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Functionally altered neurocircuits in a ratmodel of treatment-resistant depressionshow prominent role of the habenula

Natalia Gassa,1, Dirk Cleppiena,1, Lei Zhenga,e,Adam James Schwarzb,c, Andreas Meyer-Lindenbergd,Barbara Vollmayrd,f, Wolfgang Weber-Fahra,Alexander Sartoriusa,d,n

aResearch Group Translational Imaging, Department of Neuroimaging, Central Institute of Mental Health,Medical Faculty Mannheim, University of Heidelberg, Mannheim, GermanybTailored Therapeutics, Eli Lilly and Company, Indianapolis, IN, USAcDepartment of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USAdDepartment of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical FacultyMannheim, University of Heidelberg, Mannheim, GermanyeExperimental Radiation Oncology, University Medical Center Mannheim, University of Heidelberg,Mannheim, GermanyfResearch Group Animal Models in Psychiatry, Central Institute of Mental Health, Medical FacultyMannheim, University of Heidelberg, Mannheim, Germany

Received 7 August 2013; received in revised form 24 October 2013; accepted 2 December 2013

KEYWORDSHabenula;Rat;Depression;Functionalconnectivity;rCBV;Congenital learnedhelplessness

nt matter & 20130.1016/j.euroneur

thor at: Departmeberg, J5, 68159 Mlexander.sartoriusrship.

ticle as: Gass, N.the habenula. Eur

AbstractTreatment-resistant depression (TRD) remains a pressing clinical problem. Optimizing treat-ment requires better definition of the function and specificity of the brain circuits involved.To investigate disease-related alterations of brain function we used a genetic animal model ofTRD, congenital learned helplessness (cLH), and functional magnetic resonance imaging as atranslational tool. High-resolution regional cerebral blood volume (rCBV) and resting-statefunctional connectivity measurements were acquired at 9.4 T to determine regional dysfunc-tion and interactions that could serve as vulnerability markers for TRD. Effects of cLH on rCBVwere determined by statistical parametric mapping using 35 atlas-based regions of interest.Effects of cLH on functional connectivity were assessed by seed region analyses. Significantbilateral rCBV reductions were observed in the lateral habenula, dentate gyrus and subiculumof cLH rats. In contrast, focal bilateral increase in rCBV was observed in the bed nucleus of striaterminalis (BNST), a component of the habenular neurocircuitry. Functional connectivity was

Elsevier B.V. and ECNP. All rights reserved.o.2013.12.004

nt of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim,annheim, Germany. Tel.: +49 0621 17032913.@zi-mannheim.de (A. Sartorius).

, et al., Functionally altered neurocircuits in a rat model of treatment-resistant depression showopean Neuropsychopharmacology (2013), http://dx.doi.org/10.1016/j.euroneuro.2013.12.004

N. Gass et al.2

Please cite this article as: Gass, N.prominent role of the habenula. Eur

primarily enhanced in cLH rats, most notably with respect to serotonergic projections from thedorsal raphe nucleus to the forebrain, within the hippocampal-prefrontal network and betweenthe BNST and lateral frontal regions. Dysregulation of neurocircuitry similar to that observed indepressed patients was detected in cLH rats, supporting the validity of the TRD model andsuitability of high-field fMRI as a translational technology to detect and monitor vulnerabilitymarkers. Our findings also define neurocircuits that can be studied for TRD treatment inpatients, and could be employed for translational research in rodent models.& 2013 Elsevier B.V. and ECNP. All rights reserved.

1. Introduction

Major depressive episodes have been related to abnormalfunction of brain neurocircuitry (Ressler and Mayberg, 2007).Translating preclinical findings into human research implicatesthe existence of a valid animal model and a translational tool.We used congenital learned helpless rats to model treatment-resistant depression (TRD), and high-field functional magneticresonance imaging (fMRI) as a translational tool to investigatedisease-specific alterations of brain function.

Learned helplessness (LH), as introduced by Marty Selig-man, is based on the hypothesis that uncontrollable stressinduces hopelessness and depressive-like behavior. It consti-tutes a well-established animal model of depression withhigh construct, predictive, and face validity (Vollmayr andHenn, 2001b). Congenital learned helplessness (cLH) is agenetic animal model of depression directly derived fromthe LH model by taking advantage of the natural variation ofvulnerability to the effects of uncontrollable stress andselectively mating learned helpless and non-learned helplessrats. Inter alia, our established cLH strain demonstratescongenital helpless behavior, as well as anhedonia (Enkelet al., 2010), depressive-like cognitive bias (Richter et al.,2012), treatment-resistance (even to electroconvulsive shocktherapy) (Sartorius et al., 2007), and biochemical changes,such as alterations in the hippocampal glutamatergic andGABAergic systems (Sartorius et al., 2007; Zink et al., 2007,2009).

Due to the use of anesthesia and/or restraint in pre-clinical fMRI, cognitive paradigm-driven fMRI as commonlyused in human studies is not possible in the rat. However,measurements of resting brain function provide a compel-ling avenue for translational fMRI. In a paradigm-freeresting state fMRI (rsfMRI) experimental design, low-frequency blood-oxygenation level-dependent (BOLD) oscil-lations reveal functionally connected networks of brainregions. Currently, this approach is well-established inhumans (Fox and Greicius, 2010), and translational methodshave been reliably established in rodents (Lu et al., 2007;Pawela et al., 2008; Kannurpatti et al., 2008; Zhao et al.,2008; Kalthoff et al., 2011; Jonckers et al., 2011). Mostrecently we reported on the prefrontal–hippocampal cou-pling and default-mode-like network oscillations (Schwarzet al., 2013), as well as on pharmacological modulation offunctional connectivity by means of rsfMRI in anesthetizedrats (Gass et al., 2013).

BOLD-based fMRI methods are however limited in effectivespatial resolution due to matrix size trade-offs in order tomaintain a high temporal sampling, susceptibility effects andresidual image distortion. A complementary approach is to

, et al., Functionally altered neuopean Neuropsychopharmacology

quantify basal regional cerebral blood volume (rCBV) at a higherspatial resolution, using a blood pool contrast agent andacquisition method that is substantially less impacted bydistortions related to magnetic susceptibility (Gozzi et al.,2007; Moreno et al., 2006; Schobel et al., 2009). rCBV is a well-established surrogate of resting brain metabolism (Small et al.,2004) and allows smaller brain structures to be resolved.Additionally, by applying this technology we intended to get asynergistic effect by revealing information not only aboutregion-dependent functional connectivity, but also about regio-nal neuronal (dys)function. Analogously to rsfMRI, rCBV can bemeasured paradigm-free.

Severe and concurrently TRD has been successfully treatedby deep brain stimulation in the last decade (Mayberg et al.,2005; Bewernick et al., 2010; Sartorius et al., 2010; MaloneJr. et al., 2009). New hypotheses about the underlyingmalfunctional neurocircuitries in TRD coming from theserecent therapeutic achievements have been developed(Mayberg, 2009; Sartorius and Henn, 2007; Sartorius andMeyer-Lindenberg, 2009; Anderson et al., 2012; Murroughet al., 2011). Within these models many subcortical (lateralhabenula, ventral tegmental area, ventral striatum, nucleusaccumbens, basal ganglia, thalamus, hippocampus, amygdala)and cortical (medial and dorsolateral prefrontal cortex,orbitofrontal and insular cortex, subgenual and posteriorcingulum) regions have been implicated (Sartorius et al.,2013). Further evidence for a major influence of the abovementioned subcortical structures comes from a cross-speciestranslational approach, which underlines an abnormal restingstate hyperactivity in anterior midline regions in depression(Alcaro et al., 2010).

We hypothesized that there are differences in functionalbrain neurocircuitries between cLH and rats not showing LHbehavior (cNLH) that could serve as a vulnerability markersfor depression. Specifically, we sought to determine thedisease model-related dysfunction in brain functional con-nectivity and resting brain activity. Since it has beendemonstrated that within our cLH model of TRD the lateralhabenula (LHb) shows altered metabolism (Shumake et al.,2003), and additionally, depressive-like behavior was rever-sibly alleviated after pharmacological inhibition of the LHb(Winter et al., 2011), we primarily expected a functionaldifference of specific habenular neurocircuitries.

2. Experimental procedures

2.1. Animals

All procedures were conducted according to the regulations cover-ing animal experimentation within the European Union (European

rocircuits in a rat model of treatment-resistant depression show(2013), http://dx.doi.org/10.1016/j.euroneuro.2013.12.004

3Functionally altered neurocircuits in a rat model of treatment-resistant depression show prominent role of the habenula

Communities Council Directive 86/609/EEC) and within the GermanAnimal Welfare Act. Experiments were approved by the Germananimal welfare authorities (Regierungspräsidium Karlsruhe) andcarried out at the Central Institute of Mental Health, Mannheim,Germany.

We selected Sprague-Dawley rats for a breeding program on thebasis of their susceptibility to develop LH, which yielded a cLHstrain (Vollmayr et al., 2001a). Additionally, an analogous strain wasbred cNLH. 12 male rats from our cLH and 10 male rats from ourcNLH colony (73rd gerneration) were used for fMRI experiments. Allanimals (cLH: (362725) g; cNLH: (375731) g) were housed undercontrolled conditions (19–231C, 40–60% humidity) on a 12:12 h light–dark cycle (lights on at 07:00).

