Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI findings in the monetary incentive delay task

Jianguang Zeng; Jiangnan Yan; Hengyi Cao; Yueyue Su; Yuan Song; Ya Luo; Xun Yang

doi:10.1038/s41398-022-02201-8

Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI findings in the monetary incentive delay task

Zeng, Jianguang; Yan, Jiangnan; Cao, Hengyi; Su, Yueyue; Song, Yuan; Luo, Ya; Yang, Xun 2022-10-16 00:00:00 Translational Psychiatry www.nature.com/tp SYSTEMATIC REVIEW OPEN Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI ﬁndings in the monetary incentive delay task 1,6 1,6 2,3,6 4 4 5 4✉ Jianguang Zeng , Jiangnan Yan , Hengyi Cao , Yueyue Su , Yuan Song ,YaLuo and Xun Yang © The Author(s) 2022 Dysfunction of the mesocorticolimbic dopaminergic reward system is a core feature of schizophrenia (SZ), yet its precise contributions to different stages of reward processing and their relevance to disease symptomology are not fully understood. We performed a coordinate-based meta-analysis, using the monetary incentive delay task, to identify which brain regions are implicated in different reward phases in functional magnetic resonance imaging in SZ. A total of 17 studies (368 SZ and 428 controls) were included in the reward anticipation, and 10 studies (229 SZ and 281 controls) were included in the reward outcome. Our meta-analysis revealed that during anticipation, patients showed hypoactivation in the striatum, anterior cingulate cortex, median cingulate cortex (MCC), amygdala, precentral gyrus, and superior temporal gyrus compared with controls. Striatum hypoactivation was negatively associated with negative symptoms and positively associated with the proportion of second- generation antipsychotic users (percentage of SGA users). During outcome, patients displayed hyperactivation in the striatum, insula, amygdala, hippocampus, parahippocampal gyrus, cerebellum, postcentral gyrus, and MCC, and hypoactivation in the dorsolateral prefrontal cortex (DLPFC) and medial prefrontal cortex (mPFC). Hypoactivity of mPFC during outcome was negatively associated with positive symptoms. Moderator analysis showed that the percentage of SGA users was a signiﬁcant moderator of the association between symptom severity and brain activity in both the anticipation and outcome stages. Our ﬁndings identiﬁed the neural substrates for different reward phases in SZ and may help explain the neuropathological mechanisms underlying reward processing deﬁcits in the disorder. Translational Psychiatry (2022) 12:448 ; https://doi.org/10.1038/s41398-022-02201-8 INTRODUCTION used task to probe neural substrates of different reward processing Schizophrenia (SZ) is one of the most severe neuropsychiatric stages in healthy individuals and those with mental disorders disorders characterized by diverse symptoms including delusions, [9, 10]. In the MID task, subjects see a cue indicating that they will hallucinations, and thought disorders [1, 2]. Abnormal reinforce- have an opportunity to obtain a certain amount of monetary ment learning and representations of reward value are present in reward, respond to a given target, and receive immediate feedback SZ, and these impairments can manifest as deﬁcits in reward on whether they have successfully obtained the reward (see decision making [3]. Accumulating evidence suggests that reward Supplementary Materials). The anticipation phase is deﬁned by the processing abnormalities in SZ patients may arise from dopami- introduction of a cue informing participants about an upcoming nergic dysfunction within the mesocorticolimbic circuit, including potential reward, and the outcome phase refers to the period the dorsolateral prefrontal cortex (DLPFC), orbital prefrontal cortex when a reward is presented [11]. The investigation of reward (OFC), medial prefrontal cortex (mPFC), anterior cingulate cortex processing in healthy adults revealed that anticipation of reward (ACC), ventral striatum (VS, including the nucleus accumbens), was associated with the activation of multiple regions including ventral pallidum, amygdala, hippocampus and thalamus [4–6]. the striatum, ACC, anterior insula, and the central executive and Dysregulated dopaminergic modulation of reward processing is default networks [11], while the OFC and mPFC were activated considered to be fundamental to the symptoms of SZ and is often during the reward outcome phase [12]. This implies that the neural reported to be an important predictor of poor functional outcome substrates of the two stages are likely to be associated with distinct [7, 8]. patterns of activation and connectivity [12]. Based on recent studies, reward processing includes two phases To date, present studies have examined and identiﬁed several temporally, namely, the reward anticipation and reward outcome likely neural substrates for the anticipation and outcome of [9]. The monetary incentive delay (MID) task is the most widely incentives in SZ. However, due to the heterogeneity of reward 1 2 School of Economics and Business Administration, Chongqing University, Chongqing 400044, China. Center for Psychiatric Neuroscience, Feinstein Institute for Medical 3 4 Research, Hempstead, NY, USA. Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA. School of Public Affairs, Chongqing University, Chongqing 5 6 400044, China. Department of Psychiatry, State Key Lab of Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China. These authors contributed equally: Jianguang Zeng, Jiangnan Yan, Hengyi Cao. email: [email protected] Received: 19 March 2022 Revised: 21 September 2022 Accepted: 22 September 2022 1234567890();,: J. Zeng et al. paradigms and the bias introduced by including region of interest selected articles and relevant review articles to include more (ROI) analysis, the existing results are still inconsistent. During relevant studies. For studies without available coordinates at the reward anticipation, although several studies revealed reduced VS whole-brain level, we asked the authors whether they could activity in SZ [13–16], other studies reported reduced activations provide such information. Details of the literature search and in the posterior cingulate cortex and temporal regions [17]. selection were reported in Fig. 1. Compared with healthy controls (HC), activation in the VS in Studies were eligible if they met the following criteria: (1) patients was found to be either reduced or not signiﬁcantly articles that included patients (aged >18 years) diagnosed with changed (Supplementary Table 1). Reward anticipation abnorm- SZ, schizoaffective disorder, or another psychosis spectrum alities have been implicated in the pathophysiology of negative disorder based on the Diagnostic and Statistical Manual of symptoms, such as anhedonia and avolition in SZ patients [16, 18]. Mental Disorders (DSM) or International Statistical Classiﬁcation However, there is also evidence suggesting correlations between of Diseases and Related Health Problems (ICD) diagnostic anticipation dysfunction and the severity of positive symptoms criteria; (2) articles that investigated brain functional activity at [14, 19]. In terms of reward outcome, the role of striatum is the whole-brain level between adult SZ patients and HC; (3) relatively uncertain. Some behavioral and neuroimaging data have articles that used a standardized MID task or modiﬁed MID task; shown intact responses during the outcome phase [20, 21], while (4) articles that examined neuronal activity related to the MID other data have shown either hyperactivity or hypoactivity in the task using fMRI; (5) articles that identiﬁed foci of task-related striatum during monetary receipt [22–24]. Most studies report that neural changes in anticipation phase and/or outcome phase; outcome-related neural response in SZ patients is associated with and 6) articles that reported signiﬁcant resultsas3Dcoordinates both positive symptoms [25, 26] and negative symptoms [14]. in either the Talairach Atlas (Tal) or Montreal Neurological Such inconsistencies may be attributed to the small sample size, Institute (MNI) space. sample heterogeneity, and differences in paradigm design among The exclusion criteria were as follows: (1) case reports, book studies. chapters, reviews, or meta-analyses; (2) non-English articles; (3) Currently, an updated quantitative meta-analysis method called studies that included only ROI or volume of interest (VOI) ﬁndings; seed-based mapping (SDM) has emerged as a useful approach to and (4) studies in which the coordinates were not available in the identify spatially consistent brain changes reported in the article or after contacting the authors. Six fMRI studies did not literature through the use of the coordinate information reported provide group differences between SZ and HC and were thus not in each study. Few meta-analyses thus far have focused on included in our meta-analysis [23, 29–33]. Of four studies using dissociated neural responses during reward anticipation and overlapping samples [14, 34–36], the one with more subjects [14] outcome in SZ, although an increasing number of functional and the most recent study [35] were included. One study was magnetic resonance imaging (fMRI) studies have reported excluded because the SZ patients had comorbid Parkinson’s potential neural substrates of reward processing. Radua and his disease [37]. colleagues used meta-analysis to reveal alterations in VS activity during reward anticipation, feedback, and prediction error [16]. Data extraction However, VS activation in this meta-analysis was based on ROI Data extraction was independently performed and checked by approach, which would be affected by the different VS deﬁnitions two authors. The following data were extracted: the sample sizes, across the included studies. Furthermore, both individuals with SZ the mean age, the percentage of males, the duration of illness, the and those at high risk for psychosis were included in the study, severity of symptoms (Positive and Negative Syndrome Scale-Total complicating the reported results. Another meta-analysis per- (PANSS-T), PANSS-Positive (PANSS-P), PANSS-Negative (PANSS-N)), formed a whole-brain meta-analysis but only focused on the the proportion of SZ who had ever received ﬁrst-generation anticipation of reward tasks [27], while the neural substrates antipsychotics (% (percentage) of FGA users)/ second-generation underlying different reward processing phases remain unclear. antipsychotics (% of SGA users), and methodological items. Here, we performed an in-depth meta-analysis to elucidate the neurobiological basis underlying different stages of reward Meta-analysis of relevant studies processing between SZ and HC. To overcome the limitations of MID-related activation differences were analyzed using SDM previous meta-analysis work, we only included fMRI studies that (version 5.15, https://www.sdmproject.com), a novel voxel-based performed a whole-brain analysis of patients as they completed meta-analytic approach that uses the reported peak coordinates the MID paradigm and analyzed reward anticipation and reward to recreate maps depicting the effect size of group differences in outcome independently. We also explored whether brain functional activations. Peak coordinates were recreated by ﬁrst responses during different reward processes were associated with converting the peak t value to Hedges’ effect size and then symptom severity using meta-regression analysis. We expected applying a normalized Gaussian kernel to the voxels close to the that reward anticipation and reward outcome would recruit peak. In addition to evaluating the probability of a peak, SDM can different brain regions in SZ patients, and that the abnormal be used to recreate maps of the signed (i.e., positive and negative) neural activations during different stages of reward processing functional activation or differences between patients and HC by would be closely related to the severity of symptoms. using the reported peak coordinates, which makes SDM an optimal method for comparing patients and controls without biasing the results [38]. The statistical maps are created by MATERIALS AND METHODS calculating the corresponding statistics from the study maps and Study search and selection weighted by the squared root of the sample size of each study, Following recommended guidelines in the Preferred Reporting amplifying the contributions of studies with larger sample sizes Items for Systematic Reviews and Meta-Analyses statement [28], [38]. two authors independently searched the PubMed, Web of Science, The SDM has more advantages than other methods, such as the and ScienceDirect databases for relevant articles from January arbitrary Lagrangian-Eulerian (ALE) method. First, instead of 2000 to May 2021, using the following terms: (1) “schizophrenia” computing coordinates of increased and decreased activation OR “schizophrenic” OR “schizoaffective” OR “psychoses” OR separately, SDM can reconstruct both positive and negative “psychosis” OR “psychotic” OR “ﬁrst episode psychosis” OR “FEP”, differences in the same map [39]. Second, studies reporting no (2) “functional magnetic resonance imaging” OR “fMRI” OR group differences can also be included. To date, SDM has been “neuroimaging”, and (3) “monetary incentive delay task” OR widely applied in previous meta-analyses of structural and “MID”. We also manually examined the reference lists of the functional MRI studies [40–44]. Translational Psychiatry (2022) 12:448 J. Zeng et al. Fig. 1 Preferred reporting items for systematic reviews and meta-analyses (PRISMA) ﬂow diagram. Of 548 articles initially identiﬁed, a total of 17 studies were enrolled for the reward anticipation meta-analysis, and 10 studies were enrolled for the ﬁnal reward