ENSEMBLE RECORDINGS IN AWAKE RATS: ACHIEVING ...

ENSEMBLE RECORDINGS IN AWAKE RATS: ACHIEVING BEHAVIORAL REGULARITY DURINGMULTIMODAL STIMULUS PROCESSING AND DISCRIMINATIVE LEARNING

EUNJEONG LEE, ANA I. OLIVEIRA-FERREIRA, ED DE WATER, HANS GERRITSEN, MATTIJS C. BAKKER,JAN A. W. KALWIJ, TJERK VAN GOUDOEVER, WIETZE H. BUSTER, AND CYRIEL M. A. PENNARTZ

UNIVERSITY OF AMSTERDAM, THE NETHERLANDS

To meet an increasing need to examine the neurophysiological underpinnings of behavior in rats, wedeveloped a behavioral system for studying sensory processing, attention and discrimination learning inrats while recording firing patterns of neurons in one or more brain areas of interest. Because neuronalactivity is sensitive to variations in behavior which may confound the identification of neural correlates,a specific aim of the study was to allow rats to sample sensory stimuli under conditions of strongbehavioral regularity. Our behavioral system allows multimodal stimulus presentation and is coupled tomodules for delivering reinforcement, simultaneous monitoring of behavior and recording ofensembles of well isolated single neurons. Using training protocols for simple and compounddiscrimination, we validated the behavioral system with a group of 4 rats. Within these tasks, a majorityof medial prefrontal neurons showed significant firing-rate changes correlated to one or more trialevents that could not be explained from significant variation in head position. Thus, ensemblerecordings can be combined with discriminative learning tasks under conditions of strong behavioralregularity.

Key words: attention, prefrontal cortex, electrode, single unit, spike, olfactory, visual discrimination

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Traditionally, the cognitive neuroscience ofsensory processing and attention has mainlyfocused on studies in humans (Debert, Matos,& McIlvane, 2007; Hopfinger, Buonocore, &Mangun, 2000; Macaluso, Frith, & Driver,2001; Talsma, Doty, & Woldorff, 2007) andmonkeys (Everling, Tinsley, Gaffan, & Dun-can, 2006; Sugihara, Diltz, Averbeck, & Ro-

manski, 2006). There is an increasing need,however, to investigate the neural basis ofthese processes also in smaller vertebrates,such as rats and mice. Invasive electrophysio-logical recording methodology for rodents hasbeen developed to an advanced level, such thatcurrently tens to more than one hundredsingle units can be recorded simultaneously infreely moving animals (Gray, Maldonado,Wilson, & McNaughton, 1995; McNaughton,O’Keefe, & Barnes, 1983; O’Keefe & Recce,1993; Wilson & McNaughton, 1993). Todecrease the ethical burden associated withinvasive primate research and take advantageof the technological and genetic opportunitiesin behaving rodents, we sought to develop abehavioral setup for investigating neurophysi-ological correlates of cognitive processes thatdepend on sensory processing in rats that areallowed free movement within a behavioralcage, but can also display strong behavioralregularity during stimulus sampling. We de-fine behavioral regularity as stereotyped behav-ioral topography during the presentation ofstimuli that it is required to distinguish.Achieving behavioral regularity is importantnot only for a precise application of stimuli,but also to assess whether changes in neuralresponse patterns are related to cognitiveprocesses or to motor confounds. In additionto studying sensory processing, such a setup is

Eunjeong Lee is now at the Sobell Department of MotorNeuroscience and Movement Disorders, Institute ofNeurology, University College London, London, UnitedKingdom. Ana I. Oliveira-Ferreira is now at the Depart-ment of Experimental Neurology, Charite UniversityMedicine, Berlin, Germany. We wish to thank K.D. Harris(State University of New Jersey, Rutgers-Newark, NJ) andA. David Redish (University of Minnesota, Minneapolis,MN) for the use of the cluster-cutting programs Klustakwikand MClust, respectively. We thank Rein Visser, RinusWestdorp and Ruud N.J.M.A Joosten for their inputs indeveloping the behavioral setup described here. Thetechnical and conceptual contributions by Daan deZwarte, Theo van Lieshout and Ron Manuputy aregratefully acknowledged. This work was supported by BSIKgrant 03053 from SenterNovem (the Netherlands), VICIgrant 918.46.609 from NWO and EU grant 217148 toCMAP. A video clip (see p. 119) will be available in thesupplemental section of this article available at PubMed-Central.

Address correspondence concerning this article toEunjeong Lee (e-mail: [email protected]) or CyrielPennartz (e-mail: [email protected]), Department ofCognitive and Systems Neuroscience, Swammerdam Insti-tute for Life Science, University of Amsterdam, Kruislaan320, 1098SM, Amsterdam, the Netherlands.

doi: 10.1901/jeab.2009.92-113

JOURNAL OF THE EXPERIMENTAL ANALYSIS OF BEHAVIOR 2009, 92, 113–129 NUMBER 1 ( JULY)

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useful for exploring neural correlates of a widevariety of processes, such as stimulus discrim-ination learning, memory consolidation, inte-gration of multimodal sensory information,working memory, attention, decision-makingand sensorimotor control.

In primates, it has been feasible to studyneurophysiological correlates of attention byreducing motor or sensory confounds duringthe relevant period of information processing.Usually, body, head and eye positions remainstationary during the presentation of sensorystimuli, and sensory input can be kept con-stant while attentional demands are beingvaried (e.g., Steinmetz, et al., 2000; Treue &Maunsell, 1996). This stasis can be achievedusing head fixation by skull-implanted headbolts and other measures such as continuouseye tracking. We sought to achieve behavioralregularity in freely moving rodents to studyneural correlates of cognitive processes with-out marked sensorimotor confounds.

Much progress has been made in develop-ing behavioral paradigms to test sustained ordivided attention, recognition memory, work-ing memory, attentional set shifting and manyother tasks in rodents (Birrell & Brown, 2000;Brigman, Bussey, Saksida, & Rothblat, 2005;McGaughy, Turchi, & Sarter, 1994; Muir, 1996;Robbins, 2002; Sarter & McGaughy, 1998; Tse,et al., 2007), but often profound adaptationsof these tasks are necessary when motor orsensory confounds must be minimized, such asin unit recording studies. In contrast, suitablebehavioral methodology has been developedto examine the neurophysiological processingof unimodal sensory stimuli (Polley, Steinberg,& Merzenich, 2006; Szabo-Salfay, et al., 2001)and discriminative learning within a singlesensory modality (Schoenbaum, Chiba, &Gallagher, 1999; van Duuren, et al., 2007),but also this field of research may benefitfurther from novel equipment allowing stron-ger control over and monitoring of behaviorand simultaneous, time-controlled applicationof stimuli across multiple sensory modalities infreely moving rats.

To address this issue, we designed a multi-modal stimulus chamber (MMSC) and sur-rounding behavioral cage to meet the follow-ing requirements: (i) it should allow theanimal to display a stereotyped, regular behav-ior and body posture during stimulus sam-pling, at least for a restricted period of time;

(ii) stimuli should be presented to the animalin an automated and time-controlled manner,in at least two sensory dimensions (visual andolfactory); (iii) the MMSC and surroundingbehavioral cage have to be compatible withsizable headstages for independent position-ing of multiple electrodes and chronic record-ings in targeted brain areas; (iv) the cageshould offer sufficient means to assess behav-iorally whether the animal performs a sensoryor cognitive task correctly or not, that is, itshould comprise a subsystem allowing theanimal to behave and be reinforced appropri-ately. Instead of offering a solid, multidimen-sional object for the animal to explore withmany degrees of motor variability, we chosethe solution of essentially creating a ‘‘hollow’’object (i.e., the MMSC) which can be exploredin a time-controlled manner by the rat makinghead entries into it. In this article we describethe MMSC system and training proceduresused to produce behavioral regularity indiscrimination tasks so that aspects of stimuluscontrol and behavior can be clearly related tofiring of neurons in freely moving rats. Wevalidate the system by successfully training ratsin it on a sensory discrimination task, showingbehavioral disruption and adjustment when asecond, distractive set of stimuli from anothersensory modality is introduced.

METHOD

Subjects

Before the onset of experiments, maleLister-Hooded rats (N 5 4; Harlan, theNetherlands; body weight 250 g) were allowedto acclimatize for one week in a 12-hr light/12-hr dark cycle (light on 08:00) and were housedin pairs. Once the experiment started, ratswere housed solitarily. Food (Harlan Teklad,Global 18% Protein Rodent Diet) was availablead libitum. Animals had access to a waterbottle for approximately 0.5 to 1.5 hr after theend of a behavioral session. All experimentswere carried out in accordance with nationalguidelines on animal experimentation andwere conducted in a room dimly lit withorange lights.

Apparatus

Multimodal stimulus setup. The multimodalstimulus setup consisted of three subsystems

114 EUNJEONG LEE et al.

(see Figure 1): (i) a behavioral cage, theMMSC, stimulus delivery facilities and a systemfor commanding this behavioral setup, beinginstalled on a personal computer and using aRabbit 2000 microprocessor (type RCM2250,Delmation Products, Zoetermeer, the Nether-lands); (ii) a behavioral monitoring system,comprising a videocamera (Cohu2200; CohuInc., San Diego, U.S.A.), a videotracker fortracing the animal’s head position (Neuralynx,Bozeman MT, U.S.A.), a TV monitor and DVDrecorder; (iii) an electrophysiological dataacquisition system.

The larger behavioral cage (51.6 3 30.0 339.6 cm; Figure 2A) contained a grid floor anda fluid well. Both the MMSC and behavioralcage were placed inside a Faraday cage(Figure 1A; 100 3 75 3 125 cm, covered withsound-attenuating material). The MMSC andadjacent behavioral cage were separated by awall containing a head-entry port (Figure 2A).

The videocamera and a house light weremounted on one of the inside walls of thisFaraday cage. To avoid interference of video-tracked rat positions by light reflections, allparts of the behavioral cage exposed to thecamera were made of dull black materials. Thefluid well was modified after a design bySchoenbaum and Setlow (2001); its gravity-fed fluid supply system contained four lines,each operated by a solenoid valve (Versa valve,E5SM series, Doedijns, Cuijk, the Nether-lands), three of which delivered fluid to thewell (sucrose, quinine or water to flush thelines) and one controlled suction. Onsets andoffsets of nose pokes into the fluid well weredetected using an LED detector. In addition,we measured onset and duration of lickingbehavior by an optic detector (based on type:Banner, D12DAB6FP AC-coupled; ClearwaterTechnologies, Boise ID, U.S.A.). The wallpanel with head-entry port and trial onset

Fig. 1. Behavioral system for multimodal stimulus presentation and discrimination learning. The data acquisitionsystem, comprising amplifiers, oscilloscopes (OSC) and a behavioral monitoring and recording system, is shown on theleft. The multimodal stimulus system is shown on the right and includes a Faraday cage (a), an odor application system(b), a DC-powered ventilator (c), a behavioral cage (d) with attached multimodal stimulus chamber (MMSC) (e). Avideocamera (f) was attached to the ceiling of the Faraday cage and, upon neurophysiological recording, spike and EEGsignals were conveyed to the amplifiers via a headstage, cables and a commutator.