2.2. Data acquisition

All experiments were performed at a 94/20 Bruker Biospec MRIscanner (9.4 T; Bruker BioSpec, Ettlingen, Germany) with Avance IIIhardware, BGA12S gradient system with the maximum strength of705 mT/m and running Paravision 5.1 software. Transmission andreception were accomplished using a linear whole-body volumetransmitter coil combined with an anatomically shaped 4-channelreceive-only coil array for the rat brain. Rats were initiallyanaesthetized with 4% isoflurane (Baxter Deutschland GmbH,Unterschleissheim, Germany) in a mixture of N2 (70%) and O2

(30%). After positioning in the scanner (head first, prone), isofluranewas supplied at �2.5% for adjustments. Then, a 0.5 ml bolus ofmedetomidine solution (Domitors, Janssen-Cilag, Neuss; 0.07 mg/kg) was subcutaneously injected. Isoflurane was slowly discontinuedwithin the next 10 min, after which a continuous infusion ofmedetomidine solution began at a rate of 0.29 mg/kg/h. Thisanesthetic regimen ensured stable physiological conditions for theduration of the experiment (approximately 3 h). Breathing andcardiac rates were monitored using a respiration pad placedbeneath the chest (Small Animal Instruments Inc., NY, USA) and apulse oximeter attached to the hindpaw. Signals were recorded (10-ms resolution) using a signal breakout module (Small AnimalInstruments Inc., NY, USA) and a 4-channel recorder (Vellemans

N.V., Gavere, Belgium).The rsfMRI dataset was acquired approximately 15–20 min after

the start of medetomidine continuous infusion using an echo-planarimaging (EPI) sequence with the following parameters: repetitiontime/echo time (TR/TE) 1700/17.5 ms, flip angle 601, 1 segment, 29coronal slices (ascending slice order), 96� 96 imaging matrix, field ofview 35� 35 mm2, slice thickness 0.5 mm with 0.2 mm inter-slicegap, 300 acquisitions over 8.5 min. The in-plane voxel dimension was0.365 mm, and the slice stack covered the brain from the cerebellum(z�zbregma �13 mm) to the posterior olfactory bulb (z�zbregma

+6 mm).Immediately after the complete acquisition of rsfMRI data we

started rCBV measurements within the same MRI session. For rCBV,two T2-weighted images were acquired in midbrain (fromz�zbregma�6.80 mm till z�zbregma+1.60 mm) using a fast spinecho (FSE) sequence (Moreno et al., 2006) with TR/TEeff 1875/80 ms, rapid acquisition with rapid acquisition with relaxationenhancement (RARE) factor of 16, FOV=30 mm2 (with117� 117 μm2 in-plane resolution), an acquisition matrix of256� 256, 10 slices with a slice thickness of 0.8 mm and a slicedistance of 1 mm. 28 images were averaged with an overallacquisition time of 14 min. The first image was obtained withoutany contrast agent, and the second one was acquired 40 min afterintraperitoneal administration of contrast agent (10 mmol/kg with1 ml saline flush afterwards; Omniscan, GE-Healthcare, Princeton,US) in the steady-state of inflow (Moreno et al., 2006). The contrastagent was administered over 10 min with additional anesthetics of1.0% isoflurane during the application.

Please cite this article as: Gass, N., et al., Functionally altered neuprominent role of the habenula. European Neuropsychopharmacology

2.3. Generation and statistical analysis of rCBV maps

In reconstruction at the MR-system all images related to rCBVmeasurement were set to the same map slope and map offset toavoid bias due to varying image contrast over measurements. Thenthe standardized images were transferred to a workstation and voxeldimension in the image headers were scaled up by a factor of 10 forcompatibility with analysis software designed for human scale images.Spatial pre-processing was done using SPM8 tools (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/). First, the image recorded in thesteady-state of contrast agent for each measurement was spatiallyrealigned to the pre-contrast image. Second, a two-step spatialnormalization was applied to a rat brain group template withco-registered anatomical atlas positioned in the Paxinos stereotaxiccoordinate system. The transformation was done for each image setand consisted of a linear co-registration (6 degree-of-freedomrigid-body transformation) to the template and a non-linear normalization (warping). The voxel-by-voxel transformation matrices werebased on the individual transformation rules used for normalization onthe group template of high-resolution structural data measured foreach animal. These data were acquired using a high-resolutionT2-weighted FSE sequence with TR/TEeff 1200 ms/50 ms, RARE factorof 16, FOV=33.5� 28.8 mm2 (with 150� 150� 300 mm3 voxel size),an acquisition matrix of 225� 196� 96, 1 average, and an overallacquisition time of 23 min. Third, rCBV was calculated voxel-basedusing following equation:

rCBV� � ln ½SIðtÞ=SIpre�=TEwhere SI(t) is the signal intensity in a voxel in the steady state(40 min) after administration of contrast agent; SIpre is the signalintensity of the observed voxel prior to contrast agent injection.Fourth, these obtained rCBV maps were smoothed with a 4 mmisotropic Gaussian filter kernel, and standardized as follows beforestatistical analysis.

