learning-induced modulation of oscillatory activities in the mammalian olfactory system: the role of...

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Journal of Physiology - Paris 98 (2004) 467–478

Learning-induced modulation of oscillatory activities in themammalian olfactory system: The role of the centrifugal fibres

Claire Martin *, Remi Gervais, Pascal Chabaud, Belkacem Messaoudi, Nadine Ravel

Institut des Sciences Cognitives, UMR 5015 CNRS/Universite Lyon I, Bron, 69675 France

Abstract

In the mammalian olfactory system, oscillations related to odour representation have been described in field potential activities. Pre-vious results showed that in olfactory bulb (OB) of awake rats engaged in an olfactory learning, odour presentation produced a decreaseof oscillations in gamma frequency range (60–90 Hz) associated with a power increase in beta frequency range (15–40 Hz). This responsepattern was strongly amplified in trained animals. The aim of this work was twofold: whether learning also induces similar changes in OBtarget structures and whether such OB response depends on its centrifugal inputs. Local field potentials (LFPs) were recorded throughchronically implanted electrodes in the OB, piriform and enthorhinal cortices of freely moving rats performing an olfactory discrimina-tion. Oscillatory activities characteristics (amplitude, frequency and time-course) were extracted in beta and gamma range by a waveletanalysis. First, we found that odour induced beta oscillatory activity was present not only in the OB, but also in the other olfactory struc-tures. In each recording site, characteristics of the beta oscillatory responses were dependent of odour, structure and learning level. Uni-lateral section of the olfactory peduncle was made before training, and LFPs were symmetrically recorded in the two bulbs all along theacquisition of the learning task. Data showed that deprivation of centrifugal feedback led to an increase of spontaneous gamma activity.Moreover, under this condition olfactory learning was no longer associated with the typical large beta band. As a whole, learning mod-ulation of the beta oscillatory response in olfactory structures may reflect activity of a distributed functional network involved in odourrepresentation.� 2005 Elsevier Ltd. All rights reserved.

Keywords: Learning and memory; Olfactory system; Oscillations; Population coding

1. Introduction

In sensory systems, an increasing amount of studieshave found a clear relationship of mass activities with per-ception and behaviour [27,35]. These recent data suggestthat oscillatory activities observed in the different sensoryareas could play a role in coding and information process-ing, and could yield to the selection of an adapted behav-ioural response. Data obtained in the mammalianolfactory system contribute to this view. Numerous studiesdescribed oscillatory activities both in the presence and inabsence of odour. In various mammals, activity in differ-ent frequency bands ranging from 1 to 100 Hz have been

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* Corresponding author. Tel.: +33 437 91 12 36; fax: +33 437 91 12 10.E-mail address: [email protected] (C. Martin).

described in the olfactory bulb (OB), piriform cortex(PC) and lateral entorhinal cortex (LEC) of awake animals[2–4,7,14,17,36,47]. Resting electroencephalogram (EEG)or local field potential (LFP) activities collected in non-anaesthetised animals showed prominent bursts of oscilla-tions in the 40–80 Hz frequency band (gamma band)which appeared at each inspiration [1]. This observationfocused attention on the possible functional significanceof this gamma activity. More specifically the study of itsspatial distribution recorded in 64 sites on the surface ofthe rabbit OB, led to the hypothesis that they could playa role in odour representation. However, these oscillatoryactivities turned out to be more associated to the behav-ioural meaning of odours than to their chemical quality[11]. Indeed, the distribution of gamma bursts ampli-tude mostly exhibited changes in the context of olfactory

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468 C. Martin et al. / Journal of Physiology - Paris 98 (2004) 467–478

conditioning paradigms [10,12]. Recent studies in freelybe- having mice and rats [17,18,26,30,36], are consistentwith this interpretation. In parallel with the studies ongamma activity another type of rhythmic mass activity hasreceived some interest. Indeed, olfactory structures alsodisplay a slower oscillatory rhythm ranging from 15 to35 Hz, referred as the beta band activity [2,8,18,41,47].At least in OB and piriform cortex this activity is moreprominent during odour [47]. Recently, we providedevidence that, in behaving rats, odour sampling wasassociated with a clear increase in the beta range oscilla-tions (15–40 Hz) and a depression in the gamma range(60–90 Hz) in the OB. Both type of response was stronglyamplified following learning [36]. In addition, enhance-ment of the OB beta response was found to be closelyrelated to the improvement of animal performance. Inrespect to a potential role in olfactory coding, we foundthat this activity exhibited several significant differencesaccording to the recorded region in the OB (anterodor-sal vs. posteroventral) and the chemical nature of theodourant [26]. As a whole, the results of these two stud-ies stressed out the possible role of the beta oscillatoryactivity in both odour representation and olfactoryrecognition.

As proposed earlier [9,38,42], rhythmic synchronisationof neuronal discharge could provide the link between andwithin the areas involved in a functional network, andcould take part in sensory coding [20,37, Neuron specialissue, 1999 September]. In the OB, such a mechanism couldsupport spatio-temporal coding. Indeed, even if each sin-gle odourant elicit a specific spatial pattern of activity[15,16,46], spatial coding alone would suffer from overlap-ping and redundancy and most of recent studies convergedon the fact that odour identity is more likely to be repre-sented by spatio-temporal patterns [39,46]. This hypothesishas received a strong support from data in the insects olfac-tory system. Indeed, Laurent�s group provided evidence fora representation of odours by assemblies of transiently syn-chronised neurones [20]. This group also demonstrated therole of this precise relationship for disambiguating over-lapping neuronal patterns and facilitating informationtransfer between different areas networks [34]. Such arepresentation could also facilitate the expression of learn-ing-induced plasticity in the network since the convergentsynchronised inputs would favour voltage-dependant pro-cesses [37].

