Background: Dysfunctional reward processing is associated with a number of psychiatric disorders, such as addiction and schizophrenia. It is thought that reward is regulated mainly by dopamine transmission in the ventral striatum. Contemporary animal models suggest that striatal dopamine concentrations and associated behaviors are related to glutamatergic functioning in the ventral hippocampus. However, in humans the association between reward-related ventral striatal response and hippocampal glutamate levels is unclear. Methods: Nineteen healthy participants were studied using proton magnetic resonance spectroscopy to measure hippocampal glutamate levels, and functional magnetic resonance imaging to assess striatal activation and functional connectivity during performance of a monetary incentive delay task. Results: We found that ventral striatal activation related to reward processing was correlated with hippocampal glutamate levels. In addition, context-dependent functional coupling was demonstrated between the ventral striatum and both the lingual gyrus and hippocampus during reward anticipation. Elevated hippocampal glutamate levels were inversely related to context-dependent functional connectivity between the ventral striatum and the anterior hippocampus while anticipating reward. Conclusions: These findings indicate that human striatal responses to reward are influenced by hippocampal glutamate levels. This may be relevant for psychiatric disorders associated with abnormal reward processing such as addiction and schizophrenia. Keywords: reward, striatum, hippocampus, glutamate, neuroimaging Introduction Rewards are a key determinant of whether we eat, drink, or of psychiatric disorders, such as schizophrenia and addiction mate (Schultz, 2015). Reward in this context refers to the attract- (Berridge, 2012; Berridge and Kringelbach, 2015; Radua et al., ive and motivational property of a stimulus that induces goal- 2015; Luijten et al., 2017), wherein it is thought that inappro- directed behavior (Berridge and Kringelbach, 2015 Sc ; hultz, 2015). priate attribution of incentive salience to otherwise relatively Dysfunctional reward processing is associated with a number neutral environmental cues result in the formation of psychotic Received: October 13, 2017; Revised: January 25, 2018; Accepted: February 9, 2018 © The Author(s) 2018. Published by Oxford University Press on behalf of CINP. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is 1 properly cited. Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy011/4850502 by Ed 'DeepDyve' Gillespie user on 08 June 2018 2 | International Journal of Neuropsychopharmacology, 2018 Significance Statement Rewards are a key determinant of whether we eat, drink, or mate. Dysfunctional reward processing is associated with a num- ber of psychiatric disorders, such as schizophrenia and addiction. It is thought that reward processing is regulated mainly by dopamine transmission in the ventral striatum. Animal models suggest that striatal dopamine concentrations and associated behaviors are related to glutamatergic functioning in the ventral hippocampus. Here, we investigated the relationship between hippocampal glutamate levels and the ventral striatal response to reward anticipation in humans. We found that higher hip- pocampal glutamate levels are correlated with reward-related ventral striatal activity, but inversely correlated with functional connectivity between anterior hippocampus and ventral striatum during reward anticipation. This suggests that human striatal responses to reward anticipation are influenced by hippocampal glutamate levels. This may be relevant for psychiatric disorders associated with abnormal reward processing such as addiction and schizophrenia. symptoms (Heinz, 2002; Kapur, 2003) or the development of correlation (although they did report a correlation in individu- addictive behavior (Flagel et al., 2009; Berridge, 2012). als at high risk for psychosis). A study bAllen y et al. (2012) in 14 Reward processing is primarily regulated by the mesolimbic healthy participants found that greater activation in the hippo- dopamine system, which, in animals, originates in the ventral campus during performance of a verbal memory task was asso- tegmental area (VTA) and projects to the nucleus accumbens ciated with diminished striatal dopamine synthesis capacity. (Berridge, 2012; Berridge and Kringelbach, 2015; Schultz, 2015). Finally,Roiser and collea gues (2013) described a positive correl- Numerous animal studies have shown increased midbrain ation between hippocampal responses to irrelevant stimulus dopaminergic activity and elevated dopamine levels in the features and striatal dopamine synthesis capacity in 18 healthy nucleus accumbens in relation to reward anticipation (Schultz subjects. However, the relationship between hippocampal glu- et al.,1997; Roitman et al., 2004; Schultz, 