Neuroscience Letters 417 (2007) 297–302

Functional dysconnectivity of the dorsolateral in first-episode schizophrenia using resting-state fMRI Yuan Zhou a, Meng Liang a, Tianzi Jiang a,∗, Lixia Tian a, Yong Liu a, Zhening Liu b,∗∗, Haihong Liu b, Fan Kuang b a National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, PR China b Institute of Mental Health, Second Xiangya Hospital, Central South University, Changsha 410011, Hunan, China Received 30 December 2006; received in revised form 14 February 2007; accepted 21 February 2007

Abstract The known regional abnormality of the dorsolateral prefrontal cortex (DLPFC) and its role in various neural circuits in schizophrenia has given prominence to its importance in studies on the dysconnection associated with schizophrenia. Abnormal functional connectivities of the DLPFC have been found during various goal-directed tasks; however, the occurrence of the abnormality during rest in patients with schizophrenia has rarely been reported. In the present study, we selected bilateral Brodmann’s area 46 as region of interest and analyzed the differences in the DLPFC functional connectivity pattern between 17 patients with first-episode schizophrenia (FES) and 17 matched controls using resting-state fMRI. We found that the bilateral DLPFC showed reduced functional connectivities to the , posterior , thalamus and striatum in FES patients. We also found enhanced functional connectivity between the left DLPFC and the left mid-posterior and the paralimbic regions in FES patients. Our results suggest that functional dysconnectivity associated with the DLPFC exists in schizophrenia during rest. This may be partially related to disturbance in the intrinsic brain activity. © 2007 Elsevier Ireland Ltd. All rights reserved.

Keywords: Schizophrenia; fMRI; Dorsolateral prefrontal cortex; Connectivity; Resting state

Schizophrenia is increasingly considered as a disorder of Recently, brain functional activity and connectivity during improper functional integration of neural systems, i.e., dyscon- rest have increasingly been emphasized, and some investigators nection [12,30]. The symptoms of schizophrenia are thought even think that the resting brain functional activity may be at least not to be due to a single, regionally specific pathophysiology, as important as the activity evoked by tasks [26]. During rest, the but rather to result from abnormal interactions between two or brain has been suggested to exhibit a functional architecture that more regions [12]. Based on this opinion, the functional con- includes both “task-negative” and “task-positive” networks [10]. nection of the dorsolateral prefrontal cortex (DLPFC) should The study of resting-state brain function is especially applicable be especially emphasized, considering its local abnormalities to the study of schizophrenia because of the practical advantages in anatomy and function [4] and its role in various neural cir- of resting-state fMRI in terms of ease of clinical application. This cuits relevant to the anatomical and physiological mechanisms includes advantages such as the fact that resting-state fMRI is of cognitive dysfunction in schizophrenia [8]. Abundant evi- non-invasive and easy to perform without any complicated task dence from functional imaging while engaged in tasks has found design, and thus can be readily accepted by psychiatric patients dysfunctional connectivities between the DLPFC and widely including those with schizophrenia. In addition, the mental activ- distributed brain regions, including the temporal lobe [29,30], ity occurring during rest is thought to be possibly relevant to the parietal lobe [17], [23], thalamus and phenomenology of schizophrenia [21]. cerebellum [27]. Abnormal resting activities of the prefrontal lobe, includ- ing the DLPFC, have been observed in schizophrenia [15,21]. However, there are few studies in patients with schizophrenia on ∗ Corresponding author. Tel.: +86 10 8261 4469; fax: +86 10 62551993. ∗∗ the DLPFC functional connectivity during rest. Functional con- Corresponding author. Tel.: +86 731 529 2470; fax: +86 731 5554052. E-mail addresses: [email protected] (T. Jiang), nectivity during rest is often measured by correlation in low [email protected] (Z. Liu). frequency fluctuations (LFF) (<0.1 Hz) of the blood oxygen

