Sub-millisecond closed-loop feedback stimulation between arbitrary sets of individual neurons.

2.1 MB·English

by  Muller, Jan

METHODSARTICLE
NEURAL CIRCUITS published:10January2013
doi:10.3389/fncir.2012.00121
Sub-millisecond closed-loop feedback stimulation between
arbitrary sets of individual neurons
JanMüller*,DouglasJ.Bakkum andAndreasHierlemann
BioEngineeringLaboratory,ETHZürich,Basel,Switzerland
Editedby: We present a system to artificially correlate the spike timing between sets of arbitrary
SteveM.Potter,GeorgiaInstituteof neurons that were interfaced to a complementary metal–oxide–semiconductor (CMOS)
Technology,USA high-density microelectrode array (MEA). The system features a novel reprogrammable
Reviewedby: and flexible event engine unit to detect arbitrary spatio-temporal patterns of recorded
AntonioNovellino,ETTs.r.l.,Italy
action potentials and is capable of delivering sub-millisecond closed-loop feedback of
JürgStreit,UniversityofBern,
Switzerland electricalstimulationupontriggerevents inreal-time.Therelativetimingbetweenaction
*Correspondence: potentialsofindividualneurons aswellasthetemporal pattern amongmultipleneurons,
JanMüller,BioEngineering orneuronalassemblies,isconsideredanimportantfactorgoverningmemoryandlearning
Laboratory,ETHZürich, in the brain. Artificially changing timings between arbitrary sets of spiking neurons with
Basel,Switzerland.
oursystemcouldprovidea“knob”totuneinformationprocessinginthenetwork.
e-mail:[email protected]
Keywords:closed-loop,high-densitymicroelectrodearray,STDP,acausalstimulation,LTD,sub-millisecond
INTRODUCTION stimulation was shown to modify the functional connectivity
Different theories describing learningand memory inthe brain of neuronal networks, both in vivo and in vitro, as done by
havebeendeveloped,andconvergingevidenceshowsthatthepre- reprogramming the motor output of freely behaving primates
ciseactivitytimingofindividualorgroupsofneuronsmayplaya (Jackson et al., 2006a), changing the functional connectivity in
paramountroleinplasticityofneuronalcircuits.Thewell-known ratforelimbsensorimotorcortex(Rebescoetal.,2010),orshap-
spiketiming dependent plasticity (STDP)rule states that if two ing in vitro neocortical networks into predefined activity states
synaptically connected neurons fire within tens of milliseconds (Bakkumetal.,2008b).Invivosystemsusuallyrecordfromnee-
ofeachother,theconnectivity strength oftheinvolvedsynapses dlesinsertedintoacertainlocationofthebrainandsubsequently
gets potentiated or depressed depending on the firing order. In stimulate the same or another site upon the detection of activ-
pioneeringstudies,STDPruleswerediscovered(Markrametal., ity.Thesesystemsusuallycomprisetheimplantedneedles,ahead
1997) and further characterized (Bi and Poo, 1998; Song et al., stage to amplify the signals, and some means to transmit the
2000)byobservingtheeffectofcorrelatedfiringoftwoneurons acquired signals to a PC. In the case of closed-loop feedback
eitherartificiallyinducedbystimulatingapre-andapost-synaptic stimulation,thesesystemsusuallyfeatureadedicatedvery-large-
neuron with two patch-clamps or by applying trains of paired- scale-integrated application-specific circuit (VLSI ASIC) (Chen
pulsestimulito oneneuroninthe network (BiandPoo,1999). etal.,2009;Rizketal.,2009;Lee etal.,2010;Azinet al.,2011),
Furthermore,computationinanetworkislikelyduenotonlyto oruse a general-purposemicrocontroller to achieve the respec-
therelativetimingoftwoindividualneuronsbutalsotothecor- tivegoals(Mavoorietal.,2005;Zanosetal.,2011).Mostinvitro
relatedactivityofdifferentneuronsforminganassociatedgroup, systems,ontheotherhand,useadataacquisitioncard(DAQ)to
i.e.,assembly(Changetal.,2000;Izhikevich,2006).Inthisvein, sampledataforanalysisonaPC;feedbackstimulationistypically
different studies reported the existence of precise time-locked returnedthroughaDAQcardaswell.
activity patterns of multiple neurons, both in vivo and in vitro In order to accurately control the timing of feedback stimu-
(Abeles and Gerstein, 1988; Bienenstock, 1995; Ikegaya et al., lation loops within the timescales relevant for STDP to occur,
2004;Rolstonetal.,2007).Havingasystemtogeneratefeedback thedelaysintroducedbyasystemmustbeunderstood.Ageneric
stimulationquicklyandaccuratelyto interactwithsuchactivity description is given in Figure1. Different system implemen-
patternswouldexpandsuchstudiesbeyondfindingrulesgovern- tations will have different sources for and values of delays.
ingtheplasticitybetweentwocellstowardfindingrulesgoverning Signal-processingalgorithmsintroduce aninherent delayinthe
the spatio-temporal dynamics of whole networks or assemblies processing itself. Systems, which rely on general-purpose com-
(FroemkeandDan,2002;Izhikevichetal.,2004). puters,mightintroducelatenciesandjitterthroughthepresence
In recent years, different systems to artificially control such ofdatabuffers,interrupts,sharedresources,oruserinteractions,
feedback stimulation in a closed-loop manner, and thus study etc. In Figure1, the time points t0−3 and tS specify the occur-
neuronalplasticity,havebeendevelopedforbothinvivo(Jackson rence of important events. At t =0, the trigger neuron emits
0
et al., 2006b; Bontorin et al., 2007; Venkatraman et al., 2009) an action potential, which is recorded by the acquisition sys-
and in vitro applications(Bontorin et al., 2007; Hafizovicet al., tem.Afterenteringthesignal-processingstages,itisreadytobe
2007; Novellino et al.,2007;Rolston et al.,2010;Zrenner et al., detectedasaspikeeventattimet .Fromthere,thesystememitsa
1
2010;Wallachetal.,2011).Inturn,activity-dependentfeedback stimulationpulsehittingtheelectrodeattimet .Conventionally,
2
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Mülleretal. Sub-millisecondclosed-loopfeedbackstimulation
A B
FIGURE1|Schematicoverviewoflatenciesinfeedbackstimulation includingdigitalsignal-processinghardware,areal-timehostPC,orageneral
systems.(A)Thedifferentcomponentsmakingupaclosed-loopfeedback purposehostPC.Thetimepointst0−3andtScorrespondtodifferentevents
stimulationsystemareshown.Thegreencirclerepresentsthe“trigger aslistedin(B),suchastheoccurrenceofthespike;itsdetectionafter
neuron”whoseactionpotentialinitiatesthestartoftheloop.Thegreenline signal-processing;thestimulationfeedback;andtheantidromicpropagation
representsanaxonconnectingtosynapsesoftheelicitedneurondrawnin ofanactionpotentialbackintothesomaoftheelicitedneuron.AttimetS,
yellow.Theblackdashedarrowshowstheclosed-loopfeedbackstimulation thesynapseactivatesduetopre-synapticactivityofthetriggerneuron.The
path.Betweendataacquisitionandstimulationfeedback,different colorofthetracescorrespondstothecolorofthetimingsoft0−3,Sand
components,overwhichthefeedback-loopcanbeclosed,arepossible, schematicallyshowsthetimelineoftherespectivesignals.