2015). In human neuro- tamate levels and ventral striatal activity in the context of imaging research, reward processing has frequently been inves- reward processing is unclear. tigated during performance of a monetary incentive delay (MID) The aim of the present study was to examine the relation- task that involves reward anticipation and receipt (Knutson ship between hippocampal glutamate levels and the ventral et al., 2001; Bjork et al., 2004; van Hell et al., 2012J; ansma et al., striatal response to reward anticipation in humans. Nineteen 2013; Radua et al., 2015; Luijten et al., 2017). Results of studies healthy participants were studied using H-MRS to measure using this task in healthy individuals have identified the ven- hippocampal glutamate levels, and functional MRI to assess tral striatum, a brain structure predominantly comprising the striatal activation and functional connectivity during per - nucleus accumbens, being critically involved in reward process- formance of the MID task. Following contemporary animal ing (Knutson et al, 2001; Bjork et al., 2004; Knutson and Cooper, models (Lodge and Grace, 2011; Grace, 2016), we hypothesized 2005). Furthermore, increased ventral striatal activity during that increased hippocampal glutamate levels would be asso- reward processing has been shown to be related to dopamine ciated with higher activation in the ventral striatum during release in this brain region (Knutson and Gibbs, 2007Sc ; hott the anticipation of monetary reward. Because these preclin- et al., 2008). ical models describe reduced inhibitory control of glutamater - Preclinical models suggest that striatal dopamine levels and gic pyramidal neurons leading to higher striatal dopamine associated behaviors are related to the functioning of the ventral concentrations, a further prediction was that increased hip- hippocampus (Lodge and Grace, 2011; Grace, 2016). For example, pocampal glutamate levels would also be related to reduced stimulation of the ventral hippocampus produces robust and reward-related functional coupling between the hippocampus sustained increases in extracellular dopamine concentrations and ventral striatum. in the nucleus accumbens (Blaha et al., 1997 Le ; gault and Wise, 1999). In addition, experimental activation of glutamatergic Methods N-methyl-D-aspartate receptors in the ventral hippocampus dramatically increases dopamine neuron activity in the VTA Participants in a dose-dependent manner (Floresco et al., 20012003 , ; Lodge and Grace, 2006). This activation of the hippocampal glutamate Nineteen healthy volunteers participated in the study. They system is directly correlated with both dopamine release in the were recruited through advertisements on websites. The mean nucleus accumbens (Floresco et al., 2003) and the behavioral age of the subjects was 25.8 ± 5.6 years (range 20–38), and 10 were response to amphetamine (White et al., 2006Lodg ; e and Grace, male and 9 were female. Their self-reported ethnicity was white 2008). This cascade of activated glutamatergic pyramidal neu- British (n = 7), black (n = 2), Asian (n = 6), and mixed (n = 4). Mean rons driving increased striatal dopamine levels is thought to be total years of education was 15.1 ± 3.0. All participants were controlled by parvalbumin-expressing GABAergic interneurons right-handed and had no history of neurological or psychiatric in the ventral hippocampus, with reduced inhibitory control disorder, or drug or alcohol dependence. The study had National of glutamatergic pyramidal neurons leading to higher striatal Health Service UK Research Ethics Committee approval, and all dopamine concentrations (Lodge and Grace, 2011; Grace, 2016). participants gave informed consent. Only a limited number of human neuroimaging studies have examined interactions between hippocampal and stri- Reward Paradigm atal function in healthy participants. Stone and colleagues (2010) examined hippocampal glutamate levels measured with To activate reward circuitry, an adapted version of the MID task Proton Magnetic Resonance Spectroscopy H-MRS) ( and striatal as developed by Knutson and colleagues was used (Knutson dopamine synthesis capacity measured with Positron Emission et al., 2001). In this task, subjects are required to press a button Tomography in 12 healthy subjects but did not find a significant as fast as possible on seeing a target stimulus. Depending on the Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy011/4850502 by Ed 'DeepDyve' Gillespie user on 08 June 2018 Bossong et al. | 3 cue that precedes the target stimulus, subjects can either win H-MRS or avoid the loss of a certain amount of money. After each trial, H-MRS spectra (PRESS—Point RESolved Spectroscopy; subjects are given visual feedback about the amount won or lost TE = 30 ms; TR = 3000 ms; 96 averages) were acquired in the left in that trial, as well as the total amount won (Figure 1). The