In the hypothesis that large-scale synchronised neuronalassemblies are particularly important for representations ofbehaviourally meaningful stimuli, one can predict that acommon oscillatory pattern would emerge in the differentareas taking part to stimulus processing. The two setsof data presented here bring elements arguing for thishypothesis. We show that odour-induced beta and gammaresponse are not restricted to the first relay of informationprocessing, the OB, and that the effect of learning on OBresponse critically depends on interaction between OBand more central structures.

2. Materials and methods

2.1. Subjects, surgery and histology

Experiments were carried out in accordance with the European guide-lines regarding care and use of animals for experimental procedures. Allstudies were conducted on groups of Wistar rats (250–300 g) purchasedfrom Charles River Laboratories (L�Arbresle, France). Rats were anaes-thetised with equithesin (a mixture of chloral hydrate and sodium pento-barbital, 3 ml/kg, i.p.) to perform chronic implantation of monopolarrecording electrodes (80 lm, 100–500 kX). Recording sites were differentaccording to the two experiments.

In Experiment 1, electrodes were implanted unilaterally in OB (antero-posterior (AP) 6.7 mm relative to bregma, medio-lateral (ML) 1.5 mm),the anterior part of the piriform cortex (APC) (AP 2.2 mm relative tobregma, ML 4 mm), the posterior part of the piriform cortex (PPC) (AP�2.3 mm relative to bregma, ML 5–5.5 mm) and the lateral entorhinalcortex (LEC) (AP �6.3 mm relative to bregma, ML 6 mm). In Experiment2, two electrodes were implanted in each OB symmetrically: anterior site(AP +7.7 mm relative to bregma, ML 1.2 mm); posterior site (AP+6.7 mm relative to bregma, ML 1.5 mm). In addition, for this groupthe left olfactory peduncle was coronally sectioned before electrodes place-ment. This was done with a scalpel blade inserted vertically through a holemade in the skull, just rostral to the anterior olfactory nucleus (+5.2 mmrelative to bregma).

In each recorded structure, the electrode tip was positioned near theoutput cell body layer (see Fig. 1a). In the OB, electrode depth wasadjusted at the level of the mitral cell layer using electrophysiological mon-itoring of the characteristic large multiunit mitral cell activity [32,33]. ForAPC, PPC and LEC, the electrode tip as positioned near the reversingpoint of the evoked field potential induced in response to electrical stimu-lation of the OB electrode (0.1 ms pulse, 300 lA). In each case, the refer-ence electrode was positioned in the skull bone, above the corticalhemisphere, around 5 mm posterior to Bregma. All the electrodes wereconnected to a miniature socket fixed onto the rat�s head by dental cement.Two weeks of recovery separated surgery from recordings.

At the end of the experiment, rats were injected with a lethal dose ofpentobarbital and an electrocoagulation (1 mA, 6 s) was performedthrough each electrode. Brains were dissected and stored in a 10% forma-lin solution for 1 week after which olfactory bulbs were cut into 40 lmslices and stained with Cresyl Violet. For each rat, the position of eachelectrode was determined.

2.2. Behavioural procedure

The experimental set-up and the training procedure have beendescribed in detail elsewhere ([36] for Experiment 1, [26] for Experiment2). We will only briefly summarise the main points.

2.2.1. Behavioural apparatusExperiments were performed in a 40 · 63 cm size arena. One wall of the

cage, in its width axis, was equipped with an odour port, the opposite onewith a reward apparatus, either a food tray (Experiment 1) or a drinkingport (Experiment 2). Optical detectors mounted on the side of the odourport monitored nose pokes. Deodourised air constantly flowed throughthe odour port. Detection of pokes was used to trigger odour delivery. Fol-lowing a nose poke, a small volume of odourised air was added to the mainflow for a 3 s period. This was controlled through the opening and closingof solenoid valves on a two-channel flow-olfactometer. A vacuum systemensured the odour remained confined to the port. However, within this3 s period, the animal itself determined the duration of odour sampling.

The odours used were eugenol, geraniol, octanal (C8) and decanal (C10)(FLUKA, see Fig. 3c). They were obtained from evaporation of pure com-pounds from saturated granules. At the beginning of the experiment, thepercentage of saturated vapour pressure introduced in the airflow wasadjusted for each compound to be judged moderate and balanced by theexperimenters. The values were 53% for eugenol and 44% for geraniol

Fig. 1. Recording sites and typical LFPs recordings: (a) Schematic representation of localisation of the four recording sites (adapted from Paxinos andWatson, fourth edition). Numbers on the right indicate the antero-posterior distance relative to the bregma suture. The shaded zone summarises theextension of recorded sites obtained from all rats. OB, olfactory bulb, APC anterior piriform cortex, PPC, posterior piriform cortex, LEC, lateralentorhinal cortex. (b) Examples of raw signals (0.1–300 Hz) obtained in the different areas in one rat sampling geraniol (horizontal bar above the OBsignal) in beginner condition (left part) and later on in expert condition (right part). One can note the emergence of a clear beta response in the expertcondition in OB, APC and PPC.

C. Martin et al. / Journal of Physiology - Paris 98 (2004) 467–478 469

and around 10% for aldehydes (C8 andC10). In Experiment 1, the food traydelivered standard food-pellets (40 mg) (Medical Associates Inc., Georgia,Vermont). In Experiment 2, the drinking port was equipped with a pumpdelivering either a sucrose (60 mg ml�1) or a quinine (0.5 mg ml�1) solutionat a constant flow (about 3 ml/min). To ensure that animals could not pre-dict which solution would be delivered, a spout was placed at the end of thedrinking tube and replaced for each trial. As soon as the animals licked thespout, the liquid was released for a maximum of 20 s (about 1 ml). Odoursampling, food-tray approach and licking were controlled online, the corre-sponding electric signals were recorded in parallel with biological signals.

2.2.2. Behavioural proceduresRats were engaged in a go/no-go training task based on the discrimi-

nation of two odours.