outcome meta- analysis. MID monetary incentive delay, fMRI functional magnetic resonance imaging, ROI regions of interest, VOI volume of interest. We closely followed the steps taken in the published Main meta-analysis. In the pooled meta-analysis of reward literatures [45, 46]. In brief, peak coordinates of group anticipation, relative to HC, SZ exhibited lower activations in the differences and corresponding statistics were extracted from striatum (with extension to the insula and amygdala), ACC, median the included articles and then input into SDM software. cingulate cortex (MCC), right precentral gyrus and right superior Measurements (z scores and temporal gyrus (STG) in response to monetary stimuli. No brain p values) were converted into t values in advance. Standard regions showed increased activation in SZ patients compared to MNI maps of the activation differences were created using a HC (Table 2 and Fig. 2). Gaussian kernel, and the mean map was calculated represent- ing the weighted mean functional differences during the MID Sensitivity analysis. As illustrated in Supplementary Table 2, task. Statistical signiﬁcance was assessed by permutation whole-brain jackknife sensitivity analysis conﬁrmed that hypoacti- testing. The default kernel size and statistical thresholds (full vation in the bilateral striatum, ACC and MCC maintained width at half maximum [FWHM] = 20 mm, p = 0.005, peak signiﬁcance in all but one combination. The results in the right height threshold = 1, extent threshold = 10) were used to precentral gyrus and right STG maintained signiﬁcance in all but balance sensitivity and speciﬁcity [44, 46, 47]. two combinations. In addition, to assess the robustness of the ﬁndings, complementary analyses were performed, including jackknife Subgroup analyses. To control for any possible differences sensitivity analyses, subgroup analyses and meta-regression observed between studies, subgroup analyses were repeated analyses. Based on the results of meta-regression, we also several times to include only those studies that were clinically and conducted moderation analyses using a standard model [48, 49] methodologically homogenous. Therefore, we conducted sub- (see Supplementary Materials). group analysis for those studies only including chronic SZ, for those including SZ patients diagnosed by DSM, for those including SZ patients receiving medication treatment, for those using a 3-T RESULTS MRI scanner, for those using SPM software, and for those reporting MID-related brain activation differences between SZ and HC coordinates corrected for comparisons. The subgroup analysis during reward anticipation revealed that all of the aforementioned results were highly Included studies and sample characteristics. Seventeen studies replicable, except for decreased activation in the right precentral with 368 SZ and 428 HC were included in the comparison of SZ and gyrus and right STG (Supplementary Table 2). HC during reward anticipation [13–15, 17, 19, 22, 24–26, 35, 50–56] (Table 1 and Fig. 1). The mean age between SZ (32.10 years) and HC Meta-regression analyses. We next tested correlations between (32.36 years) was not signiﬁcantly different (t=−0.524, p= 0.199). anticipation-evoked activations and demographic and clinical The percentage of males among SZ patients (75.00% male) and variables, including the mean age, the percentage of males, the controls (70.01% male) was also not signiﬁcantly different duration of illness, the symptom severity and the medication (χ = 2.382, p= 0.123). variables. There were no signiﬁcant correlations between brain Translational Psychiatry (2022) 12:448 J. Zeng et al. Translational Psychiatry (2022) 12:448 Table 1. Demographic and clinical characteristics of the studies included in the meta-analysis. Studies Schizophrenia Healthy controls Methodology Phase of illness No. (male) Mean age Medication Diagnosis criteria No. (male) Mean age MRI scanner SPM Threshold Anticipation stage Abler et al., [22] Chronic SZ 12 (5) 36.70 SGA & FGA DSM-IV 12 (7) 36.20 3 T Y Uncorrected, p < 0.005 Alves et al., [17] FEP 10 (10) 22.70 SGA & FGA DSM-IV 12 (12) 34.55 3 T Y Corrected, p < 0.05 Arrondo et al., [50] Chronic SZ 22 (19) 32.73 SGA & FGA DSM-IV 21 (17) 34.33 3 T N Corrected, p < 0.05 Esslinger et al., [19] FEP 27 (20) 27.80 N DSM-IV 27 (20) 27.10 3 T Y Corrected, p < 0.05 Gilleen et al., [51] Chronic SZ 20 (20) 36.50 SGA & FGA DSM-IV 12 (12) 30.70 3 T Y Corrected, p < 0.05 Juckel et al., [13] Chronic SZ 10 (10) 26.80 N DSM-IV & ICD-10 10 (10) 31.70 1.5 T Y Uncorrected, p < 0.001 Koch et al., [35] Chronic SZ 44 (27) 34.20 SGA & FGA DSM-IV & ICD-10 44 (35) 37.10 1.5 T Y Corrected, p < 0.05 Li et al., [24] Chronic SZ 26 (15) 22.77 SGA DSM-IV 26 (15) 24.58 3 T Y Corrected, p < 0.001 Mucci et al., [52] Chronic SZ 28 (18) 33.10 SGA DSM-IV 22 (10) 31.91 3 T Y Corrected, p < 0.05 Nielsen et al., [14] FEP 31 (22) 25.90 N ICD-10 31 (22) 25.70 3 T N Corrected, p < 0.05 Schlagenhauf et al., [56] Chronic SZ 10 (9) 30.50 FGA DSM-IV 10 (9) 31.80 1.5 T Y Corrected, p < 0.05 Schlagenhauf et al., [26] Chronic SZ 15 (12) 30.10 N DSM-IV 15 (12) 30.10 1.5 T Y Corrected, p < 0.05 Schwarz et al., [55] Chronic SZ 27 (18) 32.40 SGA & FGA DSM-IV 110 (54) 30.40 3 T Y Corrected, p < 0.05 Stepien et al., [53] Chronic SZ 16 (14) 32.60 SGA DSM-IV 23 (11) 29.50 3 T Y Corrected, p < 0.05 Subramaniam et al., [15] Chronic SZ 37 (25) 45.14 SGA & FGA DSM 20 (14) 43.72 3 T Y Uncorrected, p < 0.001 Walter et al., [54] Chronic SZ 16 (8) 38.00 SGA DSM-IV 16 (7) 33.00 3 T Y Uncorrected, p < 0.001 Waltz et al., [25] Chronic SZ 17 (13) 37.80 SGA & FGA DSM-IV 17 (12) 37.80 3 T N Corrected, p < 0.05 Outcome stage Abler et al., [22] Chronic SZ 12 (5) 36.70 SGA & FGA DSM-IV 12 (7) 36.2 3 T Y Uncorrected, p < 0.005 Gilleen et al., [51] Chronic SZ 20 (20) 36.50 SGA & FGA DSM-IV 12 (12) 30.7 3 T Y Corrected, p < 0.05 Li et al., [24] Chronic SZ 26 (15) 22.77 SGA DSM-IV 26 (15) 24.58 3 T Y Corrected, p < 0.001 Mucci et al., [52] Chronic SZ 28 (18) 33.10 SGA DSM-IV 22 (10) 31.91 3 T Y Corrected, p < 0.05 Nielsen et al., [14] FEP 31 (22) 25.90 N ICD-10 31 (22) 25.70 3 T N Corrected, p < 0.05 Schlagenhauf et al., [26] Chronic SZ 15 (12) 30.10 N DSM-IV 15 (12) 30.10 1.5 T Y Corrected, p < 0.05 Schwarz et al., [55] Chronic SZ 27 (18) 32.40 SGA & FGA DSM-IV 110 (54) 30.40 3 T Y Corrected, p < 0.05 Subramaniam et al., [15] Chronic SZ 37 (25) 45.14 SGA & FGA DSM 20 (14) 43.72 3 T Y Uncorrected, p < 0.001 Walter et al., [54] Chronic SZ 16 (8) 38.00 SGA DSM-IV 16 (7) 33.00 3 T Y Uncorrected, p < 0.001 Waltz et al., [25] Chronic SZ 17 (13) 37.80 SGA & FGA DSM-IV 17 (12) 37.80 3 T N Corrected, p < 0.05 No. number, ICD-10 international statistical classiﬁcation of diseases and related health problems, 10th Edition DSM-IV diagnostic and statistical manual of mental disorders, 4th Edition, SZ schizophrenia, FEP ﬁrst episode psychosis, HC healthy controls, SGA second-generation antipsychotics, FGA ﬁrst-generation antipsychotics, Y yes, N no. J. Zeng et al. Table 2. Results of the meta-analysis for brain activation difference between SZ and HC during reward anticipation stage. Brain regions MNI SDM value p value Number Breakdown of voxels coordinates x, y, z P <HC Bilateral striatum −8,4,6 −2.662 ~0 2956 Right striatum Right lenticular nucleus, putamen, BA 11, BA 25, BA 48 Right caudate nucleus Left caudate nucleus, BA 25 Right caudate nucleus, BA 11, BA 25 Right olfactory cortex, BA 11, BA 25, BA 48 Right amygdala, BA 34, BA 48 Left striatum Right inferior network, uncinate fasciculus, inferior fronto-occipital fasciculus Right gyrus rectus, BA 11, BA 25, BA 48 Right superior longitudinal fasciculus III Right insula, BA 48 Right median network, cingulum Left olfactory cortex, BA 25 Right hippocampus, BA 34 ACC & MCC 0,12,24 −2.620 0.000005186 1931 Left median cingulate / paracingulate gyri, BA 23, BA 24, BA 32 Right median cingulate / paracingulate gyri, BA 23, BA 24, BA 32 Left anterior cingulate / paracingulate gyri, BA 10, BA 24, BA 32 Left median network, cingulum Right anterior cingulate / paracingulate gyri, BA 24, BA 32 Right median network, cingulum Left superior frontal gyrus, medial, BA 8, BA 24, BA 32 Left supplementary motor area, BA 8, BA 24, BA Right superior frontal gyrus, medial, BA 32 Right supplementary motor area, BA 32 Right precentral gyrus 50,4,36 −1.919 0.000526428 244 Right precentral gyrus, BA 4, BA 6, BA 44 Right middle frontal gyrus, BA 6, BA 9, BA 44 Right inferior frontal gyrus, opercular part, BA 44 Right postcentral gyrus, BA 4, BA 6 Right STG 62,0,−4 −1.693 0.001878560 30 Right superior temporal gyrus, BA 21, BA 38, BA Right temporal pole, superior temporal gyrus, BA 21, BA 38, BA 48 Results were threshold at p = 0.005, peak height threshold of 1, extent threshold of 10. BA Brodmann area, P patients, HC healthy controls, ACC anterior cingulate cortex, MCC median cingulate cortex, STG superior temporal gyrus, SDM seed-based d mapping, MNI Montreal Neurological Institute. MID-related activations and mean age (available in 17 studies), brain association was dependent on a third variable (including the between brain MID-related activations and percentage of males age, the sex and the medication) through the moderation analysis. (available in 17 studies), between brain MID-related activations Our moderation analysis revealed that the interactions of brain × and duration of illness (available in 12 studies), between brain age and brain × sex were not statistically signiﬁcant. In the test of MID-related activations and PANSS-P (available in 14 studies), and the moderation effect of medication, the interaction of the % of between brain MID-related activations and the % of FGA users SGA users and negative symptoms signiﬁcantly improved model (available in 17 studies) during reward anticipation. Meta- ﬁt, suggesting a moderating effect of the % of SGA users on the regression analyses revealed that the severity of negative relationship between negative symptom severity and VS activity symptoms (available in 15 studies) was negatively associated with (R change = 0.263, B = 0.173, p = 0.019). That is, for individuals in anticipation-evoked hypoactivation in the VS (MNI coordinates: the lower SGA group, a higher PANSS-N score was associated with x = 16, y = 14, z = −6, r = −0.507, p = 0.038). In addition, the % of more decreased striatum activation, while for individuals in the SGA users (available in 17 studies) was positively related to the VS higher SGA group, negative symptoms presented a null associa- activation (MNI coordinates: x = 16, y = 2, z = 0, r = 0.533, tion with striatum activity (Fig. 3 and Supplementary Table 3). p = 0.019) (Fig. 3). MID-related brain activation differences between SZ and HC Moderation analyses. Since the negative symptom severity was during reward outcome signiﬁcantly negatively related to striatum hypoactivation Included studies and sample characteristics.Regarding the (r = −0.507, p = 0.038), we further tested whether the symptom- reward outcome stage, a total of ten studies comprising 229 Translational Psychiatry (2022) 12:448 J. Zeng et al. Fig. 2 Task-evoked activation differences between SZ and HC during reward anticipation and reward outcome. A For the main analysis of the anticipation stage, SZ patients showed hypoactivation occurring in the bilateral striatum, ACC, MCC, amygdala, right precentral gyrus, and right STG, compared with HC. B For the main analysis of the outcome stage, patients showed hyperactivation in the striatum (with extension to the bilateral insula, amygdala, and hippocampus), left cerebellum, right parahippocampal gyrus, right postcentral gyrus, and right MCC, and hypoactivation in the mPFC and DLPFC compared with HC. Brain regions that showed signiﬁcant differences during the outcome stage in SZ patients relative to HC. Red indicates regions that showed hyperactivation in SZ compared with HC and blue indicates regions that showed hypoactivity in patients relative to HC. The color scale represents probability values from statistical permutation testing (z values). SZ schizophrenia, HC healthy controls, ACC anterior cingulate cortex, MCC median cingulate cortex, STG superior temporal gyrus, mPFC medial prefrontal cortex, DLPFC dorsolateral prefrontal cortex. SZ and 281 HC met the meta-analysis inclusion criteria SZ patients diagnosed by DSM, for those including SZ patients [14, 15, 22, 24–26, 51, 52, 54, 55](Table 1 and Fig. 1). The mean receiving medication treatment, for those using a 3-T MRI age between SZ (33.84 years) and HC (32.41 years) was not scanner, for those using SPM software, and for those reporting signiﬁcantly different (t = −0.539, p = 0.596). There was no coordinates corrected for comparisons. The results remained signiﬁcant difference (χ = 0.601, p = 0.438) in the percentage of largely unchanged in all of the subgroup analyses (Supplemen- males between SZ patients (67.60% male) and controls tary Table 4). (64.59% male). Meta-regression analyses. For reward outcome, the effect of Main meta-analysis. Compared with HC, SZ showed higher duration of illness could not be examined due to insufﬁcient data activations in the bilateral striatum (with extension to the bilateral (available in six studies). No signiﬁcant correlations were found insula, amygdala, and hippocampus), left cerebellum, right between outcome-evoked activations and several variables (the parahippocampal gyrus, right postcentral gyrus, and right MCC percentage of males (available in 10 studies), the % of FGA users during the outcome stage. Signiﬁcant lower activations in SZ (available in 10 studies), and the PANSS-N scores (available in patients were detected in the mPFC and bilateral DLPFC eight studies)). Hypoactivation in left mPFC was found to be compared to HC (Table 3 and Fig. 2). negatively associated with the PANSS-P scores (MNI coordinates: x = 0, y = 46, z = −10, r = −0.681, p = 0.043; available in eight Sensitivity analysis. The jackknife sensitivity analysis revealed that studies). Moreover, the % of SGA users was found to be positively the ﬁndings in the left striatum, right parahippocampal gyrus, and related to the left mPFC activation (MNI coordinates: x = 0, y = 46, right postcentral gyrus were consistent in all combinations of z = −10, r = 0.656, p = 0.028; available in 10 studies) (Fig. 3). studies. The increased activations in the right striatum left cerebellum and right MCC, as well as reduced activations in the Moderation analyses. During reward outcome, a similar pattern mPFC and DLPFC, remained signiﬁcant except for one combina- of ﬁndings emerged for the moderating effect of % of SGA users. tion (Supplementary Table 4). In detail, the interaction of SGA and positive symptoms was a signiﬁcant predictor of mPFC activity (R change = 0.457, Subgroup analyses. Similarly, we conducted subgroup analyses B = 0.230, p = 0.001). A higher PANSS-P was associated with more for those studies only including chronic SZ, for those including decreased mPFC activation among participants in the lower SGA Translational Psychiatry (2022) 12:448 J. Zeng et al. Fig. 3 Correlations and moderation analyses between clinical symptoms and brain activity during reward anticipation and reward outcome. A Scatter plot showing a signiﬁcant negative association between anticipation-evoked activity and negative symptom severity (PANSS-N) in the VS (MNI coordinates: x = 16, y = 14, z = −6, r = −0.507, p = 0.038). B Scatter plot showing a signiﬁcant positive association between anticipation-evoked activity and the % (percentage) of SGA users (the proportion of SZ who had ever received SGA) in the VS (MNI coordinates: x = 16, y = 2, z = 0, r = 0.533, p = 0.019). C Conceptual diagram of the moderating effect of the % of SGA users on the relationship between negative symptoms and striatum hypoactivation during reward anticipation. D Scatter plot showing a signiﬁcant negative association between outcome-evoked activity and the positive symptom severity (PANSS-P) in the mPFC (MNI coordinates: x= 0, y = 46, z = −10, r = −0.681, p = 0.043). E Scatter plot showing a signiﬁcant positive association between outcome-evoked activity and the % of SGA users in the mPFC (MNI coordinates: x = 0, y = 46, z = −10, r = 0.656, p = 0.028). F Conceptual diagram of the moderating effect of % of SGA users on the relationship between positive symptoms and mPFC hypoactivation during reward outcome. SZ schizophrenia, HC healthy controls, SGA second-generation antipsychotic, mPFC medial prefrontal cortex. group, whereas among participants in the higher SGA group, different brain regions in SZ patients are implicated in reward PANSS-P scores had a null association with mPFC activity (Fig. 3 anticipation and reward outcome during the MID task. and Supplementary Table 5). Anticipation-evoked brain responses in SZ During anticipation, we found that SZ patients exhibited reduced DISCUSSION activation in the mesocorticolimbic reward system in response to Our whole-brain meta-analysis of fMRI studies stressed the monetary incentives. Dopamine neurons in the midbrain project importance of examining the temporal phases (i.e., anticipation widely to the cortex and subcortical structures, including the VS, and outcome) of reward processing separately, as we showed dorsal striatum, amygdala, thalamus, and hippocampus. These dissociable neural substrates during reward anticipation and dopaminergic pathways play an important role in the modulation receipt. During reward anticipation, individuals with SZ showed of motivational processing and decision-making, and changes in a reduced response to reward in the mesocorticolimbic circuitry dopamine metabolism are thus considered as the central basis for involving the striatum, insula, ACC, MCC, amygdala, right the impairment of “wanting” and “learning” -related physiology in precentral gyrus, and right STG. In contrast, during reward SZ. “Wanting” refers to the motivational processing of the outcome, individuals with SZ showed increased activation in the incentive salience attributed to the reward and is mediated by striatal-limbic circuitry involving the bilateral striatum, insula, larger systems that encompass mesocorticolimbic dopaminergic amygdala, hippocampus, right parahippocampal gyrus, left transmission [57]. Generally, increases in dopaminergic transmis- cerebellum, right postcentral gyrus, right MCC, and decreased sion are associated with increases in motivated behavior, whereas activation in the mPFC and DLPFC when processing incentive disruption of dopaminergic functioning, through focal lesions or feedback. In addition, anticipation-evoked activation reductions in pharmacologically induced receptor antagonism/depletion, the VS were negatively correlated with negative symptoms of SZ, reduces motivated behavior [58]. VS response during reward whereas outcome-evoked activation reductions in the mPFC were anticipation has been previously shown to be attenuated in drug- negatively correlated with positive symptoms of SZ. The relation- naive patients, patients with chronic SZ, and individuals at high ship between symptom severity and brain activity was moderated risk for psychosis [13, 19, 59]. Moreover, the degree of reduced by the % of SGA users. This meta-analysis provided evidence that reward anticipation is linked to symptom severity [36]. Thus, our Translational Psychiatry (2022) 12:448 J. Zeng et al. Table 3. Results of the meta-analysis for brain activation difference between SZ and HC during reward outcome stage. Brain regions MNI SDM value p value Number Breakdown of voxels coordinates x, y, z P >HC Right striatum 28,10,−14 1.829 0.000118673 590 Right lenticular nucleus, putamen, BA 48 Right striatum Right amygdala, BA 34, BA 48 Right olfactory cortex, BA 11, BA 48 Right inferior network, inferior fronto- occipital fasciculus Right parahippocampal gyrus, BA 34, BA 48 Right insula, BA 48 Right superior frontal gyrus, orbital part, BA Right inferior frontal gyrus, orbital part, BA 11, BA 48 Right lenticular nucleus, putamen, BA 47 Right temporal pole, superior temporal gyrus, BA 34 Right hippocampus, BA 34 Left striatum −22,0,2 1.696 0.000289023 439 Left amygdala, BA 20, BA 28, BA 34 Left striatum Left lenticular nucleus, putamen, BA 48 Left insula, BA 48 Left pons Left inferior network, uncinate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus Left hippocampus, BA 34 Left superior temporal gyrus, BA 48 Left cerebellum −8,−36,−18 1.443 0.001243770 194 Left cerebellum, hemispheric lobule IV / V, BA 19, BA 30,, BA 37 Left cerebellum, hemispheric lobule VI, BA 19, BA 37 Left cerebellum, hemispheric lobule III, BA 30 Middle cerebellar peduncles Left cerebellum, hemispheric lobule VI, BA Right 30,−4,−26 1.676 0.000314832 176 Right fusiform gyrus, BA 20, BA 36 parahippocampal gyrus Right inferior network, inferior longitudinal fasciculus, uncinate fasciculus Right parahippocampal gyrus, BA 20, BA 28, BA 35, BA 36 Right median network, cingulum Right amygdala, BA 28, BA 36 Right hippocampus, BA 36 Right postcentral gyrus 52,−18,56 1.443 0.00120765 31 Right postcentral gyrus, BA 4, BA 6 Right precentral gyrus, BA 4, BA 6 Right middle frontal gyrus, BA 6 Right MCC 8,34,30 1.438 0.001398563 20 Right median cingulate / paracingulate gyri, BA 32 P <HC mPFC −10,52,6 −1.129 0.000010312 817 Left anterior cingulate / paracingulate gyri, BA 10, BA 11, BA 32 Left superior frontal gyrus, medial, BA 10, BA Left superior frontal gyrus, medial orbital, BA 10, BA 11 Right superior frontal gyrus, medial orbital, BA 10, BA 11 Left gyrus rectus, BA 11 Left median network, cingulum Right superior frontal gyrus, medial, BA 10 Right gyrus rectus, BA 11 Right anterior cingulate / paracingulate gyri, BA 10, BA 11 Translational Psychiatry (2022) 12:448 J. Zeng et al. Table 3. continued Brain regions MNI SDM value p value Number Breakdown of voxels coordinates x, y, z Left DLPFC −24,56,20 −1.033 0.000051618 442 Left middle frontal gyrus, BA 9, BA 10, BA 46 Left superior frontal gyrus, dorsolateral, BA 9, BA 10, BA 46 Right DLPFC 22,20,62 −1.036 0.000025809 143 Right superior frontal gyrus, dorsolateral, BA Results were threshold at p = 0.005, peak height threshold of 1, extent threshold of 10. BA Brodmann area; P patients; HC healthy controls, MCC median cingulate cortex, mPFC medial prefrontal cortex, DLPFC dorsolateral prefrontal cortex, SDM seed-based d mapping, MNI Montreal Neurological Institute. ﬁndings of reduced striatal activity in SZ when anticipating a Outcome-evoked responses in SZ monetary reward, likely reﬂect a blunted attribution of motiva- In contrast, at the reward outcome stage, SZ showed elevated tional salience to monetary stimuli. activations in the striatal-limbic circuitry, including the bilateral VS, Reward anticipation is also associated with the deactivations of amygdala, insula, hippocampus, right parahippocampal gyrus, left the ACC and insula region, as proposed by the aberrant salience cerebellum, right postcentral gyrus, and right MCC, and dimin- hypothesis [60, 61]. Aberrant salience refers to an abnormally ished activations in the mPFC and DLPFC. Impaired neural reduced response to a reward or related stimuli but a heightened processing during reward outcome may be independent from response to neutral or irrelevant stimuli. The salience network (SN) motivational components given that hedonic impact was found to which mainly comprises the ACC and insula, is thought to cause be independent from anticipation effects. Our meta-analysis such aberrant salience attribution [62]. The ACC has extensive revealed that SZ showed stronger activation in the VS during connections with a set of other limbic and related areas including the receipt of a reward, perhaps indicating an elevated reactivity the amygdala, OFC, and STG, and is involved in reward-related to rewarding outcomes. Consistent with our ﬁndings, past processing by encoding reward outcomes and determining the research reported that striatal activation is associated with reward effort required to obtain rewards [63]. The insular cortex has outcome and that SZ patients reveal higher striatum signals emerged in the last few years as a key region in SZ research and is during the outcome phase [54]. Furthermore, animal studies considered to be a crucial relay center of interoceptive signals that supported the involvement of the VS in the experience of pleasure integrates with exteroceptive awareness [64]. A previous major and hedonic perception of rewards [78]. As part of the limbic depressive disorder (MDD) study showed that the functional structures, the VS, amygdala, and insula are thought to play a activity and functional connectivity (FC) of the insula were signiﬁcant role in guiding behavior and facilitating learning. A important indicators of electroconvulsive therapy [65]. Several growing body of evidence suggests that the amygdala is critical SZ studies have reported the reduced gray matter and/or for feedback-guided learning behavior, and VS reﬂects the functional activity and FC within the insula–ACC SN [66, 67]. encoding of expected value of outcome and action selection for Palaniyappan and colleagues have proposed that dysfunction of the obtainment of rewards [79, 80], whereas the parahippocampal the insula–ACC SN is linked to the psychotic symptoms of SZ by gyrus is related to prediction errors [81, 82]. A similar pattern of inappropriately allocating salience to irrelevant internal or external activation within limbic regions has been reported during the stimuli [68]. Reduced FC within brain regions involving the ACC receipt of a reward [22, 25, 54]. Regarding the preferential and insula was proven to be associated with heightened affective involvement of the limbic-striatal areas in hedonic processes, the and anxiety symptoms and an increased risk of developing ﬁndings of over-responsiveness to rewarding outcome may reﬂect psychiatric disorders [69, 70]. Incentive valence, behavioral the presumed motivational signiﬁcance of hedonic experience relevance, or expectancy violation would determine the proces- underlying the reward-seeking behavior. sing the stimulus salience of momentary reward and lead to a Outcome-related increased activity was also present in the change in the brain state [68, 71]. Therefore, abnormalities in the cerebellum in SZ patients. Evidence indicates that the cerebellum mesolimbic system and the cortical SN detected when individuals plays a role in higher cortical functions, such as emotional are performing the MID task may help explain abnormal reinforcer processing and social cognition [83, 84]. It has been proposed that processing and symptoms, which appears to be a prominent the cerebellum encodes error signals and participates in feedback- characteristic of the pathophysiology of SZ. based learning. Recent ﬁndings of altered error processing in Blunted activations in the right STG and precentral gyrus of patients with cerebellar lesions conﬁrmed the hypothesis that SZ patients in response to monetary stimuli were also found feedback processing might be affected by cerebellar damage during anticipation. Decreased gray matter volume and [85, 86]. Notably, cerebellar dysfunction and hyperconnectivity changed functional activation and FC in the STG have been patterns in the cerebello-thalamo-cortical circuit have been robustly implicated in the neurophysiology of SZ [72–74]. consistently observed in SZ [87–89]. Our ﬁnding of exaggerated Pertinently, the STG plays a key role in language perception, cerebellar activation in the reward reception