0304-3940/$ – see front matter © 2007 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.neulet.2007.02.081 298 Y. Zhou et al. / Neuroscience Letters 417 (2007) 297–302 level-dependent (BOLD) signal [6]. The low frequency, resting- instructed to keep their eyes closed, relax, and move as little as state interregional correlation has been observed between possible. Functional images were collected using a gradient echo spatially distinct but functionally related regions [3,13,19], and Echo Planar Imaging (EPI) sequence sensitive to BOLD contrast has been observed to be altered in neuropsychiatric disor- (TR/TE = 2000/40 ms, flip angle = 90◦, FOV = 24 cm). Whole- ders, such as multiple sclerosis [20], Alzheimer’s disease [32] brain volumes were acquired with 20 contiguous 5-mm thick and deficit hyperactivity disorder [31]. Our previ- transverse slices, with a 1 mm gap and 3.75 mm × 3.75 mm in- ous study, which investigated the distribution of the abnormal plane resolution. For each participant, the fMRI scanning lasted resting-state functional connectivities throughout the entire for 6 min allowing 180 volumes to be obtained. brain in schizophrenia, found abnormal functional connectivities Image preprocessing was performed using a statistical between many regions, including those associated with the pre- parametric mapping software package (SPM2, Wellcome frontal cortex [18]. However, in that preliminary study, we used Department of Imaging Neuroscience, London, UK). The first a group of non-first-episode schizophrenic patients and com- 10 volumes of each functional time series were discarded and puted the functional connectivities of the whole brain which was the rest of the images were corrected for the acquisition delay roughly divided into 116 regions. Thus it could not reveal the between slices and for head motion. Motion time courses were precise and detailed connection patterns of the prefrontal cortex. obtained by estimating the values for translation and rotation In addition, the effects of medication should also be considered. for each of the 170 consecutive volumes. The participants in In the present study, which considered the special role of the this study had less than 1 mm maximum displacement in x, DLPFC in schizophrenia, we investigated the resting-state func- y or z and less than 1◦ of angular motion about each axis. tional connectivity pattern of the DLPFC (Brodmann’s area 46, Because correlation analysis is sensitive to gross head motion BA46) in a voxel-wise manner in a group of patients with first- effects, we further characterized the peak displacements as a episode schizophrenia (FES) using fMRI. Because the patients measure of head motion for each subject [16,19], and no sig- we studied had a shorter length of illness and limited exposure nificant difference in the peak displacements of head motion to antipsychotic medications, the effect of such medications on was found between the groups by a random effect two-sample brain blood flow/metabolism would be expected to be greatly t-test (0.31 ± 0.20 mm for normal controls; 0.36 ± 0.18 mm for reduced in the present study. schizophrenia; P = 0.45). To further reduce the effects of con- Seventeen FES patients (5 females, 12 males) were recruited founding factors, six motion parameters, linear drift and the from the Institute of Mental Health, Second Xiangya Hospi- mean time series of all voxels in the whole brain were removed tal and met the following criteria: (a) Diagnostic and Statistical from the data through linear regression after the fMRI images Manual-IV criteria for schizophrenia; (b) duration of illness less were normalized to the standard EPI template and smoothed than 2 years and an allowed exposure to antipsychotic treat- with a Gaussian kernel of 4 mm × 4mm× 4 mm full-width at ment of less than 2 weeks in the year preceding study entry half maximum. Then the fMRI data were temporally band- or 6 weeks life time exposure [9]; (c) right-handed; (d) no his- pass filtered (0.01–0.08 Hz). A mask was then created by taking tory of neurological or systemic illness, head injury, and drug the intersections of the normalized T1-weighted high-resolution or alcohol abuse. At the time of scanning, all patients were images of all subjects, which were stripped using the software receiving atypical antipsychotic medications, except for four, BrainSuite2 (http://brainsuite.usc.edu). Only the voxels within which were on no medication. And the symptoms of these the mask were further processed. In addition, to visualize the patients were assessed by trained and experienced psychia- statistical results, a mean anatomical image was obtained by trists using the Positive and Negative Symptom Scale (mean averaging these normalized high-resolution anatomical images 85.9 ± 21.5). Seventeen healthy, paid volunteers (5 females, 12 across all subjects. males) were recruited by advertisements and met the same (c) The DLPFC generally refers to BA46 and the ventral part of and (d) criteria as the patients (see above). The two groups BA9, and sometimes also includes BA10. This region is rela- were matched for age (25.7 ± 5.6 years for normal controls; tively unitary in function but is difficult to anatomically delimit. 22.9 ± 6.0 years for schizophrenia; P = 0.18), gender and edu- In order to define the ROI as precisely as possible, we chose cational level (13.6 ± 3.3 years for normal controls; 12.6 ± 2.2 bilateral BA46 as ROIs using the software WFU PickAtlas years for schizophrenia; P = 0.18). Subjects included 15 new (www.ansir.wfubmc.edu) [22], which has been used in a pre- subjects (9 patients, 6 controls) and 19 subjects (8 patients, 11 vious study [28]. In brief, the right ROI was generated by controls) in common with our previous study [18]. All subjects intersecting the following three parts: BA46 in the TD (Talairach gave written, informed consent prior to taking part in the study, Daemon) atlas, the right middle frontal which was approved by the Medical Research Ethics Committee in the TD AAL (Automated anatomical labeling) atlas and the of the Second Xiangya Hospital, Central South University. gray matter in the TD Type atlas. The left ROI was generated in Imaging was performed on a 1.5-T GE scanner. Foam the same way. The generated bilateral ROIs were respectively pads were used to limit head motion and reduce scanner intersected with the mask to create the final right and left ROIs. noise. Three-dimensional T1-weighted images were acquired Functional connectivity analysis was performed for the right in a sagittal orientation employing a 3D-SPGR sequence and left DLPFC. A seed reference time series for each ROI was (TR/TE = 12.1/4.2 ms, flip angle = 15◦, in-plane resolution of obtained by averaging the fMRI time series of all voxels within 256 × 256, 1.8 mm slice thickness). The fMRI scanning was the ROI. Correlation analysis was carried out between the seed carried out in darkness, and the participants were explicitly reference and the rest of the whole brain in a voxel-wise manner. Y. Zhou et al. / Neuroscience Letters 417 (2007) 297–302 299

Fig. 1. Regions showing significant functional connectivity to the right (A) and left (B) DLPFC in the normal controls. The left side of image represents the left side of brain. Warm color illustrates brain regions positively correlated with the DLPFC and cool color illustrates brain regions negatively correlated with the DLPFC. Color bar indicates T-score. The number beneath each image refers to the z coordinates of Talairach. Threshold was set at P < 0.005 (corrected). Abbreviations—DLPFC: dorsolateral prefrontal cortex; IFG: ; Ins: insula; IPL: ; ITG: ; MTG: ; PCC: posterior cingulate cortex; PCu: ; PostCG: ; pre-SMA: pre-; SFG: ; SPL: ; Str: striatum; Tha: thalamus.

Then, the correlation coefficients were transformed to z-values (IPS, BA7) (peak Talairach coordinates: (−27, −65, 39), peak using the Fisher r-to-z transformation to improve normality. t: 3.84; cluster size: 432 mm3) showed reduced positive correla- Within the normal group, individual z-values were entered tion with the right DLPFC (Fig. 2A), and the PCC extending to into a random effect one-sample t-test in a voxel-wise man- the (BA18/31) (left: peak Talairach coordinates: (−15, ner to determine the brain regions showing significantly −72, 17), peak t: −3.95; cluster size: 2403 mm3; right: peak positive or negative correlation to the right or left DLPFC. Talairach coordinates: (18, −60, 17), peak t: −3.87; cluster size: A stringent threshold of P < 0.005 (corrected for multiple 999 mm3) and its adjacent lingural gyrus (LG, BA18/19) (left: comparisons by false discovery rate) and a minimum cluster peak Talairachcoordinates: (−18, −61, −2), peak t: −3.56; clus- size of 540 mm3 (20 resampled voxels) were used in order to ter size: 864 mm3; right: peak Talairach coordinates: (21, −55, obtain the connection maps within the group. Between groups, −2), peak t: −3.79; cluster size: 1458 mm3) (all of them were the z-values were entered into a random effect two-sample included in the large cluster of PCC within the control group) t-test in a voxel-wise manner to determine the brain regions showed reduced negative correlation (i.e. closer to zero) with the that show significant differences in positive or negative right DLPFC in the FES group (Fig. 2B) (P < 0.002 corrected). correlation to the right DLPFC. A combined threshold of Comparing the left DLPFC connectivity pattern of the controls contrast maps was set at P < 0.005 for per voxel and a cluster with those of the patients, the similar regions showed reduced size of at least 405 mm3, which was equal to the corrected positive (right , BA40, peak Talairach aco- threshold of P < 0.002, determined by AlphaSim (B.D. Ward, ordinates: (39, −42, 33), peak t: 3.65; cluster size: 1242 mm3) http://afni.nimh.nih.gov/pub/dist/doc/manual/AlphaSim.pdf). or negative (left precuneus/superior parietal lobule (BA7), peak The differences identified by the above statistical method were Talairach coordinates: (−24, −47, 52), peak t: −4.2; cluster further limited to the regions showing correlation with the size: 1026 mm3) correlation in FES patients. In addition, the right DLPFC in at least one group at the combined threshold bilateral thalamus and striatum (peak Talairach coordinates: of P < 0.01 and a cluster size of at least 405 mm3. Exactly the (−21, −17, 17) and (15, −2, 14), peak t: 4.85 and 4.58; clus- same statistical analysis between groups was performed on ter size: 10,935 mm3 and 6561 mm3) showed reduced positive the connection maps of the left DLPFC. Statistical parametric correlation to the left DLPFC, and a region (peak Talairach coor- maps were superimposed on transverse sections of the average dinates: (−56, −58, 3), peak t: −3.99; cluster size: 540 mm3) structural images and the locations of regions showing signifi- in the posterior temporal lobe (BA 21/37) and a region (peak cant connectivity to the DLPFC were interpreted using known Talairach coordinates: (12, 34, −22), peak t: −4.79; cluster size: neuroanatomical landmarks. 1269 mm3) in the right orbital frontal gyrus (OFG, BA11/47) In normal controls, the regions significantly positively corre- showed stronger positive correlation to the left DLPFC in FES lated with the right ROI were similar to those in the “task-positive patients. The posterior insula (BA13) (peak Talairach coordi- network”, and the regions significantly negatively correlated nates: (−56, −58, 3), peak t: −3.99; cluster size: 540 mm3) with the right DLPFC were similar to those in the “task-negative showed enhanced negative correlation with the left DLPFC in network” (Fig. 1A). The left DLPFC showed a similar functional FES patients (Fig. 2C and D). connectivity pattern in normal controls (Fig. 1B). Unlike most previous studies, the present study used cor- Compared to the normal group, the bilateral IPL (BA40) (left: relations in interregional LFFs to investigate the functional peak Talairach coordinates: (−30, −51, 36), peak t: 3.94; cluster connection of the DLPFC during rest. LFFs have been suggested size: 459 mm3; right: peak Talairach coordinates: (42, −36, 35), to be physiologically meaningful and interregional correlations peak t: 3.21; cluster size: 432 mm3) and left intraparietal found by LFF may reflect endogenously coordinated dynamics 300 Y. Zhou et al. / Neuroscience Letters 417 (2007) 297–302

sents less interaction between neural units, but also implies the possibility of excessive enhanced interaction in schizophrenia [12,30]. In the present study, we found that the bilateral DLPFC showed significantly reduced functional connectivity with the parietal regions. Activities in the prefrontal and parietal lobes have been reported to be interdependent, and these two brain regions are strongly connected anatomically [24]. Frontal–parietal dysconnection in schizophrenia had previously been suggested by the deficit in [17] and by the reduced neural integrity of the white matter tract connect- ing the two regions [5]. Our result was consistent with these studies. The connectivities of the left DLPFC to the bilateral striatum and thalamus were found to be reduced in FES patients, which was consistent with our previous study [18], supporting the opinion that the dysconnection in prefronto-striato-pallodo- thalama-cortical loops may lead to abnormal sensory gating or modulation and induce schizophrenia symptoms, causing a form of “cognitive disorganization” [8]. More interestingly, in the present study, the right DLPFC also showed decreased negative correlations to the PCC. To the best of our knowledge this dysfunctional connectivity has not been noticed in previous studies. PCC is one of the