MID hippocampus, as previously described by Stone et al. (2009). We task consisted of 4 conditions: neutral, small reward (20 pence), employed the standard GE probe (proton brain examination) large reward (2 pounds), and loss avoidance (2 pounds). There sequence, which uses a standardized chemically selective sup- were 12 trials for each condition. The neutral condition was used pression water suppression routine. For each metabolite spec- as the control condition. Total task duration was 16 min, which trum, unsuppressed water reference spectra (16 averages) were was scanned in 2 consecutive 8-min runs. Monetary reward also acquired as part of the standard acquisition. Shimming earned by subjects was related to actual task performance, and water suppression were optimized, with auto-prescan per - starting with 10 pounds. formed twice before each scan. Using standardized protocols, The reward cue was presented for 250 ms, while the feed- the hippocampal region of interest (ROI) (20 x 20 x 15 mm; right- back was presented for 1450 ms. A correct response was left, anterior-posterior, superior-inferior) was prescribed from defined as a response before the target disappeared, but not the structural T1 scan. earlier than 100 ms after its appearance. All other responses were considered incorrect. Initial target presentation time was Data Analysis 250 ms, but this was individually adapted (±10 ms, with a mini- Task Performance mum of 150 ms and a maximum of 300 ms) to ensure approxi- Performance accuracy (mean percentage of correct responses) mately 66% accuracy for each subject. Intervals between the and reaction time were examined using a repeated-measures cue and target (the anticipation phase) varied between 3700 ANOVA with task condition (4 levels: neutral, small reward, large and 4500 ms. The inter-trial interval was 10 s for all trials (see reward, and loss avoidance) as within-subject factor. Posthoc Figure 1). analysis was performed with paired sample t tests. Image Acquisition Reward Processing All subjects underwent structural MRI, functional MRI, and Functional MRI data were preprocessed and analyzed using H-MRS scanning in one session. Images were acquired on a SPM8 (Wellcome Trust Centre for Neuroimaging). Preprocessing General Electric 3.0 Tesla HDx MR system. included realignment of functional images, co-registration with the anatomical scan, spatial normalization into standard MNI Structural MRI space, and smoothing with a Gaussian filter (FWHM= 8 mm). Structural images were acquired using a whole-brain 3-dimen- For each subject, regression coefficients for each voxel were sional sagittal T1-weighted scan, with parameters based on obtained from a general linear model regression analysis with the Alzheimer’s Disease Neuroimaging Initiative (TE = 2.85 ms; factors time-locked to task events, convolved with a canonical TR = 6.98 ms; inversion time = 400 ms; flip angle = 11º; voxel size hemodynamic response function. The design included a total 1.0x1.0x1.2 mm; for full details, see http://adni.loni.usc.edu/ of 13 regressors. Four regressors modelled anticipation activ- methods/mri-analysis/mri-acquisition/). ity for each of the 4 conditions. Eight regressors modelled the feedback activity, 1 for correct and 1 for incorrect responses for Functional MRI each of the 4 conditions. Finally, 1 regressor modelled response A total 480 T2*-weighted images were acquired in 2 runs of activity for all the 4 conditions. Group activity maps for reward 8 min each with TE= 30 ms, TR = 2.0 s, and flip angle = 75° in 39 anticipation were created, contrasting activation during reward- axial planes (3 mm thick with an inter-slice gap of 3.3 mm), with ing task conditions (both small and large reward) to that during an in-plane voxel size of 3.75 x 3.75 mm. control conditions (neutral). We focus on reward anticipation Figure 1. Reward paradigm. Each trial started with the presentation of a cue signalling a neutral, reward (small or large) or loss avoidance trial. After the cue, a target was presented to which subjects had to respond as fast as possible by pressing a button. At the end of each trial, visual feedback on performance was provided. The time between cue and target (anticipation phase) was varied between trials (3700–4500 ms). The inter-trial interval was 10 s for all trials. Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy011/4850502 by Ed 'DeepDyve' Gillespie user on 08 June 2018 4 | International Journal of Neuropsychopharmacology, 2018 because this is shown to depend on striatal dopamine function Values of the combined water-scaled measure of glutamate and (Knutson and Gibbs, 2007; Schott et al., 2008). Brain activation glutamine (Glx) were corrected for CSF content of the ROI using was examined in the bilateral striatum using a mask consisting the formula Mcorr = M*(WM + GM + 1.55 CSF)/(WM + GM), where of caudate, pallidum, and putamen, as defined in the AAL atlas M is the uncorrected metabolite value, and WM, GM, and CSF provided in SPM8. Results were FWE-corrected for the number of are the white matter, grey matter, and CSF fractions of the ROI, voxels in the bilateral striatum (P < .05). respectively (Egerton et al., 2014). These fractions were deter - mined for each subject from the structural T1 scans, which were Functional Connectivity used to localize the spectroscopy ROIs and subsequently seg- Functional connectivity analyses were performed using psycho- mented into GM, WM, and CSF using SPM8. The composite Glx physiological interaction (PPI) analysis approach (Friston et al., peak has been widely used as a marker of glutamatergic func- 1997) to examine the functional coupling during rewarding task tion, because it likely predominantly reflects glutamate levels, conditions (both small and large reward) vs control conditions which are typically 5 to 6 times higher than those of glutamine (neutral) (i.e., psychological factor). The cluster in the left ventral (Kaiser et al., 2005). striatum that was significantly activated during reward antici- pation (Figure 2) was used as the seed region. The left ventral Correlations striatum was selected as seed region, because H-MRS spectra For every subject, ventral striatal activity during reward antici- were acquired in the left hippocampus, and the anatomical pro- pation was determined by extracting regression coefficients jection from primate hippocampus to ventral striatum is pre- (b values) from the significantly activated cluster in the left dominantly ipsilateral (Friedman et al., 2002). For each subject, ventral striatum (Figure 2). Subsequently, for every subject, the first eigenvariate of the blood oxygen level-dependent sig- functional connectivity between hippocampus and ventral stri- nal within the seed region was determined, and the interaction atum during reward anticipation was assessed by extracting between activity within the seed region and the psychological connectivity coefficients resulting from the PPI analysis from factor (i.e. PPI regressor) was calculated. Individual contrast the left anterior hippocampus, as defined in the AAL atlas. We images were then created showing voxel-wise correlations with focus on the anterior hippocampus, because in humans this ventral striatal activity during reward processing. Subsequently, brain area is functionally equivalent to the ventral hippocam- these individual maps of the PPI analyses were entered into a pus described in relevant preclinical models (Grace, 2012 2017 , ). group analysis to examine functional connectivity with the left Extraction of data was performed using the Marsbar SPM tool ventral striatum during reward anticipation. Whole-brain voxel- (Brett et al., 2002). Hypotheses on the correlations between hip- wise analyses were performed, and results were FWE corrected pocampal glutamate levels and (1) activity in the left ventral at cluster level (P < .05). striatum, and (2) connectivity between left ventral striatum and left anterior hippocampus were tested using Pearson’s cor - H-MRS Quantification relation (1-sided). All spectra were analyzed with LCModel version 6.3-0A (Provencher, 1993) using a standard basis set of 16 metabolites Results (L-alanine, aspartate, creatine, phosphocreatine, GABA, glucose, glutamine, glutamate, glycerophosphocholine, glycine, myo-ino- Task Performance sitol, L-lactate, N-acetylaspartate, N-acetylaspartylglutamate, phosphocholine, and taurine), acquired with the same field Task condition had a significant effect on accuracy and reaction time (F(3,54) = 13.18, P < .001 and F(3,54) = 16.67, P < .001, respect- strength (3 Tesla), localization sequence (PRESS), and echo time (30 ms). Model metabolites and concentrations used in the ively). Accuracy on the neutral task condition (54.4 ± 10.4%) w as significantly lower than that on loss avoidance (69.8 ± 8.6%), small basis set are fully detailed in the LCModel manual (http://s- provencher-.com/pages/lcmmanual.shtml). Poorly fitted metab- reward (63.4± 8.9%), and large reward conditions (70.8 ± 11.8%) (all P < .005). Reaction times were significantly higher for neutral olite peaks (Cramer-Rao minimum variance bounds of >20% as reported by LCModel) were excluded from further analysis. trials (255± 28 ms) compared with loss avoidance (232 ± 26 ms), Figure 2. Group activity map for anticipation vs control shows significant activation in bilateral ventral striatum (n = 19; P < .05, FWE-corrected for number of voxels in bilateral striatum). Numbers below slices indicate Montreal Neurological Institute xyz coordinates. L, left; R, right. Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy011/4850502 by Ed 'DeepDyve' Gillespie user on 08 June 2018 Bossong et al. | 5 small reward (239 ± 27 ms), and large reward trials (231 ± 33 ms) Discussion (all P < .001). Accuracy and reaction times for small reward condi- This is the first human neuroimaging study examining the tions were significantly different from those for loss avoidance relationship between hippocampal glutamate concentrations and large reward conditions (all P < .05). There were no signifi- and ventral striatal reward processing. Our main findings were cant differences in task performance between loss avoidance that hippocampal glutamate levels were correlated with reward and large reward trials. anticipation-related ventral striatal activity, but inversely corre- lated with context-dependent functional connectivity between Ventral Striatal Activity During Reward Anticipation the anterior hippocampus and the ventral striatum during the anticipation of monetary reward. These findings suggest that The group map for anticipation vs control showed significant in the context of anticipating a reward, the higher the level of activity in the bilateral ventral striatum (P < .05, FWE-corrected glutamate in the hippocampus, the greater the ventral striatal for number of voxels in bilateral striatum; Figure 2). response to rewarding stimuli. Concomitantly, the higher the level of glutamate in the hippocampus, the lower the functional PPI With Left Ventral Striatum as Seed Region coupling between hippocampus and ventral striatum while anticipating monetary reward. This suggests an inverse rela- Context-dependent functional activity in the left ventral stri- tionship between hippocampal glutamate levels and its con- atum (reward anticipation > contr ol) was significantly corre- trol over ventral striatal function in the context of processing lated with that in the left lingual gyrus and left hippocampus rewarding stimuli, possibly indicating that increased hippocam- (P < .001, FWE-corrected at cluster level; Figure 3), suggesting pal glutamate levels are associated with reduced hippocampal context-dependent functional coupling between the left ventral control of striatal response to reward. Overall, the findings from striatum and these regions. the present study provide the first evidence that human striatal responses to reward anticipation are influenced by hippocam- Hippocampal Glutamate Measures pal glutamate levels. This may be highly relevant for psychiatric In this group of healthy controls, the mean combined meas- disorders associated with abnormal reward processing such as ure of glutamate and glutamine (Glx) in the left hippocampus addiction and schizophrenia. was 9.95 ± 1.96. The hippocampal spectroscopic voxel consisted Our results are consistent with accumulating evidence from of 4 ± 1% CSF, 66 ± 5% GM, and 30 ± 6% WM. Spectral quality as animal models that suggests that striatal dopamine levels and reported by LCModel were (mean± SD): signal-to-noise ratio: associated behaviors are related to functioning of the ventral 14 ± 2; line width: 8.1 ± 1.4. hippocampus (Lodge and Grace, 2011; Grace, 2016). For example, activation of glutamatergic N-methyl-D-aspartate receptors in the ventral hippocampus elevates dopamine neuron activity in Correlations the VTA in a dose-dependent manner (Floresco et al., 2001 2003 , ; Left hippocampal Glx concentrations showed a significant posi- Lodge and Grace, 2006), which is correlated with both altered tive correlation with functional activity in the left ventral stridopamine efflux in the n - ucleus accumbens (Floresco et al., 2003) atum during reward anticipation (r = 0.475, P = .020; Figure 4A), and an increased behavioral response to amphetamine (White and a significant negative correlation with context-depend- et al., 2006; Lodge and Grace, 2008). One possible explanation for ent functional connectivity between the left ventral striatum the inverse correlation between hippocampal glutamate levels and the left anterior hippocampus during reward anticipation and reward-related functional connectivity between the anter - (r = –0.409, P = .041; Figure 4B). ior hippocampus and the ventral striatum that we observed Figure 3. Group psychophysiological interaction (PPI) map for anticipation vs control with left ventral striatum as seed re= g ion (n 19; P < .001 uncorrected). Activation in left ventral striatum was significantly correlated with that in left lingual gyrus and left hippocampus (P < .001, FWE-corrected at cluster level). X, y, and z are Montreal Neurological Institute coordinates and represent the highest t value in a cluster. Numbers below slices indicate Montreal Neurological Institute z coordinates. L, left; R, right. Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy011/4850502 by Ed 'DeepDyve' Gillespie user on 08 June 2018 6 | International Journal of Neuropsychopharmacology, 2018 approach. For example, although reward-related ventral stri- atal activity has been related to dopamine release in this brain region (Knutson and Gibbs, 2007; Schott et al., 2008), it may not reflect presynaptic dopamine synthesis capacity. We showed significant activity in the bilateral ventral stri- atum and significant connectivity between left ventral striatum and both lingual gyrus and hippocampus during reward antici- pation. These results are in line with those of previous func- tional MRI studies, which have unequivocally implicated the ventral striatum as a key brain area involved in reward process- ing (Knutson et al, 2001; Bjork et al., 2004; Knutson and Cooper, 2005). In addition, several functional MRI studies examined func- tional connectivity of the ventral striatum in a reward context. For example, Schreiter and colleagues (2016) showed decreased functional connectivity between the left ventral striatum and anterior prefrontal cortex in patients with bipolar disorder - dur ing reward anticipation.W eiland et al. (2013) demonstrated increased connectivity between the ventral striatum and both paracentral lobule/precuneus and sensorimotor areas in youth with a family history of alcoholism during incentive anticipa- tion (both reward and loss conditions). Unfortunately, whereas several studies reported group differences during reward antici- pation, none of them specifically described striatal functional connectivity patterns in healthy individuals. Because disturbed reward processing has been associated with both schizophrenia and addiction (Berridge, 2012 Berridg ; e and Kringelbach, 2015; Radua et al., 2015; Luijten et al., 2017), our findings have potential implications for the understand- ing of these disorders. In particular, it is hypothesized that Figure 4. Correlation between left hippocampal Glx concentrations and (A) inappropriate attribution of incentive salience to otherwise activity in left ventral striatum, and (B) connectivity between left ventral stri- relatively neutral environmental cues leads to the formation of atum and left anterior hippocampus, both for reward anticipation vs control. a.u., arbitrary units. psychotic symptoms (Heinz, 2002; Kapur, 2003). A leading con- temporary preclinical model of psychosis proposes that these symptoms arise from a substantial decrease in the number of in the present study is that this may reflect the relationship between activated glutamatergic pyramidal neurons leading to inhibitory parvalbumin-expressing GABAergic interneurons in the hippocampus, resulting in an overactive striatal dopa- increased striatal dopamine levels and its control by inhibitory parvalbumin-expressing GABAergic interneurons in the anter - mine system through manipulation of glutamatergic pyramidal neurons (Lodge and Grace, 2011; Grace, 2016). This is consist- ior hippocampus. This is supported by preclinical models, which showed that reduced inhibitory control in the ventral hippo- ent with our findings that hippocampal glutamate levels were significantly correlated with reward anticipation-related ven- campus can lead to increased activation of glutamatergic p - yr amidal neurons, increased dopamine neuron activity in the VTA, tral striatal activity, and inversely correlated with hippocampal coupling with ventral striatal function in the context of reward and greater dopamine release in the nucleus accumbens (Lodge and Grace, 2011; Grace, 2016). processing. Some limitations have to be taken into account in interpret- Three human neuroimaging studies have previously exam- ined interactions between hippocampal and striatal function ing the results of this study. First, we focused on reward antici- pation and not on loss avoidance or feedback. This was because in healthy participants.Allen et al. (2012) demonstrated that higher activity in the left hippocampus during performance of the anticipation phase has been most strongly linked with stri- atal dopamine function (Knutson and Gibbs, 2007Sc ; hott et al., a verbal memory task was associated with reduced ventral stri- atal dopamine synthesis capacity. Roiser and colleagues (2013) 2008). Moreover, striatal incentive findings with reward are gen- erally more robust than those with loss avoidance (Knutson showed a significant positive correlation between right hip- pocampal activity in response to irrelevant stimulus features et al., 2001; Guyer et al., 2006). Second, the reported Glx signal is a composite peak, which not only incorporates glutamate but and striatal dopamine synthesis capacity, although this was present only in the dorsal striatum. The only previous study that also its precursor glutamine. However, the Glx signal has been widely used as a marker of glutamatergic function, because it has assessed the relationship between glutamate levels in the hippocampus and striatal dopamine function was conducted likely predominantly reflects glutamate levels, which are typ- ically 5 to 6 times higher than those of glutamine (Kaiser et al., by Stone and colleagues (2010). They did not find a significant correlation between hippocampal glutamate levels as measured 2005). Third, MRS techniques