For standardization of the rCBV maps the mean CBV of the wholemeasured brain volume was calculated for each individual animal,and the corresponding CBV map was divided by this value for globalstandardization.

Only subjects with an average signal drop (over whole brain)larger than 20% between the images before and after administra-tion of contrast agent were used for statistical analysis; thus rCBVmaps of 8 cLH and 7 cNLH rats were analyzed. The maps wereanalyzed based on mean values of 35 bilateral regions of interest(ROI) (see Table 1 for list of ROIs) from the atlas (Schwarz et al.,2006) testing significance with a two-sample t-test (IBM SPSSStatistics, version 20.0.0). The analysis of the maps (Figures 1 and 2)was voxel-by-voxel based (SPM8) with animal weight as a covariate.

2.4. rsfMRI pre-processing and seed region analysis

Pre-processing was done as described previously (Gass et al., 2013).In brief, the EPI time series images were corrected for magneticfield (B0) inhomogeneities using acquired FieldMap sequences(SPM8). To minimize the effect of movement on the signalintensities, the estimated movement parameter vectors wereregressed out from each voxel (FSL, version 4.1, http://www.fmrib.ox.ac.uk/fsl). Afterwards, respiratory and cardiac signalswere filtered out from each voxel using Aztec software (vanBuuren et al., 2009). A slice-timing correction was then appliedto the images (SPM8). We used this order of preprocessing steps as itminimizes temporal standard deviation (Jones et al., 2008). Thetime courses were then band-pass filtered (0.01–0.1 Hz) usingAnalysis of Functional Neuroimages (AFNI) version 2 (Cox, 1996).Finally, the time series were spatially normalized (SPM8) to a ratbrain template with co-registered anatomical atlas positioned inthe Paxinos stereotaxic coordinate system (Schwarz et al., 2006)using a three-step process: (1) creation of a mean image from all

rocircuits in a rat model of treatment-resistant depression show(2013), http://dx.doi.org/10.1016/j.euroneuro.2013.12.004

Table 1 ROI-based rCBV statistics.

Region of interest T-value p-Value

Amygdala �1.60 0.133*Bed nucleus of stria terminalis 7.82 0.000Caudate-putamen �0.80 0.438Cingulate cortex area 1 �0.45 0.659Cingulate cortex area 2 �0.47 0.644Dorsal raphe nucleus (DRN) 0.66 0.523Dorsopeduncular cortex �1.66 0.120Geniculate nucleus: lateral �2.81 0.015Geniculate nucleus: medial �2.94 0.012Globus pallidus 0.48 0.639Habenula: lateral �2.80 0.015Habenula: medial �1.07 0.303Hippocampus: anterodorsal �0.41 0.688Hippocampus: dentate gyrus �2.45 0.029Hippocampus: posterodorsal �2.04 0.062Hippocampus: posteroventral �1.50 0.158*Hippocampus: parasubiculum �4.21 0.001Hippocampus: presubiculum �2.72 0.018Hippocampus: subiculum �2.56 0.024Hippocampus: ventral (CA3) �0.72 0.485Infralimbic cortex 1.41 0.181Nucleus accumbens �0.36 0.726Orbitofrontal cortex �1.06 0.308Parietal association cortex �2.25 0.042Periaqueductal gray �1.72 0.109Prelimbic cortex 1.21 0.248Retrosplenial cortex �2.18 0.048Septum �0.91 0.378Substantia nigra �1.74 0.105Thalamus: dorsolateral �2.00 0.067Thalamus: midline dorsal �2.95 0.011Thalamus: ventromedial �2.30 0.039Ventral pallidum �0.19 0.849Ventral tegmental area �1.12 0.282Zona incerta 0.61 0.551

T-values (and corresponding p-values) of rCBV (per ROI)differences between cLH (N=8) and cNLH (N=7) animals.Negative T-values represent a mean rCBVcLH4rCBVcNLH.Significant results are marked in bold, results additionallysurviving a Bonferroni correction are marked by *.

N. Gass et al.4

time series which was then normalized to the template, (2) normalization of all images to the mean image from step 1, and (3) normalization of all images from step 2 to the template image.

We selected 27 seed regions related to depression in humans.They included similar ROIs as rCBV analysis; due to the lowerresolution of EPI hippocampal ROIs were merged and included fourparts: anterodorsal, posterodorsal, ventral (CA3, ventral subiculumand posteroventral hippocampus) and dentate gyrus/subiculum(dentate gyrus, para-, post- and presubiculum, subiculum transitionarea). The rest of ROIs included amygdala, basal ganglia (caudate-putamen, substantia nigra, globus pallidus, and ventral pallidum),bed nucleus of stria terminalis (BNST), cingulate cortex (areas 1and 2), dorsal raphe nucleus (DRN), habenula, nucleus accumbens,parietal association cortex, periaqueductal gray, prefrontal corticalseeds (infralimbic, prelimbic, orbitofrontal and dorsal peduncularcortices), retrosplenial cortex, thalamus (dorsolateral, midline

Please cite this article as: Gass, N., et al., Functionally altered neuprominent role of the habenula. European Neuropsychopharmacology

dorsal and ventromedial seeds), ventral tegmental area and zonaincerta.

Masks of seed regions were corresponded to established atlasstructures (Paxinos and Watson, 2007) using a template atlas image(Schwarz et al., 2006), except the BNST which was represented bythe cluster identical to the one showing rCBV increase in cLH rats.Habenular seed was tested both as a mask corresponding to theatlas structure and as an rCBV cluster similar to the BNST. A meantime course was extracted from each normalized, unsmoothed timeseries. Afterwards, the image data were smoothed by 0.8 mm(Gaussian filter, approximately 2 voxels in-plane). In the 1st levelanalysis the seed time course was used as a regressor for each timeseries, and then contrasts created from the 1st level analysis werefed in the 2nd level analysis to detect differences between cLH andcNLH rats using a two-sample t-test. The obtained statistic imageswere cluster-corrected in FSL (T=2.528 equal to po0.01 at 20degrees of freedom and one-tailed t-test for each contrast).

3. Results

3.1. rCBV

Voxel-by-voxel based statistics revealed two bilateral andhighly focal differences in rCBV. cLH rats had a significantlylower rCBV in the LHb, mainly in the lateral part (Figure 1)and higher rCBV in the BNST, the medial division, andanterior part (Figure 2).

Similar to voxel-wise analysis, ROI-based statistics (Table 1)identified decreased rCBV in the LHb (p=0.015) and increasedin the BNST (po0.000). In addition a significantly lower rCBVwas observed in cLH group in the hippocampal parts, namely inthe dentate gyrus (p=0.029), parasubiculum (p=0.001), pre-subiculum (p=0.018), and subiculum (p=0.024). Parts of thethalamus and geniculate nuclei showed lower rCBV in cLH rats(p(ventromedial thalamus)=0.039, p(midline dorsal thalamus)=0.011, p(lateral geniculate nucleus)=0.015, and p(medialgeniculate nucleus)=0.012).

3.2. rsfMRI seed region analysis

Altogether 10 out of 27 seeds revealed altered functionalconnectivity in cLH rats (Table 2; Figure 3). There werepredominantly increased correlations in the cLH group, withthe exception of connectivity for cingulate cortex area 1.

The strongest finding was an increased correlationbetween the DRN and forebrain regions including thesomatosensory cortex, orbital cortex, frontal cortex andcaudate-putamen, suggesting a general increase in func-tional connectivity within the serotonergic system. Out ofthe thalamic seeds tested, only the ventromedial thalamushad altered connectivity – a higher coupling with thesomatosensory cortex. Within the hippocampus, its ventralpart displayed higher correlation with the retrosplenialcortex and caudate-putamen. The retrosplenial cortex alsohad enhanced correlation with the cingulate cortex area 1.Two basal ganglia seeds demonstrated higher correlations incLH group: globus pallidus – with somatosensory cortex, andventral pallidum – with somatosensory and motor corticesand lateral septal nucleus.

The only negative correlations were observed for thecingulate cortex area 1, revealing reduced connectivity

rocircuits in a rat model of treatment-resistant depression show(2013), http://dx.doi.org/10.1016/j.euroneuro.2013.12.004

Figure 1 rCBV maps for habenula. Left: T-values for cLH (N=8)4cNLH (N=7); right: T-values for cLHocNLH; all at bregma�3.3 mm. Results of the T-statistics are color-coded without cut-off.

Figure 2 rCBV maps for bed nucleus of stria terminalis. Left: T-values for cLH (N=8)4cNLH (N=7); right: T-values for cLHocNLH;all at bregma 0.2 mm. Results of the T-statistics are color-coded as in Figure 1.

5Functionally altered neurocircuits in a rat model of treatment-resistant depression show prominent role of the habenula

with visceral sensation related structures such as motortrigeminal pterygoid and supratrigeminal nucleus.

As the BNST demonstrated a higher rCBV in cLH rats, wealso used the bilateral cluster from the voxel-wise analysis asan additional seed and found an enhanced functional cou-pling with insular and lateral orbital cortices in cLH rats. Nosignificant difference between the groups was observed forthe habenular seed.

4. Discussion

We identified altered resting brain function and neuronalnetwork connectivity in an animal model of TRD, usingmultimodal imaging to quantify changes in rCBV and func-tional connectivity in cLH rats.

High-resolution parametric mapping revealed severaldistinct, focal and bilateral regions of altered resting brainfunction in cLH rats. The lateral part of the LHb exhibitedfocally decreased rCBV in cLH vs. cNLH animals. This findingis in contrast to earlier observations in the same genetic line(cLH) demonstrating an increased excitatory synaptic trans-mission onto ventral tegmental area (VTA)-projecting LHbneurons (Li et al., 2011) and an elevated metabolism in theLHb as quantified via cytochrome oxidase histochemistry(Shumake et al., 2003). Also an antidepressant response toketamine is associated with the reduction of glucosemetabolism in the habenula of TRD patients (Carlson

Please cite this article as: Gass, N., et al., Functionally altered neuprominent role of the habenula. European Neuropsychopharmacology

et al., 2013). However the LHb is a highly heterogenousstructure and only the minority of its neurons project to theVTA; moreover, these VTA-projecting glutamatergic neuronsare not present in the lateral part where we observeddecreased rCBV (Li et al., 2011). Also, the excitatoryneurons are assumed to show less cytochrome oxidaseactivity as they are phasically (and not tonically) active(Wong-Riley, 1989). The whole LHb was explored for thecytochrome oxidase activity in the study by Shumake et al.(2003), hence the possible difference due to the localheterogeneity could have been missed. Here, we thereforesuggest that one of the possible reasons for the differencecould lay in LHb heterogeneity and an ability of rCBV in thecurrent study to examine and pick up smaller regions due toits high spatial resolution.

Other brain regions, including the subiculum, geniculatenuclei and midline dorsal thalamic region also exhibitedreduced rCBV in cLH rats. In contrast, strong focal andbilateral increases in rCBV were observed in the BNST. Thestria terminalis to which the BNST belongs, is an interconnec-tion between amygdala and thalamus and, via an additionalbundle (stria medullaris), to the habenula (Frick et al., 1992).Therefore our rCBV findings corroborate the idea that habe-nular neurocircuitry is dysfunctionally involved in our animalmodel of TRD.

While rCBV was generally lower in cLH rats, functionalconnectivity was mostly enhanced. The BNST demonstratedan increased functional coupling with several regions, such

rocircuits in a rat model of treatment-resistant depression show(2013), http://dx.doi.org/10.1016/j.euroneuro.2013.12.004

Table 2 Loci of peak voxels and cluster center of gravity for significant clusters obtained from seed-connectivity analysis.

Seed region Cluster Number ofvoxels incluster

p � log10(p) Tmax Peak voxel of cluster Cluster center of gravity Anatomical localization

X (M-L)(mm)

Y (D-V)(mm)

Z (A-P)(mm)

X (M-L)(mm)

Y (D-V)(mm)

Z (A-P)(mm)

Peakvoxel

Cluster center ofgravity

DRNcLH4cNLH

4 291 1.01E�06 5.99 5.31 4.62 �2.49 1.90 4.82 �2.72 2.10 S1FL/S1DZ

S1J

3 99 0.0075 2.12 4.57 �2.31 �5.78 3.00 �2.73 �5.15 2.60 LO/VO LO/CPu2 98 0.0080 2.10 4.6 �5.23 �2.86 �0.65 �5.65 �3.23 �0.02 S1BF S1Ulp1 74 0.0332 1.48 4.27 �4.87 �2.13 2.27 �4.01 �1.59 2.86 S1FL Fr3/S1J

HcVcLH4cNLH

2 222 4.21E�05 4.38 4.35 �1.22 �1.76 �6.49 �0.62 �1.67 �6.75 RSG RSG1 79 0.0355 1.45 5.02 4.99 �6.51 �0.65 5.21 �6.71 �1.15 CPu CPu