the loop is considered “closed” at this point. The stimulation conductacausalstimulationexperiments.An“eventengine”was
pulseevokesneuronalactivity,frequentlyactivatingnearbyaxons designedandimplementedtotriggerfeedbackstimulationatthe
(Bakkum et al., 2008a) whose signals propagate antidromically occurrenceofactivitypatterns,suchasthosedescribedinIkegaya
towardthesomauntilelicitinganactionpotentialattimet .In etal.(2004)andRolstonetal.(2007).Patternscouldbeofalmost
3
thecasedepictedinFigure1,wherethetriggerneuronissynap- arbitrary length and could consist of up to 1000’s of individual
ticallyconnected totheelicited neuron,anadditionalbiological elements, only limited by the available resources of the FPGA.
time,t ,denotesthedurationofanactionpotentialpropagation Configurations for the event engine could be (re)loaded within
S
through the axon of the trigger neuron until synaptic activa- milliseconds. Unique to this system is the possibility to enable
tion of the elicited neuron. In case where t −t −t is faster low-latency, high-throughput, STDP-likeexperiments as well as
0 1 2
than t −t , that is when the signal propagates faster through acausal stimulations across many individual neurons, or neu-
0 S
theartificialfeedback-loopthandowntheaxontowardthebio- ronalassembliesinparallelthroughthesimultaneousapplication
logical synapse, acausal stimulation, and thus the introduction of manyfeedback stimulationloops. Toinfer changesin synap-
of long-term depression (LTD) according to the STDP rule, is tic strengths, correlations between putative mono-synaptically
possible. connected neurons (Fujisawa et al., 2008) can be monitored
In order to apply closed-loop stimulation feedback pre- using extracellular spikes. Inthe future, high-throughput STDP
cise and fast enough to study plasticity at the timescales of experiments will be possible by adding a patch electrode to the
STDP or acausal stimulation, and flexible enough to interact systeminordertomonitorchangesinintracellularpost-synaptic
with cell assemblies, we developed a field-programmable gate currents.
array (FPGA)-based system, interfaced with a complementary
metal–oxide–semiconductor high-density microelectrode array METHODS
(CMOS-MEA). The CMOS-MEA features a total of 126 read- SYSTEMARCHITECTURE
outand42 stimulationchannels, whichcanbeconnected to an The main design goals were to implement (1) multiple feed-
almostarbitrarysubsetof11,0115×7µm2electrodes,arranged backstimulationloops(2)tomatcharbitraryspikepatternswith
ina2×1.75mm2array.Thefeedbackstimulationloopisclosed (3) short latencies (<1ms) and (4) high accuracy(<50µs) (5)
around the CMOS-MEA using an FPGA that performs signal- while still recording from all available 126 channels. A main
processing,suchasspike-detectionandfeedbackgeneration.The component of the presented system is an FPGA, used to hijack
systemfunctionalitywasverifiedusingculturednetworksofcor- signals traveling between the analog-to-digital converter on the
tical neurons and glia. The minimum programmablelatency of CMOSdeviceandthehostPC.Duetotheinherentparallelnature
the closed-loop stimulation feedback (t −t −t ) was 400µs ofFPGAs,signal-processingandfeedbackgenerationusingdata
0 1 2
withjitterbelow50µs,suitabletoinduceSTDP.Thisisfasterthan from additional recording channels can be done without intro-
manyaxonalpropagationdelays(t −t ),renderingitpossibleto ducingadditionaldelaysorjitter.
0 S
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Mülleretal. Sub-millisecondclosed-loopfeedbackstimulation
The system consists of three main parts as shown in outside of the sensor array, instead of directly below the elec-
Figure2.Thefirstisahigh-densityCMOS-MEAdevicefeaturing trodes asdonein active-pixel sensor devices(APS) (Berdondini
on chip signal-conditioning, stimulation, and analog-to-digital et al., 2009), to provide space for larger circuitry elements that
conversion (ADC) units (Frey et al., 2010), described in more producelessnoise.Thisschemealsoallowsforreducingthepitch
detail in the next section. It is plugged into a custom printed of the electrodes below the spatial requirements of the readout
circuit board (PCB) that provides reference voltages and clock electronics.SeeFreyetal.(2010)formoredetails.