NEURAL RECORDING WITH BEHAVIORAL REGULARITY IN RATS 115

light was situated on the opposite side of thebehavioral cage (Figure 2A). To promote stasisof the rat’s head and body position duringstimulus sampling, the head-entry port wasplaced at a relatively elevated position abovethe grid floor (center point: 9.5 cm abovefloor; diameter 3.0 cm) and a shelf (2 3 7 30.7 cm) was installed onto the wall, 4.8 cmbelow the center of the port. In practice, ratseasily learned to place their forepaws onto the

shelf while poking into the port. Both theMMSC and surrounding behavioral cage werecommanded and monitored by the Rabbit2000 microprocessor system; software forbehavioral control was written in Dynamic Cand Visual C++.

Trial onset was marked by lighting a greenLED on the right side of the head-entry port(Figure 2A). To detect head entry and with-drawal, we constructed a dual-beam infrared

Fig. 2. Details of the multimodal stimulus chamber (MMSC) and adjacent behavioral cage. A: the behavioral cageincluded a head-entry port (a) for gaining access to the MMSC; a horizontal shelf upon which the rat put its forepawsduring stimulus sampling (b); a light for signalling trial onset (c); an LCD screen for presenting visual stimuli (d); and afluid well (e). B: MMSC, with head-entry port (a); LCD screen (d); and odor delivery nozzle (f). C: fluid well, with LEDdetecting ‘‘nose down’’ response (g); optic sensor detecting licking behavior (h); and three nozzles for fluid delivery(one of which is indicated by ‘i’). D: front panel of the MMSC with head-entry port fitted with LED (j) and a mirror (k)for creating a dual beam, facilitating detection of head entry.


light detector (Figure 2D; Farnell, Leeds UK,Sharp photodetector, type 970-7840) using aset of two mirrors 90u angled to each other.The MMSC contained two air-pipes (forremoving odor stimuli), a speaker and amicrophone for presenting and detectingsound stimuli (details of which will not bepresented here) and a 43.2-cm (17 inch) flatmonitor for visual stimuli (Figure 2B). Theodor application and removal system wasbased on a design by Schoenbaum that usedvacuum suction (Schoenbaum, 2002), but weused ventilators in addition to vacuum lines toquickly remove large-volume odor remnantsfrom the MMSC. A custom-made camera withtelescopic lens was placed inside the MMSC forvisual inspection of the rat’s eye and headposition inside the MMSC. The computerscreen displaying visual stimuli was placedopposite to the wall segregating the MMSCfrom the larger behavioral cage (Figure 2B),so that the rat was facing the screen upon headentry at a distance of approximately 14 cm.While a large part of the screen was covered bya wall plate, the visual stimuli were presentedthrough a transparent, plexiglass window inthis plate (12 3 9 cm) to prevent leakage ofodor out of the MMSC.

Odor application system and control ofstimulus timing. To achieve optimal timing ofodor application, we set up an airflow contain-ing a preselected odor already well in advanceof stimulus onset, routing this airflow througha bypass until the moment of odor presenta-tion in the MMSC. First, odorized air, collectedfrom each of nine glass vials containingfragrance odorant oil (Tokos B.V.,Noordscheschut, the Netherlands), was mixedin a 1:1 ratio with clean air pumped in via apressure line. At a flow rate of 1.5 l/min, thismixture was conducted to an odor-selectionstation composed of 10 solenoid valves (typeET-2M-12V DC, Clippard Instruments, Cincin-nati OH, U.S.A.). During the intertrial interval(ITI) an odor presentation was prepared byopening a series of valves that routed theodorized air flow via a bypass unit into anexhaust line operated by a modified DC-powered ventilator (motor type: AXH 230KC-A, Oriental Motor Co., Torrance CA,U.S.A; fan type: Cross-Flow Blower, TAS18B-002, Trial S.P.A, Italy; capacity 3.0 l/min.; valve2 ‘‘bypass unit’’ and switch 4 ‘‘fan out’’,respectively). Meanwhile, the air flow was

prevented from entering the MMSC by keep-ing two other valves closed (valves 1 and 3).Both during trials and ITIs, operation of theexhaust ventilator kept the MMSC undernegative pressure to avoid possible leakage ofodor into the behavioral cage. Once the ratpoked his head into the chamber, the exhaustventilation was turned off (switch 4 at ‘‘fanout’’ closed) and 300 ms following nose pokeonset, the odorized air was routed into theMMSC by opening valve 1 and closing valve 2,while valve 3 remained closed. Followingstimulus sampling (.700 ms), odorized airwas removed by activating a vacuum line (valve3; 25 kPa) as well as the bypass route again(valve 2 open and switch 4 on), whereas valve 1was closed. Following head withdrawal andfluid sampling, the valve controlling vacuumsuction (valve 3) was closed again and the odorcontrolling system was returned to ITI state.

For fast presentation of visual stimuli, thecomputer was programmed to retrieve theappropriate file from a multimedia event listduring the ITI. During the ITI the visualpattern remained occluded by a black screen(‘‘mask’’), so that the visual stimulus wasretrieved from memory and prepared forpresentation, but not yet presented to therat. The latency between the computer com-mand and onset of the visual stimulus was lessthan 10 ms. This method of presentation wasfaster by about 260 ms and more reliable thanwhen the visual stimulus had to be retrievedfrom memory upon stimulus presentation.After at least 300 ms had elapsed followinghead entry into the MMSC, the black screenwas removed; it was reinstated again after thestimulus sampling period (.700 ms) was over.

Procedure

General aspects of behavioral tasks. Althoughvarious types of task were employed, thebehavioral setup will be explained accordingto the structure of the most basic task used, asimple discrimination (SD) task. The onset ofa trial was marked by a trial light turning on(Figures 2A and 3); a trained animal subse-quently poked its head into the entry port(Figure 2A) and thereby gained access to theMMSC (Figure 2A, B). Once its head wasstationary inside this chamber, a visual orolfactory stimulus was presented for 700 ms.Each stimulus belonged to a pair of stimuliwithin the same sensory modality, one of


which (S+, the positive stimulus) was coupledto reward if the animal performed a correct(‘Go’) response (150 ml sucrose solution,0.3 M in distilled water; Merck) and the other(S2, the negative stimulus) to an aversivestimulus that punished ‘Go’ responses to thisstimulus (150 ml quinine solution, 0.02 M indistilled water; Sigma). The animal learned togenerate a Go response following an S+(‘‘hit’’) and a NoGo response following anS2 (‘‘correct rejection’’). Following stimulusdelivery and head retraction from the port, theGo response consisted of a locomotor re-sponse to the fluid well (Figures 2 and 3),and an additional ‘‘nose down’’ response intothe fluid well, which was required to last atleast 500 ms before fluid was delivered. Therationale for implementing the locomotor, ormovement, period was twofold. First, it offeredan opportunity to consider movement re-sponse latency as an additional measure oflearning (Figure 6). Second, in previous stud-ies we found interesting neural correlates ofreward expectancy specifically during this trialperiod (Van Duuren et al., 2007). When theseactions were either omitted or the rat failed tovisit the fluid site within 5 s, performance wasclassified as a correct rejection (for the S2) ora ‘‘miss’’ (failure to Go following an S+). A‘‘false alarm’’ response was scored when therat made an erroneous Go response followingan S2. After a reinforcer was delivered to thewell, the rat was allowed to consume it within8 s, after which a vacuum line was activated toremove the fluid, and water was directlyflushed in and out again to clean the tray.The duration of the ITI ranged from 12 to 15 s

and was selected pseudorandomly. More com-plicated behavioral tasks included multimodalcompound discrimination (see ‘‘fifth phase’’of training below).

Behavioral training. Prior to the main exper-iment, the rat went through five pretraining(‘shaping’) phases, including habituation tothe behavioral cage. In the first phase (onesession, 15 min) every head poke into theMMSC, followed by a nose down into the fluidwell, was rewarded with sucrose solution. Inthe second phase (2–5 sessions, 50 trials persession), the animal was required to keep itshead in the stimulus port for a period thatvaried from 500 ms in early sessions to1000 ms in later sessions in order to receive areward. In the third phase (1–2 sessions, 80trials per session), upon head entry for at least300 ms, a visual or odor stimulus was present-ed for 700 ms. Reward was delivered when therat sustained his head poke for at least1000 ms and subsequently moved to and keptits nose in the fluid well for at least 500 ms. Ifthe rat retracted his snout from the well before500 ms had elapsed, no reward was deliveredand a new trial was initiated.

In the fourth phase (6–14 sessions, 80 to 112trials per session), one of two stimuli from asingle modality was presented, with visualstimuli in the initial sessions and olfactorycues in the latter sessions. A ‘‘Go’’ responsewas reinforced with sucrose following the S+; aGo response led to delivery of quinine solutionfollowing the S2. S+ and S2 trials werepresented pseudorandomly in a 1:1 ratio. Eachsession contained several blocks, each com-posed of eight S+ and eight S2 trials. Rats

Fig. 3. General time schedule of a trial for both simple and compound discrimination. A trial was initiated by theonset of a trial light. Upon a head poke by the animal into the MMSC, a single unimodal stimulus was applied (SD) or twostimuli of different modality were simultaneously presented (CD). Upon head withdrawal from the MMSC, the ratgenerated either a NoGo or Go response. In case of a Go response, the rat walked over to the fluid well (movementperiod), put its nose down into this well and consumed a volume of sucrose or quinine solution. Trials were separated byan intertrial interval.


were required to make at least 70% correctrejections on the S2 trials for at least twoconsecutive blocks of trials (cf. Garner, et al.,2006). This criterion was based on correctrejections because, in general, the rats showeda much stronger tendency to perform Goresponses than to withhold these. When therat met the criterion for two consecutivesessions, it was trained on a novel set of twoexemplars in each of the two sensory dimen-sions. Thus, by the end of the fourth phase therat had been trained on a total of fourexemplar sets, two in each dimension.

In the fifth phase, the rat was first trained ona continued SD schedule to distinguish twoexemplars that had been used in a previoustraining phase, viz. as the first stimulus set usedwithin the same modality as currently applied.When the criterion was met again, compounddiscrimination (CD) was introduced: in addi-tion to the modality previously used for SD,new examplars from a second modality werepresented synchronously with the same exem-plars from the first modality. The newly addedmodality was the irrelevant dimension andthus conveyed no predictive power aboutwhich stimulus in the other modality wouldbe followed by reward or punishment in caseof a Go response. Each of the two exemplarsfrom the relevant dimension was co-presentedwith each of the exemplars from the irrelevantdimension (Figure 4). Across sessions, thenumber of blocks gradually increased fromseven to nine, resulting in a total of 144 trialsper session.

The video clip that is included as asupplement to the online version of this articleshows a typical rat’s behavior in two consecu-tive trials. The clip starts with a Go trial andmoves on to a NoGo trial in a compounddiscrimination task.

Multi-electrode array, surgery and data acquisi-tion. After pretraining, the animals (bodyweight : 400–460 g at time of surgery) under-went surgery and implantation of a tetroderecording array (‘‘hyperdrive’’; Gothard,Skaggs, Moore, & McNaughton, 1996; Gray,et al., 1995; Lansink, et al., 2007). A tetrode isa microbundle of four tiny electrode wires(each about 13 mm in diameter) twistedtogether (Gray, et al., 1995; Lansink, et al.,2007; McNaughton, et al., 1983; O’Keefe &Recce, 1993; van Duuren, et al., 2007). Thearray contained 12 tetrodes, two reference

electrodes, each with a diameter of about25 mm, and two extra electrodes for recordingEEG (a twisted pair of Teflon-coated stainless-steel wire, 50 mm in diameter). Tetrodes weremounted on independently movable drivers,emerging at the bottom end of the hyperdrivefrom a ‘‘flat’’ (i.e., roughly ellipsoid) bundle(approximate dimensions: 0.8 3 2.0 mm) andfitting into the mediolateral width of themedial prefrontal cortex.

Before surgery, the rats were given oralampicillin (30 mg/kg, Eurovet, the Nether-lands) mixed with 10% sucrose solution on a 3-day-on/2-day-off regimen. Animals were anes-thetized with Hypnorm (0.06 ml/100 g bodyweight, i.m.; 0.2 mg/ml fentanyl and 10 mg/ml fluanison; Janssen Pharmaceutics, Beerse,Belgium) and dormicum (0.03 ml/ 100 g, s.c.;midazolam 1.0 mg/kg; Roche, Woerden, theNetherlands) and mounted in a Kopf stereo-taxic frame with bregma and lambda in thehorizontal plane. Surgery involved the stereo-taxic implantation of the flat tetrode bundlethrough a rectangular craniotomy (about 2 33 mm) above the right medial prefrontalcortex (center point, AP: +3.0 mm, ML: asclose to the sagittal sinus as possible). Afterremoving the dura and placing the bundlesflush on the cortical surface, the cortex wascovered with a layer of Silastic (i.e., a biocom-patible, silicone elastomere, World PrecisionInstruments, Berlin, Germany). One hole wasdrilled over the right hippocampus (AP:23.8 mm, ML: 2.4 mm) and the extra EEGelectrodes were inserted into dorsal hippo-campus (DV: 3.3 mm). The hyperdrive andelectrodes were kept in place with dentalcement and eight anchor screws, one at thecontralateral side serving as ground.

Upon recovery from anesthesia, rats wereadministered 0.3 ml/ 100 g of diluted Fyna-dine (10% in physiological saline, s.c.; Flunix-inum 50 mg/ml, Schering-Plough AnimalHealth, Brussels, Belgium) for analgesia, andreceived oral doses of ampicillin (30 mg/kg)for 3 days consecutively and on a 10-day-off/10-day-on regimen for the duration of theexperiment. Starting at the day of surgery,tetrodes were gradually moved down towardsthe prelimbic cortex across a period of 7 days.The two reference electrodes were placed inthe superficial layer of the dorsal frontalcortex or anterior cingulate cortex (Fr2,ACC; Paxinos & Watson, 1998). After a week


of recovery, the rats performed the same taskas in the fifth phase of training and with thesame examplars, while at the same timeparallel spike and EEG recordings wereperformed across 64 channels.

Neuronal signals were passed through a 54-channel unity-gain amplifier headstage (Neur-alynx) and amplified, filtered (5,0003 and0.6–6 kHz for spikes, 10,0003 and 1–475 Hzfor EEG recordings) and transmitted to theCheetah Data Acquisition system (Neuralynx).

Signals that crossed an amplitude thresholdtriggered a brief (1 ms) digitization at 32 kHzon all channels of the tetrode, and the spikewaveforms were stored on a personal comput-er. A circular array of light-emitting diodes(LEDs) was mounted on the headstage totrack the animal’s position during behavioralrecording at 25 frames/s. A behavioral-eventsignal, generated by the rabbit system, wasdelivered via a serial-to-parallel converter(type: AVR-H128, ATMega, Lelystad, the Neth-

Fig. 4. Stimulus presentation schedules of the simple (SD) and compound (CD) discrimination tasks. Chronologicalorder is from top to bottom. Four rats were trained to discriminate visual stimuli first (top row) and then proceeded withsimple odor discrimination. This training was followed, first, by compound discrimination with odor as relevantdimension (using four combinations consisting of two novel odors and two novel visual patterns; CD set 1) andsubsequently with vision as relevant dimension (CD set 2, using novel examplars in both the visual and olfactory domain).Note that in the CD phase, the S+ and S2 were combined with exemplars in the irrelevant dimension. The 4 rats allexperienced the same visual and olfactory examplars in the same order.


erlands) to the TTL input port on theAnalogue-Digital Interface (Neuralynx) tosynchronize neural and behavioral-event data.In addition, the behavior of all rats wasrecorded on DVD.

Spikes were sorted off-line on the basis ofthe amplitude and principal components ofevents recorded on all four tetrode channelsby means of semiautomatic and manualclustering algorithms (KlustaKwik andMClust), resulting in a spike time series foreach of the isolated cells (for further details,see Lansink, et al., 2007 and van Duuren, et al.,2007).

Data Analysis

Neural data were analyzed by custom-madecode and toolboxes in Matlab (MathWorks,Gouda, Netherlands). To assess correlationsbetween neuronal firing rate and task events,we produced a smoothed peri-event timehistogram (PETH) using a local regressionmethod (Loader, 2004; ‘‘logfic’’ toolbox inopen-source Chronux algorithms, http://chronux.org) after averaging across trials.The smoother was a quasi-Gaussian functionwith window using 0.3 fixed bandwidth. Aftersmoothing, a two-sample Kolmogorov-Smirnov(KS) test was used to detect differences infiring patterns in trials with positive (reward-ing) versus negative (punishing) outcome.Changes in firing rate during the trial periodwere defined as activity increments or decre-ments relative to baseline firing levels, whichwere measured in the time window from 29 to22 s before the onset of the trial light. Inorder to avoid assumptions on particular spiketrain distributions (e.g., Poisson), we used abootstrapping method to estimate the distri-bution of mean firing-rate values for each binof the ITI. By this method the collection ofspike counts per trial was randomly resampledfor each time bin 1000 times with replace-ment, and next a 95% confidence interval inmean firing rate was calculated by using acorrected percentile method (cf. Wiest, Bent-ley, & Nicolelis, 2005). Only correct trials wereconsidered.

In order to examine variation in the rat’shead position during the stimulus samplingperiod, we used video-tracking data to calculatethe mean Euclidean travel distance of the rat’shead center per trial, calculated by summationof all sample-to-sample changes in head posi-

tion over the relevant stimulus periods. Toassess whether the rat assumed a different headposition depending on the type of trial andimpending response, we first applied a two-wayanalysis of variance (ANOVA) with trial type(hits versus correct rejections and SD versusCD) as factors, and Euclidan distance as thedependent measure. Moreover, we computedthe mean X- and Y-positions of the rat’s headduring stimulus sampling in simple and com-pound discrimination sessions, as well as 95%confidence intervals around the mean usingbootstrapping.

Histology

After finishing a recording experiment,small electrolytic lesions were made at thetetrode endpoints in the brain area of interestby passing current (25 uA, 10 s per lesion)through one of the leads of each tetrode. Oneday later rats received an overdose of Nembu-tal (0.2 ml/ 100 g body weight; CEVA SanteAnimale, the Netherlands) and their brainswere fixed through transcardial perfusion with0.9% NaCl solution followed by 4% parafor-maldehyde in 0.1 M Phosphate buffer(pH 7.0, Klinipath, the Netherlands). Brainswere cut in coronal sections (40 mm) using aVibratome (Leica, type VT-1000S, Wetzlar,Germany) and Nissl-stained.

RESULTS

Behavior

All 4 rats learned to perform the SD and CDtasks at least until criterion, although thenumber of sessions needed to reach criterionvaried across rats (e.g. Figure 5). Learning waswell monitored by tracking the percentage ofcorrect rejections (Figure 5). Acquisition ofcorrect rejections for individual rats and meanpercentage of hits as a function of progressivevisual SD sessions is plotted in Figure 5A, whileFigure 5B represents acquisition of the olfac-tory SD task.

Response latencies (i.e., time lapsed be-tween the rat’s withdrawal from the MMSCand its nose poke into the fluid well) for hitsand false alarms are depicted in Figure 6A forvisual discrimination. By the ninth visualtraining session, the average latency for hitswas significantly shorter than for false alarms(Figure 6A, p , .05 for sessions 9–12, paired t-


test following ANOVA). Except for the initialsession, the response latency differences werenot significantly different for subsequentsimple olfactory discrimination studied in thesame 4 rats (Figure 6B), possibly because taskacquisition in the olfactory dimension pro-ceeded more quickly than with visual stimuli, p, .05, paired t-test. The number of sessions toreach criterion was 11.25 6 1.89 (mean 6s.e.m.) for visual SD, and 4.25 6 0.48 forolfactory SD.

Figure 7A illustrates correct rejections onthe subsequent CD task, using odor as therelevant (i.e., outcome-predicting) dimensionand vision as the irrelevant, distracting dimen-sion. All 4 rats attained criterion performance

in the first session, which was composed of aninitial set of SD trials (using only odor asstimulus; trial blocks labeled SD1–SD3 inFigure 7A), followed by a switch to compoundstimulation (blocks CD1–CD5) as soon ascriterion was reached. The distracting visualstimulus resulted in a mild and brief decreasein performance in only one rat (change fromSD3 to CD1: +3.1 6 9.4%; n.s., N 5 4).

In contrast, when the rats were trained in asimple discrimination paradigm with vision asthe relevant dimension, addition of odors asirrelevant stimuli in the CD phase led to a

Fig. 5. Performance in simple discrimination learning.(A) The percentage of correct rejections (NoGo responsesto S2) in the visual discrimination task was plotted inblack as a function of session number for 4 individual ratsindicated by different symbols. The mean percentage ofhits (Go responses to S+) of the same rats is shown in gray.Inset shows average performance in each block of the lastsession in the main panel. Criterion was at 70% correctrejections in two consecutive blocks. (B) Idem for olfactorydiscrimination, which followed the visual task in time.

Fig. 6. Response latencies in simple discriminationlearning. (A) Response latency in simple visual discrimi-nation plotted as function of session number; opentriangles symbolize mean latency for false-alarm (errone-ous Go) responses, filled circles symbolize hits (correct Goresponses). The mean latency was different (p , .05,ANOVA) for these two types of responses in the final foursessions (marked by *). (B) Idem for simple olfactorydiscrimination; the latency for hits and false-alarmresponses differed significantly only in the first session.


strong but temporary deterioration of perfor-mance (change from SD to CD1: 256.3 610.8%, p , .05, N 5 4, paired t-test).

Neurophysiological Data

Two rats, both having undergone pretrain-ing and the SD and CD tasks illustrated in

Figure 5 and 7, were fitted with a microdrivecontaining a tetrode array converging into aflat bundle impinging upon the medial pre-frontal cortex. Rats recovered within a few daysafter surgery, and were able to maintain headposition as they did prior to surgery. Postmor-tem histology confirmed that the tetrodespenetrated into the medial prefrontal cortex,comprising the dorsal regions FR2 and CG1(Paxinos & Watson, 1998) as well as prelimbiccortex.

We analyzed a total of nine recordingsessions during which rats performed a visual(five sessions) or olfactory (four sessions)discrimination task. These sessions yielded atotal of 301 well-isolated single units with anaverage of 33.4 6 3.8 units per session. Firingpatterns were analyzed by constructingsmoothed PETHs synchronized to the onsetof a trial event. Of these units, 196 units(65.1%) displayed responses to task events thatwere statistically significant relative to baselineactivity. Most of these units with task correlates(60.7%, N 5 119) showed firing rate incre-ments, whereas task events correlated todecrements were observed in a remaining39.3% of units (within a time window of 21.5to 3.5 s relative to stimulus onset at t 5 0 s). Inshort, all events or phases relevant for taskperformance were well represented in mPFCpopulations, including neural responses dur-ing stimulus sampling, movement, waiting andconsuming fluids. Figure 8 presents two exam-ples of single units displaying differentialactivity in hit and correct rejection trialsduring the sampling period of SD tasks. Oneunit showed a firing rate increment mainly atand after a late stage of stimulus presentationin the visual SD task, but also discriminatedbetween the hit and correct rejection (Fig-ure 8A; p , .05, KS test). A second unit,recorded in a different rat performing odordiscrimination, showed a similar firing pattern,although the difference between the neuralresponses was not significant (Figure 8B; p ..05, KS test).

Head Movement During Stimulus Sampling

In a total of 10 sessions from the 2 rats (SD:6 sessions, 3 with odors, 3 with vision; CD: 4sessions) we analyzed behavioral variationduring the stimulus sampling period, asassessed from changes in head position. Thetotal head travel distance per trial did not

Fig. 7. Discriminative performance before and afterthe transition from simple to compound discriminationlearning. The percentage of correct rejections is plotted asa function of trial blocks, each of which contained eight S+trials and eight S2 trials. (A) presents the transition fromsimple olfactory discrimination to the compound phase,where odor remained the relevant dimension. This sessionfollowed the olfactory SD task (Figure 5 and 6B) in time.In (B) rats performed simple visual discrimination andproceeded with the compound phase, keeping vision asrelevant dimension. This session followed the transitionalSD-to-CD olfactory task (Figure 7A) in time. See Figure 5for plotting conventions and behavioral criterion.


Fig. 8. Examples of peri-event time histograms (PETHs) synchronized on stimulus onset, taken from two medialprefrontal single units. (A) Raster plots of PETHs for correct responses on S+ (left) and S2 (right) trials in a simple visualdiscrimination task. A correct response on the visual S+ consisted of a Go response towards the fluid well (outcome:sucrose solution), whereas a correct response on the S2 was a NoGo response. The graph below the raster plots shows thesmoothed mean firing rate for Correct S+ (black) and Correct S2 (grey) trials, departing from a bin size of 50 ms. Thetwo curves were significantly different at p , .05 as indicated by a horizontal bar on top of the curves. (B) Idem as (A), butnow for a simple odor disrimination task. Curves for Correct S+ (black) and Correct S2 (grey) did not differ significantly.


differ significantly between hit and correctrejection and SD versus CD trials (hit duringSD: 4.24 6 0.08 mm versus correct rejectionduring SD: 4.31 6 0.12 mm; hit during CD:4.15 6 0.11 mm versus correct rejectionduring CD: 4.17 6 0.20 mm; two-way ANOVA,p . .05). Likewise, no significant differencewas found in the mean X and Y positionsplotted as a function of time from stimulusonset (Figure 9). Despite the great similaritiesin head positions during hit and correctrejection trials, the graphs illustrate that thestimulus sampling period was not marked by acomplete stasis of the head, but rather by aslight net movement on the order of a fewmillimeters. Thus, head movement was pre-

sent, but in a relatively stereotyped, regularmanner.

DISCUSSION

A behavioral setup was constructed with theaim of presenting a multimodal, hollow objectto allow rats to sample sensory stimuli underconditions of strong behavioral regularity.Stimuli could be presented in an automatedand temporally precise way, and the surround-ing cage was equipped with a fluid port whererewarding (sucrose) or aversive stimuli (qui-nine solution) were delivered. Furthermore,the MMSC and surrounding cage permittedstable ensemble recordings from animals that

Fig. 9. Mean head position during the stimulus sampling period of the simple discrimination task (both visual andolfactory sessions were included, N 5 3 and N 5 7, respectively). Graphs show mean head position for Correct S+ andCorrect S2 trials in SD tasks (A, B; solid and dashed lines, respectively) and SD (dash-dotted line) versus CD (dotted line)in Correct S+ trials (C, D) and Correct S2 trials (E, F). Mean head position was computed based on frame-to-framepositions of the center of the rat’s head as estimated by the Cheetah Neuralynx system for videotracking LEDs on the rat’sheadstage (sampling rate: 25 frames/s). Grey bands flanking the mean-position curves indicate 95% confidence intervals,which were obtained by a bootstrapping method (Zoubir & Iskander, 2004). Dark grey areas reflect overlap in confidenceintervals between Correct S+ and Correct S2 trials or between SD and CD trials. X position (A, C and E) and Y position(B, D and F) are plotted as a function of time elapsed from stimulus onset. Although the head was not stationary duringstimulus sampling, there was no significant difference between Correct S+ and Correct S2 trials in SD, or between SDand CD studied for Correct S+ and Correct S2 trials separately.


had been chronically implanted with an arrayof individually movable tetrodes, connectingto a sizable headstage (diameter: 5.6 cm)positioned above the rat’s head. Although inthis study we only trained rats to performsensory-discrimination learning under undis-tracted (SD) or distracted (CD) conditions,the behavioral setup is useful to study a muchwider range of cognitive processes, includingattentional control, multisensory integration,working memory and sensorimotor control.

Considering that the associative learningprocedures were completed by all 4 rats testedin this study and ensemble recordings weremade from 2 rats, it can be concluded that theoverall requirements set in the Introductionwere largely met, although this conclusiondeserves further comment. First, primaryevidence for associative learning in a SD taskwith visual or olfactory stimuli was presented inFigures 5 and 6. Whereas the percentage ofcorrect rejections can be regarded as a safemeasure of discriminative operant condition-ing in a task where animals produce Goresponses by default, the difference in re-sponse latency for hits versus false alarmsprovided an additional measure of learning.That latencies for hits to visual stimuli becamegradually shorter than for false alarms may beexplained, on the one hand, by a strengthen-ing of the stimulus–reward association and itsutilization in hit trials, whereas on the otherhand an increased latency in false alarm trialswas likely coupled to an increased ability towithhold responding until, finally, this type ofresponse was minimized altogether (Fig-ure 6A).

Despite the observation that the same 4 ratswere capable of visual as well as olfactorydiscrimination learning (Figure 5), it is inter-esting to note that all animals were slower inacquiring visual as compared to olfactoryconditioning. Following initial SD acquisition,the odor also appeared to act as a strongerdistractor than the visual stimulus, in the sensethat task performance was more heavily dis-rupted upon the SD–CD transition in thevisual task (Figure 7B) than in the olfactorytask (Figure 7A). Although the serial positionof these two tasks in the overall trainingschedule was different, this interpretation issupported by the fact that all rats were wellabove criterion before the distracting stimuliwere introduced. That the rats were faster in

acquiring olfactory discrimination relative tothe visual task is well in agreement with theliterature, although few studies (Brushfield,Luu, Callahan, & Gilbert, 2008) have directlycompared learning in both modalities withinthe same animals (for olfactory discrimination:Eichenbaum, Shedlack, & Eckmann, 1980; Kay& Freeman, 1998; Sara, Roullet, & Przyby-slawski, 1999; Schoenbaum & Eichenbaum,1995; Tronel & Sara, 2002; van Duuren, et al.,2007; for visual discrimination: Bussey, Muir, &Robbins, 1994; Cook, Geller, Zhang, & Gowda,2004; Markham, Butt, & Dougher, 1996; Minini& Jeffery, 2006; Simpson & Gaffan, 1999).

A further comment should be made con-cerning the requirement of temporal preci-sion of stimulus delivery. On the one hand, thefast and reliable responding after reachingcriterion demonstrates that animals werecapable of appropriate stimulus samplingduring the 700-ms presentation period, whichimplies that odor puffs were sufficientlydiscrete in both time and space to enableanimals to perform olfactory conditioningefficiently. In this respect, the rats effectivelyfunctioned as ‘‘biosensors’’ for validating thesystems for visual and olfactory presentation.On the other hand, this approach clearly setslimits to the extent that temporal precision ofodor pulses can be claimed, whereas fast onsetand offset of visual stimuli was reliablyachieved using the masking method (seeMethod). To achieve trial-discrete odor pre-sentation, our system was equipped with adual-exhaust system consisting of a powerful,fast fan and a vacuum line, while a bypasssystem connected to the fan subserved rapidodor onset and largely avoided the problem of‘‘dead space’’ (i.e. in between multiple valvesfor flow switching and the MMSC). Thesetechnical measures illustrate how odor appli-cation can be applied to larger chambervolumes on at least a trial-discrete basis.

Behavioral regularity during stimulus sam-pling is of great importance when one wishesto exclude motor confounds while examiningneural correlates of stimulus processing, at-tention or related cognitive processes. First,execution of a relatively stereotyped samplingbehavior was facilitated by the physical layoutof the wall panel which required the animal toplace its forepaws on a shelf below the head-entry port (Figure 2). Second, the behavioralsetup was equipped with a system for video-


tracking head position by way of headstageLEDs. The mean travel distance of the headduring stimulus sampling did not differsignificantly during Correct S+ versus CorrectS2 trials during SD and CD. Furthermore, inthe course of sampling, the mean X and Ypositions of the head did not differ signifi-cantly between these trial types (Figure 9),even though these coordinates varied onaverage by a few millimeters during thesampling period. The videotracking system,relying on headstages that are attached to acable and are situated approximately 5 cmabove the animal’s head, has a similar errormargin. Altogether, these data indicate that ahigh degree of body–head regularity is achiev-able in rats processing sensory inputs.

The neural correlates observed during visualor olfactory SD performance pertained to alltemporal phases of learning trials (stimulus,response, waiting, and reinforcement phases)and included subsets of stimulus-selectiveresponses (Figure 8; whether this selectivityrelates to feature tuning or motivational valueremains to be determined). These results arein basic agreement with previous mPFCrecordings studies in freely moving rats (Baeg,et al., 2003; Chang, Chen, Luo, Shi, &Woodward, 2002; Euston & McNaughton,2006; Mulder, Nordquist, Orgut, & Pennartz,2000; Pratt & Mizumori, 2001). Despite thevariety of cognitive processes studied, a com-mon denominator in mPFC recordings hasbeen the broad coverage of relevant taskcomponents and phases by neural activitychanges in mPFC. Although this patterningof neural activity may be explained by thenotion derived from primate studies (Lauwer-eyns, et al., 2001; Rainer, Asaad, & Miller,1998; Rao, Williams, & Goldman-Rakic, 2000)that the PFC has the capacity to filter outirrelevant information and focus on task-relevant events, this notion must be testedfurther. In this respect an advantage of thecurrent behavioral setup is that a high degreeof body–head regularity can be paired with thepresentation of a multitude of stimuli fromdifferent modalities.

Apart from the experimental advantagestouched upon above, the behavioral setupoffers possibilities to study in rodents amultitude of cognitive tasks and their respec-tive neurophysiological underpinnings. Usingthis technology, investigators may record large

neuronal ensembles with single-unit resolu-tion and combined with continuous local fieldpotential measurements so that questions ofneural synchrony, coherence and populationcoding can be addressed in a wide range ofbehavioral and cognitive conditions.

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Received: September 12, 2008Final Acceptance: April 2, 2009


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