cannot distinguish between intra- cellular and extracellular metabolite concentrations, and thus with H-MRS and striatal dopamine synthesis capacity assessed with Positron Emission Tomography, although they did find a hippocampal metabolite levels as demonstrated in the current study reflect both. correlation in subjects at clinical high risk for psychosis. None of these previous experiments examined associations between In conclusion, our study shows for the first time that in healthy volunteers, higher hippocampal glutamate levels are hippocampal glutamate levels and striatal activity during reward processing. Therefore, discrepancies between these and correlated with reward anticipation-related ventral striatal activ- ity, but inversely correlated with context-dependent functional our findings may be explained by differences in neuroimaging Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy011/4850502 by Ed 'DeepDyve' Gillespie user on 08 June 2018 Bossong et al. | 7 connectivity between the anterior hippocampus and the ventral Friston KJ, Buechel C, Fink GR, Morris J, Rolls E, Dolan RJ (1997) striatum during the anticipation of monetary reward. This sug- Psychophysiological and modulatory interactions in neuro- gests that human striatal responses to reward anticipation are imaging. Neuroimage 6:218–229. influenced by hippocampal glutamate levels. Grace AA (2012) Dopamine system dysregulation by the hippo- campus: implications for the pathophysiology and treatment of schizophrenia. Neuropharmacology 62:1342–1348. Acknowledgments Grace AA (2016) Dysregulation of the dopamine system in the pathophysiology of schizophrenia and depression. Nat Rev This work was supported by the Netherlands Organisation for Scientific Research (Veni fellowship to M.G.B.), the Wellcome Neurosci 17:524–532. Grace AA (2017) Dopamine system dysregulation and the patho- Trust (091667/Z/10/Z to P.M.), the National Institute for Health Research, UK (NIHR-CS-11-001 to S.B.), the Medical Research physiology of schizophrenia: insights from the methylazox- ymethanol acetate model. Biol Psychiatry 81:5–8. Council, UK (MR/J012149/1 and MC_PC_14105 v.2 to S.B.), and the King’s Challenge Fund (R120525). Guyer AE, Nelson EE, Perez-Edgar K, Hardin MG, Roberson-Nay R, Monk CS, Bjork JM, Henderson HA, Pine DS, Fox NA, Ernst M (2006) Striatal functional alteration in adolescents charac- Statement of Interest terized by early childhood behavioral inhibition. J Neurosci 26:6399–6405. None. Heinz A (2002) Dopaminergic dysfunction in alcoholism and schizophrenia: psychopathological and behavioral correlates. References Eur Psychiatry 17:9–16. Allen P, Chaddock CA, Howes OD, Egerton A, Seal ML, Fusar- Jansma JM, van Hell HH, Vanderschuren LJ, Bossong MG, Jager G, Kahn RS, Ramsey NF (2013) THC reduces the anticipatory Poli P, Valli I, Day F, McGuire PK (2012) Abnormal relationship between medial temporal lobe and subcortical dopamine nucleus accumbens response to reward in subjects with a nicotine addiction. Transl Psychiatry 3:e234. function in people with an ultra high risk for psychosis. Schizophr Bull 38:1040–1049. Kaiser LG, Schuff N, Cashdollar N, Weiner MW (2005) Age-related glutamate and glutamine concentration changes in normal Berridge KC (2012) From prediction error to incentive sali- ence: mesolimbic computation of reward motivation. Eur human brain: 1H MR spectroscopy study at 4 T. Neurobiol Aging 26:665–672. J Neurosci 35:1124–1143. Berridge KC, Kringelbach ML (2015) Pleasure systems in the Kapur S (2003) Psychosis as a state of aberrant salience: a frame- work linking biology, phenomenology, and pharmacology in brain. Neuron 86:646–664. Bjork JM, Knutson B, Fong GW, Caggiano DM, Bennett SM, schizophrenia. Am J Psychiatry 160:13–23. Knutson B, Adams CM, Fong GW, Hommer D (2001) Anticipation Hommer DW (2004) Incentive-elicited brain activation in adolescents: similarities and differences from young adults. of increasing monetary reward selectively recruits nucleus accumbens. J Neurosci 21:RC159. J Neurosci 24:1793–1802. Blaha CD, Yang CR, Floresco SB, Barr AM, Phillips AG (1997) Knutson B, Cooper JC (2005) Functional magnetic resonance imaging of reward prediction. Curr Opin Neurol 18:411–417. Stimulation of the ventral subiculum of the hippocampus evokes glutamate receptor-mediated changes in dopa- Knutson B, Gibbs SE (2007) Linking nucleus accumbens dopa- mine and blood oxygenation. Psychopharmacology (Berl) mine efflux in the rat nucleus accumbens. Eur J Neurosci 9:902–911. 