Chronic stress disrupts neural coherence between cortico-limbic … · 2019-07-09 · 2006, 2010;...

ORIGINAL RESEARCH ARTICLEpublished: 06 February 2013

doi: 10.3389/fncir.2013.00010

Chronic stress disrupts neural coherence betweencortico-limbic structuresJoão Filipe Oliveira 1,2†, Nuno Sérgio Dias1,2,3†, Mariana Correia 1,2, Filipa Gama-Pereira 1,2,Vanessa Morais Sardinha1,2, Ana Lima1,2, Ana Filipa Oliveira 1,2, Luís Ricardo Jacinto1,2,4,Daniela Silva Ferreira 1,2, Ana Maria Silva1,2, Joana Santos Reis1,2, João José Cerqueira 1,2 andNuno Sousa1,2*1 School of Health Sciences, Life and Health Sciences Research Institute (ICVS), University of Minho, Braga, Portugal2 ICVS/3B’s - PT Government Associate Laboratory, Braga/Guimarães, Portugal3 DIGARC, Polytechnic Institute of Cávado and Ave, Barcelos, Portugal4 Department of Industrial Electronics, University of Minho - Campus de Azurém, Guimarães, Portugal

Edited by:Michael Brecht, HumboldtUniversity Berlin, Germany

Reviewed by:Christiaan P. De Kock, VU UniversityAmsterdam, NetherlandsDaoyun Ji, Baylor Collegeof Medicine, USA

*Correspondence:Nuno Sousa, Instituto de Ciênciasda Saúde e da Vida (ICVS),Escola de Ciências daSaúde - Universidade do Minho,Campus de Gualtar,4710-103 Braga, Portugal.e-mail: [email protected]†These authors equally contributedto this work.

Chronic stress impairs cognitive function, namely on tasks that rely on the integrityof cortico-limbic networks. To unravel the functional impact of progressive stress incortico-limbic networks we measured neural activity and spectral coherences between theventral hippocampus (vHIP) and the medial prefrontal cortex (mPFC) in rats subjected toshort term stress (STS) and chronic unpredictable stress (CUS). CUS exposure consistentlydisrupted the spectral coherence between both areas for a wide range of frequencies,whereas STS exposure failed to trigger such effect. The chronic stress-induced coherencedecrease correlated inversely with the vHIP power spectrum, but not with the mPFCpower spectrum, which supports the view that hippocampal dysfunction is the primaryevent after stress exposure. Importantly, we additionally show that the variations invHIP-to-mPFC coherence and power spectrum in the vHIP correlated with stress-inducedbehavioral deficits in a spatial reference memory task. Altogether, these findings resultin an innovative readout to measure, and follow, the functional events that underlie thestress-induced reference memory impairments.

Keywords: chronic stress, coherence, power spectrum, hippocampus, prefrontal cortex

INTRODUCTIONStress is a constant in the daily life of the modern societies. Eachsubject is constantly challenged and threatened by a large vari-ety of unpredicted events. Under stressful situations, a primaryresponse is set up, in order to restore homeostasis and pro-mote behavioral adaptation; however, prolonged stress exposuremay trigger maladaptive responses that lead to severe manifes-tations such as learning and memory deficits or anxious anddepressive-like behavior (Popoli et al., 2011; Sousa and Almeida,2012). Whereas hippocampal structural damage and impairedplasticity were initially recognized to underlie these manifesta-tions (Sousa et al., 2000), subsequent studies demonstrated thatthe medial prefrontal cortex (mPFC), an area intimately relatedwith working memory processes and cognitive stimuli integra-tion, is also a key target of chronic stress (Cerqueira et al., 2007a,b;Liston et al., 2009). At a functional level, such neuronal compro-mise was correlated with a strong impairment of plasticity in thehippocampus-PFC pathway (Cerqueira et al., 2007a).

Although mechanisms of plasticity are generally accepted asreadouts of interregional connections, much information onneuronal dynamics is lost due to the supra-physiological pro-tocols typically used. Since previous data suggests that chronicunpredictable stress (CUS) triggers disconnections in specificbrain circuits, additional measures such as power spectra andphase coherence of local field potentials (LFPs) under stressfulconditions urge to be assessed. LFPs reproduce summated

individual conductance and synaptic inputs of networks com-posed by ensembles of firing neurons and surrounding glia, andtherefore are an excellent readout of network dynamics (Buzsáki,2006, 2010; Perea et al., 2009; Jia et al., 2011). LFPs reflect thetemporal pattern of activity that acts on local networks that aredirectly connected (Varela et al., 2001); importantly, the ventralhippocampus (vHIP) and the prelimbic subfield of the medialPFC are linked by monosynaptic connection (Jay and Witter,1991; Thierry et al., 2000; Tierney et al., 2004). Moreover, phasecoherence between the hippocampus and cortex was proposedto correlate with acquisition of information and memory for-mation (Buzsáki, 1996; Popa et al., 2010; Fell and Axmacher,2011). In fact, previous studies using maze-based paradigmsto test different types of memory, reveal that rats displayedincreased theta phase coherence between the PFC and the HIPby the time they take a decision based in a previous expe-rience (Jones and Wilson, 2005; Benchenane et al., 2010); inaddition, hippocampal theta rhythms were shown to synchro-nize with PFC single cell (Siapas et al., 2005) and field activities(Hyman et al., 2011). Beta coherence between hippocampusand mPFC was also shown to be necessary for effective com-munication during visual object processing (Sehatpour et al.,2008). Interestingly, impaired coherence in the hippocampus-mPFC was observed after loss of PFC function (Brockmannet al., 2011) and in models of schizophrenia (Sigurdsson et al.,2010).

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Oliveira et al. Chronic stress disrupts cortico-limbic coherence

Based on these assumptions we hypothesize that stress-induced deleterious effects on the function of the PFC andhippocampus may be in a large extent due to alterations inphase coherence between these areas. The present study testedthis hypothesis by recording neural activity simultaneously fromthe mPFC and vHIP in rats exposed to short-term and chronicstress; the use of different periods of exposure to stress providedan insight of the temporal dynamics of the onset of stress-inducedchanges. Power spectrum densities and coherence were also ana-lyzed, and correlations between them were studied and comparedwith classical long-term potentiation measurements. In addi-tion, in a separate set of rats, variations in coherence and powerspectrum were correlated with behavioral performance.

RESULTSSTRESSED RATS DISPLAY INCREASED POWER SPECTRUM DENSITIESIN THE vHIP AND mPFCPower spectra translate the amplitude of the signals recorded ina brain region on the frequency domain. power spectrum density

(PSD) analysis of the recorded LFPs from the mPFC and vHIP ofall studied rats allowed the thorough characterization of poweractivity in a wide range of frequencies (Delta, 1–4 Hz; Theta,4–12 Hz; Beta, 12–20 Hz; Low Gamma, 20–40 Hz; High Gamma,40–90 Hz) for those regions at a basal state.

Regarding the function of the vHIP, short term stress (STS)triggered an increase of PSD in the theta, beta, low gamma andhigh gamma frequencies, while in the delta band no signifi-cant variation to controls (CON) was recorded (Figures 1A–C;see Table 1 for statistical values). Importantly, CUS exposure-induced a persistent increase in PSD in all frequency bandsanalyzed which was always higher than controls and STS(Figures 1A–C; see Table 1).

In contrast, PSD in the mPFC was only affected by the expo-sure to STS in beta and low gamma frequencies when comparedto control rats (Figures 1D–F; Table 1); however, exposure toCUS triggered an increase in the PSD in the theta, beta andlow gamma and high gamma frequency bands (Figures 1D–F;Table 1).

FIGURE 1 | Stressed rats show increased PSD in multiple frequencybands both in the ventral hippocampus and medial PFC. Representativetraces of raw data (black line) recorded simultaneously from the vHIP (A) andmPFC (D) of a rat of each group; the red line represents theta filteredcomponent, as example. Power Spectral Density (PSD) values of the vHIP(B) recordings and the mPFC (E) recordings, for controls (CON), short-term

stress (STS), and chronic unpredictable stress (CUS); each horizontal line inthe Y-axis represents the spectrogram of an individual rat. Group comparisonof the PSD values from vHIP (C) and mPFC (F) in the delta (1–4 Hz), theta(4–12 Hz), beta (12–20 Hz), low gamma (20–40 Hz), and high gamma(40–90 Hz) frequency bands. ∗Statistically different from CON, p < 0.05;#Statistically different from CUS, p < 0.05; error bars represent SD.


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Table 1 | Statistical values of the group comparisons of PSD and coherence for each frequency band in the first set of animals.

CON vs. STS

Band vHIP PSD mPFC PSD

delta theta beta low gamma high gamma delta theta beta low gamma high gamma

Z -value −1.47 −2.06 −2.29 −2.18 −2.41 0.00 −1.59 −2.06 −2.06 −0.53p-value 0.14 0.03 0.01 0.02 0.01 1.00 0.11 0.03 0.03 0.60

Band Coherence

delta theta beta low gamma high gamma

Z -value 2.76 2.18 1.94 1.23 −0.05p-value 0.00 0.06 0.08 0.22 0.95

CON vs. CUS



Z -value −2.95 −3.32 −3.32 −3.32 −3.32 −0.98 −2.38 −2.38 −2.76 −1.92p-value 0.00 0.00 0.00 0.00 0.00 0.33 0.01 0.01 0.00 0.05

Band Coherence


Z -value 2.76 2.76 3.04 2.29 1.26

p-value 0.00 0.00 0.00 0.01 0.21

STS vs. CUS



Z-value −1.88 −2.52 −2.66 −2.59 −2.02 −1.81 −1.31 −0.03 −0.81 −1.59p-value 0.05 0.00 0.00 0.00 0.04 0.06 0.19 0.97 0.42 0.11

Band Coherence


Z -value −1.03 1.10 1.81 1.88 1.17p-value 0.31 0.27 0.06 0.05 0.24

Each table represents the Z- and p-values of pairwise comparisons of vHIP PSD, mPFC PSD, and coherence values in the control (CON), short-term stress (STS),

and chronic unpredictable stress (CUS) groups. These values correspond to the graphs presented in Figures 1 and 2. Comparisons made by Mann–Whitney test;

statistical significance is highlighted in yellow (p ≤ 0.05).

STRESS DECREASES SPECTRAL COHERENCE BETWEEN THE vHIPAND mPFCCoherence between brain regions measures the matching oftemporal structure in signals recorded from those regions. Thetemporal structure, or phase, is a powerful measure since it doesnot depend on signal amplitude and two signals are said to besynchronous if their rhythms’ phase match (Varela et al., 2001).Coherence analysis of the signals obtained simultaneously fromthe vHIP and mPFC was used to study phase coherence betweenthese regions of the brain (Figure 2). The exposure of the ratsto STS caused a significant decrease of phase coherence in the

delta band when compared to the observed in controls (CON)(Figure 2A for individual analysis, Figure 2B for group compari-son by frequency band; statistic results on Table 1). Interestingly,exposure to CUS-induced a pronounced decrease in phase coher-ence when comparing to CON rats in the delta, theta, alpha,beta and low gamma bands, and in the low gamma band whencompared to STS; in the high gamma band, coherence levelsof CUS subjects were statistically undistinguishable from thoseobtained in the CON rats (Figures 2A,B; Table 1) and thereforefurther analysis was focused on the data observed for frequenciesbelow 40 Hz.




FIGURE 2 | Chronic stress decreases the coherence between theventral hippocampus (vHIP) and the medial prefrontal cortex(mPFC). (A) Spectral coherence of controls (CON), short term stress(STS), and chronic unpredictable stress (CUS); each horizontal line in theY-axis represents the spectrogram of an individual rat (B) Group

comparison of the coherence values between mPFC and vHIP for delta(1–4 Hz), theta (4–12 Hz), beta (12–20 Hz), low gamma (20–40 Hz), andhigh gamma (40–90 Hz) frequency bands. ∗Statistically different fromCON, p < 0.05; #Statistically different from CUS, p < 0.05; error barsrepresent SD.

STRESS-INDUCED LOSS OF COHERENCE CORRELATES WITHINCREASED PSD IN THE vHIPIn order to disclose whether stress affects the relationship betweenpower activity and coherence observed in the vHIP and mPFCof CON rats, a correlation between both measures was explored(Figure 3).

PSD recorded from the vHIP of CON rats did not correlate sig-nificantly with vHIP-mPFC coherence in the range of frequencybands analyzed (0–40Hz; CON in Figures 3A,B). Exposure tostress triggers a negative correlation between theta vHIP-PSD anddelta-theta and low gamma coherence which links the observa-tions in Figures 1 and 2, where coherence decreases as the powerincreases in vHIP as a result of exposure to stress. Such negativecorrelations are absent between vHIP-mPFC coherence and PSDrecorded from the mPFC of stressed animals suggesting that thesetwo measures are not linked. Interestingly, CON rats show a clearpositive correlation between theta coherence and all frequen-cies in mPFC PSD which seems to be disrupted by the chronicexposure to stress (Figures 3C,D).

STRESS EXPOSURE IMPAIRED LTP INDUCTION IN THEHIPPOCAMPAL-mPFC LINKTo compare the above described results with classical electrophys-iological measures of synaptic plasticity, we have analyzed theability to induce LTP in this neuronal connection. When sub-jected to high frequency stimulation (HFS) in the vHIP, the slopeof evoked PSPs recorded in the mPFC of CON rats increasedabout 52.1 ± 9.0% and remained elevated for at least 90 min, inthe form of long term potentiation (LTP; as a measure of neural

plasticity between the two regions; Figure A1A). The CUS ratsdisplayed the previously described impairment of LTP betweenthe vHIP and mPFC (CUS, 19.6 ± 4.7%; p < 0.05) (Cerqueiraet al., 2007a), while the STS rats maintained the LTP valueswhen compared to the CON rat (STS, 43.5 ± 3.5%; p > 0.05;Figure A1B).

BEHAVIORAL PERFORMANCE CORRELATES WITH VARIATIONS INCOHERENCE AND POWER SPECTRUM DENSITYAn independent set of control and chronically stressed rats wastested for cognitive function in order to assess an eventual linkbetween the chronic stress-induced coherence impairment andpower increase observed in the first set of rats and the previ-ously described cognitive impairments triggered by the chronicstress protocols described in the literature (Cerqueira et al., 2007a;Dias-Ferreira et al., 2009). The analysis of corticosterone lev-els as a measure of efficacy of the stress protocol confirmedthat the CUS protocol induced a chronic stress state in thestressed rats (CON, 48.2 ± 5.9 ng/ml; CUS, 414.8 ± 41.5 ng/ml;p = 0.002).

Chronic stress triggered deficits in the spatial reference mem-ory task, since CUS rats swim longer that controls to find theplatform and the learning curves of CON and CUS are signifi-cantly different (Figure 4A; p = 0.02). Post-hoc analysis compar-isons revealed significant impairments in reference memory inCUS rats on day 2 (Figure 4A; day 2, t-value = 3.126, p < 0.05;day 1, t-value = 2.178; day 3, t-value = 1.285; day 4, t-value =1.480; p > 0.05). Importantly, the analysis of swimming speed ofeach group reported that both CON and CUS rats swim at a same




FIGURE 3 | Correlations between spectral coherence and power spectraldensities in ventral hippocampus (vHIP) and medial prefrontal cortex(mPFC). The graphs present Pearson values for correlations betweenvHIP-mPFC spectral coherence and vHIP (A,B) or mPFC (C,D) power spectraldensities and respective p-values against null hypothesis (corr = 0), for CON

and CUS rats (A,C and B,D, respectively). For each brain region, statisticallysignificant correlations are represented in the right panel by color above darkblue (p < 0.05); the direction of the correlation, positive or negative, is givenin the left panel by the color code (green to red, positive correlation; green toblue, negative correlation).

speed in the water maze (Figure A2; p > 0.05) and post-hoc anal-ysis sustained this observation for each day (day 1, t-value = 0.81;day 2, t-value = 0.93; day 3, t-value = 2.38; day 4, t-value = 1.83;p > 0.05), excluding any locomotor deficit due to the chronicstress treatment. Additionally, chronic stress triggered a behav-ioral flexibility impairment, since CUS rats spent less time in thenew quadrant that control rats (Figure 4B; p = 0.04) in the rever-sal learning task of the Morris Water Maze, in agreement with datapreviously reported (Cerqueira et al., 2007a).

Again, we confirmed in this additional set of rats that CUStriggered a general increase in power recorded in the vHIPwhen compared to the CON rats (Figures 4C, A3A; Table 2).Similarly, the CUS rats displayed an increased PSD in the mPFCwhen compared to the CON rats (Figures 4D, Figure A3B;Table 2). Regarding the coherence between the vHIP and mPFC(Figure 4E), the stressed rats displayed a general decrease ofcoherence in a wide range of frequency bands when comparedto controls, except for the low gamma band, where a similar ten-dency was observed although not significant (Figure 4F; Table 2).These results were in accordance with the data recorded for thefirst set of rats, sustaining a profound affection of the networkafter chronic exposure to unpredictable stressors.

Subsequently, we searched for pairwise correlations amongcognitive performance in each day of the spatial reference mem-ory task, cognitive performance in the reversal learning task,coherence between the mPFC and vHIP and power spectra inthese brain regions (Figures 4G,H). Data shows that the dif-ferent performance of stressed and control rats on the second

day of the reference memory task inversely correlates with thevalue of coherence measured between the vHIP and mPFC foreach of those rats (Figure 4H) in the delta (r = −0.79), theta(r = −0.88) and high gamma (r = −0.77) bands, meaning thatthe coherence between the two regions is crucial for the good per-formance in this task. Additionally, we observed that the increasein theta power in the vHIP directly correlates with higher escapelatencies in the second day of test (Figure 4H; r = 0.71), disclos-ing a link between stress-triggered increase in theta vHIP powerand worse performance in this task by CUS rats.

DISCUSSIONExposure to CUS was previously shown to induce deleteriouseffects at a morphological level in the hippocampus (Sousa et al.,2000) and mPFC (Cerqueira et al., 2007b), which were sug-gested to underlie the deficits observed in behavior paradigmsthat rely on those areas in rodents (Cerqueira et al., 2007a; Dias-Ferreira et al., 2009) and in humans (Soares et al., 2012). In thiswork, using anesthetized rats, we show an unequivocal decreasein phase coherence in stressed subjects when compared withtheir non-stressed rats. Additionally, PSD extracted from LFPsrecorded in the mPFC of the CUS subjects increased signifi-cantly between 4 and 40 Hz, while a global increase of PSD inthe vHIP was observed for both STS and CUS rats. We showfinally that the decrease in delta, theta and high gamma coherenceand the increase in theta power in the vHIP correlate with theworse performance in the reference memory task of the MorrisWater Maze.




FIGURE 4 | CUS-induced changes in PSD and coherence correlate withimpairments in cognitive performance. (A,B) Cognitive performance of thestudied rats in water maze based tests for spatial reference memory andbehavioral flexibility; (A) Learning curves of the reference memory task ofcontrol (CON) and chronically stressed (CUS) rats. (B) Average trial time inthe new quadrant given as a percentage of the total escape latency for thereversal learning task. (C–F) Analysis of the LFP signals recorded in the vHIPand mPFC of the CON and CUS rats; Power Spectral Density (PSD) values ofthe vHIP (C) recordings and the mPFC (D) recordings, for controls (CON)and chronically stressed (CUS); (E) Spectral coherence of controls (CON) and

chronic unpredictable stress (CUS); in (C–E) each horizontal line in the Y-axisrepresents the spectrogram of an individual rat; (F) Group comparison of thecoherence values between mPFC and vHIP for delta (1–4 Hz), theta(4–12 Hz), beta (12–20 Hz), low gamma (20–40 Hz), and high gamma(40–90 Hz) frequency bands. (G,H) Correlation between behavior andelectrophysiological performances of the recorded rats; (G) p-values forPearson correlations between behavior and electrophysiologicalperformances for each rat; significant correlations highlighted in yellow;(H) Correlation plot for each significant correlation observed in G.*Statistically different from CON, p < 0.05; error bars represent SD.

The impact of stress in PSD and coherence between intercon-nected brain regions is currently under scrutiny. A recent studyreported a decrease in coherence around 4 Hz between both areasbut no significant changes in PSD (Lee et al., 2011). The presentdata is quite distinct to the findings of that study. Although bothsets of data report to the connection between the HIP and PFC,differences in experimental conditions may explain these appar-ently discrepant findings. First, in the present study we haverecorded from a more ventral hippocampal region than the onerecorded in the Lee et al. study; this is very relevant, since ourplacement was chosen based on evidence that the monosynap-tic hippocampus-PFC connection originates in the vHIP (Jay andWitter, 1991). Moreover, it has been shown that the electrophys-iological response of the vHIP to stress is remarkably different

from the one observed in more dorsal regions (Maggio and Segal,2009). The second methodological aspect that deserves merit tobe highlighted is that the stress paradigms used in both studieswere also different. While Lee et al. (2011) used a repeated stressparadigm, the unpredictability of stressor presentation of the CUSprotocol used in our work was shown to be crucial for the stress-consequence severity in the neural regions affected (Maier andWatkins, 2005; Amat et al., 2006); this might also justify theseverity of effects observed in our data.

CUS rats presented significant increases of PSD, when com-pared to non-stressed rats, in both vHIP and mPFC. Interestingly,the present results show that STS also increase PSD, but moreextensively in the vHIP. Since power activity translates the ampli-tude of the signals recorded in a brain region for a given




Table 2 | Statistical values of the group comparisons of PSD and coherence for each frequency band in the second set of animals.

CON vs. CUS



Z -value −1.87 −1.87 −1.87 −1.87 −1.87 −1.87 −2.16 −2.16 −2.16 −1.87p-value 0.05 0.05 0.05 0.05 0.05 0.05 0.02 0.02 0.02 0.05

Band Coherence


Z -value 1.87 2.16 1.87 1.01 2.16

p-value 0.05 0.02 0.05 0.34 0.02

Each table represents the Z- and p-values of pairwise comparisons of vHIP PSD, mPFC PSD, and coherence values in the control (CON) and chronic unpredictable

stress (CUS) groups. These values correspond to the graphs presented in Figure 4. Comparisons made by Mann–Whitney test; statistical significance is highlighted

in yellow (p ≤ 0.05).

frequency, which in turn represents the extent of neuron recruit-ment to fire on a particular rhythm, one may conclude thatexposure to stress caused an increase in neuronal activity, morepronounced in the vHIP, that progresses with time also to otherbrain regions, such as the mPFC. This temporal sequence hasbeen previously proposed by our behavioral data (Cerqueira et al.,2007a) and is of great relevance to understand the progressionof cognitive deficits in stress-related pathologies. The under-lying mechanisms for the augmented PSD are still unknown.However, it seems reasonable to admit that an imbalance inexcitatory/inhibitory inputs is present. Several lines of evidencepoint on this direction. On one hand, stress exposure was shownto enhance the release of excitatory neurotransmitters (such asglutamate, dopamine, norepinephrine, or acetylcholine) in thehippocampus and PFC (Finlay et al., 1995; Mark et al., 1996;Feenstra, 2000; Moghaddam, 2002; Dazzi et al., 2004); on theother hand, it is known that GABAergic activity is reduced afterstress exposure in these brain regions (Otero Losada, 1988; Hasleret al., 2010). Interestingly, once the increase in PSD is establishedin the vHIP, the changes in the mPFC might also be due to an aug-mented afferent excitatory input; in this case an early increase inthe activation of hippocampal neurons could lead consequentlyto overactivation of monosynaptically connected (Jay and Witter,1991; Thierry et al., 2000; Tierney et al., 2004) neurons in themPFC. Such uncontrolled and desynchronized neuronal activityincrease is likely to underlie the striking decrease in coherencebetween the vHIP and the mPFC observed after CUS, which maytrigger a compensatory mechanism, translated by an increasedpower activity, in order to attempt to restore the decreased coher-ence in this neuronal network. This detrimental effect fits with theloss of important connections during neuronal atrophy verified instressed subjects (Cerqueira et al., 2007a,b).

Coherence, as a measure of synchronization between the oscil-lations of cortical and limbic regions, was shown to underliegood behavior performance, namely supporting memory pro-cessing (Buzsáki, 1996, 2010; Jones and Wilson, 2005; Siapas et al.,2005; Benchenane et al., 2010; Popa et al., 2010; Hyman et al.,2011). In this scope, it is predictable that a decrease of coherencemay cause impairments in the functions attributed to the regions

that are connected by such circuits. Indeed, decreased coher-ence in the hippocampus-mPFC was shown to affect directly thePFC function (Brockmann et al., 2011). Based in the presentobservations, we suggest that the pronounced loss of vHIP-mPFC coherence between 1–40 Hz after chronic stress exposureunderlie the previously described stress-related behavior impair-ments, which are dependent on the normal hippocampal andprefrontal function in those frequency bands (Cerqueira et al.,2007a). Importantly, the CUS-induced decrease in vHIP-mPFCcoherence is associated with an enhancement of neuronal activ-ity, measured by PSD, in coincident frequencies in both regions.The correlation of these two electrophysiological phenomenarevealed an inverse correlation between vHIP-mPFC coherenceand the hippocampal function, but not between mPFC activityand vHIP-mPFC coherence. This indicates a putative leading roleof hippocampal firing on the disruption of this direct pathwayby chronic stress exposure; the hippocampal disruption would,in turn, compromise the behavior outputs dependent on thispathway. In fact, these observations confirm previously reportedbehavioral data, in which reference memory (hippocampal-dependent) was impaired after 3 days of stress, while behaviorflexibility (PFC-dependent) was only after a longer period ofexposure to stress (Cerqueira et al., 2007a). Accordingly, thissequential behavior impairment is supported by a reduction ofspine density and apical dendrite arborization of pyramidal neu-rons of layers II/III of the PFC, precisely where the hippocampalafferents establish synapses (Radley et al., 2004; Cerqueira et al.,2007b). Finally, it is noteworthy that after STS rats show a gen-eral increase in vHIP PSD, which is less extent in the mPFC of thesame rats, and may indicate an early affection of the hippocampalneural activity by stress. Interestingly, in contrast to CUS, STS ratsdo not present yet signs of LTP impairment.

In addition, we confirmed that the decrease of vHIP-mPFCcoherence and increase in PSD is linked to the poorer cognitiveperformance of stressed rats, as we found significant correlationsbetween reference memory performance and electrophysiologi-cal data. This evidence is of major relevance since it establishesfor the first time the link between the affection of the neuralnetwork after chronic stress exposure and the cognitive decline




observed in the stressed subjects. Importantly, it confirms thatcoherence and neural activity, namely in the theta band, is severelyaffected in the stressed rats and is disruptive for the entrainmentof the hippocampal-cortical connection and, consequently, forgood behavior performance (Buzsáki, 1996; Jones and Wilson,2005; Siapas et al., 2005; Benchenane et al., 2010; Popa et al., 2010;Hyman et al., 2011).

In summary, the present data reveals that chronic stress pri-marily affects hippocampal activity, which in turn will inducedamage in prefrontal dendritic trees, disrupting the HIP-PFCconnection and triggering a decrease in coherence between thetwo areas. Since neural coherence is a measure of regional inter-play, behavior outcomes dependent on this interplay are severelyaffected, as showed by direct correlations between decreasein vHIP-mPFC coherence and reference memory performance.These findings provide a novel readout of the dynamics of stressdeleterious effects in corticolimbic networks and are of relevanceto better understand the mechanisms underlying stress-inducedimpairment in cognitive performance.

MATERIALS AND METHODSANIMALS AND TREATMENTSAll experiments were conducted in accordance with localregulations (European Union Directive 86/609/EEC) andNational Institutes of Health guidelines on animal care andexperimentation.

Two months-old male Wistar–Han rats (Charles RiverLaboratories, Spain) were housed in groups of two under stan-dard laboratory conditions (lights on from 8:00 A.M. to 8:00 P.M.;room temperature 22◦C; ad libitum access to food and water). Agroup of rats was submitted to 28 days of CUS. Briefly, rats wereexposed to a stressor (1 h/day) of one of several aversive stimuli[cold water (18◦C), restraint, overcrowding, exposure to a hot airstream, noise or shaking]; the stressors were presented in a ran-dom order. This stress paradigm was shown previously to inducepersistently a pattern of consequences characterized by elevatedplasma levels of corticosterone, the primary glucocorticoid of therat, and reduced thymus weights (Cerqueira et al., 2007a). STSwas induced to a second group of rats with one stressor daily (sim-ilar to CUS) for 6 days. A third group of rats was handled daily andserved as controls (CON). Electrophysiological recordings wereperformed for each rat the day after the end of treatment.

An additional set of rats was used to search for correlationsbetween behavioral performance and variations in power spec-tra in vHIP and mPFC and in coherence between these regions.Corticosterone levels were measured in blood serum sampledbetween 9:00 and 10:00 A.M. using a commercially availableELISA kit (Cayman Chemical, USA).

SURGERYRats were anesthetized with sodium pentobarbital (60 mg/kg,i.p., supplemented each 60 min throughout the experiment) andplaced in a stereotaxic frame. Rectal temperature was main-tained at 37◦C by a homoeothermic blanket (Stoelting, Ireland).Experimental procedures for implantation and recording extra-cellular field potentials in the prelimbic area (PL) of themedial PFC have been described previously (Rocher et al., 2004;Cerqueira et al., 2007a). Briefly, Platinum/Iridium recording

electrodes (Science Products, Germany) were placed in the PL(coordinates, 3.3 mm anterior to bregma, 0.8 mm lateral tothe midline, 4.0 mm below bregma) and a concentric bipo-lar tungsten/stainless-steel electrode (WPI, USA) was positionedinto the ipsilateral CA1/subicular region of the vHIP (coordi-nates, 6.5 mm posterior to bregma, 5.5 mm lateral to the midline,5.3 mm below bregma), according to the atlas of Paxinos andWatson (2005).

In vivo RECORDING OF LOCAL FIELD POTENTIALS IN THE mPFC ANDVENTRAL HIPPOCAMPUSLFP signals obtained from both electrodes were amplified, filtered(0.1–3000 Hz, LP511 Grass Amplifier, Astro-Med, Germany),acquired (Micro 1401 mkII, CED, UK) and recorded on apersonal computer running Signal Software (CED, UK). Afterreaching fully anesthetized state, 100 s of local field activity wasrecorded at the sampling rate of 250 Hz (for representative tracessee Figures 1A–D). After the electrophysiological protocols, abiphasic 1 mA stimulus was delivered to both electrodes. Ratswere sacrificed and perfused a solution of paraformaldehyde 4%.Brains were carefully removed and sectioned in 50 µm slices.Brain slices containing the PFC and hippocampus were processedwith a light Giemsa staining for determination of electrode posi-tion; the lesion caused by the biphasic stimulus identified theelectrode position and the recordings were discarded wheneverone of the electrodes failed the targeted position (about 12%of the recordings). In total we analyzed 6 CON, 9 STS, and 12CUS rats; an additional set of 4 CON and 4 CUS were usedto establish correlations between behavioral performance andelectrophysiological data (Figure A4).

In vivo STUDY OF SYNAPTIC PLASTICITY BETWEEN THE mPFC ANDVENTRAL HIPPOCAMPUSSynaptic plasticity was tested in anesthetized rats by inducing LTPas described previously (Cerqueira et al., 2007a). Briefly, the elec-trode inserted in the CA1/subicular region was used to deliverstimuli to induce a characteristic monosynaptic field excitatorypostsynaptic potential (fEPSP) in the PFC (Figure 1A; inset). Testpulses (100 ms) were delivered every 30 s at an intensity enoughto evoke a potential about 70% of its maximum (250–500 µA;S88X Grass Stimulator, Astro-Med, Germany). The evoked poten-tial to such stimulation is likely to reflect summated PSPs. Basalresponses were recorded during 30 min and followed by LTPinduction, which was obtained performing HSF, that consistedof two series of 10 trains (250 Hz, 200 ms) at 0.1 Hz, 6 min apart,delivered at test intensity. The size of LTP induction was measuredby changes in the slope of responses to additional 90 min stimu-lating each 30 s. PSP slopes were analyzed using Signal software(CED, UK; sampling rate, 10 KHz) and expressed as a percent-age change of the mean responses to basal stimulation before andafter HFS.

BEHAVIORAL ANALYSISBehavioral tests were conducted as described previously(Cerqueira et al., 2007a), using water maze-based tests to assessspatial reference memory and behavior flexibility. The spatialreference memory task, highly dependent of the integrity ofthe function of the hippocampus (Morris, 1984), assesses the




ability of rats to learn the position of the hidden platform, basedon external cues placed outside the pool. Rats were placed, facingthe wall of the maze, in each of the four imaginary pool quadrantsat the beginning of each of the four daily trials. A trial is con-sidered complete when the rat escapes onto the platform; whenthis escape fails to occur within 120 s, the rat is gently guided tothe platform and an escape latency of 120 s is recorded for thattrial. Rats are allowed to spend 30 s on the escape platform beforebeing positioned at a new starting point. Time spent to reach theplatform (escape latency) was recorded in the consecutive trials.During the reference memory task, the platform was set in thesame imaginary pool quadrant and rats were tested during 4 days.Data on average escape latencies to the platform on days 1–4 wereanalyzed as a reference memory test.

To perform the reversal learning task, a PFC-dependent func-tion (De Bruin et al., 1994), on day 5, the escape platform waspositioned in the opposite (new) quadrant and rats were testedin a 4-trial paradigm, similar to that described above. For thisreverse-learning task, time spent swimming in the new quadrantwere recorded and analyzed as a measure of behavioral flexibility.

DATA ANALYSIS AND STATISTICSThe PSD of PFC and hippocampus regions, as well as the coher-ence between both regions, were performed on the 2-channel100 s long LFP signals acquired at the start of the experimentfor each rat. Each measure was applied on 1 s long segments andthe average of all segments was considered for statistical groupanalysis. Both measures were assessed in a wide range of fre-quencies: delta (1–4 Hz); theta (4–12 Hz); beta (12–20 Hz); lowgamma (20–40 Hz); high gamma (40–90 Hz). All LFP recordswere thoroughly inspected and those that presented significantnoise corruption were excluded from further analyses. PSD andcoherence were calculated with custom-written MATLAB-basedprograms (MathWorks, Natick, MA).

PSD analysisThe PSD of each channel was calculated through the 10 × log10of the multiplication between the complex Fourier transform ofeach 1 s long data segment and its complex conjugate. The meanPSD of each channel was evaluated for all frequencies from1 to 90 Hz.

Spectral coherence analysisCoherence analysis was based on multi-taper Fourier analysis.Coherence was calculated by custom-written MATLAB scripts,using the MATLAB toolbox Chronux (http://www.chronux.org)

(Mitra and Pesaran, 1999). Coherence has been calculated foreach 1 s long segments and their mean was evaluated for allfrequencies from 1 to 90 Hz.

Coherence-PSD correlationsThe correlation values were calculated between the follow-ing paired frequency-domain vectors: coherence—mPFC PSD;coherence—vHIP PSD. The correlation measures were calculatedthrough a custom-written MATLAB program that computes pair-wise Pearson’s coefficient between frequency-domain (1 Hz bins)coherence and PSD vector pairs. The p-values were calculatedthrough a two-tailed t-test.

Statistical group analysisThe group mean comparisons were calculated through non-parametric Mann–Whitney tests.

Multiple comparisons, for instance to compare LTP inductionin the three groups (Figure A1), were made using non-parametricKruskal–Wallis test followed by Dunn’s corrections.

Performance of each group in the reference memory task andrespective swim speeds were compared using repeated-measuresANOVA, being the difference between groups in each day calcu-lated by Bonferroni post-hoc tests.

Pearson correlation coefficients were calculated betweenbehavioral parameters and PSD, for both PFC and hippocampusregions, and vHIP-mPFC coherence.

ACKNOWLEDGMENTSThe authors work was supported by FEDER funds throughOperational program for competivity factors—COMPETEand by national funds through FCT—Foundation forScience and Technology (FCT) fellowships (João FilipeOliveira by SFRH/BPD/66151/2009; Luís Ricardo Jacinto bySFRH/BD/40459/2007), a Marie Curie Fellowship (João FilipeOliveira by PIEF-GA-2010-273936) and Grants from BIALFoundation (138/2008 to João José Cerqueira and 61/2010 toJoão Filipe Oliveira and Vanessa Morais Sardinha) and FCT (JoãoFilipe Oliveira, Ana Lima, and Ana Filipa Oliveira by PTDC/SAU-NSC/118194/2010; Nuno Sérgio Dias, Luís Ricardo Jacinto,João José Cerqueira, and Nuno Sousa by FCT/PTDC/SAU-ENB/118383/2010; Nuno Sérgio Dias, Daniela Silva Ferreira,Joana Santos Reis, João José Cerqueira, and Nuno Sousa byFCOMP-01-0124-FEDER-022674). The authors would like tothank Rui Gomes for the help in the application of electrophysio-logical techniques and Luís Martins and Miguel Carneiro for thehistological preparations.

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Conflict of Interest Statement: Theauthors declare that the researchwas conducted in the absence of anycommercial or financial relationshipsthat could be construed as a potentialconflict of interest.

Received: 07 November 2012; accepted:16 January 2013; published online: 06February 2013.Citation: Oliveira JF, Dias NS, CorreiaM, Gama-Pereira F, Sardinha VM, LimaA, Oliveira AF, Jacinto LR, Ferreira DS,Silva AM, Reis JS, Cerqueira JJ andSousa N (2013) Chronic stress disruptsneural coherence between cortico-limbicstructures. Front. Neural Circuits 7:10.doi: 10.3389/fncir.2013.00010Copyright © 2013 Oliveira, Dias,Correia, Gama-Pereira, Sardinha, Lima,Oliveira, Jacinto, Ferreira, Silva, Reis,Cerqueira and Sousa. This is an open-access article distributed under the termsof the Creative Commons AttributionLicense, which permits use, distributionand reproduction in other forums, pro-vided the original authors and sourceare credited and subject to any copy-right notices concerning any third-partygraphics etc.


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APPENDIX

FIGURE A1 | Chronic unpredictable stress decreases synapticplasticity between the ventral hippocampus (vHIP) and the medialprefrontal cortex (mPFC). (A) Time course of LTP induction after highfrequency stimulation (HFS); each circle represents the average of 10normalized fEPSP slopes with SEM; three groups are depicted: controls

(CON, blue), short term stress (STS, green) and chronic unpredictablestress (CUS, red); (inset) representative recordings of fEPSPs pre- andpost-HFS (scale bar: 1 mV; 5 ms) of a CON rat; (B) Normalized values ofLTP averaged for the three groups of rats: CON, STS, and CUS;∗statistically different from controls, p < 0.05; error bars represent SD.

FIGURE A2 | Chronic stress exposure does not induce locomotordeficits. Average swimming speeds of CON (blue) and CUS (red) ratsduring the 4 days spatial reference memory task. No differences areobserved between groups in each day (p > 0.05); error barsrepresent SD.




FIGURE A3 | Stressed rats show increased PSD in multiplefrequency bands both in the ventral hippocampus andmedial PFC in the second set of rats. Group comparison ofthe power spectral density (PSD) values from vHIP (A) and

mPFC (B) in the delta (1–4 Hz), theta (4–12 Hz), beta (12–20 Hz),low gamma (20–40 Hz) and high gamma (40–90 Hz) frequencybands. ∗Statistically different from CON, p < 0.05; error barsrepresent SD.

FIGURE A4 | Identification of electrode recording sites. Left panel,recording site location in control (CON, blue), short term stress (STS, green)and chronic unpredictable stress (CUS, red) rats, within the medial prefrontal

cortex (A, mPFC) and ventral hippocampus (B, vHIP); Images adapted fromPaxinos and Watson, 2005. Right panel, Cresyl Violet stained 50 µm sectionswith an electrolytic lesion at the recording site.



Chronic stress disrupts neural coherence between cortico-limbic structuresIntroductionResultsStressed Rats Display Increased Power Spectrum Densities in the vHIP and mPFCStress Decreases Spectral Coherence Between the vHIP and mPFCStress-Induced Loss of Coherence Correlates with Increased PSD in the vHIPStress Exposure Impaired LTP Induction in the Hippocampal-mPFC LinkBehavioral Performance Correlates with Variations in Coherence and Power Spectrum Density

DiscussionMaterials and MethodsAnimals and TreatmentsSurgeryIn vivo Recording of Local Field Potentials in the mPFC and Ventral HippocampusIn vivo Study of Synaptic Plasticity between the mPFC and Ventral HippocampusBehavioral AnalysisData Analysis and StatisticsPSD analysisSpectral coherence analysisCoherence-PSD correlationsStatistical group analysis

AcknowledgmentsReferencesAppendix

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