phase appears to which is consistent with previous reports linking this region reﬂect the importance of cerebellum in controlling the reward with auditory hallucinations in SZ [75]. However, the temporal process in psychosis. area is sensitive to socially relevant information and may also Reduced activation in response to reward was observed in the be linked to incentive salience processing [76]. The precentral DLPFC and mPFC during the outcome. Pertinently, the prefrontal gyrus has also been associated with behavioral responses to cortex is a heterogeneous area that is critical to reward-based motivationally signiﬁcant events [77]. Abnormally reduced decision-making. Studies have demonstrated that the DLPFC is reward-related activity in the precentral gyrus and STG in SZ implicated in higher-order cognitive control, especially for reward would imply a reduction in salience to rewarding events, as well values and effort calculations [90, 91], whereas the mPFC is a key as motivated goal-directed behavior by associations with node for emotion-related reward processes and value-based reinforcing events. decision-making through interactions with the VS and amygdala Translational Psychiatry (2022) 12:448 J. Zeng et al. [92, 93]. Furthermore, reduced FC in medial prefrontal-striatal accordance, previous reports show that the more serious network is related to disrupted cognitive control and reward negative symptoms are, the stronger the reduction in striatal processing [94]. Promoting local, long-range, and dynamic activation under the condition that patients took fewer SGA connectivity within the frontal areas could effectively improve [13, 35]. Moreover, the striatal activation reduction was cognitive function [95]. Because the PFC exerts top-down control inversely correlated with the severity of negative symptoms in over striatal dopamine-induced activity and drives synchrony patients being not treated with SGA [98]. A recent European between speciﬁc corticolimbic circuit regions [96], we speculated Psychiatric Association guidance paper argued SGA (i.e., that reduced cortical excitability in the prefrontal region might amisulpride) has certain potential in the treatment of negative trigger elevated striatal and limbic responses. symptoms and suggested that a switch to SGA should be considered for patients who are treated with FGA [105]. Correlations between clinical symptoms and brain activity at additionally, a randomized controlled trial revealed that SGA different reward stages showed statistically signiﬁcant effects on negative symptoms During reward anticipation, the meta-regression analysis revealed [106]. In the present study, we present preliminary evidence for a signiﬁcant negative correlation between VS hypoactivation and a moderating role of SGA in the relationship between clinical the severity of negative symptoms. In line with this, a strong symptoms and brain activity. The symptom-brain relationship is association of reduced VS activation during reward anticipation complex, and further studies of how this relationship changes with negative symptoms was observed in previous studies as modulation of antipsychotic treatment need to be validated [13, 16]. As the activity of this region mediates incentive in controlled clinical trials. motivation or wanting of reward, this result may suggest that impaired striatal activity is involved in the pathophysiology of The heterogeneity in the subgroup analyses of anticipation motivational deﬁcits in SZ patients. A similar result was observed stage in our meta-analysis in the association with current antipsychotic Notably, the results showed that the brain activity in the right drug use. Speciﬁcally, we found that VS hypoactivation was STG did not survive in the subgroup analyses for studies positively associated with the % of SGA users. Consistent with this including chronic SZ patients and studies including SZ patients ﬁnding, Juckel and colleagues reported an improvement in receiving medication treatment. The medial-temporal lobe, reduced VS activity in patients taking SGA but not in those taking including the STG, is probably the most extensively investigated FGA or those who were unmedicated [97]. Since SGA has less brain structure in SZ. STG is believed to be a major anatomical blockade of striatal D receptors, it may enhance the treatment of substrate for auditory hallucinations and thought disorders in negative symptoms and maintain motivation to reach potential SZ [107]. Although STG abnormalities have been well demon- rewards owing to less blockade of striatal D receptors [98]. In this strated in SZ, some studies have reported negative results for regard, the linkages between blunted striatal anticipating function STG abnormalities [36, 51, 53]. A meta-analysis of voxel-based and negative symptoms would help to explain the different facets morphometry in SZ reported that 6 of 15 studies showed no of reward processing in the correlation of behavioral disturbances. signiﬁcant brainvolumedifferenceinthe STGwhencompared During reward outcome, our meta-regression analysis further with controls [108]. Furthermore, an attenuated response in the revealed that reward-related hypoactivity in the mPFC was STG during the anticipation of monetary incentives has been negatively associated with positive symptoms. Dysfunction in found in medication-free SZ patients but not in medicated the mPFC may result in hallucinations and delusions [26]. Several patients [14, 36]. It is well known that SZ is a chronic psychiatric postmortem and fMRI studies have provided evidence for disorder that can be effectively controlled but likely requires abnormal anatomical and FC of the mPFC, which is implicated lifelong treatment. Previous neuroimaging studies of SZ in psychiatric symptoms and impaired cognitive function in SZ examined chronically ill patients, for whom ﬁndings are and MDD patients [99, 100]. For example, previous studies found potentially inﬂuenced by disease course and medication. that hyperconnectivity between the mPFC and default mode Exposure to antipsychotic drugs may have an effect on brain network was correlated with more serious positive symptoms in structure and function [109–111]. For example, increased SZ patients [101]. Along similar lines, an association between cortical thickness and increased anticipation-related brain disrupted error feedback in the mPFC and delusion severity was activity in the STG over treatment time have been observed, observed [102]. Our study also found that mPFC activation was which is associated with symptomatic improvement [36, 112]. positively associated with the % of SGA users during the outcome Importantly, it has been suggested that the improvement of phase. As mentioned above, SGA administration could improve positive symptoms was signiﬁcantly associated with the the dysfunction of the PFC and positive symptoms. Our meta- normalization of reward-related activation [36]. SZ patients regression results suggested that the neural processing of reward who show a long illness duration may also experience a outcomes in the mPFC may be related to the pathophysiology of neurotoxic effect on their brain structure and function positive symptoms in SZ patients. Notably, although the regres- [113, 114]. Furthermore, the STG can be cytoarchitectonically sion analysis results during reward outcome are statistically and functionally divided into several subdivisions [115]. The signiﬁcant, they are preliminary and require future research to complexity and heterogeneity of the STG may account for the obtain a better understanding of their effects. inconsistency. Our exploratory moderation analyses revealed that SGA use In addition, our current subgroup analysis of studies that was a signiﬁcant moderator of the symptom-brain relationship applied a 3-T MRI scanner also found that STG activity showed during reward anticipation and outcome: results were negative some heterogeneity. Different studies used different MRI in patients taking fewer SGAs and null in patients taking more scanners with different MRI ﬁeld strengths, which could SGAs. In patients in the group taking more SGA, negative introduce potential bias. One possible explanation for this is symptoms presented a null association with brain activity. It is that in a high-strength ﬁeld, echo planar imaging results in a well documented that SGA is presumed to act as a treatment for higher signal-to-noise ratio but also increases susceptibility negative symptoms [103] and multiple neuroprotective effects artifacts [116]. In particular, it is inﬂuenced in regions with on the brain [104]. It is likely that SGA affect symptoms and the susceptibility artifacts, especially for imaging the temporal brain simultaneously, and thereby reduces and weakens the lobes [117]. Future studies should investigate the inﬂuence of link between symptoms and brain activity in patients taking different magnetic strengths on imaging presentation, and more SGA; On the other hand, in patients taking fewer SGA, the meta-analyses with homogeneous magnetic ﬁeld strength are symptoms were inversely related to brain activity. In needed to conﬁrm this ﬁnding. Translational Psychiatry (2022) 12:448 J. Zeng et al. Clinical implications CONCLUSION The biological markers of different stages of reward processing The present study examined neural mechanisms underlying may help elucidate the complex and multifaceted symptoms as different phases of reward processing in SZ patients and their well as neurobehavioral disruptions observed in SZ patients. relevance to clinical symptomology. Patients with SZ showed Dysfunction in reward processing is regarded in the DSM-5 as a hypoactivation in the mesocorticolimbic circuit during reward key factor in the anhedonic symptoms of SZ [118]. Previous anticipation and elevated activation in the striatal-limbic circuitry studies found that SZ patients have impaired motivation to pursue but reduced responses in the DLPFC and mPFC were elicited by rewards and reduced activation in the reward pathway during the monetary outcomes. Anticipation-evoked VS hypoactivation was presentation of reward stimuli, although pleasure in consuming linked to negative symptoms, and outcome-evoked mPFC rewards is largely intact [7]. Deﬁcits in any reward component, activation was linked to positive symptoms. Our ﬁndings showed including reward valuation, reward expectancy, and action dissociated neurobiological mechanisms in different aspects of selection, may preclude an individual from engaging in goal- reward processing and have the potential to clarify the complex directed actions for rewards, regardless of whether the reward is brain-behavior relationships in SZ. perceived as pleasurable once obtained. In other words, the construct of anhedonia that reﬂects deﬁcits in hedonic capacity is closely linked to the constructs of reward anticipation, valuation, REFERENCES and motivation. In our meta-analysis, we found that anticipation 1. Howes OD, Murray RM. 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Clinical, available at https://doi.org/10.1038/s41398-022-02201-8. behavioral, and neural measures of reward processing correlate with escitalopram response in depression: a Canadian Biomarker Integration Network in Depression Correspondence and requests for materials should be addressed to Xun Yang. (CAN-BIND-1) Report. Neuropsychopharmacology. 2020;45:1390–1397. 121. Cheung MW, Vijayakumar R. A guide to conducting a meta-analysis. Neu- Reprints and permission information is available at http://www.nature.com/ ropsychol Rev. 2016;26:121–128. reprints Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional afﬁliations. ACKNOWLEDGEMENTS This work was supported by the National Natural Science Foundation of China (grant number 31700964); Fundamental Research Funds for the Central Universities of China (grant number 2020CDJSK01XK02); Graduate research and innovation foundation of Chongqing (grant number CYB22053); the Venture & Innovation Open Access This article is licensed under a Creative Commons Support Program for Chongqing Overseas Returnees (grant numbers cx2019154, Attribution 4.0 International License, which permits use, sharing, cx2020119); the Social Science Foundation of Chongqing (grant number adaptation, distribution and reproduction in any medium or format, as long as you give 2020YBGL80); the Research on Teaching Reform Program of Chongqing University appropriate credit to the original author(s) and the source, provide a link to the Creative (grant number 2019Y04) and the Key R&D Projects of Science and Technology Commons license, and indicate if changes were made. The images or other third party Department of Sichuan Province (grant number 2019YFS0217). material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory AUTHOR CONTRIBUTIONS regulation or exceeds the permitted use, you will need to obtain permission directly J.Z., and X.Y. contributed to the study conception and design and supervised the from the copyright holder. To view a copy of this license, visit http:// study. J.Y., H.C., Y. Su, Y. Song, and Y.L. contributed to the analysis and manuscript creativecommons.org/licenses/by/4.0/. preparation; J.Y., Y. Su, Y. Song, and Y.L. helped perform the analysis with constructive discussions. X.Y., H.C., and J.Z. wrote the manuscript, which was reviewed by all authors and approved for publication. © The Author(s) 2022 Translational Psychiatry (2022) 12:448 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Translational Psychiatry Springer Journals http://www.deepdyve.com/lp/springer-journals/neural-substrates-of-reward-anticipation-and-outcome-in-schizophrenia-1bbDwg2yV0

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Publisher: Springer Journals
Copyright: Copyright © The Author(s) 2022
eISSN: 2158-3188
DOI: 10.1038/s41398-022-02201-8
Publisher site: See Article on Publisher Site

Abstract

Translational Psychiatry www.nature.com/tp SYSTEMATIC REVIEW OPEN Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI ﬁndings in the monetary incentive delay task 1,6 1,6 2,3,6 4 4 5 4✉ Jianguang Zeng , Jiangnan Yan , Hengyi Cao , Yueyue Su , Yuan Song ,YaLuo and Xun Yang © The Author(s) 2022 Dysfunction of the mesocorticolimbic dopaminergic reward system is a core feature of schizophrenia (SZ), yet its precise contributions to different stages of reward processing and their relevance to disease symptomology are not fully understood. We performed a coordinate-based meta-analysis, using the monetary incentive delay task, to identify which brain regions are implicated in different reward phases in functional magnetic resonance imaging in SZ. A total of 17 studies (368 SZ and 428 controls) were included in the reward anticipation, and 10 studies (229 SZ and 281 controls) were included in the reward outcome. Our meta-analysis revealed that during anticipation, patients showed hypoactivation in the striatum, anterior cingulate cortex, median cingulate cortex (MCC), amygdala, precentral gyrus, and superior temporal gyrus compared with controls. Striatum hypoactivation was negatively associated with negative symptoms and positively associated with the proportion of second- generation antipsychotic users (percentage of SGA users). During outcome, patients displayed hyperactivation in the striatum, insula, amygdala, hippocampus, parahippocampal gyrus, cerebellum, postcentral gyrus, and MCC, and hypoactivation in the dorsolateral prefrontal cortex (DLPFC) and medial prefrontal cortex (mPFC). Hypoactivity of mPFC during outcome was negatively associated with positive symptoms. Moderator analysis showed that the percentage of SGA users was a signiﬁcant moderator of the association between symptom severity and brain activity in both the anticipation and outcome stages. Our ﬁndings identiﬁed the neural substrates for different reward phases in SZ and may help explain the neuropathological mechanisms underlying reward processing deﬁcits in the disorder. Translational Psychiatry (2022) 12:448 ; https://doi.org/10.1038/s41398-022-02201-8 INTRODUCTION used task to probe neural substrates of different reward processing Schizophrenia (SZ) is one of the most severe neuropsychiatric stages in healthy individuals and those with mental disorders disorders characterized by diverse symptoms including delusions, [9, 10]. In the MID task, subjects see a cue indicating that they will hallucinations, and thought disorders [1, 2]. Abnormal reinforce- have an opportunity to obtain a certain amount of monetary ment learning and representations of reward value are present in reward, respond to a given target, and receive immediate feedback SZ, and these impairments can manifest as deﬁcits in reward on whether they have successfully obtained the reward (see decision making [3]. Accumulating evidence suggests that reward Supplementary Materials). The anticipation phase is deﬁned by the processing abnormalities in SZ patients may arise from dopami- introduction of a cue informing participants about an upcoming nergic dysfunction within the mesocorticolimbic circuit, including potential reward, and the outcome phase refers to the period the dorsolateral prefrontal cortex (DLPFC), orbital prefrontal cortex when a reward is presented [11]. The investigation of reward (OFC), medial prefrontal cortex (mPFC), anterior cingulate cortex processing in healthy adults revealed that anticipation of reward (ACC), ventral striatum (VS, including the nucleus accumbens), was associated with the activation of multiple regions including ventral pallidum, amygdala, hippocampus and thalamus [4–6]. the striatum, ACC, anterior insula, and the central executive and Dysregulated dopaminergic modulation of reward processing is default networks [11], while the OFC and mPFC were activated considered to be fundamental to the symptoms of SZ and is often during the reward outcome phase [12]. This implies that the neural reported to be an important predictor of poor functional outcome substrates of the two stages are likely to be associated with distinct [7, 8]. patterns of activation and connectivity [12]. Based on recent studies, reward processing includes two phases To date, present studies have examined and identiﬁed several temporally, namely, the reward anticipation and reward outcome likely neural substrates for the anticipation and outcome of [9]. The monetary incentive delay (MID) task is the most widely incentives in SZ. However, due to the heterogeneity of reward 1 2 School of Economics and Business Administration, Chongqing University, Chongqing 400044, China. Center for Psychiatric Neuroscience, Feinstein Institute for Medical 3 4 Research, Hempstead, NY, USA. Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA. School of Public Affairs, Chongqing University, Chongqing 5 6 400044, China. Department of Psychiatry, State Key Lab of Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China. These authors contributed equally: Jianguang Zeng, Jiangnan Yan, Hengyi Cao. email: [email protected] Received: 19 March 2022 Revised: 21 September 2022 Accepted: 22 September 2022 1234567890();,: J. Zeng et al. paradigms and the bias introduced by including region of interest selected articles and relevant review articles to include more (ROI) analysis, the existing results are still inconsistent. During relevant studies. For studies without available coordinates at the reward anticipation, although several studies revealed reduced VS whole-brain level, we asked the authors whether they could activity in SZ [13–16], other studies reported reduced activations provide such information. Details of the literature search and in the posterior cingulate cortex and temporal regions [17]. selection were reported in Fig. 1. Compared with healthy controls (HC), activation in the VS in Studies were eligible if they met the following criteria: (1) patients was found to be either reduced or not signiﬁcantly articles that included patients (aged >18 years) diagnosed with changed (Supplementary Table 1). Reward anticipation abnorm- SZ, schizoaffective disorder, or another psychosis spectrum alities have been implicated in the pathophysiology of negative disorder based on the Diagnostic and Statistical Manual of symptoms, such as anhedonia and avolition in SZ patients [16, 18]. Mental Disorders (DSM) or International Statistical Classiﬁcation However, there is also evidence suggesting correlations between of Diseases and Related Health Problems (ICD) diagnostic anticipation dysfunction and the severity of positive symptoms criteria; (2) articles that investigated brain functional activity at [14, 19]. In terms of reward outcome, the role of striatum is the whole-brain level between adult SZ patients and HC; (3) relatively uncertain. Some behavioral and neuroimaging data have articles that used a standardized MID task or modiﬁed MID task; shown intact responses during the outcome phase [20, 21], while (4) articles that examined neuronal activity related to the MID other data have shown either hyperactivity or hypoactivity in the task using fMRI; (5) articles that identiﬁed foci of task-related striatum during monetary receipt [22–24]. Most studies report that neural changes in anticipation phase and/or outcome phase; outcome-related neural response in SZ patients is associated with and 6) articles that reported signiﬁcant resultsas3Dcoordinates both positive symptoms [25, 26] and negative symptoms [14]. in either the Talairach Atlas (Tal) or Montreal Neurological Such inconsistencies may be attributed to the small sample size, Institute (MNI) space. sample heterogeneity, and differences in paradigm design among The exclusion criteria were as follows: (1) case reports, book studies. chapters, reviews, or meta-analyses; (2) non-English articles; (3) Currently, an updated quantitative meta-analysis method called studies that included only ROI or volume of interest (VOI) ﬁndings; seed-based mapping (SDM) has emerged as a useful approach to and (4) studies in which the coordinates were not available in the identify spatially consistent brain changes reported in the article or after contacting the authors. Six fMRI studies did not literature through the use of the coordinate information reported provide group differences between SZ and HC and were thus not in each study. Few meta-analyses thus far have focused on included in our meta-analysis [23, 29–33]. Of four studies using dissociated neural responses during reward anticipation and overlapping samples [14, 34–36], the one with more subjects [14] outcome in SZ, although an increasing number of functional and the most recent study [35] were included. One study was magnetic resonance imaging (fMRI) studies have reported excluded because the SZ patients had comorbid Parkinson’s potential neural substrates of reward processing. Radua and his disease [37]. colleagues used meta-analysis to reveal alterations in VS activity during reward anticipation, feedback, and prediction error [16]. Data extraction However, VS activation in this meta-analysis was based on ROI Data extraction was independently performed and checked by approach, which would be affected by the different VS deﬁnitions two authors. The following data were extracted: the sample sizes, across the included studies. Furthermore, both individuals with SZ the mean age, the percentage of males, the duration of illness, the and those at high risk for psychosis were included in the study, severity of symptoms (Positive and Negative Syndrome Scale-Total complicating the reported results. Another meta-analysis per- (PANSS-T), PANSS-Positive (PANSS-P), PANSS-Negative (PANSS-N)), formed a whole-brain meta-analysis but only focused on the the proportion of SZ who had ever received ﬁrst-generation anticipation of reward tasks [27], while the neural substrates antipsychotics (% (percentage) of FGA users)/ second-generation underlying different reward processing phases remain unclear. antipsychotics (% of SGA users), and methodological items. Here, we performed an in-depth meta-analysis to elucidate the neurobiological basis underlying different stages of reward Meta-analysis of relevant studies processing between SZ and HC. To overcome the limitations of MID-related activation differences were analyzed using SDM previous meta-analysis work, we only included fMRI studies that (version 5.15, https://www.sdmproject.com), a novel voxel-based performed a whole-brain analysis of patients as they completed meta-analytic approach that uses the reported peak coordinates the MID paradigm and analyzed reward anticipation and reward to recreate maps depicting the effect size of group differences in outcome independently. We also explored whether brain functional activations. Peak coordinates were recreated by ﬁrst responses during different reward processes were associated with converting the peak t value to Hedges’ effect size and then symptom severity using meta-regression analysis. We expected applying a normalized Gaussian kernel to the voxels close to the that reward anticipation and reward outcome would recruit peak. In addition to evaluating the probability of a peak, SDM can different brain regions in SZ patients, and that the abnormal be used to recreate maps of the signed (i.e., positive and negative) neural activations during different stages of reward processing functional activation or differences between patients and HC by would be closely related to the severity of symptoms. using the reported peak coordinates, which makes SDM an optimal method for comparing patients and controls without biasing the results [38]. The statistical maps are created by MATERIALS AND METHODS calculating the corresponding statistics from the study maps and Study search and selection weighted by the squared root of the sample size of each study, Following recommended guidelines in the Preferred Reporting amplifying the contributions of studies with larger sample sizes Items for Systematic Reviews and Meta-Analyses statement [28], [38]. two authors independently searched the PubMed, Web of Science, The SDM has more advantages than other methods, such as the and ScienceDirect databases for relevant articles from January arbitrary Lagrangian-Eulerian (ALE) method. First, instead of 2000 to May 2021, using the following terms: (1) “schizophrenia” computing coordinates of increased and decreased activation OR “schizophrenic” OR “schizoaffective” OR “psychoses” OR separately, SDM can reconstruct both positive and negative “psychosis” OR “psychotic” OR “ﬁrst episode psychosis” OR “FEP”, differences in the same map [39]. Second, studies reporting no (2) “functional magnetic resonance imaging” OR “fMRI” OR group differences can also be included. To date, SDM has been “neuroimaging”, and (3) “monetary incentive delay task” OR widely applied in previous meta-analyses of structural and “MID”. We also manually examined the reference lists of the functional MRI studies [40–44]. Translational Psychiatry (2022) 12:448 J. Zeng et al. Fig. 1 Preferred reporting items for systematic reviews and meta-analyses (PRISMA) ﬂow diagram. Of 548 articles initially identiﬁed, a total of 17 studies were enrolled for the reward anticipation meta-analysis, and 10 studies were enrolled for the ﬁnal reward outcome meta- analysis. MID monetary incentive delay, fMRI functional magnetic resonance imaging, ROI regions of interest, VOI volume of interest. We closely followed the steps taken in the published Main meta-analysis. In the pooled meta-analysis of reward literatures [45, 46]. In brief, peak coordinates of group anticipation, relative to HC, SZ exhibited lower activations in the differences and corresponding statistics were extracted from striatum (with extension to the insula and amygdala), ACC, median the included articles and then input into SDM software. cingulate cortex (MCC), right precentral gyrus and right superior Measurements (z scores and temporal gyrus (STG) in response to monetary stimuli. No brain p values) were converted into t values in advance. Standard regions showed increased activation in SZ patients compared to MNI maps of the activation differences were created using a HC (Table 2 and Fig. 2). Gaussian kernel, and the mean map was calculated represent- ing the weighted mean functional differences during the MID Sensitivity analysis. As illustrated in Supplementary Table 2, task. Statistical signiﬁcance was assessed by permutation whole-brain jackknife sensitivity analysis conﬁrmed that hypoacti- testing. The default kernel size and statistical thresholds (full vation in the bilateral striatum, ACC and MCC maintained width at half maximum [FWHM] = 20 mm, p = 0.005, peak signiﬁcance in all but one combination. The results in the right height threshold = 1, extent threshold = 10) were used to precentral gyrus and right STG maintained signiﬁcance in all but balance sensitivity and speciﬁcity [44, 46, 47]. two combinations. In addition, to assess the robustness of the ﬁndings, complementary analyses were performed, including jackknife Subgroup analyses. To control for any possible differences sensitivity analyses, subgroup analyses and meta-regression observed between studies, subgroup analyses were repeated analyses. Based on the results of meta-regression, we also several times to include only those studies that were clinically and conducted moderation analyses using a standard model [48, 49] methodologically homogenous. Therefore, we conducted sub- (see Supplementary Materials). group analysis for those studies only including chronic SZ, for those including SZ patients diagnosed by DSM, for those including SZ patients receiving medication treatment, for those using a 3-T RESULTS MRI scanner, for those using SPM software, and for those reporting MID-related brain activation differences between SZ and HC coordinates corrected for comparisons. The subgroup analysis during reward anticipation revealed that all of the aforementioned results were highly Included studies and sample characteristics. Seventeen studies replicable, except for decreased activation in the right precentral with 368 SZ and 428 HC were included in the comparison of SZ and gyrus and right STG (Supplementary Table 2). HC during reward anticipation [13–15, 17, 19, 22, 24–26, 35, 50–56] (Table 1 and Fig. 1). The mean age between SZ (32.10 years) and HC Meta-regression analyses. We next tested correlations between (32.36 years) was not signiﬁcantly different (t=−0.524, p= 0.199). anticipation-evoked activations and demographic and clinical The percentage of males among SZ patients (75.00% male) and variables, including the mean age, the percentage of males, the controls (70.01% male) was also not signiﬁcantly different duration of illness, the symptom severity and the medication (χ = 2.382, p= 0.123). variables. There were no signiﬁcant correlations between brain Translational Psychiatry (2022) 12:448 J. Zeng et al. Translational Psychiatry (2022) 12:448 Table 1. Demographic and clinical characteristics of the studies included in the meta-analysis. Studies Schizophrenia Healthy controls Methodology Phase of illness No. (male) Mean age Medication Diagnosis criteria No. (male) Mean age MRI scanner SPM Threshold Anticipation stage Abler et al., [22] Chronic SZ 12 (5) 36.70 SGA & FGA DSM-IV 12 (7) 36.20 3 T Y Uncorrected, p < 0.005 Alves et al., [17] FEP 10 (10) 22.70 SGA & FGA DSM-IV 12 (12) 34.55 3 T Y Corrected, p < 0.05 Arrondo et al., [50] Chronic SZ 22 (19) 32.73 SGA & FGA DSM-IV 21 (17) 34.33 3 T N Corrected, p < 0.05 Esslinger et al., [19] FEP 27 (20) 27.80 N DSM-IV 27 (20) 27.10 3 T Y Corrected, p < 0.05 Gilleen et al., [51] Chronic SZ 20 (20) 36.50 SGA & FGA DSM-IV 12 (12) 30.70 3 T Y Corrected, p < 0.05 Juckel et al., [13] Chronic SZ 10 (10) 26.80 N DSM-IV & ICD-10 10 (10) 31.70 1.5 T Y Uncorrected, p < 0.001 Koch et al., [35] Chronic SZ 44 (27) 34.20 SGA & FGA DSM-IV & ICD-10 44 (35) 37.10 1.5 T Y Corrected, p < 0.05 Li et al., [24] Chronic SZ 26 (15) 22.77 SGA DSM-IV 26 (15) 24.58 3 T Y Corrected, p < 0.001 Mucci et al., [52] Chronic SZ 28 (18) 33.10 SGA DSM-IV 22 (10) 31.91 3 T Y Corrected, p < 0.05 Nielsen et al., [14] FEP 31 (22) 25.90 N ICD-10 31 (22) 25.70 3 T N Corrected, p < 0.05 Schlagenhauf et al., [56] Chronic SZ 10 (9) 30.50 FGA DSM-IV 10 (9) 31.80 1.5 T Y Corrected, p < 0.05 Schlagenhauf et al., [26] Chronic SZ 15 (12) 30.10 N DSM-IV 15 (12) 30.10 1.5 T Y Corrected, p < 0.05 Schwarz et al., [55] Chronic SZ 27 (18) 32.40 SGA & FGA DSM-IV 110 (54) 30.40 3 T Y Corrected, p < 0.05 Stepien et al., [53] Chronic SZ 16 (14) 32.60 SGA DSM-IV 23 (11) 29.50 3 T Y Corrected, p < 0.05 Subramaniam et al., [15] Chronic SZ 37 (25) 45.14 SGA & FGA DSM 20 (14) 43.72 3 T Y Uncorrected, p < 0.001 Walter et al., [54] Chronic SZ 16 (8) 38.00 SGA DSM-IV 16 (7) 33.00 3 T Y Uncorrected, p < 0.001 Waltz et al., [25] Chronic SZ 17 (13) 37.80 SGA & FGA DSM-IV 17 (12) 37.80 3 T N Corrected, p < 0.05 Outcome stage Abler et al., [22] Chronic SZ 12 (5) 36.70 SGA & FGA DSM-IV 12 (7) 36.2 3 T Y Uncorrected, p < 0.005 Gilleen et al., [51] Chronic SZ 20 (20) 36.50 SGA & FGA DSM-IV 12 (12) 30.7 3 T Y Corrected, p < 0.05 Li et al., [24] Chronic SZ 26 (15) 22.77 SGA DSM-IV 26 (15) 24.58 3 T Y Corrected, p < 0.001 Mucci et al., [52] Chronic SZ 28 (18) 33.10 SGA DSM-IV 22 (10) 31.91 3 T Y Corrected, p < 0.05 Nielsen et al., [14] FEP 31 (22) 25.90 N ICD-10 31 (22) 25.70 3 T N Corrected, p < 0.05 Schlagenhauf et al., [26] Chronic SZ 15 (12) 30.10 N DSM-IV 15 (12) 30.10 1.5 T Y Corrected, p < 0.05 Schwarz et al., [55] Chronic SZ 27 (18) 32.40 SGA & FGA DSM-IV 110 (54) 30.40 3 T Y Corrected, p < 0.05 Subramaniam et al., [15] Chronic SZ 37 (25) 45.14 SGA & FGA DSM 20 (14) 43.72 3 T Y Uncorrected, p < 0.001 Walter et al., [54] Chronic SZ 16 (8) 38.00 SGA DSM-IV 16 (7) 33.00 3 T Y Uncorrected, p < 0.001 Waltz et al., [25] Chronic SZ 17 (13) 37.80 SGA & FGA DSM-IV 17 (12) 37.80 3 T N Corrected, p < 0.05 No. number, ICD-10 international statistical classiﬁcation of diseases and related health problems, 10th Edition DSM-IV diagnostic and statistical manual of mental disorders, 4th Edition, SZ schizophrenia, FEP ﬁrst episode psychosis, HC healthy controls, SGA second-generation antipsychotics, FGA ﬁrst-generation antipsychotics, Y yes, N no. J. Zeng et al. Table 2. Results of the meta-analysis for brain activation difference between SZ and HC during reward anticipation stage. Brain regions MNI SDM value p value Number Breakdown of voxels coordinates x, y, z P <HC Bilateral striatum −8,4,6 −2.662 ~0 2956 Right striatum Right lenticular nucleus, putamen, BA 11, BA 25, BA 48 Right caudate nucleus Left caudate nucleus, BA 25 Right caudate nucleus, BA 11, BA 25 Right olfactory cortex, BA 11, BA 25, BA 48 Right amygdala, BA 34, BA 48 Left striatum Right inferior network, uncinate fasciculus, inferior fronto-occipital fasciculus Right gyrus rectus, BA 11, BA 25, BA 48 Right superior longitudinal fasciculus III Right insula, BA 48 Right median network, cingulum Left olfactory cortex, BA 25 Right hippocampus, BA 34 ACC & MCC 0,12,24 −2.620 0.000005186 1931 Left median cingulate / paracingulate gyri, BA 23, BA 24, BA 32 Right median cingulate / paracingulate gyri, BA 23, BA 24, BA 32 Left anterior cingulate / paracingulate gyri, BA 10, BA 24, BA 32 Left median network, cingulum Right anterior cingulate / paracingulate gyri, BA 24, BA 32 Right median network, cingulum Left superior frontal gyrus, medial, BA 8, BA 24, BA 32 Left supplementary motor area, BA 8, BA 24, BA Right superior frontal gyrus, medial, BA 32 Right supplementary motor area, BA 32 Right precentral gyrus 50,4,36 −1.919 0.000526428 244 Right precentral gyrus, BA 4, BA 6, BA 44 Right middle frontal gyrus, BA 6, BA 9, BA 44 Right inferior frontal gyrus, opercular part, BA 44 Right postcentral gyrus, BA 4, BA 6 Right STG 62,0,−4 −1.693 0.001878560 30 Right superior temporal gyrus, BA 21, BA 38, BA Right temporal pole, superior temporal gyrus, BA 21, BA 38, BA 48 Results were threshold at p = 0.005, peak height threshold of 1, extent threshold of 10. BA Brodmann area, P patients, HC healthy controls, ACC anterior cingulate cortex, MCC median cingulate cortex, STG superior temporal gyrus, SDM seed-based d mapping, MNI Montreal Neurological Institute. MID-related activations and mean age (available in 17 studies), brain association was dependent on a third variable (including the between brain MID-related activations and percentage of males age, the sex and the medication) through the moderation analysis. (available in 17 studies), between brain MID-related activations Our moderation analysis revealed that the interactions of brain × and duration of illness (available in 12 studies), between brain age and brain × sex were not statistically signiﬁcant. In the test of MID-related activations and PANSS-P (available in 14 studies), and the moderation effect of medication, the interaction of the % of between brain MID-related activations and the % of FGA users SGA users and negative symptoms signiﬁcantly improved model (available in 17 studies) during reward anticipation. Meta- ﬁt, suggesting a moderating effect of the % of SGA users on the regression analyses revealed that the severity of negative relationship between negative symptom severity and VS activity symptoms (available in 15 studies) was negatively associated with (R change = 0.263, B = 0.173, p = 0.019). That is, for individuals in anticipation-evoked hypoactivation in the VS (MNI coordinates: the lower SGA group, a higher PANSS-N score was associated with x = 16, y = 14, z = −6, r = −0.507, p = 0.038). In addition, the % of more decreased striatum activation, while for individuals in the SGA users (available in 17 studies) was positively related to the VS higher SGA group, negative symptoms presented a null associa- activation (MNI coordinates: x = 16, y = 2, z = 0, r = 0.533, tion with striatum activity (Fig. 3 and Supplementary Table 3). p = 0.019) (Fig. 3). MID-related brain activation differences between SZ and HC Moderation analyses. Since the negative symptom severity was during reward outcome signiﬁcantly negatively related to striatum hypoactivation Included studies and sample characteristics.Regarding the (r = −0.507, p = 0.038), we further tested whether the symptom- reward outcome stage, a total of ten studies comprising 229 Translational Psychiatry (2022) 12:448 J. Zeng et al. Fig. 2 Task-evoked activation differences between SZ and HC during reward anticipation and reward outcome. A For the main analysis of the anticipation stage, SZ patients showed hypoactivation occurring in the bilateral striatum, ACC, MCC, amygdala, right precentral gyrus, and right STG, compared with HC. B For the main analysis of the outcome stage, patients showed hyperactivation in the striatum (with extension to the bilateral insula, amygdala, and hippocampus), left cerebellum, right parahippocampal gyrus, right postcentral gyrus, and right MCC, and hypoactivation in the mPFC and DLPFC compared with HC. Brain regions that showed signiﬁcant differences during the outcome stage in SZ patients relative to HC. Red indicates regions that showed hyperactivation in SZ compared with HC and blue indicates regions that showed hypoactivity in patients relative to HC. The color scale represents probability values from statistical permutation testing (z values). SZ schizophrenia, HC healthy controls, ACC anterior cingulate cortex, MCC median cingulate cortex, STG superior temporal gyrus, mPFC medial prefrontal cortex, DLPFC dorsolateral prefrontal cortex. SZ and 281 HC met the meta-analysis inclusion criteria SZ patients diagnosed by DSM, for those including SZ patients [14, 15, 22, 24–26, 51, 52, 54, 55](Table 1 and Fig. 1). The mean receiving medication treatment, for those using a 3-T MRI age between SZ (33.84 years) and HC (32.41 years) was not scanner, for those using SPM software, and for those reporting signiﬁcantly different (t = −0.539, p = 0.596). There was no coordinates corrected for comparisons. The results remained signiﬁcant difference (χ = 0.601, p = 0.438) in the percentage of largely unchanged in all of the subgroup analyses (Supplemen- males between SZ patients (67.60% male) and controls tary Table 4). (64.59% male). Meta-regression analyses. For reward outcome, the effect of Main meta-analysis. Compared with HC, SZ showed higher duration of illness could not be examined due to insufﬁcient data activations in the bilateral striatum (with extension to the bilateral (available in six studies). No signiﬁcant correlations were found insula, amygdala, and hippocampus), left cerebellum, right between outcome-evoked activations and several variables (the parahippocampal gyrus, right postcentral gyrus, and right MCC percentage of males (available in 10 studies), the % of FGA users during the outcome stage. Signiﬁcant lower activations in SZ (available in 10 studies), and the PANSS-N scores (available in patients were detected in the mPFC and bilateral DLPFC eight studies)). Hypoactivation in left mPFC was found to be compared to HC (Table 3 and Fig. 2). negatively associated with the PANSS-P scores (MNI coordinates: x = 0, y = 46, z = −10, r = −0.681, p = 0.043; available in eight Sensitivity analysis. The jackknife sensitivity analysis revealed that studies). Moreover, the % of SGA users was