signals.ThedigitaldataasprovidedbytheCMOS-MEAaretrans-
mittedthroughalow-voltagedifferentiallinktoreducesensitivity FPGA
to electromagnetic interferences as caused, for example, by a A reprogrammable Virtex II pro FPGA (Xilinx Inc., San Jose,
nearbyincubator.ThesecondpartisanFPGA,whichreadsinthe USA) was used as an intermediate signal-processing device
differentialsignalsandsubsequentlyperformssignal-processing, betweentheCMOS-MEAandthehostPCtoperformreal-time
spike-detection,andfeedbackstimulation,aswellascompression signal-processing,decision-makingandfeedbackgeneration.The
andframingofthedatatobesentviaTCP/IPoverEthernettoa FPGA acquires digital data coming from the differential link
hostPC,thethirdmainpart.OnthehostPC,furtherdataanaly- and forwards it to a PC over Ethernet. The Virtex II pro fea-
siscanbeperformedonlineoroffline.Itisalsousedtoprogram turesanembeddedPowerPCmicroprocessorrunningat300MHz
andcontroltheCMOS-MEAdeviceduringexperimentationwith that operates a Linux kernel with a Busybox operating sys-
different settings, like amplifier gain or electrode-to-amplifier tem. TheTCP/IPstackoftheLinuxkernelhandlesthenetwork
routing,inordertobeadoptedforuseindifferentexperimental communication and data transfer. As the embedded PowerPC
sessions. microprocessor is relatively slow, compared to modern CPUs,
this provides a bottleneck for fast data transmission. We mea-
CMOSDEVICE sured the latency between the TCP/IP stack of the FPGA and
The CMOS-MEA includes 126 readout channels with pro- the host PC to be 83±21ms (mean ± SD, N =308) at full-
grammableamplification(0dBto80dB),onchipADCssampling framedatatransmission,whichislargerthantheSTDPwindow
at 20kHz, and stimulation capabilities (see below). It features ofuptotensofmilliseconds.Onesolutiontothisproblemmight
a sensorareaof2×1.75mm2 with atotal of11,011electrodes, be to stop streaming of the full data readout, while performing
each with a size of 5×7 µm2 and a pitch of 18µm. Beneath a closed-loop experiment and to only route out the data chan-
theelectrodesresidesasophisticatedanalog-switchingmatrixto nelsstrictlyneededfortheclosed-loopfeedbackstimulation.This
connect an almost arbitrary subset of the 11,011 electrodes to wouldfreesomeofthebandwidthoftheEthernetlinkandmake
the 126 readout channels. The readout electronics were placed it available for faster feedback stimulation. Crucially, however,
FIGURE2|Overviewofthepresentedclosed-loopsystem,implemented VirtexIIproFPGAboardfromDigilentInc.,Pullman,USA.ThehostPCrunning
withaCMOS-MEA,anFPGA,andahostPC.(A)Micrographofthe dataacquisitionandvisualizationsoftwareisconnectedtotheFPGAthrough
CMOS-MEAhighlightingtheelectrodearray,amplificationandstimulation Ethernet.(C)Schematicdiagramofthesetup.Thediagramshowsthe
units,andthedigitalcorewithaninsetshowingaclose-upofthestimulation acquisition(upperpart)andstimulationpath(lowerpart).Thefeedback
buffer.(B)PhotographoftheCMOS-MEApluggedintothecustom stimulationloopisclosedaroundtheCMOS-MEAandtheFPGA.The
printed-circuitboard,whichisconnectedthroughanLVDSlinktotheXilinx componentsaredescribedindetailinthetext.
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Mülleretal. Sub-millisecondclosed-loopfeedbackstimulation
we would lose the possibility to simultaneously monitor neural temporalresolutionsetbythesamplingfrequency,i.e.,20kHz.As
activity elsewhere in the cultured network by applying such a aconsequence,certaindesiredoperationsmightnotmakesense,
paradigm.Another optionmight beto bypasstheEthernet link asthebiologicalneuronshavesomeinherentvariabilityinwhen
bystreamingthedatadirectlytoaDAQcard,attachedtothehost theyspike.Forexample,theusermightwanttomatchapattern,
PC,andtosendstimulationinformationbackthroughasecond wheretwoneuronsspiketogether(seeFigure3E).Toachievethis,
linktotheFPGA.Allthesemethodsarelesspracticalthanusing aSPREADINGmodule“spreads”thespikepulseintimeinorder
theuniversalTCP/IPconnection, whichplugsintoalmostevery to compensate for jitter. This way, the subsequent AND mod-
kind of host PC and does not require additional hardware. An ulecangenerateanoutputeventwheneverthetwoneuronsfire
attractivealternativeforachievinglowlatencieswastoimplement togetherwithinaspecifiedrangeoftime.AsdiscussedinIkegaya
allneededsignal-processingandfeedbackgenerationdirectlyon et al. (2004)andRolston et al.(2007), 2msissuitableformost
the FPGA. The next paragraphshighlight the different building recurring patterns. Another module can be used to convert the
blocksneededtoimplementsuchascheme.AlthoughtheFPGA spread-outspikepulsebackinto a single one-shot event, which
canbereprogrammed atwill, this istime-consuming anderror then can be used, for example, to trigger the stimulation unit
proneand,therefore,notsuitableduringanexperimentalsession. onlyonceperspread-outpulse.Theparticularselectionofimple-
Toaccommodatereprogramming,amoreflexible,module-based mented modules (aslisted in Table1) represents a minimal set,
designwasdevelopedinVHDLandprogrammedintotheFPGA which, if combinedinthe appropriateway,allowsformatching
logictogetherwithasoftwareinterfacetoquicklyreconfigurethe different kindsofevents, suchasspecific spatio-temporal activ-
connectivityoftheindividualmodules(see“EventEngine”). itypatterns,timesequences,networkbursts,localbursts,etc.In
orderto keeptheeventengineasflexibleaspossibleandadapt-
SPIKE-DETECTION abletodifferent,possiblyunforeseenpatternmatchingsequences,
One such signal-processing building block is spike-detection, theimplementationofaminimalsetofsmallbuildingblockshas
which extracts spiking events from the raw voltage traces, been chosen over the approach, where each envisioned pattern
recorded at the electrodes. Spike-detection is implemented as a wouldrequireasingle,butmorecomplex,andlessflexiblebuild-
thresholdcrossing.Thesignalsarefirstdigitallyband-passfiltered ingblock.Thus,availablemodulescanbecombinedtogetherin
withatwo-tabButterworthfilter(500Hz–3kHz)tosuppressDC almostinfinitedifferentways,limitedonlybytheavailableFPGA
offsetcomponentsandhigherfrequencynoise;thiswillempha- memorythatkeepstrackofallsource-sinkassociations.