191:813–822. Legault M, Wise RA (1999) Injections of N-methyl-D-aspartate Brett M, Anton JL, Valabregue R, Poline JB (2002) Region of interest analysis using an SPM toolbox. Neuroimage 16:abstract 497. into the ventral hippocampus increase extracellular dopa- mine in the ventral tegmental area and nucleus accumbens. Egerton A, Stone JM, Chaddock CA, Barker GJ, Bonoldi I, Howard RM, Merritt K, Allen P, Howes OD, Murray RM, Synapse 31:241–249. Lodge DJ, Grace AA (2006) The hippocampus modulates dopa- McLean MA, Lythgoe DJ, O’Gorman RL, McGuire PK (2014) Relationship between brain glutamate levels and clin- mine neuron responsivity by regulating the intensity of phasic neuron activation. Neuropsychopharmacology ical outcome in individuals at ultra high risk of psychosis. Neuropsychopharmacology 39:2891–2899. 31:1356–1361. Lodge DJ, Grace AA (2008) Amphetamine activation of hippocam- Flagel SB, Akil H, Robinson TE (2009) Individual differences in the attribution of incentive salience to reward-related pal drive of mesolimbic dopamine neurons: a mechanism of behavioral sensitization. J Neurosci 28:7876–7882. cues: Implications for addiction. Neuropharmacology 56:139–148. Lodge DJ, Grace AA (2011) Hippocampal dysregulation of dopa- mine system function and the pathophysiology of schizo- Floresco SB, Todd CL, Grace AA (2001) Glutamatergic afferents from the hippocampus to the nucleus accumbens regu- phrenia. Trends Pharmacol Sci 32:507–513. Luijten M, Schellekens AF, Kühn S, Machielse MW, Sescousse late activity of ventral tegmental area dopamine neurons. J Neurosci 21:4915–4922. G (2017) Disruption of reward processing in addiction: an image-based meta-analysis of functional magnetic reson- Floresco SB, West AR, Ash B, Moore H, Grace AA (2003) Afferent modulation of dopamine neuron firing differentially regu- ance imaging studies. JAMA Psychiatry 74:387–398. Provencher SW (1993) Estimation of metabolite concentrations lates tonic and phasic dopamine transmission. Nat Neurosci 6:968–973. from localized in vivo proton NMR spectra. Magn Reson Med 30:672–679. Friedman DP, Aggleton JP, Saunders RC (2002) Comparison of hippocampal, amygdala, and perirhinal projections to Radua J, Schmidt A, Borgwardt S, Heinz A, Schlagenhauf F, McGuire P, Fusar-Poli P (2015) Ventral striatal activation dur - the nucleus accumbens: combined anterograde and retro- grade tracing study in the Macaque brain. J Comp Neurol ing reward processing in psychosis: a neurofunctional meta- analysis. JAMA Psychiatry 72:1243–1251. 450:345–365. Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy011/4850502 by Ed 'DeepDyve' Gillespie user on 08 June 2018 8 | International Journal of Neuropsychopharmacology, 2018 Roiser JP, Howes OD, Chaddock CA, Joyce EM, McGuire P (2013) Stone JM, Day F, Tsagaraki H, Valli I, McLean MA, Lythgoe DJ, Neural and behavioral correlates of aberrant salience in indi- O’Gorman RL, Barker GJ, McGuire PK, OASIS (2009) Glutamate viduals at risk for psychosis. Schizophr Bull 39:1328–1336. dysfunction in people with prodromal symptoms of psych- Roitman MF, Stuber GD, Phillips PE, Wightman RM, Carelli RM osis: relationship to gray matter volume. Biol Psychiatry (2004) Dopamine operates as a subsecond modulator of food 66:533–539. seeking. J Neurosci 24:1265–1271. Stone JM, Howes OD, Egerton A, Kambeitz J, Allen P, Lythgoe DJ, Schott BH, Minuzzi L, Krebs RM, Elmenhorst D, Lang M, Winz O’Gorman RL, McLean MA, Barker GJ, McGuire P (2010) Altered relationship between hippocampal glutamate levels and OH, Seidenbecher CI, Coenen HH, Heinze HJ, Zilles K, Düzel E, Bauer A (2008) Mesolimbic functional magnetic reson- striatal dopamine function in subjects at ultra high risk of ance imaging activations during reward anticipation correl- psychosis. Biol Psychiatry 68:599–602. ate with reward-related ventral striatal dopamine release . van Hell HH, Jager G, Bossong MG, Brouwer A, Jansma JM, J Neurosci 28:14311–14319. Zuurman L, van Gerven J, Kahn RS, Ramsey NF (2012) Schreiter S, Spengler S, Willert A, Mohnke S, Herold D, Erk S, Involvement of the endocannabinoid system in reward Romanczuk-Seiferth N, Quinlivan E, Hindi-Attar C, Banzhaf processing in the human brain. Psychopharmacology (Berl) C, Wackerhagen C, Romund L, Garbusow M, Stamm T, Heinz 219:981–990. A, Walter H, Bermpohl F (2016) Neural alterations of fronto- Weiland BJ, Welsh RC, Yau WY, Zucker RA, Zubieta JK, Heitzeg striatal circuitry during reward anticipation in euthymic MM (2013) Accumbens functional connectivity during reward bipolar disorder. Psychol Med 46:3187–3198. mediates sensation-seeking and alcohol use in high-risk Schultz W (2015) Neuronal reward and decision signals: from youth. Drug Alcohol Depend 128:130–139. theories to data. Physiol Rev 95:853–951. White IM, Whitaker C, White W (2006) Amphetamine-induced Schultz W, Dayan P, Montague PR (1997) A neural substrate of hyperlocomotion in rats: Hippocampal modulation of the prediction and reward. Science 275:1593–1599. nucleus accumbens. Hippocampus 16:596–603. Downloaded from https://academic.oup.com/ijnp/advance-article-abstract/doi/10.1093/ijnp/pyy011/4850502 by Ed 'DeepDyve' Gillespie user on 08 June 2018
International Journal of Neuropsychopharmacology – Oxford University Press
Published: Feb 10, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera