal bursting activity recorded from the

whole array. The noise of the system is approximately

11–15 �VRMS. The spatial and temporal resolution of the

device enables visualization of local spike propagations aswell as whole network (bursting) activities [54], [125]. The

chips have been reported to be reusable after cleaning the

devices with isopropanol and rinsing in de-ionized water.

The high-density system is commercially available from the

company B3Brain,[ Landquart, Switzerland.2

C. Multiparameter Sensor ChipThe integration of several different sensor types on one

chip for monitoring not only electrical cell activity, but

also temperature, cell metabolism, and cell adhesion has

been developed by the University of Rostock in coopera-

tion with the semiconductor company Micronas GmbH,Freiburg, Germany3 [123], [131]. The aim is to monitor

electrical signals as well as metabolic parameters with one

sensor chip. The applications are in the field of basic

research and drug screening.

The developed system, the concept of which is illus-

trated in Fig. 13, provides online monitoring of cellular

reactions under well-controlled experimental conditions.

The system includes cell-potential field-effect transistors(CPFET, sensitive gate areas of 6� 1 �m2) and palladium

electrodes (10-�m diameter, palladium features low cell

toxicity according to [133]) to measure the electrical cell

2http://www.3brain.com/.3http://www.micronas.com.

Fig. 11. (a) Overview of the high-density electrophysiological platform. The system includes the CMOS-MEA chip, the interface board,

and a work station equipped with a frame grabber for capturing and storing the data. Reprinted from [54] with permission. (b) Schematic of

the in-pixel preamplifier. (c) Detailed schematic of the five-transistor operational transconductance amplifier (OTA) used in the preamplifier.

Reprinted from [130] with permission.

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activity as shown in Fig. 14(a) [123], a sensor to monitor

the temperature of the cell culture, and ion-sensitive field-

effect transistors (ISFETs) to monitor the pH in the cel-

lular microenvironment, a recording of which is shown in

Fig. 14(b) [132]. The ISFETs allow for monitoring local

acidification and respiration in in vitro cell networks. The

interdigitated electrodes are used to measure the cell ad-

hesion by means of impedance measurements [134]. Cell

health can be characterized by the degree of adhesion of

electrically active cells to transducers. According to the

authors, impedimetric measurements using interdigitated

electrode structures have been found to provide informa-

tion on the cell density and number, the cell adhesion, and

the cellular morphology, since an alternating current (ac)

Fig. 12. Acquired activity during a propagating burst event. Data from a rat hippocampal neuronal culture (31 DIV, 7.7-kHz sampling,

4096 electrodes). View of the overall active area as an image sequence. Each frame is computed at a different time and shows the burst

propagation over the network. Reprinted from [125] with permission.

Fig. 13. Cell monitoring system concept: thermoregulated cell culture chamber with fluid handling system and different microsensors

(ISFET: ion-selective FET; ENFET: enzyme FET; ISE: ion-selective electrode; CPFET: cell potential FET; TD: temperature diode;

CCD: charge-coupled device) Reprinted from [132] with permission.

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between the electrodes is influenced by the presence andstructural properties of living cells growing on these elec-

trode structures. The system as shown in Fig. 13 is com-

mercially available through Bionas GmbH, Rostock,

Germany.4 Toxicology investigations with this system

have been described, e.g., in [135]. More information on

how different chemicals trigger cellular responses of pre-

vailingly electrogenic cells can be found in the literature

[45], [46], [90], [126], [132], [136]–[138].

D. Portable Cell-Based BiosensorField-portable and handheld cell monitoring systems

have been developed at the Department of ElectricalEngineering, Stanford University [14], [126]. To realize

field-portable detectors for chemical and biological agents,

considerable changes must be made relative to the equip-

ment used in typical laboratory-based situations. First, the

entire system must be robust, relatively compact, and able

to be self-powered for a reasonable operational period.

Second, the cells must be packaged in a way as to maintain

sterility and proper environmental conditions for the cul-ture, and yet allow the introduction of unknown agents.

Typically, the cells, MEAs, and potentially some fluidic

interfaces are combined into a user-replaceable cartridge.

The cells must also be maintained at constant pH, osmo-

larity, and temperature, typically via chemical buffering,

humidification, and closed-loop thermal control [12], [46],

[139]. The high sensitivities of cells to changes in these

parameters can lead to false Bsignals[ if they are not tightlycontrolled. In addition, the sample preparation, which is

typically done manually in the laboratory, must be auto-

mated so that it can be carried out under realistic envi-

ronmental conditions.

Since the first such work presented in [46], majorefforts toward realizing field-portable systems have been

undertaken [139]. As an example, a handheld recording

system (Fig. 15) with integrated cell cartridges incorporat-

ing closed-loop thermal control and front-end amplifica-

tion and multiplexing electronics was developed [12], [14].

A die microphotograph of the CMOS chip used in this

portable device with a floor plan overlay is shown in

Fig. 15(b). Each chamber has one large pseudoreferenceelectrode, two stimulation electrodes, four arrays of

16 microelectrodes, multiple temperature sensors, and

nine 16-channel multiplexers. Digital logic, which uses a

three-wire serial interface, controls the multiplexers. The

poly(dimethylsiloxane) gasket seal contacts the top surface

of the die except for the two elliptical chamber areas and

the bond pads. The temperature is regulated by an on-chip

temperature controller. The goal of the temperature regu-lation system is to maintain the substrate beneath the cells at

a defined temperature even when exposed to environmental

transients. An n-channel metal–oxide–semiconductor

(NMOS) transistor is used as the heating element [Fig. 16(a)].

The primary biological sensors of the cell cartridge are

multiple arrays of 16 gold-coated planar microelectrodes

of 10-�m diameter. Both chambers have four arrays of

16 electrodes, resulting in 128 total sensor channels on asingle cartridge. Each microelectrode has a connection to

two separate multiplexers. One connection leads directly

to a multiplexer (for platinization, impedance measure-

ments, and unbuffered action potential measurements),

while the other connection goes to a low-noise source

follower, the output of which is routed through the second

multiplexer [for buffered action potential measurements;

Fig. 16(a)]. This configuration allows for simultaneousrecordings from four buffered and four unbuffered micro-

electrodes per chamber. A large pseudoreference/counter4http://www.bionas.de.

Fig. 14. (a) Extracellular recordings from one of the chip electrodes (approximately 40 superimposed neuronal action potentials).

Reprinted from [123] with permission. (b) Extracellular acidification measurements in a neuronal network on a silicon chip as performed

with ISFETs in a flow-through system. The pump cycle was 5 min ‘‘pump on’’ and 10 min ‘‘pump off.’’ During the pump-off period, the pH of the

medium decreased significantly due to the acidification through the presence of the cells. In the pump-on period, fresh medium was pumped

through the chamber. Reprinted from [132] with permission.

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electrode in each chamber is used to hold the solution at a

nearly constant potential during the measurements. The

analog portion of the handheld device includes low-noise

amplifiers, the auxiliary channel amplifiers, and ADCs(temperature, system power, reference voltage, battery

voltage), the stimulation system, and a pump control sys-

tem. The low-noise amplifiers connect to the eight chan-

nels of buffered source-follower cartridge outputs. The

amplifier system was designed to provide a gain of 505

across a 16 Hz–3 kHz bandwidth with 1 �VRMS of input-

referred noise.Signals from HL-1 cells (cardiomyocyte cell line) were

recorded at eight days in vitro [Fig. 16(b)]. The typical

amplitude of the recorded signals was in the 400 �VPP

Fig. 16. (a) Circuit block diagrams of the CMOS cell cartridge. Temperature control system showing components and off-chip connections (top)

and block diagram of one microelectrode sensor channel showing the unbuffered and source–follower–buffered connections (bottom).

(b) Extracellular action potential waveforms recorded with the handheld system from HL-1 cells (cardiomyocyte cell line) growing for eight days

in chamber A ðVA2Þ and chamber B ðVB3Þ of a cell cartridge. These signals were averaged 16 times and are of typical shape and amplitude

(300–400 �VPP). Reprinted from [12] with permission.

Fig. 15. (a) Handheld cell-based biosensor system. Front view showing the cartridge, pump, display, and control buttons; back internal view

showing the electronic subsystems on the right. (b) Microphotograph of the 6� 9 mm2 die. The lightened elliptical shading was added to

highlight the cell chamber surface areas. Each chamber has four arrays (quadrants) of 16 microelectrodes each. The serial digital interface

controls the eighteen 16-channel multiplexers. Reprinted from [12] with permission.

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range with the largest observed signal amplitudes being1.3 mVPP.

E. Fully Integrated Bidirectional Low-Density andHigh-Density Electrode Systems

Two types of planar monolithic microsystems in CMOS

technology that provide bidirectional communication (sti-

mulation and recording) to cultured electrogenic cells or

slice preparations are presented in this section [52], [53],

[104], [105], [128]. Both microsystem chips are directlyused as a substrate for cell culturing, they feature circuitry

units for stimulation and immediate cell signal treatment,

and provide on-chip signal transformation as well as digital

interfaces, so that a very fast, almost real-time interaction

(2-ms loop time from event recognition to a defined sti-

mulation) is possible at good signal quality. The low-

density system (Section IV-E1) has the circuitry units

repeated with each electrode (pixel approach), whereas forthe high-density system (Section IV-E2), a switch matrix

strategy has been pursued, and the electronics have been

shifted to chip space outside the array in order to achieve

better lateral resolution and, at the same time, high signal

quality. Sample recordings of spontaneous and stimulated

electrical activity with neuronal and cardiac cell cultures

will be shown in Section IV-E4.

1) Low-Density 128-Electrode System: A micrograph of the

monolithic low-density CMOS microsystem is shown in

Fig. 17 [105]. The 6.5 mm � 6.5 mm chip comprises

128 stimulation- and recording-capable electrodes in an

8 � 16 array and an integrated reference electrode. The

system is structured in a modular design (Fig. 17). Each

pixel of the microelectrode array incorporates the signal-transducing electrode, a fully differential bandpass filter

for immediate signal conditioning, a mode storage unit,

and a buffer for stimulation. The pitch of the pixel units is

250 �m.

Electrode pitch, size, and shape are very flexible, and

the electrode material can be selected from a large variety

of materials, since the electrodes are realized during the

post-CMOS processing, as described in [104] and [105]. Adigital control unit is also integrated on the chip and con-

trols the multiplexing, the electrode selection for stimula-

tion, and the reset of single electrodes. Also it contains the

successive-approximation registers of the ADCs and the

interface to the outside world. The overall setup includes,

besides the chip, an FPGA and a laptop; see Section IV-E3.

Implementing filters and buffers at each electrode

offers important advantages. 1) The signal is amplified andfiltered in close proximity of the electrodes, which makes

the design less sensitive to noise and interference picked

up along connection lines. 2) One stimulation buffer per

electrode ensures that the commanded stimulation wave-

form can be reliably transmitted to each selected electrode

and that it is independent of the overall number of

electrodes selected for stimulation. 3) The high-pass filter

removes offset and drift of the biochemical signals so thatthe signal can be amplified before it is multiplexed. 4) The

low-pass filter (LPF) limits the noise bandwidth and works

as an antialiasing filter for the multiplexing and for the

subsequent ADC.

The schematic of the in-pixel circuitry components,

which have been optimized for low noise and small area, is

shown in Fig. 18. The first readout stage is a high-pass filter

Fig. 17. Micrograph of the 128-electrode CMOS system chip (6.5 � 6.5 mm2) and closeup of one pixel. The different components include the

128-electrode array (8 � 16) featuring amplification and filtering circuitry units associated with each electrode; 16 ADCs; digital control and

interface; DAC for stimulation; temperature sensor. The closeup shows one pixel repeating unit featuring the two CMOS aluminum contacts,

one for readout, one for stimulation, and the final platinum electrode shifted sideways from those contacts (see also Section IV-E3).

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to eliminate drift and offset of the metal electrode. The gain

of the filter is 20 dB defined by the capacitance ratio C1=C2.

The corner frequency is given by the capacitor C2 and theresistor R. The value of C2 is a tradeoff between gain accuracy

and corner frequency. Given the spatial constraints imposed

by the 250-�m pitch, a 200-fF capacitance was chosen for C2.

To realize a corner frequency of 1 Hz, a large resistance R is

required. Such large resistance has been realized by using a

MOS resistor (see [140]) with a gate length of 100 �m and a

gate width of 1 �m. The absolute value of the resistor can be

externally controlled by changing the gate voltage. Thecorner frequency can be tuned from approximately 1 Hz to

about 1 kHz. A second design that makes use of a MOS diode

to realize such large resistances has been implemented as a

test structure (see [141] and [142]). For the MOS-diode-

based approach, no reference voltage is required, but the

filter stage is not tunable as it is with the MOS resistor. The

corner frequency of the diode-based design was measured to

be approximately 1 Hz.In the subsequent filter stage, a passive MOSFET-C

LPF limits the noise bandwidth and prevents aliasing. The

area (90 � 45 �m2) of the passive LPF was minimized by

using MOS resistors that are tunable by modification of the

gate voltage and by using MOS capacitors. The corner

frequency of the filter can be tuned from about 1 to

30 kHz. Following the LPF, an additional gain stage am-

plifies the signals and allows for fast multiplexing. Thisbuffer is a fully differential version of the amplifier pre-

sented in [143] and has a gain of 30 dB.

The in-pixel circuitry unit also includes stimulation

capabilities. Any arbitrary stimulation pattern (with a

maximum sampling rate of 60 kHz and 8-b resolution) canbe applied to any electrode. The readout circuitry at each

electrode can individually be reset to its operating point in

order to suppress artifacts evoked by the stimulation pulses

from the stimulated electrode itself or from neighboring

electrodes. The stimulation buffer (Fig. 18) comprises a

differential input stage ðM1;M10Þ with an active load ðM2Þand is connected in a unity gain configuration (OUT con-

nected to gate of M10). The class-AB stage is formed by thetransistors M3, M4, M5, and M6, where M3 and M4, both

of which are diode connected, bias the output transistors

M5 and M6 [89]. The power consumption is 45 �W for

very small inputs at a current Ibias of 2 �A and a supply

voltage of 5 V. However, when slewing, the amplifier can

deliver up to several milliamps to the electrode. The whole

buffer occupies an area of 42 �m � 32 �m. Transmission

gates are used as switches (Stim) to connect the buffer tothe electrode. For more details on the circuitry see [104]

and [105].

A total equivalent input noise of the pixel circuitry of

11.7 �VRMS (0.1 Hz to 100 kHz) has been measured. The

electrodes are continuously read out at a sampling rate of

20 kHz per electrode. A gain of 1000 or 3000 can be

selected. The overall power consumption of the chip is

120 mW at 5-V supply. Electrogenic cells are very sensitiveto temperature, so that even subtle temperature changes

may change the cell activity level and may even lead to cell

Fig. 18. Circuitry unit, which is repeated at each electrode. It comprises a stimulation buffer, a high-pass filter, an LPF, and a final amplification

stage. The low-frequency corners of the filters are realized by using MOS resistors. The cutoff frequency of the filters can be adjusted by

changing the gate voltages (Vb_HPF and Vb_LPF) of the MOS resistors. Reprinted with permission from [105].

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death. Therefore, excessive power consumption and heat

dissipated by the electronics directly underneath the cellshas to be avoided or accounted for by regulating the tem-

perature of the culture liquid. An on-chip temperature

sensor has been implemented to monitor the chip

temperature. Operating the chip with liquid on the surface

leads to a temperature rise of less than 1 �C with respect to

ambient temperature upon operation, so that additional

cooling of the system is not required. Circuits operating at

low frequency (down to 1 Hz) might be sensitive to leakagecurrents, the effect of which has been reduced by the fully

differential design of the in-pixel readout circuitry.

Furthermore, electromagnetic coupling is also generally

reduced in a fully differential architecture.

2) High-Density 10 011-Electrode System: A workaround

for the dilemma of achieving high signal-to-noise ratios

and, at the same time, high lateral resolution in the re-cordings (see Section II), is presented here [52], [53],

[129]. Instead of simultaneously reading from all electro-

des, which requires the front-end amplifiers to be located

directly at each recording electrode, the workaround in-

cludes the realization of a matrix of switches and memory

cells (little area needed and negligible noise contribution)

underneath the electrodes to route a subset of these

electrodes to circuitry units (channels) placed outside thearray, where no area constraints apply [52], [53], [129].

This way, high-density electrodes are combined with high-

performance circuitry, which features noise levels as low

as 3 �VRMS. It is important to mention that the imple-

mentation enables an almost arbitrary selection of elec-

trodes (cohesive blocks, lines, single electrodes here and

there) to be connected to the 126 available readout chan-nels. The electrode selection, which can be changed within

approximately 2 ms, can be adapted to the biological-

sample structure, and one can do, e.g., a large-area activity

screening or mapping of the functional connectivity and

then proceed to a detailed study of a certain area or net-

work. The large redundancy in the data gained from such

detailed recordings in the area of a single cell can be

effectively used for spike sorting to enable a precise, tem-porally and spatially highly resolved reconstruction of, e.g.,

the extracellular potential landscape of a single cell, which

can be used to test and validate corresponding models.

The microsystem chip is 7.5 � 6.1 mm2 in size, and

features 11 011 metal electrodes as well as 126 bidirec-

tional circuitry channels, each of which is equipped with

recording and stimulation electronics [Fig. 19(a)]. The

electrodes feature a diameter of 7 �m and are placed at apitch of 18 �m (honeycomb pattern) in an area of 2.0 �1.75 mm2 yielding a density of 3150 electrodes/mm2

[Fig. 19(b)].

Flexibility in the electrode selection is attained by an

analog switch matrix, integrated underneath the electrode

array, which consists of 13-k memory cells and analog

switches to define the routing from the electrodes to the

amplifiers of the channel units [52], [53], [129]. In brief,the memory cells store the information whether the re-

spective switch is closed or not, i.e., whether an electrode

is connected via several switches to one of the readout/

stimulation channels. To obtain the settings of the

switches for a selected set of electrodes, the switch matrix

Fig. 19. (a) Micrograph of the MEA chip (7.5�6.1 mm2). The electrode array is surrounded by the first and second amplification and filtering stages

and the stimulation buffers. Below the array is the shift register used to program the array and on the right-hand side are the third amplifier

stages, ADCs, and the digital core. (b) Colored scanning electron micrograph of chicken dorsal root ganglion neurons (two days in vitro) cultured on

the chip illustrating size and density of the microelectrodes (blue) in comparison to the neurons (green). Reprinted from [53] and [129] with

permission.

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is represented as a graph, and a max-flow, min-cost opti-mization problem is solved using an integer-linear prog-

ram (ILP). Arcs from spots of interest to a set of electrodes,

on which the signal can be measured, are assigned a cost,

such as the Euclidean distance or a value that is inversely

proportional to the signal quality. Simulations for the task

of routing 126 randomly distributed spots to the 126 read-

out channels using the Euclidean distance as a cost mea-

sure were carried out to assess the ability to select spots ofinterest. The average distance from any spot of interest to

its closest electrode was 6.75 �m for the set used

ðn ¼ 2000Þ. The implemented routing scheme provides

an average distance to the connected electrode of 7.1 �m,

where 114.6 of the 126 spots can be read out via the closest

electrode. One hundred two electrodes in a 6 � 17 rec-

tangular configuration constitute the largest obtainable

coherent electrode block. Although the implementedswitch matrix provides sufficient flexibility in the elec-

trode selection for most experiments, this will be further

improved in the near future by incorporating two routing

switches/memory bits per electrode instead of currently

only one. This can easily be realized by using a CMOS-

technology with a feature size of 0.35 �m or less, while

preserving or even increasing the array spatial resolution.

A block diagram of the overall device is shown inFig. 20 [53], [129]. For readout, the signals are amplified

and filtered using three stages, each including a two-stage,

Miller-compensated amplifier. The gain is programmable

via the digital interface from 1 to 10 000 in 18 steps to

account for the large variation in the signal amplitudes of

the different cell types. The maximal gain of the first stageis 30. This stage also provides a first-order high-pass filter

with adjustable cutoff frequency (0.3–100 Hz). The

bandwidth is limited with the Miller capacitance to either

15 or 50 kHz in the first, and to 3.5 or 14 kHz in the second

stage. The signals are multiplexed after the second stage,

sampled at 20 kSamples/s per channel and digitized with

an 8-b successive-approximation ADC. The data are

transferred off-chip along with the chip-status informationand a cyclic redundancy check (CRC) for transmission

error detection. More information is available in [129].

The stimulation capability is provided through flash

digital-to-analog converters (DACs) and stimulation buf-

fers (Fig. 20). Electrical stimuli can be delivered through

two 10-b DACs, which enable the simultaneous application

of two different stimulation patterns to two selected

subsets of the 126 connected electrodes. The most recentimplementation of the stimulation circuit features voltage

and current stimulation and relies on a set of digitally

controlled switches to switch between these two stimula-

tion modes [144]. The same class-AB operational amplifier

is used for both modes and is operated in high output

current, i.e., voltage mode or high gain, i.e., current mode.

In voltage mode, the circuit is configured as a voltage

follower with low output impedance to approximate anideal voltage source. The class-AB functionality is realized

by a local common-mode feedback structure in the

amplifier [145]. In current mode, the circuit is a positive

current conveyor of type II (CCII+) [146]. The CCII+ is

composed of the same operational amplifier that is used in

Fig. 20. Block diagram showing the electrode array and addressing and the on-chip circuitry. The figures at the top indicate the number of

realizations: 126 readout/stimulation channels, 16 ADCs for readout, 2 DACs for stimulation. Two channels are used to read out the on-chip

temperature sensor and the potential on a separate electrode without amplification or filtering. The digital circuitry, which interfaces with the

outside world, includes a recording control unit and a command decoder. The probe access is for testing purposes. Reprinted with permission

from [129].

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voltage configuration (now with high gain), plus additional

transistors. This circuit features high output impedance,

since it has to approximate an ideal current source, and it

copies the current from the negative input terminal of the

operational amplifier to the output stage. For more details

on the stimulation circuit, see [129] and [144].

Two additional channels are used to record the on-chip

temperature and the electrode DC potential. A onceprogrammable 16-b ID identifies the chips for automated

information access and transfer to a database. The low-

power design minimizes heating of the biological prepa-

ration [52], [129].

3) Fabrication, Packaging, and Setup: Both MEA chips

have been fabricated in an industrial 0.6-�m CMOS

process with three metal layers, two poly silicon layers,and a high-resistance poly silicon layer at XFAB, Erfurt,

Germany.5 Special post-CMOS processing and packaging

steps are necessary to make the packaged chip ready for

operation under physiological conditions in liquid phase.

The contact material as received from the CMOS

foundry is aluminum, a material, which is known to be

unstable in physiological solutions and to be toxic for many

cells. To avoid cell poisoning and undesirable electro-chemistry or chip corrosion, the electrode material was

selected to be platinum. A two-mask postprocessing proce-

dure was applied to cover the Al electrodes with biocom-

patible platinum. During this processing the electrodes

were shifted sideways [Fig. 21(a)] [147], so that the alu-

minum could be sealed with a passivation stack. The

passivation stack consisted of alternating Si3N4 and SiO2

layers with a total layer thickness of 1.6 �m. The finalelectrode location is on top of the original chip passivation

shifted away from the CMOS metal contacts (see also

Fig. 17). The opening of the passivation stack in the areas

of the new electrode locations leaves platinum metal

electrodes exposed to the liquid. Pt-black was afterwards

grown to reduce the electrode impedance [not shown in

Fig. 21(a)].

Neurons have been cultured for many months on the

chips with this 1.6-�m passivation stack, and the chips

have been reused multiple times. Each of the processed

chips has been mounted and wire-bonded onto a small

printed-circuit board [Fig. 21(b)]. A water-resistant

medical epoxy was used to encapsulate the bond wiresand pads. A glass ring forms a bath that contains a suitable

amount of cell medium.

The recording setup includes a chip-support board, an

FPGA for data acquisition and feedback, and a laptop

computer for data analysis, visualization, and storage

(Fig. 22) [129]. The chip-support board can be placed in

an incubator (humidity contents 60% and even larger) and

provides sockets for five packaged chips [Fig. 21(b)] thatcan be operated simultaneously. This is to avoid mechanical

perturbation by handling devices with plated cells prior to

measurements. The support board provides all necessary

clock and digital control signals, as well as all required

analog references to the chips. The value of the references

can be programmed using the on-board microprocessor.

This processor also monitors temperature and humidity. To

minimize the amount of required connections, the data areserialized on the board and sent via two twisted-pair links at

16 MB/s. By using a serial low-voltage differential signal

(LVDS) protocol, a six-wire ribbon cable is sufficient to

connect the board with the rest of the system.

The main data acquisition and feedback control unit is

realized using the Xilinx Virtex-II-Pro FPGA platform.6

This component features fast data-processing algorithms,

implemented on the programmable logic, and also hoststwo PowerPC cores, both capable of running a Linux ope-

rating system with clock frequencies up to 300 MHz

(Fig. 22) [129]. The data are converted back to a parallel

representation, the data streams from the different chips

5http://www.xfab.com/.

Fig. 21. (a) Scanning electron microscope cross-sectional image of the chip showing the post-CMOS processing needed for biocompatibility

and corrosion protection: platinum processing and shifting of the electrodes to the side on top of the original chip passivation.

(b) Packaged chip on a custom-designed printed circuit board. Reprinted from [52] with permission.

6http://www.xilinx.com/support/documentation/user_guides/ug012.pdf.

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are separated, and a CRC is performed. The extracted data

are then distributed via an internal data bus to the data

processing units, e.g., spike-detection and data-compression

units. These units use direct memory access (DMA) to write

the results into the system memory, where they can be

accessed from applications running on the PowerPC. As the

chips produce large amounts of data, which need to be storedfor later processing, a compression block was designed. It is a

lossless compression that encodes the difference between

two data points in time using Rice coding [148] with an

adaptive algorithm to update the compression parameters

depending on the measured signal properties [149]. The

application program running on the PowerPC core is

responsible for the data transport between the FPGA core

and the supervising computer.The third component is the software running on the PC

(Fig. 22) [129]. It consists of a server application and sev-

eral clients connected to the server. As high-density MEAs

have a complex structure with an electrode routing matrix

and a programmable gain, the server implements five chip-

emulator modules. Every time the real chip configuration

is changed, the same changes are applied to the corre-

sponding emulators [129]. The client applications can thenretrieve the currently connected electrodes, gain, and

filter settings from the emulators. All communication links

from the chip to the PC are protected by CRCs in either

direction, which enables error detection and ensures data

integrity.

4) Measurement Results: Dissociated and randomly

seeded cell cultures of electrogenic cells, such as neuronsor cardiac myocytes, have been well established as bio-

logical preparations with MEAs [83], [130], [150]–[152].

Primary neurons are usually isolated from brains of em-

bryonic or postnatal rodents, since these cells exhibit a

high degree of plasticity, a characteristic that is required

for developing neuronal networks in vitro [153]. The ability

to record and stimulate cultured cells has provided unique

experimental setups for studying the cellular activity over

extended periods of time, ranging from hours to weeks

[154], [155].

a) Recording: Recordings from cardiomyocytes, also

under dosing of pharmacologically active agents, and re-

cordings from neuronal cells in rat brain slices at sub-

cellular resolution have been selected from a wealth of

measurements and will be shown here.Cardiomyocytes are responsible for heart contractions

and are the dominant cell type in the normal heart with

respect to volume. Irregularities in heartbeat, due to

cardiac electrical dysfunction, are one of the most frequent

causes of mortality and morbidity in the industrialized

society. Therefore, elaborate in vitro models are needed

that enable to study how potent pharmaceutical agents

affect cardiac electrophysiology. Primary neonatal rat car-diomyocytes can be cultured directly on the chip, they

become electrically active very quickly, and provide com-

parably large signal amplitudes. The recording parameters

included a bandpass filter range between 10 Hz and 5 kHz

at a sampling frequency of 20 kHz. The cardiomyocytes

form a confluent layer on the chip and show spontaneous

activity, a regular beating driven by pacemaker heart cells

in the culture. Recordings of field potentials (synchronousactivity of patches of heart cells) of the spontaneously

beating cells after five days in vitro are shown in Fig. 23(a).

In this example, the cells have been activated by dosing

phenylephrine and beat at a rate of about 10 Hz. The sig-

nals feature amplitudes between 1 and 1.5 mV. In com-

paring the extracellular signal of Fig. 23(a) and (b) with

the intracellular signals displayed in Fig. 4(b), it is obvious

that it is mostly the fast Naþ current contribution to po-tential changes that is recorded by extracellular measure-

ments [61], as the signal duration is on the order of only

1–2 ms.

Drastic changes in the signal characteristics can be ob-

served upon dosing, e.g., lidocaine to the beating culture.

Lidocaine is a common local anesthetic and an antiar-

rhythmic drug. Lidocaine blocks the fast voltage-gated

sodium (Naþ) channels in the cell membrane and alters

Fig. 22. Schematic of the overall recording setup, which includes a chip-support board, an FPGA for data acquisition and feedback, and

a laptop computer for data analysis, visualization, and storage. A photograph of the support board with plugged-in chips is shown on the left-hand

side. �C denotes microcontroller, LVDS is low-voltage differential signal, and UART means universal asynchronous receiver transmitter.

Reprinted with permission from [129].

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the depolarization of cardiac cells and neurons. With suf-

ficient blockade, the membrane of, e.g., a presynaptic

neuron will not depolarize and so fail to transmit an action

potential, leading to its anesthetic effects. The effect of

lidocaine dosage can be seen in Fig. 23(b) and (c). The use

of a larger array of electrodes enables the recording and

evaluation of a multitude of relevant parameters. The data

in each row represent an average over a large set of cardiacelectrical potentials, recorded with 126 electrodes. The

dosage of lidocaine drastically alters the waveform as can

be seen in the first column when comparing peak-to-peak

voltages and the time span between the positive and

negative peak. As the fast sodium channels are blocked, the

amplitude drastically drops from 2.2 to 0.37 mVPP, and the

time span between the peaks is increased from 0.35 to 2.8 ms.

The wave propagation speed, i.e., the speed, at which theelectrical potential wave travels across the electrode array

area, is also massively reduced from 360 to 105 mm/s,

whereas the culture beating frequency increases from 0.7 to

0.9 Hz. The dependence on the concentration of the dosed

pharmaceutical agent can be seen in comparing the graphs

and values for 5 and 10 mg/ml [Fig. 23(b), second and third

row, and Fig. 23(c)]. All the above mentioned parameters can

be used to characterize the effects of drug dosage on tissuelevel and provide complementary information to single-cell

patch clamp measurements currently routinely conducted in

pharmaceutical industry. For more details on the interpre-

tation of the signal characteristics and waveforms of

extracellularly recorded cardiomyocyte signals, also upon

dosage of pharmacologically important substances, see [61],

[156], and [157]. Further, MEAs have been used to assess the

effects of lentivirus-induced genetic modifications of cardi-

omyocytes and to show the possibilities of using cardiac

microtissues transplanted onto confluent cultures as pace-maker units [158].

As an exemplary neuronal preparation, acute sagittal

cerebellar slices from rats were placed on high-density

CMOS MEAs [Fig. 1(b)], and the temporal evolution of

single-cell action potentials was studied in detail. The signals

of a single Purkinje neuronal cell, the most important cell

type in this kind of preparation, were simultaneously visible

on more than 50 of the tightly spaced electrodes [53].Purkinje cells (PCs) are spontaneously active and are

effectively disconnected from each other because the parallel

fibers are cut in a sagittal slice [48]. In addition, the

excitatory input from the deep cerebellar nuclei via climbing

fibers is missing. The PC electrical fields can thus be

considered independent from each other, which facilitates

spike sorting and eases waveform interpretations.

Spikes in the voltage traces varied considerably inshape, and the signals on neighboring electrodes showed a

high degree of synchronicity, which, respectively, indicates

Fig. 23. (a) Field potential recording of a confluent layer of regularly beating cardiomyocytes from neonatal rat (embryonic day 5) after

phenylephrine dosage (100 �M/L) after five days in vitro. (b) Characteristic changes upon dosage of different concentrations of lidocaine

(5 and 10 mg/ml) to a cardiac culture. The first column shows average signals of all electrical potentials recorded within a 20-s time window.

The raster plots in the second column show the distribution of electrical activity over all electrodes or channels as a function of time

(a rhythmic synchronous activity pattern can be observed). The propagation plots in the third column show the spreading of the electrical wave,

which originates from the upper left corner, with time. The lines labeled with 5, 10, 15, etc., represent the location of the wave front at 5, 10, and

15 ms after activity starts. (c) Characteristic parameters that change upon lidocaine dosage; Upp is the peak-to-peak voltage of the signal,

tPP is the time span between positive and negative peak, v denotes the wave propagation speed, and f is the culture beating frequency.

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that different neurons contribute to the overall signal on

each electrode and that the same neuron provides signals

on various electrodes [Fig. 24(a)]. The spike shape distri-butions were analyzed using independent component

analysis (ICA) to identify and separate spikes originating

from different neurons.

Spike-triggered averages of the signals on all electrodes

in a region of interest were calculated for each identified

unit, and the potential distribution generated by an indi-

vidual Purkinje cell was analyzed as shown in Fig. 24(b).

Spike amplitudes ranged from the detection limit (�35 �V,�4� noise level) up to a few hundred �V, with firing rates

of 7–35 Hz. No significant cross correlation of spike trains

from neighboring PCs was observed. This fact and the

large number of electrodes allowed for an effectiveapplication of independent-component analysis (ICA).

The firing rates may be somewhat underestimated, since

priority was given to precision over sensitivity during

spike sorting in order to obtain accurate cell footprints, i.e.,

accurate extracellular-potential distributions.

The high-temporal resolution characteristics of the

evolution of a single action potential in the identified cells

could be demonstrated (Fig. 25). The current-source-density analysis (second spatial derivative of the electrical

Fig. 24. (a) Recordings of spontaneous activity obtained from an acute parasagittal cerebellar slice. Electrical signals from six neighboring

electrodes: Differently shaped spikes identified through spike sorting are marked in color. Each cell is detectable on more than one electrode,

but not on all six. The electrode number assignment is shown at the left. (b) Footprint of a cell reconstructed from recordings at full spatial

resolution: Potential distribution at the time of the first negative peak (circle: center of all negative peaks weighted with the peak amplitudes;

square: center of all positive peaks). Frequency band: 5 Hz–3.5 kHz. Colored contour lines represent equipotential lines at half-peak amplitude,

i.e., �63 �V for the blue line in the negative or somatic region (blue), and þ18 �V for the red line in the positive or dendritic region (red).

Reprinted with permission from [53].

Fig. 25. Current-source-density analysis for the same cell at several points in time (green: current sink; orange: current source). The sink

moves from the soma at 0.4 ms to the proximal dendrites at 0.6 ms and covers the dendritic area, while the soma repolarizes. The outlines of

cell soma (blue) and dendritic area (red) again represent equipotential lines at half-peak amplitude. The gray dots mark the electrodes used

to record from. Reprinted with permission from [159].

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signals) revealed distinct dipole fields oriented in parallel

to the chip surface. At spike onset, there was a pronounced

current sink around the presumptive location of the PC

soma and an equivalent, but spatially less focused, source

in the region of the dendritic tree (Fig. 25). The sink then

shifted towards the region of the proximal dendrites,

where it slowly faded away. This passive backpropagation

of an action potential, i.e., the gradual movement of thecurrent sink into the region of the proximal dendrites,

where initially the source has been located, was clearly

visible and reproducible.

b) Stimulation: Stimulation features, as also realized

by other groups for in vivo applications [5], [160], [161],

have been implemented on the CMOS chips here as well.

Voltage and current stimulation was included in the

designs, and stimulation buffers have been implemented ateach electrode (Section IV-E1) or in each channel

(Section IV-E2). The implementation of buffers is due to

the fact that the number of activated stimulation

electrodes and, therefore, the load for the stimulation

circuitry can vary. The buffers are powered down, if the

respective electrode or channel has not been selected for

stimulation (see Figs. 18 and 20). In order to stimulate

with a variety of waveforms, a stimulation signal samplingrate of 60 kHz has been chosen, which, in turn, entails the

use of buffers with slew rates of 3 V/16 �s ¼ 0.2 V/�s at a

load of 20 nF.

An important aspect for stimulation includes the elec-

trode impedance. Studies on the electrode impedance have

been reported in [73], [89], and [162], from which it was

evident that the impedance of the electrode varies in de-

pendence of electrode size, electrode material, and cell

growth [163]. The capacitance of a 30-�m diameter elec-

trode has been measured to vary from 200 pF for bright

platinum (Pt) to 20 nF for Pt-black. The charge-transfer

resistance of the Pt electrode is on the order of several

hundred megaohms.

Electrical stimulation pulses affect the recordings on

the stimulating electrode and on neighboring electrodes by

creating large artifacts, which may superimpose on ormask action potentials occurring during the decay time of

an artifact. There are several methods to eliminate stimu-

lation artifacts, which are computationally expensive and/

or require real-time data processing [114], [115]. An alter-

native is to include artifact suppression measures in the

stimulation/recording circuitry [5], [56], [160], [161],

[164]. In the systems presented here, artifact cancellation

has been implemented directly in the pixel/channel cir-cuitry. To prevent high-pass filter saturation upon applica-

tion of large signal amplitudes, a reset switch (see Fig. 18)

has been implemented in the feedback of the first am-

plifier. This switch holds the amplifier in the buffer mode

and brings the filter back into the operation range within

less than 100 �s [104], [105].

The effectiveness of the on-chip reset function for sti-

mulation artifact suppression is demonstrated inFig. 26(a). Bipolar pulses (220-�s overall duration) of

different amplitudes (�0.15 V and�1 V) in saline solution

have been applied, while the reset has been operational

(red trace �0.15 V; green trace �1 V) or not (blue trace

�0.15 V; black trace �1 V). The recordings from the sti-

mulating electrode are shown [105]. The readout filter for

the red and green trace was reset 50 �s before the sti-

mulation pulse was applied, and kept until 50 �s after the

Fig. 26. (a) Efficiency of the on-chip reset function for stimulation. Bipolar pulses (220-�s overall duration) of different amplitudes

(�0.15 V and �1 V) in saline solution have been applied, and the reset has been operational (red trace �0.15 V; green trace �1 V) or not

(blue trace �0.15 V; black trace �1 V). Without reset, it takes 20–100 ms for the recording circuitry to return to the measurement range.

The inset shows a closeup of the initial 20 ms at higher temporal resolution. Reprinted with permission from [105]. (b) Successful excitation

of spikes in cortical neurons from rat brain at 250-�m distance from the stimulation site. A single bipolar stimulation pulse of �800 mV and

50-�s duration was used to stimulate the cells in this example. The inset shows the poststimulus time histogram of this channel based on

142 stimulation pulses. Reprinted with permission from [105].

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stimulation pulse was finished. Without reset, it takes

20–100 ms (depending on the stimulation amplitude) for

the recording circuitry to return to the measurementrange. With reset, it takes less than 5 ms for the recording

circuitry to return to the measurement range. It is worth

mentioning that a stimulation sequence always ends with a

stimulation of a value close to the equilibrium potential of

the electrode before simulation so that the electrode

quickly returns to its equilibrium potential after the

stimulation procedure.

Stimulation experiments have been carried out withcardiomyocytes and neuronal cultures [105], [128], [129],

[144], [165]. Fig. 26(b) shows an example of a successful

excitation of spikes in a culture of cortical rat neurons

recorded at a 250-�m distance from the stimulation site

(low-density chip [104], [105]). A single bipolar stimula-

tion pulse of �800 mV and 50-�s duration was used to

stimulate the cells in this example. The inset shows the

poststimulus time histogram of this channel that includesthe results of 142 subsequent stimulation pulses. The first

event or neuronal signal generally occurs between 2 and

3 ms after the stimulation pulse with a very high proba-

bility of 96%.

The switching scheme of the high-density array that is

generally used to route a subset of electrodes to the read-

out channels of the system (Section IV-E2) can also be

used for stimulation. This means that every single elec-trode in the array can be chosen as the stimulation point.

This way, very localized stimulation can be performed

through a single 7-�m diameter electrode, so that generally

high spatio–temporal resolution stimulation and recording

can be performed using the MEA. Local stimulation and

the respective response propagation tracing through the

culture have been performed in an experiment shown in

Fig. 27 [166]. Stimuli (biphasic voltage pulses between

100- and 400-�s duration and þ=�0.7–1.3-V magnitude

per phase) were applied to a single electrode located in thebottom left corner and evoked activity of a subset of neu-

rons. Raw voltage traces are coded in color scale in the first

row of Fig. 27. A somatic action potential (blue) produces

spikes on multiple neighboring electrodes with peaks often

around �400 �V, some even exceeding a millivolt. How-

ever, the scale was reduced here in order to observe pro-

pagating action potentials. These are clearly seen when

plotting the minimum voltage recorded on each electrodesince the stimulus, as done in the bottom row. Each frame

is composed of 108 electrode configurations, and re-

sponses were averaged over 60 trials per configuration.

Each configuration comprises 6 � 17 electrodes and has

been scanned across the entire array. The culture was six

weeks old and seeded with 10 000 cells. As is evident from

the bottom row of Fig. 27, it was possible to observe the

antidromic propagation of action potentials along axonsand the subsequent occurrence of somatic action poten-

tials in the respective cells (blue spots, A and B in upper

row). Obviously, axonal electrical activity of cells A and B

has been triggered at the stimulation site, and the elec-

trical wave has then backpropagated along the axon to the

soma and led to cell depolarization [166]. It is remarkable

that the comparably weak electric activity of axons, tiny

structures of 1-�m diameter can be recorded by meansof high-density arrays of extracellular electrodes.

Finally, it is important to mention that the high-density

chips have been used to perform more than 20 000 stimu-

lations in a rat neuronal culture without damage to the

electrodes or the chips. This opens a route to a variety of

interesting experiments and, at the same time, proves the

efficiency of the passivation and packaging procedure.

Fig. 27. Propagation of axonal action potentials. Raw voltage traces (top row) and traces binned over 2 ms (bottom row) are color-coded.

Stimuli applied to a single electrode (arrow in first panel) evoked a subset of neurons, and somatic action potentials (blue) were detected by

multiple neighboring electrodes. The color scale was reduced in order to zoom-in on axonal APs (yellow). To sample all electrodes, coherent

6 � 17 electrode recording configurations were scanned across the array, and responses after 60 stimuli per configuration were averaged.

Reprinted with permission from [166].

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V. CONCLUSION AND OUTLOOK

The use of CMOS technology offers decisive advantages for

recording electrical signals from cells in vitro with regardto number and density of recording sites or electrodes that

can be used and with regard to obtained signal quality.

Integrated multiplexers and on-chip electronics enable

high-quality recording or stimulation through a large num-

ber of transducers and allow for attaining cellular or even

subcellular resolution. Moreover, elaborate user interfaces

along with electronic functionality on-chip and chip

self-identification features help the nonexpert user tocomfortably work with these high-performance devices.

A strong thrust goes in the direction to further increase

the number of stimulation and recording electrodes. In

pursuing this goal it has to be taken into account that a

large number of electrodes also generates a huge volume of

recorded data. Therefore, data sorting, standardized or

automated data interpretation, and data compression will

become pivotal issues. Methods like online spike detectionusing, e.g., an FPGA, will be very important to be able to

handle the data volume of long-term recordings from elec-

trode arrays with several hundreds or thousands of elec-

trodes. The approach of having a high-density array of

electrodes, where only a selected subset of the electrodes

in regions of interest is connected to recording and stimu-

lation channels by means of a switch matrix, seems also to

be beneficial for controlling the amount of recorded data.Another important trend includes the integration of other

sensor types into the system, such as chemical sensors

(electrolyte concentration, pH, and oxygen content) to

observe cellular metabolic characteristics or to monitor

neurotransmitters, or impedance sensors to study the local

electrolyte concentration, the cell attachment, or possibly

to get information on cell location and tissue morphology.

CMOS microsystem platforms will have, most proba-bly, a major scientific and technological impact, particu-

larly in neuroscience and neuromedical research. They

will enable fundamental neurophysiological insights at the

cellular and circuit level for investigating dynamic altera-

tions in neuronal connectivity patterns and provide a new

approach to investigate the behavior and information pro-cessing capabilities (including learning) of large popula-

tions of neurons in vitro or in slices. They may even open

routes to the design of dedicated hybrid Bintelligent[systems combining evolutionarily optimized highly paral-

lel information processing capabilities (of, e.g., brain cells)

with the more serial ones of microelectronics.

The CMOS-based systems will also find applications in

medical diagnostics and pharmacology. The systems can beused for assessing dose-related effects of all kinds of

chemicals or pharmacologically active substances [25],

[45], [46], [167]. This holds particularly true for long-term

measurements and multiple dosings or dosing sequences,

which cannot be studied using the patch clamp method

owing to the inherent short cell viability time (usually on

the order of hours) as a consequence of the invasive nature

of the method.Finally, CMOS-based integrated systems may also have

a large impact on in vivo applications in the field of neural

probes and prosthetics [4], [5], [50], [168]–[171]. There,

they may constitute a viable approach to recover skeletal

muscle function [168], [169] and to restore visual per-

ception [172], [173] or functions of the auditory system

[174], [175]. For practical neural prostheses, viable inter-

faces with tissue for months, years, or even decades will berequired. Mismatch in the mechanical properties (stiff

devices and soft tissue), inflammations, depletion of

neurons in the insertion region, tissue reaction, and probe

encapsulation with glial tissue yet compromise the long-

term electrical-recording quality and reliability and will

have to be addressed [50]. h

Acknowledgment

The authors would like to thank R. Pedron, K.-U. Kirstein,D. Scheiwiller, M. Ballini, J. Mueller, W. Franks, and

F. Greve for contributing to the development of the overall

system. U. Wahlen, D. Jackel, J. Sedivy, C. D. Bustamante,

D. Bakkum, and B. Roscic are acknowledged for help with

the measurements and the data analysis.

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ABOUT T HE AUTHO RS

Andreas Hierlemann (Member, IEEE) received

the Diploma in chemistry from the University of

Tubingen, Tubingen, Germany, in 1992 and the

Ph.D. degree in physical chemistry from the

Eberhard-Karls University, Tubingen, Germany,

in 1996.

After that, he held two postdoctoral positions

at the Texas A&M University, College Station

(1997) and at the Sandia National Laboratories,

Albuquerque, NM (1997–1998). In 1999, he joined

the Department of Physics, ETH Zurich, Zurich, Switzerland, where he

was appointed Associate Professor of Microsensorics in June 2004. In

April 2008, he became Full Professor of Biosystems Engineering at the

Department of Biosystems, Science and Engineering (D-BSSE) of ETH

Zurich in Basel, Switzerland. His research interests include the develop-

ment of integrated chemical and biomicrosensor systems, the develop-

ment of microfluidic techniques for cell handling and cell characterization,

and the direct coupling of biological entities, such as neurons or heart cells,

to microelectronic chips.

Urs Frey received the diploma in electrical

engineering from ETH Zurich, Basel, Switzerland,

in 2003 and the Ph.D. degree in electrical engi-

neering from the Physical Electronics Laboratory,

the Department of Information Technology and

Electrical Engineering, ETH Zurich, in 2008.

From 2008 to 2009, he was with the Bio

Engineering Laboratory, ETH Zurich, where he

was leading the CMOS-based MEA activities. In

2009, he joined IBM Research, Zurich, Switzerland.

The focus of his activities is on system design and interface circuitry for

CMOS-based sensors and storage devices.

Hierlemann et al. : Growing Cells Atop Microelectronic Chips: Interfacing Electrogenic Cells In Vitro

Vol. 99, No. 2, February 2011 | Proceedings of the IEEE 283

(PDF) Growing Cells Atop Microelectronic Chips: Interfacing Electrogenic Cells In Vitro With CMOS-Based Microelectrode Arrays - DOKUMEN.TIPS (33)

Sadik Hafizovic received the diploma in micro-

system technology from IMTEK, University of

Freiburg, Freiburg, Germany, in 2002.

He worked on his diploma thesis at the Tabata

Laboratories, Ritsumeikan University, Japan. From

2002 to 2007, he was with the Physical Electronics

Laboratory, ETH Zurich, Basel, Switzerland. From

2008 to 2010, he was a Researcher at the Bio

Engineering Laboratory, ETH Zurich. The focus of

his research activities was on atomic force

microscopy and CMOS-based microelectrode arrays for neuronal inter-

faces. Currently, he is CEO of Zurich Instruments, Zurich, Switzerland.

Flavio Heer (Member, IEEE) received the diploma

in physics and the Ph.D. degree from ETH Zurich,

Basel, Switzerland, in 2001 and 2005, respectively.

Since 2005, he has been a Senior Researcher at

the Bio Engineering Laboratory, ETH Zurich,

where he is involved in system design and

interface circuitry for CMOS-based biosensors

and biochemical sensors. His research interests

include signal processing and circuit design for

sensor interfaces. Moreover, he is a cofounder of

Zurich Instruments, Zurich, Switzerland.

Hierlemann et al.: Growing Cells Atop Microelectronic Chips: Interfacing Electrogenic Cells In Vitro

284 Proceedings of the IEEE | Vol. 99, No. 2, February 2011

(PDF) Growing Cells Atop Microelectronic Chips: Interfacing Electrogenic Cells In Vitro With CMOS-Based Microelectrode Arrays - DOKUMEN.TIPS (2024)

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