found to be positively the ﬁndings in the left striatum, right parahippocampal gyrus, and related to the left mPFC activation (MNI coordinates: x = 0, y = 46, right postcentral gyrus were consistent in all combinations of z = −10, r = 0.656, p = 0.028; available in 10 studies) (Fig. 3). studies. The increased activations in the right striatum left cerebellum and right MCC, as well as reduced activations in the Moderation analyses. During reward outcome, a similar pattern mPFC and DLPFC, remained signiﬁcant except for one combina- of ﬁndings emerged for the moderating effect of % of SGA users. tion (Supplementary Table 4). In detail, the interaction of SGA and positive symptoms was a signiﬁcant predictor of mPFC activity (R change = 0.457, Subgroup analyses. Similarly, we conducted subgroup analyses B = 0.230, p = 0.001). A higher PANSS-P was associated with more for those studies only including chronic SZ, for those including decreased mPFC activation among participants in the lower SGA Translational Psychiatry (2022) 12:448 J. Zeng et al. Fig. 3 Correlations and moderation analyses between clinical symptoms and brain activity during reward anticipation and reward outcome. A Scatter plot showing a signiﬁcant negative association between anticipation-evoked activity and negative symptom severity (PANSS-N) in the VS (MNI coordinates: x = 16, y = 14, z = −6, r = −0.507, p = 0.038). B Scatter plot showing a signiﬁcant positive association between anticipation-evoked activity and the % (percentage) of SGA users (the proportion of SZ who had ever received SGA) in the VS (MNI coordinates: x = 16, y = 2, z = 0, r = 0.533, p = 0.019). C Conceptual diagram of the moderating effect of the % of SGA users on the relationship between negative symptoms and striatum hypoactivation during reward anticipation. D Scatter plot showing a signiﬁcant negative association between outcome-evoked activity and the positive symptom severity (PANSS-P) in the mPFC (MNI coordinates: x= 0, y = 46, z = −10, r = −0.681, p = 0.043). E Scatter plot showing a signiﬁcant positive association between outcome-evoked activity and the % of SGA users in the mPFC (MNI coordinates: x = 0, y = 46, z = −10, r = 0.656, p = 0.028). F Conceptual diagram of the moderating effect of % of SGA users on the relationship between positive symptoms and mPFC hypoactivation during reward outcome. SZ schizophrenia, HC healthy controls, SGA second-generation antipsychotic, mPFC medial prefrontal cortex. group, whereas among participants in the higher SGA group, different brain regions in SZ patients are implicated in reward PANSS-P scores had a null association with mPFC activity (Fig. 3 anticipation and reward outcome during the MID task. and Supplementary Table 5). Anticipation-evoked brain responses in SZ During anticipation, we found that SZ patients exhibited reduced DISCUSSION activation in the mesocorticolimbic reward system in response to Our whole-brain meta-analysis of fMRI studies stressed the monetary incentives. Dopamine neurons in the midbrain project importance of examining the temporal phases (i.e., anticipation widely to the cortex and subcortical structures, including the VS, and outcome) of reward processing separately, as we showed dorsal striatum, amygdala, thalamus, and hippocampus. These dissociable neural substrates during reward anticipation and dopaminergic pathways play an important role in the modulation receipt. During reward anticipation, individuals with SZ showed of motivational processing and decision-making, and changes in a reduced response to reward in the mesocorticolimbic circuitry dopamine metabolism are thus considered as the central basis for involving the striatum, insula, ACC, MCC, amygdala, right the impairment of “wanting” and “learning” -related physiology in precentral gyrus, and right STG. In contrast, during reward SZ. “Wanting” refers to the motivational processing of the outcome, individuals with SZ showed increased activation in the incentive salience attributed to the reward and is mediated by striatal-limbic circuitry involving the bilateral striatum, insula, larger systems that encompass mesocorticolimbic dopaminergic amygdala, hippocampus, right parahippocampal gyrus, left transmission [57]. Generally, increases in dopaminergic transmis- cerebellum, right postcentral gyrus, right MCC, and decreased sion are associated with increases in motivated behavior, whereas activation in the mPFC and DLPFC when processing incentive disruption of dopaminergic functioning, through focal lesions or feedback. In addition, anticipation-evoked activation reductions in pharmacologically induced receptor antagonism/depletion, the VS were negatively correlated with negative symptoms of SZ, reduces motivated behavior [58]. VS response during reward whereas outcome-evoked activation reductions in the mPFC were anticipation has been previously shown to be attenuated in drug- negatively correlated with positive symptoms of SZ. The relation- naive patients, patients with chronic SZ, and individuals at high ship between symptom severity and brain activity was moderated risk for psychosis [13, 19, 59]. Moreover, the degree of reduced by the % of SGA users. This meta-analysis provided evidence that reward anticipation is linked to symptom severity [36]. Thus, our Translational Psychiatry (2022) 12:448 J. Zeng et al. Table 3. Results of the meta-analysis for brain activation difference between SZ and HC during reward outcome stage. Brain regions MNI SDM value p value Number Breakdown of voxels coordinates x, y, z P >HC Right striatum 28,10,−14 1.829 0.000118673 590 Right lenticular nucleus, putamen, BA 48 Right striatum Right amygdala, BA 34, BA 48 Right olfactory cortex, BA 11, BA 48 Right inferior network, inferior fronto- occipital fasciculus Right parahippocampal gyrus, BA 34, BA 48 Right insula, BA 48 Right superior frontal gyrus, orbital part, BA Right inferior frontal gyrus, orbital part, BA 11, BA 48 Right lenticular nucleus, putamen, BA 47 Right temporal pole, superior temporal gyrus, BA 34 Right hippocampus, BA 34 Left striatum −22,0,2 1.696 0.000289023 439 Left amygdala, BA 20, BA 28, BA 34 Left striatum Left lenticular nucleus, putamen, BA 48 Left insula, BA 48 Left pons Left inferior network, uncinate fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus Left hippocampus, BA 34 Left superior temporal gyrus, BA 48 Left cerebellum −8,−36,−18 1.443 0.001243770 194 Left cerebellum, hemispheric lobule IV / V, BA 19, BA 30,, BA 37 Left cerebellum, hemispheric lobule VI, BA 19, BA 37 Left cerebellum, hemispheric lobule III, BA 30 Middle cerebellar peduncles Left cerebellum, hemispheric lobule VI, BA Right 30,−4,−26 1.676 0.000314832 176 Right fusiform gyrus, BA 20, BA 36 parahippocampal gyrus Right inferior network, inferior longitudinal fasciculus, uncinate fasciculus Right parahippocampal gyrus, BA 20, BA 28, BA 35, BA 36 Right median network, cingulum Right amygdala, BA 28, BA 36 Right hippocampus, BA 36 Right postcentral gyrus 52,−18,56 1.443 0.00120765 31 Right postcentral gyrus, BA 4, BA 6 Right precentral gyrus, BA 4, BA 6 Right middle frontal gyrus, BA 6 Right MCC 8,34,30 1.438 0.001398563 20 Right median cingulate / paracingulate gyri, BA 32 P <HC mPFC −10,52,6 −1.129 0.000010312 817 Left anterior cingulate / paracingulate gyri, BA 10, BA 11, BA 32 Left superior frontal gyrus, medial, BA 10, BA Left superior frontal gyrus, medial orbital, BA 10, BA 11 Right superior frontal gyrus, medial orbital, BA 10, BA 11 Left gyrus rectus, BA 11 Left median network, cingulum Right superior frontal gyrus, medial, BA 10 Right gyrus rectus, BA 11 Right anterior cingulate / paracingulate gyri, BA 10, BA 11 Translational Psychiatry (2022) 12:448 J. Zeng et al. Table 3. continued Brain regions MNI SDM value p value Number Breakdown of voxels coordinates x, y, z Left DLPFC −24,56,20 −1.033 0.000051618 442 Left middle frontal gyrus, BA 9, BA 10, BA 46 Left superior frontal gyrus, dorsolateral, BA 9, BA 10, BA 46 Right DLPFC 22,20,62 −1.036 0.000025809 143 Right superior frontal gyrus, dorsolateral, BA Results were threshold at p = 0.005, peak height threshold of 1, extent threshold of 10. BA Brodmann area; P patients; HC healthy controls, MCC median cingulate cortex, mPFC medial prefrontal cortex, DLPFC dorsolateral prefrontal cortex, SDM seed-based d mapping, MNI Montreal Neurological Institute. ﬁndings of reduced striatal activity in SZ when anticipating a Outcome-evoked responses in SZ monetary reward, likely reﬂect a blunted attribution of motiva- In contrast, at the reward outcome stage, SZ showed elevated tional salience to monetary stimuli. activations in the striatal-limbic circuitry, including the bilateral VS, Reward anticipation is also associated with the deactivations of amygdala, insula, hippocampus, right parahippocampal gyrus, left the ACC and insula region, as proposed by the aberrant salience cerebellum, right postcentral gyrus, and right MCC, and dimin- hypothesis [60, 61]. Aberrant salience refers to an abnormally ished activations in the mPFC and DLPFC. Impaired neural reduced response to a reward or related stimuli but a heightened processing during reward outcome may be independent from response to neutral or irrelevant stimuli. The salience network (SN) motivational components given that hedonic impact was found to which mainly comprises the ACC and insula, is thought to cause be independent from anticipation effects. Our meta-analysis such aberrant salience attribution [62]. The ACC has extensive revealed that SZ showed stronger activation in the VS during connections with a set of other limbic and related areas including the receipt of a reward, perhaps indicating an elevated reactivity the amygdala, OFC, and STG, and is involved in reward-related to rewarding outcomes. Consistent with our ﬁndings, past processing by encoding reward outcomes and determining the research reported that striatal activation is associated with reward effort required to obtain rewards [63]. The insular cortex has outcome and that SZ patients reveal higher striatum signals emerged in the last few years as a key region in SZ research and is during the outcome phase [54]. Furthermore, animal studies considered to be a crucial relay center of interoceptive signals that supported the involvement of the VS in the experience of pleasure integrates with exteroceptive awareness [64]. A previous major and hedonic perception of rewards [78]. As part of the limbic depressive disorder (MDD) study showed that the functional structures, the VS, amygdala, and insula are thought to play a activity and functional connectivity (FC) of the insula were signiﬁcant role in guiding behavior and facilitating learning. A important indicators of electroconvulsive therapy [65]. Several growing body of evidence suggests that the amygdala is critical SZ studies have reported the reduced gray matter and/or for feedback-guided learning behavior, and VS reﬂects the functional activity and FC within the insula–ACC SN [66, 67]. encoding of expected value of outcome and action selection for Palaniyappan and colleagues have proposed that dysfunction of the obtainment of rewards [79, 80], whereas the parahippocampal the insula–ACC SN is linked to the psychotic symptoms of SZ by gyrus is related to prediction errors [81, 82]. A similar pattern of inappropriately allocating salience to irrelevant internal or external activation within limbic regions has been reported during the stimuli [68]. Reduced FC within brain regions involving the ACC receipt of a reward [22, 25, 54]. Regarding the preferential and insula was proven to be associated with heightened affective involvement of the limbic-striatal areas in hedonic processes, the and anxiety symptoms and an increased risk of developing ﬁndings of over-responsiveness to rewarding outcome may reﬂect psychiatric disorders [69, 70]. Incentive valence, behavioral the presumed motivational signiﬁcance of hedonic experience relevance, or expectancy violation would determine the proces- underlying the reward-seeking behavior. sing the stimulus salience of momentary reward and lead to a Outcome-related increased activity was also present in the change in the brain state [68, 71]. Therefore, abnormalities in the cerebellum in SZ patients. Evidence indicates that the cerebellum mesolimbic system and the cortical SN detected when individuals plays a role in higher cortical functions, such as emotional are performing the MID task may help explain abnormal reinforcer processing and social cognition [83, 84]. It has been proposed that processing and symptoms, which appears to be a prominent the cerebellum encodes error signals and participates in feedback- characteristic of the pathophysiology of SZ. based learning. Recent ﬁndings of altered error processing in Blunted activations in the right STG and precentral gyrus of patients with cerebellar lesions conﬁrmed the hypothesis that SZ patients in response to monetary stimuli were also found feedback processing might be affected by cerebellar damage during anticipation. Decreased gray matter volume and [85, 86]. Notably, cerebellar dysfunction and hyperconnectivity changed functional activation and FC in the STG have been patterns in the cerebello-thalamo-cortical circuit have been robustly implicated in the neurophysiology of SZ [72–74]. consistently observed in SZ [87–89]. Our ﬁnding of exaggerated Pertinently, the STG plays a key role in language perception, cerebellar activation in the reward reception phase appears to which is consistent with previous reports linking this region reﬂect the importance of cerebellum in controlling the reward with auditory hallucinations in SZ [75]. However, the temporal process in psychosis. area is sensitive to socially relevant information and may also Reduced activation in response to reward was observed in the be linked to incentive salience processing [76]. The precentral DLPFC and mPFC during the outcome. Pertinently, the prefrontal gyrus has also been associated with behavioral responses to cortex is a heterogeneous area that is critical to reward-based motivationally signiﬁcant events [77]. Abnormally reduced decision-making. Studies have demonstrated that the DLPFC is reward-related activity in the precentral gyrus and STG in SZ implicated in higher-order cognitive control, especially for reward would imply a reduction in salience to rewarding events, as well values and effort calculations [90, 91], whereas the mPFC is a key as motivated goal-directed behavior by associations with node for emotion-related reward processes and value-based reinforcing events. decision-making through interactions with the VS and amygdala Translational Psychiatry (2022) 12:448 J. Zeng et al. [92, 93]. Furthermore, reduced FC in medial prefrontal-striatal accordance, previous reports show that the more serious network is related to disrupted cognitive control and reward negative symptoms are, the stronger the reduction in striatal processing [94]. Promoting local, long-range, and dynamic activation under the condition that patients took fewer SGA connectivity within the frontal areas could effectively improve [13, 35]. Moreover, the striatal activation reduction was cognitive function [95]. Because the PFC exerts top-down control inversely correlated with the severity of negative symptoms in over striatal dopamine-induced activity and drives synchrony patients being not treated with SGA [98]. A recent European between speciﬁc corticolimbic circuit regions [96], we speculated Psychiatric Association guidance paper argued SGA (i.e., that reduced cortical excitability in the prefrontal region might amisulpride) has certain potential in the treatment of negative trigger elevated striatal and limbic responses. symptoms and suggested that a switch to SGA should be considered for patients who are treated with FGA [105]. Correlations between clinical symptoms and brain activity at additionally, a randomized controlled trial revealed that SGA different reward stages showed statistically signiﬁcant effects on negative symptoms During reward anticipation, the meta-regression analysis revealed [106]. In the present study, we present preliminary evidence for a signiﬁcant negative correlation between VS hypoactivation and a moderating role of SGA in the relationship between clinical the severity of negative symptoms. In line with this, a strong symptoms and brain activity. The symptom-brain relationship is association of reduced VS activation during reward anticipation complex, and further studies of how this relationship changes with negative symptoms was observed in previous studies as modulation of antipsychotic treatment need to be validated [13, 16]. As the activity of this region mediates incentive in controlled clinical trials. motivation or wanting of reward, this result may suggest that impaired striatal activity is involved in the pathophysiology of The heterogeneity in the subgroup analyses of anticipation motivational deﬁcits in SZ patients. A similar result was observed stage in our meta-analysis in the association with current antipsychotic Notably, the results showed that the brain activity in the right drug use. Speciﬁcally, we found that VS hypoactivation was STG did not survive in the subgroup analyses for studies positively associated with the % of SGA users. Consistent with this including chronic SZ patients and studies including SZ patients ﬁnding, Juckel and colleagues reported an improvement in receiving medication treatment. The medial-temporal lobe, reduced VS activity in patients taking SGA but not in those taking including the STG, is probably the most extensively investigated FGA or those who were unmedicated [97]. Since SGA has less brain structure in SZ. STG is believed to be a major anatomical blockade of striatal D receptors, it may enhance the treatment of substrate for auditory hallucinations and thought disorders in negative symptoms and maintain motivation to reach potential SZ [107]. Although STG abnormalities have been well demon- rewards owing to less blockade of striatal D receptors [98]. In this strated in SZ, some studies have reported negative results for regard, the linkages between blunted striatal anticipating function STG abnormalities [36, 51, 53]. A meta-analysis of voxel-based and negative symptoms would help to explain the different facets morphometry in SZ reported that 6 of 15 studies showed no of reward processing in the correlation of behavioral disturbances. signiﬁcant brainvolumedifferenceinthe STGwhencompared During reward outcome, our meta-regression analysis further with controls [108]. Furthermore, an attenuated response in the revealed that reward-related hypoactivity in the mPFC was STG during the anticipation of monetary incentives has been negatively associated with positive symptoms. Dysfunction in found in medication-free SZ patients but not in medicated the mPFC may result in hallucinations and delusions [26]. Several patients [14, 36]. It is well known that SZ is a chronic psychiatric postmortem and fMRI studies have provided evidence for disorder that can be effectively controlled but likely requires abnormal anatomical and FC of the mPFC, which is implicated lifelong treatment. Previous neuroimaging studies of SZ in psychiatric symptoms and impaired cognitive function in SZ examined chronically ill patients, for whom ﬁndings are and MDD patients [99, 100]. For example, previous studies found potentially inﬂuenced by disease course and medication. that hyperconnectivity between the mPFC and default mode Exposure to antipsychotic drugs may have an effect on brain network was correlated with more serious positive symptoms in structure and function [109–111]. For example, increased SZ patients [101]. Along similar lines, an association between cortical thickness and increased anticipation-related brain disrupted error feedback in the mPFC and delusion severity was activity in the STG over treatment time have been observed, observed [102]. Our study also found that mPFC activation was which is associated with symptomatic improvement [36, 112]. positively associated with the % of SGA users during the outcome Importantly, it has been suggested that the improvement of phase. As mentioned above, SGA administration could improve positive symptoms was signiﬁcantly associated with the the dysfunction of the PFC and positive symptoms. Our meta- normalization of reward-related activation [36]. SZ patients regression results suggested that the neural processing of reward who show a long illness duration may also experience a outcomes in the mPFC may be related to the pathophysiology of neurotoxic effect on their brain structure and function positive symptoms in SZ patients. Notably, although the regres- [113, 114]. Furthermore, the STG can be cytoarchitectonically sion analysis results during reward outcome are statistically and functionally divided into several subdivisions [115]. The signiﬁcant, they are preliminary and require future research to complexity and heterogeneity of the STG may account for the obtain a better understanding of their effects. inconsistency. Our exploratory moderation analyses revealed that SGA use In addition, our current subgroup analysis of studies that was a signiﬁcant moderator of the symptom-brain relationship applied a 3-T MRI scanner also found that STG activity showed during reward anticipation and outcome: results were negative some heterogeneity. Different studies used different MRI in patients taking fewer SGAs and null in patients taking more scanners with different MRI ﬁeld strengths, which could SGAs. In patients in the group taking more SGA, negative introduce potential bias. One possible explanation for this is symptoms presented a null association with brain activity. It is that in a high-strength ﬁeld, echo planar imaging results in a well documented that SGA is presumed to act as a treatment for higher signal-to-noise ratio but also increases susceptibility negative symptoms [103] and multiple neuroprotective effects artifacts [116]. In particular, it is inﬂuenced in regions with on the brain [104]. It is likely that SGA affect symptoms and the susceptibility artifacts, especially for imaging the temporal brain simultaneously, and thereby reduces and weakens the lobes [117]. Future studies should investigate the inﬂuence of link between symptoms and brain activity in patients taking different magnetic strengths on imaging presentation, and more SGA; On the other hand, in patients taking fewer SGA, the meta-analyses with homogeneous magnetic ﬁeld strength are symptoms were inversely related to brain activity. In needed to conﬁrm this ﬁnding. Translational Psychiatry (2022) 12:448 J. Zeng et al. Clinical implications CONCLUSION The biological markers of different stages of reward processing The present study examined neural mechanisms underlying may help elucidate the complex and multifaceted symptoms as different phases of reward processing in SZ patients and their well as neurobehavioral disruptions observed in SZ patients. relevance to clinical symptomology. Patients with SZ showed Dysfunction in reward processing is regarded in the DSM-5 as a hypoactivation in the mesocorticolimbic circuit during reward key factor in the anhedonic symptoms of SZ [118]. Previous anticipation and elevated activation in the striatal-limbic circuitry studies found that SZ patients have impaired motivation to pursue but reduced responses in the DLPFC and mPFC were elicited by rewards and reduced activation in the reward pathway during the monetary outcomes. Anticipation-evoked VS hypoactivation was presentation of reward stimuli, although pleasure in consuming linked to negative symptoms, and outcome-evoked mPFC rewards is largely intact [7]. Deﬁcits in any reward component, activation was linked to positive symptoms. Our ﬁndings showed including reward valuation, reward expectancy, and action dissociated neurobiological mechanisms in different aspects of selection, may preclude an individual from engaging in goal- reward processing and have the potential to clarify the complex directed actions for rewards, regardless of whether the reward is brain-behavior relationships in SZ. perceived as pleasurable once obtained. In other words, the construct of anhedonia that reﬂects deﬁcits in hedonic capacity is closely linked to the constructs of reward anticipation, valuation, REFERENCES and motivation. In our meta-analysis, we found that anticipation 1. Howes OD, Murray RM. 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Clinical, available at https://doi.org/10.1038/s41398-022-02201-8. behavioral, and neural measures of reward processing correlate with escitalopram response in depression: a Canadian Biomarker Integration Network in Depression Correspondence and requests for materials should be addressed to Xun Yang. (CAN-BIND-1) Report. Neuropsychopharmacology. 2020;45:1390–1397. 121. Cheung MW, Vijayakumar R. A guide to conducting a meta-analysis. Neu- Reprints and permission information is available at http://www.nature.com/ ropsychol Rev. 2016;26:121–128. reprints Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional afﬁliations. ACKNOWLEDGEMENTS This work was supported by the National Natural Science Foundation of China (grant number 31700964); Fundamental Research Funds for the Central Universities of China (grant number 2020CDJSK01XK02); Graduate research and innovation foundation of Chongqing (grant number CYB22053); the Venture & Innovation Open Access This article is licensed under a Creative Commons Support Program for Chongqing Overseas Returnees (grant numbers cx2019154, Attribution 4.0 International License, which permits use, sharing, cx2020119); the Social Science Foundation of Chongqing (grant number adaptation, distribution and reproduction in any medium or format, as long as you give 2020YBGL80); the Research on Teaching Reform Program of Chongqing University appropriate credit to the original author(s) and the source, provide a link to the Creative (grant number 2019Y04) and the Key R&D Projects of Science and Technology Commons license, and indicate if changes were made. The images or other third party Department of Sichuan Province (grant number 2019YFS0217). material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory AUTHOR CONTRIBUTIONS regulation or exceeds the permitted use, you will need to obtain permission directly J.Z., and X.Y. contributed to the study conception and design and supervised the from the copyright holder. To view a copy of this license, visit http:// study. J.Y., H.C., Y. Su, Y. Song, and Y.L. contributed to the analysis and manuscript creativecommons.org/licenses/by/4.0/. preparation; J.Y., Y. Su, Y. Song, and Y.L. helped perform the analysis with constructive discussions. X.Y., H.C., and J.Z. wrote the manuscript, which was reviewed by all authors and approved for publication. © The Author(s) 2022 Translational Psychiatry (2022) 12:448

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Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI findings in the monetary incentive delay task

Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI findings in the monetary incentive delay task

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Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI findings in the monetary incentive delay task

Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI findings in the monetary incentive delay task

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