size the action potential frequency components. The detection
thresholdlevelisuser-programmableandtypicallysetaround4.5 STIMULATION/FUNCTIONGENERATOR
timesthenoisestandarddeviation.Duringexperimentation,this The CMOS-MEA has 42 on-chip integrated stimulation units,
valuecanbedeterminedbysoftwarerunningonlineonthehost whicharedrivenbytwo10bitDACs.OntheFPGAisafunction
PC.Afteranidentifiedspikeevent,wesetaprogrammablerefrac- generator implemented to achieve arbitrary stimulation wave-
toryperiodto3ms.Afterstimulation,detectionwasdisabledfor forms. A defined waveform has to be programmed at the start
3msaswell,toavoidoscillatingloopsduetofeedbackstimulation of the experiment. We used biphasic, first positive then nega-
artifactsbeingfalselyclassifiedasspikes. tive voltage pulses of 200µs duration per phase and ±300 or
400mV amplitude. The stimulation buffers can be chosen to
EVENTENGINE operateinvoltage-orcurrentmode(Livietal.,2010).Whenever
To avoid time-consuming reprogramming of the FPGA fabric, the event engine outputs an event, the appropriate stimulation
a more flexible and modular event-based scheme for feedback buffer, located on the CMOS-MEA, gets connected, and the
generation (Event Engine) wasdesigned and implemented. The function generator starts its operation. Stimulation artifacts on
event engine consists of small building blocks, called modules, the readout channels could result in falsely detected spikes and
eachofwhichimplementsaspecificsimplefunction.Eachmod- cause a reverberation problem for low-latency feedback-loops.
ulehasoneormoreeventsinksasinputsandoneeventsource Therefore, spike-detection is blanked during a time period of a
as an output. By connecting the event sources to the appropri- fewmillisecondsafterstimulationonset.
ateeventsinks,different,almostarbitrarypatternmatching,and
eventhandlingalgorithmscanbeachieved. Table1summarizes CULTURES
the implemented modules. Figure3 shows different basic con- Theperformanceoftheclosed-loopsystemwastested withcor-
figurations to achieve defined pattern matching. In Figure3A, tical neurons and glia grown over the CMOS-MEA. Animal
the simplest closed-loop configuration is depicted, where the handling protocolswereapprovedbythe Basel-StadtVeterinary
sourceofaspike-detectionmodulegetsconnectedtothesinkof officeaccordingtoSwissfederallawsonanimalwelfare.Briefly,a
adelayunitandfromtheretoastimulationfunctiongenerator. time-pregnantratwasanesthetizedusingisoflurane,thendecap-
Wheneverthesourceproducesanevent(i.e.,inthiscasedetectsa itated to gain E18 embryos. Cortices were extracted from the
spike), the sink triggers a stimulation pulseafter adefined time embryos and dissociated enzymatically in trypsin (Invitrogen)
delay. By means of software, the sources can be connected to followed by mechanical trituration. A layer of laminin (Sigma)
sinksdynamicallyandrapidlywithinmillisecondswhilerunning over a layerof poly(ethyleneimine) (Sigma)wasused to adhere
anexperimentsuchthatpatternmatchingcanadapttoongoing between 20 and 40k cells. Plating media consisted of 850µL
activityinthelivingculture.Onenotablepropertyisthelackof ofNeurobasal,supplementedwith10%horseserum(HyClone),
timebinning.Eachspikegetsrepresentedasasinglepulsewitha 0.5mMGlutaMAX(Invitrogen),and2%B27(Invitrogen).After
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Mülleretal. Sub-millisecondclosed-loopfeedbackstimulation
Table1|Aminimalsetofmodulesmakinguptheeventengine.
DELAY(t,A) DelaystheeventAbyadefinedamountoftimet.
AND(A,B) Emitsanevent,whenbothofthetwoinputevents,AandBoccurredsimultaneously.
OR(A,B) Emitsanevent,wheneitherofthetwoinputeventsAorBoccurred.
INH(t,A,B) Emitsanevent,whenaneventonA,however,noeventonBoccurredinadefinedtime
window,t,inordertocreateinhibitoryfeedback-loops.
RAND(p,A) PropagatestheeventAtotheoutputordropsitafteraBernoulli-distributedpseudo-random
variablewithadefinableprobability,p.
ACCU(n,A,B) Increments(eventA)ordecrements(eventB)aninternalaccumulatorandemitsanevent
afteradefinablethreshold,n,hasbeenreached,afterwhichitisresettozero.
SPREAD(t,A) SpreadstheeventAintimeforadefinedtime,t.
SPREAD−1(A) Convertstheonsetofaspread-outeventAbackintoasingleevent.
DETECTION(c) Emitsanevent,whenthespecifiedchannel,c,detectedaspike.
STIMULATION(c,A) Generatesastimulationpulseonthespecifiedchannel,c,wheneverinputeventAhappened.
START Singlepulseaftersystemstart-up,whichcanbeusedtostartrepetitivestimulationprotocols.
Configurableparametersarerepresentedinitalics(t,p,n,c),andinputeventsaredenotedinboldletters(A,B).
A E
B
F
C G
D H
FIGURE3|Exampleconfigurationsoftheeventengine.Stitchingtogether theonsetoftheevent.(F)WhentheeventonchannelBhappens
theappropriatesetofmodulesallowstheeventenginetobeconfiguredto subsequentlytoaneventonchannelA,aneventCisgenerated(G)AnACCU
matchavarietyofpatternsinordertotriggerfeedbackstimulation.Different moduleissettoincrement,wheneitheraneventonchannelAORchannel
minimalexamplesareshown.(A)ADELAYelementisinsertedaftera Bhappened,andtodecrement,whenadelayedeventfromchannelB
DETECTIONmoduletotriggerSTIMULATIONafteraprogrammabledelay. (traceC)arrived.Inthisexample,theACCUthresholdissettothreeevents.
Thisconfiguration,withthedelaysettozero,wasusedfortheexperiments Oncethethresholdisreached,theinternalcountergetsresettozero.When
showninFigures5,7.(B)EitheraneventonchannelAORaneventon thethreeinputeventshappenshortlyaftereachother,astimulationevent
channelBtriggersstimulation.(C)Inaprogrammabletimewindowbefore getsemitted.Asshownintheexample,thedelayedchannelB(traceC)
andafteraneventonchannelA,theremaynotbeanyeventonchannelBin decrementstheaccumulatorandthusdelaysorprohibitscrossingofthe
ordertotriggerstimulation(traceC).(D)ARANDmodulepropagatesor threshold.(H)Allmodulescanbecombinedtogethertoachievealmost
discardstheevents,inthiscasewithaprobabilityof½.(E)Eventson arbitrarilycomplexpatternmatching.Forexample,thisconfigurationwas
channelAandchannelBarefedthroughSPREADmodulesintoanAND usedtomatchthepatternofFigure6.Theformuladescribingthispatternis:
module,whichoutputsevents(ontraceC),whenbothinputsareactive.The STIMULATION(1,SPREAD−1(AND(AND(SPREAD(2ms,A),SPREAD(2ms,
intermediatetraceCisfedintoaSPREAD−1moduletotriggerstimulationat B)),SPREAD(2ms,C)))).
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Mülleretal. Sub-millisecondclosed-loopfeedbackstimulation
24h, the plating media was changed to growth media: 850µL
of DMEM (Invitrogen), supplemented with 10% horse serum, A B 100 µV 2 ms
0.5mM GlutaMAX, and 1mM sodium pyruvate (Invitrogen). 9 10
Cultures matured for 3–4 weeks prior to experimentation, and 11
experimentswereconductedinsideanincubatortocontrolenvi- 10
ronmentalconditions(34.5◦Cand5%CO2).Forfurtherdetails 4 5 8 9
seeHalesetal.(2010). 1 8
7
EVALUATIONANDRESULTS 6
This section begins with data characterizing the suitability of 3 5
our setup to perform closed-loop feedback stimulation experi- 4
ments,usingculturesofcorticalneuronsandgliaforvalidation. 2 3
First,theprocessofidentifyingneuronstobeusedinclosed-loop 0 67 2
feedback stimulation will be described. Then the system’s loop Voltage (µV) 11 1
speedandjitterperformancewillbequantified.Anexampleevent 200 µm
−100
enginewasruntoprovidestimulationfeedback,triggeredbyan
activity pattern. Preliminary dataand techniques to analyzethe
FIGURE4|Identificationofdirectlyevocableactionpotentials.
consequences of such stimulation on the functional connectiv-
(A)Datarecordedinresponsetorepeatedstimulationofoneelectrode
itybetween neuronswillbepresented anddiscussed.Finally,an (blackcross)fromthewhole2×1.75mm2sensorareaoftheCMOS-MEA
experimentalsessiontoinduceLTDthroughacausalstimulation (eachpixelisoneelectrode).Recordingelectrodeconfigurationswere
willbesketched,anditsimplicationsdiscussed.Datainthefigures scannedacrossthearrayinsetsof126electrodesatatime.Forevery
demonstrateproof-of-principleexperimentsfromindividualcul- configuration,datawererecordedfor12msafterstimulationonset.The
amplitudeofthenegativevoltagepeakwithinthese12msiscolor-coded
tures,thesetuphas,however,beensuccessfullyappliedtomany
andclippedat−100µV.Blueindicatesthedetectionofdirectlyevoked
tensofcultures.
somaticactionpotentials.(B)Exampletracesfrom11somasandthe
stimulationpulseareshownontheright.Tracesfrom30stimulationtrials
RECORDING/STIMULATIONSELECTIVITY areoverlaid,withthemediantracehighlightedinblack.Thestimulation
High-density CMOS-MEAs can potentially sample from com- artifactwasblankedpriortorecording.Numbersareorderedbyincreasing
plete neuronal populations. Due to the high-density (18µm distancefromthestimulationsite.
pitch) of the CMOS electrode array, every neuron lying on the
2×1.75mm2 array can be bidirectionally addressed. On the As shown, recording and stimulation with the CMOS-MEA
otherhand,whenstimulatingoneelectrode, adefinedsubsetof feature high spatial resolution and, therefore, are locally very
neurons is often directly activated in response (Bakkum et al., confined.However,thefactsthatoneelectrodecandetectsignals
2008a). Figure4 showssuch a scenario. In Figure4A, oneelec- from more than one neuron, and that the stimulation through
trode,markedwithablackcross,wasstimulatedmultipletimes, one electrode can directly evokeaction potentials of more than
andtheevokedactivity wasrecordedduringawindowof12ms one neuron have to be considered when planning closed-loop
after stimulation onset. The median calculated over all voltage feedback stimulation experiments. In this case, the feedback-
tracesfiltersoutnoiseandspontaneouslyspikingneurons/traces. loopisnotclosedbetweentwoneurons,butincludestwosetsof
Reliable activity (usually with a jitter on the order of 100µs or neurons.
below) is considered due to an antidromic action potential ini-
tiated at the neuron’s axon (Lipski, 1981). Since only a subset FEEDBACKLATENCIES
of 126 out of the 11,011 electrodes can be readout simulta- According to the rules of STDP, the timing window to induce
neously, the stimulation sequence was repeated multiple times, long-term potentiation (LTP) atsynapses isbetween lessthan a
each time with a different subset of electrodes, until all elec- fewmillisecondsanduptotensofmillisecondspost-synapticacti-
trodes were covered. After recording all sequences, the traces vation beforeandafterpre-synaptic activity. Thus,eventhough
of the individual recordings were aligned in time. To high- feedback cycles of 5–10ms are fast enough to induce LTP, we
light the electrodes that recorded elicited action potentials, the aimed at reaching cycle-times below 1ms to enable the system
negative peak of the recorded voltage level during 12ms after to perform acausal stimulations, as explained in the respective
stimulation is color-coded and clipped at −100µV. The red sectionbelow.
circles around the exemplified 11 spots highlight neurons that Figure5showstheoverlayof128tracesofthefeedback-loop.
fired directly elicited action potentials. Their traces are indi- Here, the event engine was configured to detect events on only
vidually shown in Figure4B, demonstrating that the elicited onechannelandstimulateimmediatelyafterdetection,i.e.,with-
action potentials were reliably and precisely fired after a given out any further delays in order to test the system performance
time, and only in a few cases (traces 2, 4, 6, 9), activity with (cf. Figure3A). The traces are aligned at the onset-time of the
different timing occurred. These could stem from a different stimulationpulse,andtimezeroissettobeatthenegativepeak
neuron that happened to sit near the same electrode and/or ofthespikeofthetriggerneuron.Inredarethetracesfromthe
from action potentials occurring within a coincident network trigger neuron, and in black, the traces from the elicited neu-
burst. ron. The timing between a trigger neuron spike and the onset
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Mülleretal. Sub-millisecondclosed-loopfeedbackstimulation
t −t 1.25 ms
0 3 40
400100
30
) stimulation artifact 300 S
µV tim
( 20
de 50 ula
mplitu 10 tion A
A 0 0 m
ding −10 plitud
or −50 e
c −20 (
e trigger spike elicited spike m
R −300 V
−400 t −t 0.85 ms −30 )
−100 2 3
t −t 0.2 ms −40
1 2
t −t 0.2 ms
−0.5 00 1 0.5 1 1.5 2 −50
FIGURE5|Feedbackstimulationperformance.Onehundredand elicitedinallbutfourcasesafterstimulation.Themedianoverallelicited
twenty-eighttracesfromaclosed-loopstimulationsequencearealignedat tracesisshowninboldwhite.Theantidromicpropagationdelayforthe
thestimulationonset-timeandoverlaid.Tracesinredshowthetriggerspikes elicitedspikeswasaround0.85ms.Thedifferenttimings,detectiondelay,
withthemedianoveralltriggertracesshowninboldred.Thestimulation stimulationdelay,andantidromicpropagationdelaysumuptothefullloop
artifactisgrayed-outforbettervisualclarity.Thetracesinblackshowspikes, delayof1.25ms.
of the stimulation pulse was 200µs, i.e., 4 sampling periods. ±50µsandarosefromthefactthatneuralactivityis,ofcourse,
Thisdelayarisesasfollows:50µs(1 samplingperiod)wasused not aligned to the samplingperiod ofthe CMOS-MEA(50µs).
to buffer the incoming data in the FPGA; 100µs accounted for Theexact time ofthe threshold crossingrelative to thenegative
the delay of the two-tab Butterworth filter and the last 50µs spikepeakdepends,amongotherthings,ontheslopeofthespike
account for all other delays, such as synchronizing the stimula- waveform.Sincetherecordedsignalwasnotinterpolatedbetween
tionpulsewiththerecordingsamplingtime. Delaysforsending samples,thiswasanunavoidablesourceforjitter.
digital data between the CMOS device and the FPGA were on
the orderofnanoseconds and thus arenegligible. Whenstimu- PATTERNMATCHING
latingwithbiphasicvoltagepulses,thesteep negativetransition, To demonstrate the event engine in operation, feedback
whichinjectsnegativecurrent(I=C×dV/dt),isthetimepoint, stimulation,triggeredbyanactivitypattern,wasperformed.For
when a cell is activated (Wagenaar et al., 2004; Bakkum et al., the dataset presented in Figure6, the event engine was pro-
2008b). Thus, this time point wastaken to measure the latency grammed according to Figure3H and classified spontaneous
betweenstimulationandanelicitedspike.Inthecasedepictedin activity patterns asfollows: Aneuronrecorded onelectrode N2
Figure5,thistiming is0.85ms,andtheoveralllatencybetween firesanactionpotential;thenanactionpotentialisrecordedfrom
trigger neuron activity and a spike on the elicited neuron was a neuron onelectrode N3 after 3ms; finally anaction potential
1.25ms. is recorded on electrode N1 after another 1.5ms. Each individ-
As can be seen in Figure5, besides achieving short feedback ualeventoccurrencewasallowedtohaveajitterof±1ms.After
cycles, anotheradvantageofusingdigitalhardware(inthis case successful identification of such a pattern, a stimulation pulse
FPGAs) for feedback generation is that no additional jitter is wasemittedtoelicitactionpotentialsonadifferentneuron,NE.
introduced,assuchasystemisfullydeterministic.Sourcesofjitter Thecellculturesunderinvestigationstypicallyexpressedbursting
inothersystems(Hafizovicetal.,2007;Rolstonetal.,2010)that behavior,andthiswaswhenalmostallofthepatternsoccurred.
closethefeedback-looparoundgeneral-purposeorreal-timeper- During bursts, the cells usually fired more than once at an ele-
sonal computers are, for example, system interrupts that might vatedfrequency,andthisexplainswhytheneuronsonelectrodes
disrupt the data processing, or buffer sizes of the USB, TCP/IP, N1–N3 showed additional spikes “outside” of the detected pat-
or DAQ cards, which have to be set large enough in order to tern. Nevertheless, the patternmatching event engine identified
guaranteefulldatathroughput.Usuallythesebuffershaveasize 22activitypatternoccurrencesduring12minofrecording.
largerthanonesampleperiod.Dependingonwhenaneventhap-
penedinsidethisbuffer,thelatencycouldbelargerorsmallerand CORRELATIONANALYSIS
thus introduce jitter. Thiscanbe avoidedby usingdigital hard- To assess the connectivity between different neurons and
wareto hijack the datastream. Inourcase, thejitter wasbelow the efficacy of change, induced by the closed-loop feedback
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Mülleretal. Sub-millisecondclosed-loopfeedbackstimulation
N3
5 ms
N1 N2
8 ms
N2
3.5 ms
N3
N1
2 ms
±400 mV
100 µV 1 ms
NE
100 µm
NE
−8 −5 −3.5 0 1.75
FIGURE6|Pattern-matchingfeedbackstimulation.Electrodetraceswere spread-out-windowssetintheeventengine.Ayellowboxofarbitrarywidth
recordedfromneuronssittingonthreedifferentelectrodesN1–N3while isdrawnaroundtheelicitedactivityofneuronNE.Abovethetraces,negative
performingpatternmatching.Thepatternwasmatched22timeswithin peaktimesaremarkedwithblackverticalbars,showingspikesclustered
12min,alloverlaidanddrawninlight-graycolor.Onearbitrarypatternis withinthecoloredboxes.Thefigureontherightshowselectrodelocations
highlightedwithblacktraces.The12msbeforeand4msafterstimulation andthetimingsmakingupthepatterntomatchaswellastheantidromic
pulseareshown.Theorange,green,andbluecoloredboxesrepresentthe propagationdelayof2mstotheelicitedneuron.
stimulation, cross-correlation curves (Perkel et al., 1967) were down the axonal arbor to the synapses depends on the propa-
computed between spike trains of the trigger neuron and the gation velocity of action potentials along axons and the length
elicited neurons. When exceeding a 95% confidence interval oftheaxons.Actionpotential conductionvelocitiesinunmyeli-
(Brillinger, 1976), correlationis considered significant. Figure7 natedaxonswerereportedaround0.2–0.4ms−1 (Debanneetal.,
shows three descriptive cases, comparing the cross-correlation 2011). As demonstrated in Figure5, the closed-loop stimula-
curvesfrom1hofspontaneousactivity beforeandafterclosed- tion (t −t ) can be as fast as 0.4ms, meaning acausal stim-
0 2
loop feedback stimulation was applied for 1h. To evaluate sig- ulation is possible for trigger neurons (t ) with unmyelinated
0
nificanceofthechange,asimilarprocedureasinFujisawaetal. axons that synapse to an elicited neuron (t3/S) after a mini-
(2008)wasused.Briefly,thetwotimes1hofspontaneousactivity mumaxiallengthof80–160µm.Figure8showssuchanacausal
recordingsweredividedintosmallerbinsof10mindurationand stimulation procedure. First, before applying a closed-loop, the
wererandomlyassignedtobebeforeoraftertheclosed-loopstim- activity between different neurons was measured then evalu-
ulation.Cross-correlationfromthisshuffleddatawascomputed ated by computing the cross-correlation. In the example in
for both “before” and “after” and the difference was evaluated. Figure8,thefiringactivity ofthesecondneuronBwithrespect
Thisprocedurewasrepeated 1000 times to generateasurrogate to the first neuron A was elevated around a delay of 2.5ms,
dataset. Pointsonthex-axis,wherethetruedifferenceislarger implying neuronAhas afunctional connection with neuronB.
than 95% of the surrogate data, were assigned to be significant Integratingthecross-correlationcurve,whereitexceedsthecon-
and are marked with an orange bar in Figure7. Assessing the fidence intervals around 2–3ms after the reference time zero,
true connectivity of neuronal networks by means of extracellu- reveals an integral probability of around 40% chance for neu-
larmeasurements is difficult, and using the cross-correlationto ron B to spike 2–3ms after neuron A had fired. Once two
thatendisnotideal,aseffectslikecommoninputsorfiringrate such neurons could be identified, closed-loop stimulation can
changes cannot be easily explained. However, in our context of be applied between them with a very short feedback cycle. In
evaluatingtheeffectoffeedbackstimulation,wedonotnecessar- thepresented example, thedelayfromthetriggerneuronto the
ilyseektopreciselyexplainthechangesinnetworkconnectivity, elicited spike was around 1ms, smaller than the average delay
but to rather demonstrate that a change occurred at all and to between the occurrence of their spontaneous action potentials.
whatextent. The closed-loop feedback stimulation was applied for 20min,
and, afterwards, the correlation was measured again. Now, the
ACAUSALSTIMULATION correlationnolongerexceededtheconfidenceintervalsataround
One motivation for very short feedback cycles is to open the 2–3ms after the trigger neuron. Note, however, that Bi and
possibility of acausal stimulation. If the closed-loop stimula- Poo (1998) have shown that LTD can only be induced, if the
tion(t −t )isfasterthanthetimeittakestheactionpotential spontaneous synaptic efficiency is not strong enough to evoke
0 2
to travel along the axon and hit the synapses (t −t ), acausal a post-synaptic action potential. Otherwise, the post-synaptic
0 S
stimulationand,therefore,inductionofLTDbymeansofclosed- Ca2+ influx dominates, and LTP will occur. For the experi-
loop feedback stimulation is possible. The time that it takesfor ment showninFigure8,the elicited neuronspikedonlyafrac-
anaction potential, initiated at the axonalhillock, to propagate tion of the time, and provided an intermediary synapse; in all
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Mülleretal. Sub-millisecondclosed-loopfeedbackstimulation
A B C
Corr 7 4 6 before
− after
X
d significant
e
z
ali
m
or 4
N 1 0
−20 20 −100 100 −600 600
Time (ms) Time (ms) Time (ms)
60 60 60
40 40 40
20 20 20
Time (min)
0 0 0
−20 20 −20 20 −100 100−100 100 −600 600−600 600
FIGURE7|Cross-correlationanalysis.Threedescriptivecasesofchanges withblackdashedlines.Cross-correlationiscomputedbasedontrainswith
incorrelatedfiringbetweentriggerneuronsandelicitedneurons. 9000–13000spikesperneuron.(A)Relativeprobabilityremainedconstant,
Spontaneousactivitywasrecorded1hbeforeand1haftertheapplicationof butthetimingbetweentriggerneuronandelicitedneuronchangedand
closed-loopfeedbackstimulation.Periods,wherethedifferenceexceededa becamemoresynchronous.(B)Theelicitedneuronbecamemorelikelyto
confidencebound(seetext),wereassignedtobesignificantandare fireinconcertwiththetriggerneuron.(C)Relativetimingwithinanetwork
indicatedwithanorangebar.The95%confidenceintervalsareindicated burstchanged.
e
A B C D ps
a
yn A
s
al
ci
artifi 0.4 ms
~2.5 ms
~2.4 ms ±0.4 ms ~1.1 ms
0.7 ms
B
100 µm
±400 mV E
before CL during CL after CL
FIGURE8|Schematicofan acausal stimulationsequence. situationasin(A)butwithaclosed-loop feedbackstimulationapplied.Due
(A) Spontaneous activity before application of the closed-loop. Shown to the low-latency loop, the timedelay of the yellow spikes with respect
spike traces are the median waveform of several spikes aligned atthe to the green ones wasreduced byabout 1.3ms.For neuron A,the trace
negative peak. Top: Spiketrace ofthe trigger neuron, A,ingreen. waszeroed at the start ofthe stimulation pulse. (C) Sameas(A)
Middle: Examplespike trace of acorrelated neuron, B,drawnin yellow. but after the application of the closed-loop feedback stimulation. The
Thetimedelaybetweentheplotted spikesofneuronAandneuron Bwas cross-correlation no longer showsasignificant peak for latencies larger
chosen to align withthe maximum peak of the cross-correlation curve. than zero. The time delay between the plotted spikes ofneuron A and
Bottom:Cross-correlation curveofspike-times ofneuronBwithrespect to neuron B wasagain chosen to alignwith the maximum peak of the
neuron A.95% confidence intervals aredrawn with dotted red lines. cross-correlation. (D) Geometric sketch ofthe situation. The trigger neuron
Cross-correlations were computed withtrains having 2000–3000 spikes. A and itsaxon are shown ingreen and the elicited neuron B inyellow.
Significantly elevated correlated activity ofneuron B canbe detected (E)Comparison ofthetwocross-correlation curves before (black)andafter
around 2.4 ±0.4msafter neuron A fired anaction potential. (B) Same (red) the acausal stimulation withtheir 95% confidence intervals.
other cases, evoked excitatory post-synaptic currents (EPSCs) simultaneously, extracellular recordings targeted to many trig-
remainedbelowthethreshold.Furtherexperimentsarerequired ger neurons, and an elicited neuron on the CMOS-MEA
before drawing conclusions. Additionally, to explore LTD and could be combined with an intracellular patch-clamp, attached
LTP in more depth, and advantageously, across many synapses to the elicited neuron and measuring the incoming EPSCs.
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Mülleretal. Sub-millisecondclosed-loopfeedbackstimulation
DISCUSSION of hundreds of synapses in parallel. Furthermore, by hooking
Withthepresentedsystem,capableofapplyingmultipleflexible up the patch-clamp system to the event engine through dedi-
feedback-loopssimultaneously, many different experiments will cated spike-detection and stimulation modules, feedback-loops
bepossible. The dynamicclamptechnique proved to be avalu- could be applied through the patch-clamp between extracel-
able tool for investigating the membrane dynamics involved in lularly recorded and intracellularly stimulated (or vice versa)
action potential generation (Destexhe and Bal, 2009; Economo neurons.
et al., 2010). In such systems, intracellularly applied closed- Although,duetothehigh-densityofelectrodes,potentiallyall
loop-controlledvoltagefeedbackenablesthemanipulationofcell neuronscanberead outindividually, the recorded signalsfrom
membrane functions. Similarly, extracellularly applied closed- twodifferentneurons,locatedclosetoeachother,aresometimes
loop stimulation feedback, as presented in this work, might difficult to separate. A spike-sorting step, incorporated prior to
provideausefultoolforinvestigating cellularandnetwork level event detection, can help to sort, and separate even neurons
plasticityandenablethemanipulationofneuronalnetworkfunc- recorded from with the same electrodes. This holds in particu-
tions. Potential questions include how information processing lar forusing high-density electrode arrays(Frankeet al., 2012).
and the amount of memory that can be stored in a cultured Thespike-sortingmightenabletheidentificationofneuronswith
network are influenced by adding one or more feedback-loops. smallerspikingamplitudes,closetothenoiselevel,andtheidenti-
Furtherexperimentsmightinvolvemoredetailedstudiesofboth ficationofmoreneuronsorcellassemblies.However,adrawback
LTP and LTD of individual sets of neurons by implementing of more sophisticated spike-sorting algorithms is an additional
causalandacausalfeedback-loopsbetweenthem.Usingthepat- timedelayinthedetectionphase(t −t ).Spike-sorting,together
0 1
tern matching capabilities of the event engine will allow for withintracellularstimulationthroughpatch-clampasdescribed
extending plasticity studies to the network level. For example, above, could eliminate the aforementioned limitations in sec-
investigations of the temporal orderand history ofspiketrains, tion “Recording/stimulation selectivity”: Trigger spikes can be
similartothosereportedbyFroemkeandDan(2002)andIkegaya assignedtoanindividualneuronthroughspike-sorting,andstim-
etal.(2004),couldbeperformed,however,inparallelonmultiple ulationpulseswillonlyactivate actionpotentialsinthepatched
different neurons and pathwaysand, in addition, the respective neuron.
pathways could be dynamically altered by targeted closed-loop
feedbackstimulations.Furtherrulesgoverningplasticitybeyond CONCLUSION
theclassicalSTDPcouldbeinvestigated. ByusinganFPGAtoperformsignal-processing,aswellasfeed-
An inherent limitation of extracellular recording systems is back generation, fast, and flexible loop cycles have been real-
the inability to directly measure EPSCs. Conventional plastic- ized. Our approach using reconfigurable digital hardware to
itystudiesrely onpatch-clamp to directly measurethe EPSCto perform computationally intensive tasks, such as signal filter-
assesssynapticconnectivitystrength.Sincethesecurrentsarenot ing, spikeidentification, decision-making,andfeedbackgenera-
accessible with extracellular measurement techniques, indirect tion, is a compromise between traditionally employed methods
methods to assess synaptic connectivity have to be employed. either using a general-purpose(micro-) processor, which intro-
Although cross-correlation seems attractive and is commonly duces additional latencies, and jitter, and the highly integrated
usedtoassessconnectivity,eitherbetweendifferentbrainregions application-specific circuits (VLSI ASICs), which are much less
or networks, or even between individual cells, it remains to be flexibleintermsofadaptationstonewexperimental paradigms.
investigatedtowhatextentcorrelationanalysisunveilsthedirect Ourachievedclosed-loopfeedbacklatenciesarelowerthanmany
synaptic strength between neurons. A combination of patch- axonal propagation delays and thus enable acausal stimulation.
clamp techniques and MEAs would provide a more direct way Due to the flexible event engine, high-throughput experiments
to measure the EPSC than through the computation of cross- applyingmanyfeedback-loopsinparallelareconceivable.
correlationcurves. By patching the post-synaptic neuron, EPSC
strengths can be directly measured and related to extracellu- ACKNOWLEDGMENTS
larly recorded pre-synaptic activity. Combining the advantages We thank Milos Radivojevic and Marta Lewandowska for cul-
ofbothtechniques,i.e.,thepreciseEPSCmeasurementsthrough turing assistance and Felix Franke, Michele Fiscella, Ian Jones,
patch-clamp, and the large-scaleparallel, extracellular measure- and David Jäckel for helpful discussions. This work was finan-
ments and stimulations through CMOS-MEAs with flexible cially supported through the ERC Advanced Grant 267351
feedback-loopsprogrammedbythe eventengine, wouldgreatly “NeuroCMOS” and the Swiss National Science Foundation
expand experimental horizons. One could study the plasticity AmbizioneGrantPZ00P3_132245.
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