VMTcLH4cNLH

1 84 0.0080 2.1 5.32 �5.60 �2.13 �1.02 �6.04 �3.49 �0.45 S1BF S1Ulp

Cg2cLH4cNLH

1 69 0.0168 1.78 5.08 �1.58 �0.67 4.09 �2.13 �0.63 4.42 M2 M2

VPcLH4cNLH

1 66 0.0200 1.70 4.80 �1.22 �3.95 �0.29 �1.76 �3.09 0.35 LS S1/M1

GPcLH4cNLH

1 67 0.0207 1.68 5.28 �5.60 �5.05 �0.29 �5.75 �4.65 �0.15 S2 S1Ulp

BNSTcLH4cNLH

1 66 0.0227 1.64 4.72 �3.77 �6.51 2.63 �2.70 �6.07 2.44 AIV LO

HcADcLH4cNLH

1 71 0.0256 1.59 4.13 �2.68 �5.05 �8.32 �2.52 �4.85 �7.89 ECIC CIC

RScLH4cNLH

1 73 0.0342 1.47 3.8 0.24 �1.76 3.36 0.01 �1.45 3.63 Cg1 Cg1

Cg1cLHocNLH

1 68 0.0428 1.37 5.14 �1.95 �8.33 �9.41 �2.21 �7.35 �9.30 5Pt Su5

Coordinates are given in the stereotaxic space of Paxinos and Watson (2007). [M-L, mediolateral; D-V, dorsoventral; A-P, anteroposterior; 5Pt, motor trigeminal, pterygoid; AIV, agranularinsular cortex, ventral part; BNST, bed nucleus of stria terminalis; Cg1, cingulate cortex, area 1; Cg2, cingulate cortex, area 2; CIC, central nucleus of inferior colliculus; CPu, caudate-putamen; DRN, dorsal raphe nucleus; ECIC, external cortex of inferior colliculus; Fr3, frontal cortex, area 3; GP, globus pallidus; HcAD, anterodorsal hippocampus; HcV, ventralhippocampus; LO, lateral orbital cortex; LS, lateral septal nucleus; M1, primary motor cortex; M2, secondary motor cortex; RS, retrosplenial cortex; RSG, retrosplenial granular cortex;S1, primary somatosensory cortex; S1BF, primary somatosensory cortex, barrel field; S1DZ, primary somatosensory cortex, dysgranular zone; S1FL, primary somatosensory cortex,forelimb region; S1J, primary somatosensory cortex, jaw region; S1Ulp, primary somatosensory cortex, upper lip region; Su5, supratrigeminal nucleus; VO, ventral orbital cortex; VMT,ventromedial thalamus; VP, ventral pallidum.]

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acology(2013),

http://dx.doi.org/10.1016/j.euroneuro.2013.12.004

Figure 3 Maps of resting-state functional connectivity for seed regions (a–j). Slice coverage in zbregma: (a) �0.8 to 3.6 mm; (b)�8.8 to �1.2 mm; (c) 2.8 to 4.0 mm; (d) �9.2 to �6.4 mm; (e) �9.2 to �8.0 mm; (f) 3.6 to 4.8 mm; (g) �0.4 to 0.8 mm; (h)�0.8 to 0.4 mm; (i) 2.0 to 3.2 mm; (j) �2.0 to �0.8 mm. Maps were thresholded at T=2.528, p=0.01. [Abbreviations: BNST – bednucleus of stria terminalis; Cg1 – cingulate cortex, area 1; Cg2 – cingulate cortex, area 2; DRN – dorsal raphe nucleus; GP – globuspallidus; HcAD – anterodorsal hippocampus; HcV – ventral hippocampus; RS – retrosplenial cortex, VMT – ventromedial thalamus,VP – ventral pallidum.]

7Functionally altered neurocircuits in a rat model of treatment-resistant depression show prominent role of the habenula

as prelimbic, lateral orbital and insular cortices, caudate-putamen, entorhinal and motor cortices in cLH rats. Inter-estingly, BNST lesions prevent the LH effect, i.e. it blocksfreezing potentiation after inescapable shock (Hammacket al., 2004). The functional alterations of the BNSTobserved in our study may therefore mediate learning asso-ciated with stress in cLH rats, a notion that is also supportedby data showing BNST critical involvement in associativelearning after stressful experience (Bangasser et al., 2005)and response to sustained threat (Walker et al., 2003). On theother hand, it may also reflect vulnerability to depressivebehavior after chronic stress.

The most widespread alterations in functional connectiv-ity were observed in relation to the DRN, demonstrating anincreased correlation with forebrain regions including theorbital and frontal cortices, caudate-putamen and somato-sensory cortex in cLH rats. No effect was detected for DRNin rCBV analysis; however the brain coverage of acquiredrCBV images did not include the whole DRN structure, hencethe effect could have been missed. The DRN is the majorsource of serotonin and serotonergic projections in the brainand has been implicated in the pathophysiology of depres-sion for several decades. Interestingly, the increased frontal

Please cite this article as: Gass, N., et al., Functionally altered neuprominent role of the habenula. European Neuropsychopharmacology

connectivity with the DRN in the TRD model was primarilylateral rather than medial and involved orbitofrontal andsensorimotor regions rather than the medial prefrontalcortex (mPFC). Whereas a recent report (Warden et al.,2012) demonstrated that optogenetic stimulation of mPFCneurons projecting to the DRN cause an increased mobility(hence, a presumed antidepressant effect) in the rat forcedswim test, this may reflect different functional roles oforbital versus medial prefrontal brain regions in depression.Orbitofrontal cortex is involved in reward processing withits lateral part being punishment-sensitive (Kim, 2013).

Furthermore, cLH rats had increased correlation betweenthe ventral hippocampus and the retrosplenial cortex. It isremarkable that out of all the hippocampal subdivisions, theventral part was the most affected, especially in the light ofrecent studies demonstrating that it may encode more foremotional and reward relevant contents compared withspatially relevant information coded in the dorsal part(Royer et al., 2010; Sotres-Bayon et al., 2012). Increasedhippocampal–retrosplenial coupling parallels findings inhumans showing a positive correlation of depression severitywith increased functional connectivity between hippocam-pus and posterior cingulate cortex (Goveas et al., 2011).

rocircuits in a rat model of treatment-resistant depression show(2013), http://dx.doi.org/10.1016/j.euroneuro.2013.12.004

N. Gass et al.8

The retrosplenial cortex also had an increased correlationwith the cingulate cortex, a finding that mirrors thereported increased functional connectivity within theprecuneus-anterior cingulate cortex default mode circuitin TRD patients (Lui et al., 2011).

Regions processing sensory information were also affected.The only negative finding in connectivity was observed forthe coupling between cingulate cortex area 1 and motortrigeminal pterygoid/supratrigeminal nucleus, both of whichmediate visceral sensation. Also the somatosensory cortexwas part of several clusters (DRN, ventromedial thalamus,ventral pallidum and globus pallidus) with altered functionalconnectivity. In rCBV there was a reduced signal in lateraland medial geniculate nuclei in cLH rats indicating a possiblecompromised relay of visual and auditory information.

Besides a direct involvement of habenular neurocircuitryour results implement a genetic effect on the serotonergicand the reward pathways in the TRD model. However, theLHb and the amygdala were not directly associated withfunctional connectivity changes themselves. This may reflectthe fact that the LHb, or even the lateral subregion of theLHb identified by the high-resolution rCBV mapping is too tinyto be meaningful implemented as a seed region (due to smalloverlap caused by interindividual image averaging). A similareffect may be relevant for the amygdala, since its smallconstituent nuclei have specific and certainly highly differ-ential functional roles. Additionally, basal parts of theamygdala are highly sensitive to susceptibility artefacts infunctional imaging.

Most of our results analogous to TRD findings lie in thedomain of functional connectivity changes (habenular, DRNand hippocampal/default mode neurocircuitry) which sup-port the neurophysiological validity of the cLH model andthe presence of circuit-level vulnerability markers fromfunctional imaging as a translational technology for testingetiopathology of depression and profiling potential newtreatments. Therefore, our results corroborate the evi-dence for a “resting state hypothesis” of depression(Northoff et al., 2011). The targets of deep brain stimula-tion studies in TRD patients include subgenual anteriorcingulate cortex, lateral habenula, medial forebrain bun-dle, anterior limb of internal capsule and nucleus accum-bens (Hoflich et al., 2013; Schlaepfer et al., 2013; Sartoriuset al., 2013), and further studies applying deep brainstimulation in cLH rats at these sites would add more tothe knowledge of mechanisms of its antidepressant effectsby combining it with “imaging” approaches (like e.g. rCBV,rsfMRI, electroencephalography, functional immediate earlygene mapping) (Kiening and Sartorius, 2013).

Role of funding source

The research leading to these results has received support (to AS)from the Federal Ministry of Education and Research (BMBF01EW1110) in the framework of the European Research Area Net-work (ERA-NET NEURON) program. This research was also supportedby the Innovative Medicine Initiative Joint Undertaking under Grantagreement no. 115008 of which resources are composed of EFPIA in-kind contribution and financial contribution from the EuropeanUnion's Seventh Framework Program (FP7/2007–2013).

Please cite this article as: Gass, N., et al., Functionally altered neuprominent role of the habenula. European Neuropsychopharmacology

Contributors

NG, AS, WWF, DC, AJS, BV designed the study and wrote theprotocol. Authors NG, WWF and AS managed the literature searchesand analyses. Authors WWF, NG, DC, AJS and LZ undertook thestatistical analysis, and author AS wrote the first draft of themanuscript. All authors contributed to and have approved the finalmanuscript.

Conflict of interest

AJS is an employee and shareholder of Eli Lilly and Company. Allother authors declare that they have no conflicts of interest.

Acknowledgments

We thank Felix Hörner and Claudia Falfan-Melgoza for theirexcellent technical assistance.

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