Experiment 1. The animals learnt to go immediately (go response) to thefood tray following sampling of odour S+ (geraniol) and to stay nearby(no-go response) when sampling odour S� (eugenol). Correct goresponses were reinforced with one food pellet. There was no negativereinforcement in this experiment.

Experiment 2. The animals learnt to go immediately (go response) to thedrink delivery following sampling of odour S+ and to avoid licking (no-goresponse) when sampling odour S�. In this experiment, four odours wererandomly presented, two S+ odours (geraniol and octanal (C8)) and twoS-odours (eugenol and decanal (C10)). Correct go responses were rein-forced with sucrose, incorrect no-go responses were punished withquinine.


For each rat, one daily session consisted of 20–30 trials (50% S + /50%S� randomly distributed) with a 1 min inter-trial interval. Opening theodour port door indicated to the rat that a new trial was initiated. The ani-mal determined the duration of odour sampling. The experimenter endedthe trial after a maximum of 30 s following odour sampling onset by clos-ing the odour port door. For each trial, the rat behavioural responselatency was quantified as the time elapsed between the odour port entryand detection at the reward apparatus. This parameter will be referredto as the behavioural response latency. Due to different individual behav-ioural strategies in solving the task, an individual criterion was defined todifferentiate go and no-go responses. For each rat and for each session, anaverage latency value for go responses was calculated from the 10 go trialsof the session. When, on a given trial, this value was greater than the aver-age go value +2 STD, the response was classified as a no-go response.Otherwise, the response was classified as a go response. The learning cri-terion was fixed at 80% of correct choices on two consecutive sessionsincluding at least 70% of correct no-go responses.

2.3. Electrophysiological recordings

The whole experimental arena was placed in a Faraday cage. Neuralactivity was acquired in parallel from each electrode, through unitary gainfield effect transistors positioned in the headstage of the recording cable toreduce movement artefacts. The cable was connected to a swivelling elec-trical connector that allowed free movements. The LFP signals togetherwith events markers (nose pokes and licks signals) were amplified(·600), filtered (0.1–300 Hz), digitised (sampling frequency 2000 Hz)(Wavebook 512, Iotech, Inc., Cleveland, Ohio) and stored on a computer.

2.4. Signal analysis

The time window of analysis was fixed to 4 s centred on the odouronset (nose poke-in detection). For each trial, signal analysis was carriedout on 3 time periods: a 1000 ms reference period extending from 1.5 to0.5 s before odour onset, a 500 ms period before odour onset (pre-period,pre), and a 1000 ms period after odour-onset (odour-period, odour). Sig-nal analysis was performed with ELAN (Pack software developed atINSERM U280 (Lyon, France, http://www.lyon.inserm.fr/280). For eachtrial, a time-frequency analysis was carried out, based on Morlet waveletanalysis applied to the signal between 2 and 100 Hz, in order to defineprecisely and without any a priori knowledge the limits of the frequencyband of interest. We used complex gaussian Morlet�s wavelets with thefollowing characteristic: a ratio f/rf of 7, with the frequency ranging from8 to 100 Hz in 1 Hz step [40]. At 8 Hz, this leads to a wavelet duration(2rt) of 278 ms and to a spectral bandwidth (2rf) of 2.3 Hz; at 20 Hz, toa wavelet duration of 111.4 ms and to a spectral bandwidth of 5.8 Hz;and at 100 Hz, to a wavelet duration of 22.2 ms and to a spectral band-width of 28.6 Hz. The time resolution of the method thus increased withfrequency.

For each trial, a power threshold (mean ± STD) was calculated on thereference period. The signal of odour and pre periods was compared to thereference period for each 2 Hz frequency bins: bursts of oscillation abovethreshold were considered as significant peaks. For each electrode andeach trial, only the most powerful peak was selected for analysis, and itsfrequency, power and latency were extracted.

Odour-induced changes in gamma band (60–90 Hz) consisted of longlasting periods of depression. Because of the continuous nature of thischange, the wavelet time-frequency deconvolution that we used for thetransient beta band analysis was not optimal for capturing the durationand the amplitude of this depression. Instead, we used the time-varyingfast Fourier transform using the Welch spectral estimation method[43,6]. To this end, power spectra were computed on 150 ms time windowsliding by step of 50 ms. Power baseline was calculated on the same refer-ence period as for wavelet analysis. For each time window within the twoperiods, a threshold for significant changes was calculated as the mean ofthe logarithmic value of the power during baseline ±2 STD. For each per-iod, the occurrence rate of response was defined as the ratio of number of

150 ms time windows where a significant decrease occurred divided by thetotal number of time windows during this period. Thus the occurrence ratevaried from 0 to 1.

2.5. Statistical analysis

In both experiments, ANOVA tests were performed to compare odour-induced changes in the different conditions on the power variable. Threeindependent factors were tested (odour, electrode localisation and levelof training) and one paired factor, the period factor (pre, odour). More-over, the analysis on the timing of beta activity among the different levelsof the olfactory network was performed using Chi square comparisons ofthe distribution of beta bursts latencies.

3. Results

3.1. Behavioural performances

3.1.1. Experiment 1: Two odours go-no go task

Among the 5 rats engaged in this experiment, only 3were kept for the analysis. This selection was based onthe quality of the electrophysiological signals in the fourstructures investigated. No significant differences werefound among these rats as regard the course of the learningcurve. They took an average of 312 ± 67 trials to reach thecriterion. Regarding the duration of odour sampling, therewas no significant difference between beginners and expertsand between eugenol and geraniol. The median value ofsampling duration was 550 ms.

3.1.2. Experiment 2: Four odours go-no go task

Performances of rats with unilateral section of the olfac-tory peduncle were not different from those observed inintact animals. The 4 rats learned the four odours: C8and geraniol as go odours rewarded with sucrose andC10 and eugenol as no-go odours, associated with the neg-ative reinforcement quinine. As the task was a go/no-go,improvement in behavioural performance came fromincreased latencies in behavioural responses to the no-goodours eugenol and C10. From that point of view, the 4rats learned more rapidly to inhibit their behaviouralresponse to C10 than to eugenol: (7.75 ± 2.9 sessions forsessions for C10 and 10.75 ± 3.75 sessions for eugenol).Indeed, the average number of trials to reach the criterionwas significantly lower for C10 than for eugenol (66 ± 12vs. 102 ± 20 trials F(1,6) = 8.872, p < 0.05).

Sampling duration exhibited differences according tothe odours and the learning level (level-odour effectF(6,1026) = 2.947, p < 0.01). The four odours could bedivided in two groups: duration was significantly higherfor aldehydes (C8 and C10) than for eugenol and geraniol(post-hoc test p < 0.01). For eugenol and geraniol samplingduration decreased significantly during learning whereasthere was a tendency of increase for aldehydes (mean sam-pling duration for aldehydes: beginners 1132 ± 99 experts1307 ± 52, p = 0.07; eugenol/geraniol: beginners 1063 ±102 experts 811 ± 31, p < 0.05).

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3.2. Electrophysiological data

In Experiments 1 and 2, general characteristics of betaand gamma rhythms before and during odour samplingwere similar to those described in earlier studies [7,36,26].Typically, spontaneous activity was characterised by burstsof gamma activity (60–90 Hz) and no sign of beta activity(15–40 Hz). During odour sampling, gamma activityalmost disappeared whereas beta bursts appeared in eachstructure. This odour-induced response was amplified afterlearning (see Fig. 1b). Previous experiments have describedthe response in the OB. We here described these character-istics in the different structures and the effect of unilateralolfactory peduncle sectioning.

3.2.1. Experiment 1: Two odours go/no-go task

Typical example of raw signal obtained in the four struc-tures are shown in Fig. 1, while Fig. 2 summarised charac-teristics of the beta response in both beginners and experts.For the beta response, results of ANOVA analysis ofpower values pointed at the following results. All factors(structure, learning level and odour) and their interactionswere found significant. As a consequence, we analysedwhat happened in each recorded site separately. In eachstructure, the odour effect was only found significant inexpert condition (OB: F(1,62) = 9.61, p < 0.003; APC:F(1,58) = 9.975, p < 0.003; PPC: F(1,66) = 15.154, p <0.0005; LEC: F(1,62) = 15.478, p < 0.0005).

We then compared in each condition (beginner andexpert for eugenol and geraniol) the beta power in the dif-ferent structures. In each condition, the factor structure

Fig. 2. Effects of learning on the beta (15–40 Hz) response characteristics during

amplifies the beta response. Bars indicate the average ratio of maximal energygeraniol S+ (black bars). indicate a significant difference between the two odoof occurrence of beta bursts. Bars indicate the average distribution in the fourbins of 200 ms following odour onset. Each bar illustrates the percentage of pperiod lasting from 0 to 1000 ms. In beginners (upper part) one can note the widIn expert (lower part), the whole distribution now differed between odourants, pwas different between eugenol and geraniol (p < 0.05).

was found significant (beginners: geraniol: F(3,62) =11.18, p < 0.0005 eugenol: F(3,85) = 14.063, p < 0.0005;experts: geraniol: F(3,91) = 11.618, p < 0.0005; eugenol:F(3,157) = 6.854, p < 0.0005). Moreover, this effect wasin interaction with the level of training and the odour(structure-level-odour F(3,395) = 4.403, p < 0.005). Post-hoc comparisons in each condition led to the followingresults: in beginners, odour induced an increase in powerin beta band similar in OB and LEC and significantlyhigher than in APC and PPC (p < 0.0005). Response inthe two parts of PC did not differ. In experts, the compar-isons between the structures led to different results espe-cially regarding LEC. The power in this structure wasfound closer to what was observed in PPC and APC. Thischange was mainly due to the fact that learning inducedsignificant increase in power in each structure except inLEC (F(1,99) = 1.502, p = 0.223) (level effect in OB:F(1,95) = 12.709, p = 0.001; in APC: F(1,95) = 10.699,p = 0.001 and in PPC: F(1,106) = 18.971, p < 0.0005). Tobetter account for learning-induced changes in power ineach structure we expressed the beta response in expertsas a ratio of what was observed in the same condition inbeginners. The results are plotted in Fig. 2a. The ANOVArevealed that the amplification of beta response was differ-ent in each structure (structure effect F(3,248) = 6.350,p < 0.005). This analysis also confirmed that power ofLEC beta response was not modified following learning.In OB and piriform cortex amplification ranged from 2to 11-fold-factor. Beta power in OB and APC was ampli-fied without any significant difference among odours. Inthe PPC however, the response was much more amplified

odour sampling in the four recorded structures (Experience 1): (a) learningobserved in experts vs. beginners in response to eugenol S� (grey bars) andurants within the same structure (p < 0.05). (b) Learning modifies the timerecorded structures of maximal energy in the beta band within successiveeaks for each 200 ms bin relative to the total number of peaks during theespread and similar distribution of occurrence in response to both odours.articularly for the second and fourth time bins. indicate that power ratio


in response to geraniol than to eugenol (odour effectF(1,66) = 18.254, p < 0.005).

As regard the occurrence time of the beta response ineach structure, we studied the latency distribution of betapeaks in 5 bins of 200 ms during the odour period (seeFig. 2b). Chi-square comparisons of the distributions inthe different experimental conditions led to the followingconclusions. First, in beginners as well as in experts, the dis-tribution of beta peaks did not differ among the structures.As a consequence, responses were pooled. Results areshown in Fig. 2b and the analysis revealed that peaks wereuniformly distributed within the 5 bins during the odourperiod (geraniol: Chi-square = 0.9646, p < 0.05; eugenol:Chi-square = 2.40, p < 0.05). However, for both odours,learning strongly modified this distribution (Chi-squareexperts/beginners: geraniol: 19.378; eugenol: 43.349 p <0.05). In experts, for each odour, the distribution wasnon-uniform and the maximal peak of energy now occurredbetween 200 and 600 ms in response to eugenol and 400 and800 for geraniol (Fig. 2b). To summarise odour samplinginduced a burst of beta oscillatory activity at variable laten-cies from trial to trial. On average, the temporal distributionof these responses was similar in each recorded structure.Finally, while in beginners, the distributions were similarfor both odours used, learning tuned the occurrence timeof beta response in an odour specific pattern.

3.2.2. Experiment 2: Four odours go/no-go task

This experiment aimed at determining characteristics ofboth odour induced beta and gamma response in the intactand deafferented OB.

3.2.3. Odour induced beta activity was odour dependant

First, as four odours were presented in this task, differ-ences in expression of beta activity according to the odourswere analysed in the intact OB. Three parameters wereextracted, frequency, power and occurrence time of themaximum power peak.

Frequency decreased significantly between beginnersand expert rats without interaction with odour or site (leveleffect F(1,498) = 7.655, p < 0.01, beginners 24 Hz, experts22.9 Hz). On the contrary, power and occurrence timeexhibited differences according to the odour. Consideringpower, there was an interaction between the odour andthe learning level (level-odour F(3,484) = 2.765, p < 0.05)as well as the recording site (site-odour F(3,484) =15.005, p < 0.01). In beginners, in the anterior site, betaoscillatory power was the same for the four odours whereasin the posterior site C8 induced a significantly higherresponse (F(3,90) = 7.806, p < 0.005). (Fig. 3b, left part).In experts, on both sites there was an increase of theresponses to all odours except C10 (S�). Learning-inducedchanges in power were different for each odour. Thus, inexperts, beta activity power showed significant differencesbetween the different odours.

The time of occurrence of the maximal peak in the 15–40 Hz range was shorter in the anterior than in the poster-

ior recording site, in all conditions (F(1,498) = 5.657,p < 0.05). For the two sites, this value significantlydecreased from beginners (mean value for the four odours:anterior 1047 ms, posterior 1273 ms) to experts (F(1,498) =30.900, p < 0.01). An effect of the odour quality was alsofound, but only in experts (F(3,339) = 69.965, p < 0.01).When compared to eugenol and geraniol the main effectwas that the maximal amplitude for beta activity appearedlater for aldehydes, even later for C8 (C8, anterior 1257 ms,posterior 1283 ms, C10 anterior 847 ms, posterior 1043 ms).Eugenol and geraniol were not different one from the other(eugenol, anterior 636 ms, posterior 529 ms, geraniol ante-rior 603 ms, posterior 702 ms).

In summary, consistently with previous observations,present data showed that learning-induced increase in betaoscillatory power and change in latencies observed duringodour sampling was specific of the odour quality.

3.2.4. Learning induced beta activity increased is related

to animal�s behavioural performances (Fig. 3c)

As presented above, rat learned to inhibit its response toC10 earlier than to eugenol. We investigated whether thisdifference was also correlated with changes in electrophys-iological signals. Indeed, in a previous study [26] wereported that change of beta activity amplitude in the pos-terior site was correlated with behavioural performancesduring the intermediate level, i.e. all the sessions betweenbeginners and expert levels. Here, we analysed evolutionof the signal amplitude of the posterior site along learning,for the four odours, in anterior and posterior recordingsites. This analysis was conducted for each daily recordingsession of the three defined conditions: beginners, interme-diates and experts (Fig. 3c). As beta oscillatory power didnot increase significantly between beginners and expertsfor C10, this odour was excluded from analysis. Changesof the amplitude were then compared between C8, eugenoland geraniol. As presented in Fig. 3c, beta power increaseoccurred as earlier as day 3 of training for C8. By contrast,for eugenol and geraniol, beta oscillatory amplitude stayedto a very low level until day 7. However, interestingly, evo-lution of amplitude for these two odours did not exhibitedsignificant difference (p < 0.05), so data were pooled for thefollowing analysis. The evolution also differed betweenanterior and posterior sites. For posterior sites, we foundsignificant differences in power between odours from day3 to day 12 (Kruskall–Wallis p < 0.05). For anterior sites,this effect was less pronounced and appeared later (day 6and 7, Kruskall–Wallis p < 0.05). Evolution in amplitudeof the beta response for eugenol paralleled the timerequired by animals to master the task for this odour. Itmust be pointed out that the amplitude of beta activityfor the ‘‘go’’ odours, C8 and geraniol, paralleled the behav-ioural results of C10 and eugenol respectively. Indeed,response amplitude increased earlier for C8 than for gera-niol, and animals took on average 3 days less to reachthe criteria with C10 as no-go odour when compared toeugenol as no-go odour. Thus, increase of beta response

Fig. 3. Unilateral peduncle section affects differentially OB gamma (60–90 Hz) and beta (15–40 Hz) oscillatory activities and in intact OB evolution of beta

responses parallels behavioural performances: (a) gamma oscillations are amplified in posterior OB. Bars indicates mean power (n = 316 trials) in thegamma band for the anterior (left) and posterior (right) recording sites. Data are presented for intact (grey) and sectioned (black) olfactory bulb for twotime periods: PRE, between 1500 and 500 ms before odour sampling, and ODOR, between 0 and 1000 ms after the odour sampling onset. In eachcondition, power in sectioned OB is higher than in intact OB. For both intact and sectioned side, mean power decreased significantly between PRE andODOR periods ( significantly different when compared to the PRE period. p < 0.05). This effect was significantly amplified in the posterior site ( ,significantly different when compared to the anterior site p < 0.05). (b) Learning related amplification of the beta response is abolished. Bars indicate meanpower in the 15–40 Hz band for the intact (left) and sectioned side (right) in the anterior (top) and posterior (bottom) recording sites. Mean maximalpower is represented during the odour period for the four odours collected in beginners and expert conditions. It should be noticed that power scales(ordinate axis) are different between anterior and posterior sites, since energy is much higher in posterior sites. Only the intact side showed significantdifferences among odours in experts ( , p < 0.05). D indicates a significant difference in power between intact and sectioned sides. (c) In intact OB, maximalpower of the beta response in posterior recording sites evolves differentially across odourants and matched improvement of behavioural performances. Thefour odours are presented separately. The horizontal bar on the x-axis indicates days for which power of beta response to C8 was significantly higher whencompared to eugenol and geraniol. Arrows point the session for which behavioural learning to the criterion was reached in response to the 2 NoGo odoursC10 (descending arrow) and to eugenol (ascending arrow).


along daily training sessions appeared with different laten-cies within the odours. In addition, this increase occurredearlier in the posterior site of the olfactory bulb, i.e. within1–2 days before animals reached the criterion.

3.2.5. Effect of peduncle section on gamma activity

Section of the olfactory peduncle modifies spontaneous

activity and response to odours. Visual inspections of raw

signals (Fig. 4) showed that in the side of the lesion bothbeta (15–40 Hz) and gamma (60–90 Hz) oscillatory activitywere altered by peduncle section in both bulbar recordingsites. In the intact bulb, no change were observed bothqualitatively and quantitatively.

First, in absence of odour stimulation, gamma activitywas enhanced in the sectioned OB as can be seen inFig. 4. Activity was compared between the sectioned and

Fig. 4. Section of olfactory peduncle compromises emergence of high amplitude beta response following learning: upper part: typical OB LFPs recordings(0.1–300 Hz) obtained simultaneously from the ipsilateral side to the peduncle section (left part) and from the intact side (right part). The animal was in theexpert condition and sampled eugenol (S- NoGo stimulus). One can seen in the sectioned side obvious amplification of gamma activity before odoursampling, persistence of fast activity during odour period with no beta activity. Middle part time-frequency representations obtained from waveletanalysis. Frequency of the signal (y-axis, from 10 to 100 Hz) is represented as a function of time (x-axis, from �1000 to 2000 ms relative to odour onset)and power (colour bar, lV2). Bottom part: energy profiles from time frequency analysis in beta band (dotted line) and gamma band (full line). Arrowsindicates odour onset. In the sectioned side, gamma bursts are highly amplified and to some extend remain during odour sampling. In the intact sidevariation in the beta range is obvious following odour sampling with two peaks of energy. Gamma activity is present but weak before odour sampling (flatline is due to scale of y-axis) and completely absent during odour.


intact side during inter-trial intervals, while rats were inactive exploration of the experimental arena. In the intactside, we observed the classical fast gamma oscillatory activ-ity (60–90 Hz) appearing in bursts within each respiratorycycle. In the sectioned side, the bursting activity was stillpresent but strongly increased in amplitude. Importantly,the slow rhythm (about 6 Hz) associated to respirationremained.

The ANOVA for power values conducted on the refer-ence period (from �1500 to �500 ms prior to odour onset)confirmed these observations (Fig. 3a). As there was no sig-nificant effect of the learning level in gamma oscillationspower, all data were grouped. Analysis showed an effectof the section in interaction with the recorded region(F(1,1524) = 72.259, p < 0.01). For both anterior and pos-terior parts of the OB, gamma power was stronger in thesectioned site. This effect was stronger for the posterior part.

Second, in the sectioned OB, gamma activity persistedduring odour sampling (Fig. 4). In sectioned OB, even ifodour sampling was still associated with a gamma depres-sion, gamma bursts were still observed during this period.We first quantified the gamma decrease. The mean powervalue during odour period was extracted after baseline cor-rection relative to the reference period. In contrary to theintact OB, gamma decrease was not different betweenbeginners and experts. Pattern of gamma responses variedsignificantly according to recording sites and whether theywere obtained from the intact or the sectioned side. Therecording region and side strongly influenced this decrease(Fig. 3a) (region-side interaction F(1,1478) = 21.512,p < 0.01, odour-side effect F(1,1478) = 2.811, p < 0.05).Gamma decrease was stronger in posterior, but for bothregions, gamma power decrease was more important forsectioned than for intact OB. This is likely a consequence


of the higher gamma level observed in the reference periodin sectioned side. As showed in previous studies, no effectof the odour quality was obtained in the intact side. Onthe contrary, significance of odour effect was reached forthe sectioned side (anterior F(3,343) = 2.634, p < 0.05; pos-terior F(3,404) = 2.792, p < 0.05, for both geraniol 5 C10post-hoc).

To summarise, section of the peduncle strongly modifiedgamma oscillatory activity. This was visible mainly onspontaneous activity recorded during freely explorationof the rat in the arena, but also during odour sampling.The power of gamma bursting activity was largelyenhanced, and even if it strongly decreased during odoursampling, bursts were still present. This was never observedin intact animals.

3.2.6. Effect of peduncle section on beta activity

Odour-induced beta activity (15–40 Hz) was also alteredin sectioned OB both in beginners and experts animals.Moreover, for the two levels, as it was the case for gammaactivity, the two recording sites in the bulb exhibited strongdifferences. Qualitatively, the main difference was theabsence of the large odour-induced activity previouslyobserved as animals became experts. This can be observedin Fig. 4a. We first quantified this effect by measuring thenumber of trials with a significant response in the 15–40 Hz frequency band. According to this variable the OBipsilateral to the peduncle section exhibited less betaresponses (48.5%) compared to the intact side (69%)(Fisher test t(a = 0.05) = 7.958). Despite the decreased rateof responses, some activity remains in the 15–40 Hz fre-quency range. Consequently, we quantified and comparedthis remaining response for the two sides. Peduncle sectiondecreased expression of beta (15–40 Hz) activity both inbeginners and expert animals (Fig. 3b). This effect of sec-tion was in interaction with the odour quality and therecording region (beginners F(3,245) = 3.094, p < 0.05,experts F(3,581) = 3.447, p < 0.05). In beginners, betapower was significantly higher in the intact OB comparedto the contralateral side only in posterior region(F(3,142) = 3.016, p < 0.05 no significant effect was foundin the anterior region p > 0.5). In addition, this impairmentwas observed for all odours excepted C8. In expert rats,beta activity was also dramatically reduced in the sectionedOB compared to the intact one, for both regions and for allodours (ANOVA: anterior part: C8 and C10, p < 0.05,eugenol and geraniol p < 0.01; posterior part, four odoursp < 0.01).

In the OB ipsilateral to the section, there was no interac-tion between the learning level and the recorded region.Pooled data from the two training levels and the two bul-bar recorded regions revealed no effect of odour quality.However, for all the odours, beta odour-induced activityin expert rats was stronger than in beginners (F(1,356) =7.393, p < 0.01 l). Even if a weak increase in beta powerremained in the sectioned side, no more odour-specificresponse was observed.

To sum up, peduncle section resulted in a drastic reduc-tion in OB odour-induced beta response with a more pro-nounced effect in posterior sites.

4. Discussion

As suggested in early studies [7,36,26] the present exper-iments further stressed the possible functional importanceof the beta oscillatory response for odour processing. First,we show that this slow odour-induced activity (around25 Hz) is not only present in the first olfactory relay, theolfactory bulb, but also in the piriform cortex and to a les-ser extend in the entorhinal cortex. In OB and PC, powerof the beta activity is enhanced following learning. More-over, in trained animals beta bursts occur in a reduced timewindow during odour sampling (see Fig. 2b). Interestingly,this time window is different for each odour. Second, dataobtained with new odourant pairs confirm that odour qual-ity and training level modulate amplitude and time courseof the beta response. Third, we confirm that OB gammaactivity is under control of centrifugal fibres. In trainedintact rats gamma bursts are depressed during odour sam-pling. After section of the olfactory peduncle, spontaneousgamma activity power is enhanced and some gamma activ-ity remains even in the presence of odours. Finally, we pro-vide evidence that the beta response and its modulation dueto learning require the integrity of connections between theOB and the rest of the brain.

4.1. Gamma activity

Gamma oscillations observed in spontaneous activity,while the rat was exploring the conditioning arena wereconsistent with the fast activity extensively described byseveral authors since Adrian [1] in the hedgehog olfactorysystem [12,13,18]. Gamma bursts were mainly observed inthe OB and APC [7].

In the context of go/no-go learning tasks, we alwaysobserved an inhibition of gamma bursts during odour sam-pling. In addition, even if gamma decrease was higher afterlearning it did not depend of the chemical nature of theodour. On the contrary, it has been observed in expert ani-mals to depress before odour onset, while the animal wasapproaching the port and was unable to predict neitherthe stimulus nor the reward [36]. This is consistent withthe hypothesis that gamma activity would be more relatedto the context of the behavioural tasks than to the nature ofthe stimulus itself [18].

Peduncle section strongly modified the expression ofgamma activity. Indeed, in the sectioned side OB exhibiteda huge gamma activity still locked to the respiratoryrhythm. This effect was also described in the awake rabbitduring reversible cryogenic blockade of the peduncle [13],and in anaesthetised rat following peduncle section [29].These results suggest that action of centrifugal inputs tothe OB result in a reduction in gamma bursting activity.


Through modelling, various hypotheses have been pro-posed for the origin of gamma oscillatory activity. It hasbeen suggested to be the result of a negative feedback loopbetween excitatory and inhibitory connections [11] throughthe reciprocal synapse between mitral and granule cells [29]or produced by mutual inhibition among granule cells[19,22]. As centrifugal input connects largely onto the basaldendrite of granule cells, the effect of feedback connectioncould be either to enhance mutual inhibition of those cellsvia excitatory input or to directly inhibit the granule cells[18,21].

4.2. Beta activity

Contrary to gamma oscillatory activity, beta oscillatoryactivity is strictly odour-induced. Several types of dataargue for an important role of the beta response in odourprocessing. First, most of the tested odours induced anon-homogeneous response in the OB. This was true whenusing different variables for response quantification: changein signal power, frequency and latency of the maximal peakof energy [26].

Second, bulbar beta response can be amplified by a 10-fold factor following learning and the amplitude of thechange differed among odours. This effect was previouslydescribed with eugenol and geraniol but remained weak[26] and reinforced in the present study with two aldehydes.Indeed, odour induced beta oscillatory activity was higherfor C8 that for the other odours. As can be seen in Fig. 3c,C8 and C10 share similar structures. However, the reasonwhy structurally similar odours (C8 and C10) induced lar-ger difference in OB responses than two a priori very differ-ent odours (geraniol and eugenol) remains unclear. Incontrast, there were fewer differences among ‘‘similar’’odourants considering the time of occurrence of beta activ-ity after odour onset, as beta activity occurred later for C8and C10 than for eugenol and geraniol. At this level, wecan only hypothesise that neurones involved in representa-tion of the four odours are differently represented at therecording sites sampled in this study. Consequently, ifoscillatory activity results from synchronised activation ofan assembly of neurones responding to a given stimulus,its characteristics may differ according to the odoursampled.

Even if characteristics of beta activity were closely asso-ciated to odour quality, OB beta response also stronglydepended on its behavioural valence acquired through con-ditioning. Importantly, learning-associated amplificationof the beta response was observed for positively reinforced(go odours), non-reinforced and negatively reinforced stim-uli. Thus amplification does not seem to be modulatedby odour behavioural valence. Moreover, spatio-temporalcharacteristic of the beta response in experts rats seemedto reflect both odour quality and its behavioural valence.

Even if beta activity was weak in beginners, we broughtevidence that it was yet related to the odour sampling.First, in the OB, beta power increased during sampling

relative to the preceding period (odour port approach) atleast in the posterior site [26], second, the number of signif-icant peaks was not different between beginners andexperts, whereas this parameter was affected by pedunclesection.

The odour-induced beta oscillatory bursts were not onlycorrelated with odour quality but also with discriminationperformance. Analysis of data collected in the intermediatelevel of training provided information of how amplitude ofodour induced beta oscillations evolved over days in thecourse of learning. We first observed that beta activityincreased sooner in the posterior site. In addition, specifi-cally in this region, a trial-by-trial analysis revealed thatpeaks power value were significantly correlated with behav-ioural response latencies in the late phase of intermediatelevel but not in the early phase [26]. It is important to stressthat beta activity increase occurred primarily during ses-sions that precede reaching to the learning criterion. Datapresented in the present study strongly reinforced thisresult. The training was performed with four differentodours instead of two. Analysis of behavioural perfor-mances showed that animals learned C10 more rapidlythan eugenol. In parallel, we found that amplitudeincreased simultaneously with performance improvement.For example, increase in the beta response developedaround day 3 to C8 and around day 7 to eugenol and gera-niol. In addition, this result invalidates the hypothesis thatthe increased beta activity could simply result fromrepeated exposures to the odourants. If it was true, evolu-tion of the response would be the same for all odourantsused.

In previous experiment, we tested the specificity of betaactivity [26]. Presentation in experts rats of a novel discrim-ination task showed that odour sampling no longerinduced the large beta response to both go and no-goodours. Responses were similar to the one observed atthe initial phase of the first task. This was observed in spiteof the fact that rats sampled the odours actively andpromptly ran toward the reward dispenser. Importantly,the large beta response to novel odours re-emerged as soonas rats started to improve their performance. This sup-ported the hypothesis of a strong link between the largeOB beta response and olfactory discrimination. In addi-tion, absence of the large beta response following introduc-tion of a new set of stimuli rendered very unlikely thatamplification simply results from a general increase inattention.

Odour sampling, particularly in experts animals wasassociated with a beta response in OB, APC and PPCand LEC. The response occurred in a narrow frequencyrange from 20 to 26 Hz. In addition, the time window ofoccurrence of the maximal peak of energy in each structurewas narrower in experts than in beginners. To summarise,before learning a weak beta oscillatory response to odoursemerged in each structure at variable intervals on a periodof 1 s after odour sampling. Learning tuned the emergenceof beta oscillatory responses on a shorter period and differ-


ently for each odour (with a peak between 200 and 400 msfor eugenol and 400 and 800 ms for geraniol).

Previous studies have revealed that piriform cortex[24,28,44,45] and lateral entorhinal cortex [28] exhibitedchanges in odour responses after operant conditioning.Data from the present study confirm the functional heter-ogeneity between anterior and posterior PC previouslyobserved [7,23,25,28]. Indeed, Experiment 1 showed thattrained animals displayed a more pronounce amplificationof the beta response in the posterior than in the anteriorPC. Thus, similarly to what was found in the OB, learningmodified piriform cortex reactivity in a spatially non-homogeneous manner. As regard entorhinal cortex, learn-ing do not induced change in power of beta bursts.However, as in other areas, the time course of beta oscilla-tory response was significantly modified and synchronisedwith the other areas.

As a whole, the presence of a common frequency oscil-lation across areas involved in odour processing could rep-resent a neural correlate of olfactory recognition. Assuggested in the introduction, it could facilitate or resultfrom inter-area neuronal synchrony. Challenge of thishypothesis required further investigations.

Unilateral section of olfactory peduncle markedly mod-ified in the treated side both beta and gamma activities: nomore beta could be observed in the OB during odour sam-pling and gamma range oscillatory activity was increased.Surgery was designed to section mostly downstream con-nections from structures that project to the OB and toavoid the lateral olfactory tractus (LOT) which conveyolfactory information from OB to piriform and entorhi-nal cortices. It is important to notice that in spite of theunilateral section, rats exhibited the same behaviour asintact animals. Electrophysiological recordings showedthat OB–PC connections are required for normal expres-sion of the beta response.

Although beta and gamma activities are both likely gen-erated by the same bulbar cell types (relay neurones andinterneurones) each rhythm seems to be triggered by differ-ent set of inputs. This view emerges from the observationthat the two phenomenon never co-occurred [5,36] andare affected differentially following deafferentation of theOB from the rest of the brain. Indeed, what was observedfollowing this procedure suggest that gamma activity whichcharacterised resting activity critically depends on weakinput from olfactory receptor activation. Bulbar beta activ-ity seems to emerge from the combination of strong olfac-tory receptor activation during olfactory sampling togetherwith action of centrifugal fibres.

Bi-directional information transfer existing amongolfactory structures may modulate the emergence of betaoscillatory activity according to the different behaviouralstates in the learning paradigm [4,2,7,29]. Indeed, in therat, studies of coherence of oscillatory activities withinthe olfactory areas have suggested that a centrifugal influ-ence from the entorhinal cortex to OB was exerted duringexpectation of learned odours [18]. Modelling also showed

that synaptic changes associated with Hebbian plasticitywould give rise to a beta rhythm [31]. Thus, in our study,learning could strengthen connections within a functionalnetwork involving olfactory bulb and higher structures,and so increase beta activity. In the present experiment,peduncle section was not reversible and was performedbefore learning. Thus, the results could be interpreted intwo different ways: either the beta activity did not developeither it developed but the section blocked its expression.What would happen if the peduncle had been transientlyinactivated after the rat was expert, i.e. after beta activityhas increased?

To conclude, the findings that beta response could befound at different levels of the olfactory system, and its dis-ruption following peduncle section may indicate that thisoscillatory phenomenon could be associated with a func-tional network. However, further investigations are neededto assess its putative role in odour representation.

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