regions having the highest metabolic activity during rest [25] and plays a central role in the “task-negative” network (i.e., the default mode net- work) [13,25]. The DLPFC is one of those regions constituting the “task-positive” network, which is anti-correlated with the “task-negative” network [10]. The two anti-correlated networks have been suggested as reflecting the intrinsic brain functional organization [10]. In the resting brain of healthy subjects, the right DLPFC has been reported to be negatively correlated with the PCC [11,13], as we observed in the normal group. Although the precise mental processes supported by the intrinsic brain functional organization remain to be elucidated, our finding of the reduced negative correlation between the right DLPFC and the PCC may suggest, for the first time, functional disintegration in the intrinsic brain functional activity. In addition, we found abnormal enhanced connectivities between the left DLPFC and paralimbic regions (OFG and Fig. 2. Alterations in the right and left DLPFC functional connectivity in insula), whose structure and function have been found to be the FES. The left side of image represents the left side of brain. Color bar indicates the T-score. The number beneath each image refers to the z coor- abnormal in schizophrenia [2,7,14]. This finding suggests that dinates of Talairach. Threshold was set at P < 0.002 (corrected). (A) Regions further investigation should focus on the dysfunctional integra- that showed reduced positive correlation to the right DLPFC. (B) Regions that tion between the DLPFC and the paralimbic system. Moreover, showed reduced negative correlation to the right DLPFC. (C) Regions in the present study, we observed the enhanced functional con- that showed difference in positive connectivity to the left DLPFC. (D) Regions nectivity between the left DLPFC and the posterior MTG; that showed difference in negative connectivity to the left DLPFC. Warm color illustrates normal > FES and cool color illustrates normal < FES in (C) and however, Liang et al. [18] reported that the functional connec- (D). Abbreviations—IPL: inferior parietal lobule; IPS: intraparietal suclus; Ins: tivity between the MTG and the prefrontal cortex obtained by insula; LG: lingular gyrus; MTG: middle temporal gyrus; OFG: orbitral frontal computing the correlation using the mean time series of these gyrus; PCC: posterior cingulate cortex; SG: supramarginal gyrus; SPL: superior regions was decreased in schizophrenia. We speculate that this parietal lobule; Str/Tha: striatum and thalamus. inconsistency may be due to the functional heterogeneity of the temporal sub-regions. This suggests that it will be necessary to in large-scale neuronal populations [1]. We found that some investigate the resting-state frontotemporal connectivity in detail regions showed abnormally reduced or enhanced functional in the future. connectivity to the bilateral DLPFC in FES even during rest. There are several issues to be addressed in the present study. The trend is consistent with our previous study [18] and sup- Although we found significant alterations in the DLPFC func- ports the “dysconnection” opinion. In this case, dysconnection tional connection pattern in schizophrenia, it is difficult to means that improper functional integration not only repre- distinguish whether the abnormal correlation patterns represent Y. Zhou et al. / Neuroscience Letters 417 (2007) 297–302 301 some sort of “autonomous” pathology that leads to abnormal [9] W.W. Fleischhacker, I.P. Keet, R.S. Kahn, EUFEST Steering Committee, brain function and subjective experience during scanning, or The European First Episode Schizophrenia Trial (EUFEST): rationale and whether abnormal cognition and experience during scanning, design of the trial, Schizophr. Res. 78 (2005) 147–156. [10] M.D. Fox, A.Z. Snyder, J.L. Vincent, M. Corbetta, D.C. Van Essen, M.E. from other neuropsychological causes, lead to the observed Raichle, The is intrinsically organized into dynamic, anticor- intergroup differences in correlation patterns. This needs to be related functional networks, Proc. Natl. Acad. Sci. U. S. A. 102 (2005) investigated in the future. In addition, in the present study, we 9673–9678. used a relatively low sampling rate (TR=2s) for multislice [11] P. Fransson, Spontaneous low-frequency BOLD signal fluctuations: an acquisitions. Under this sampling rate, cardiac and respiratory fMRI investigation of the resting-state default mode of brain function hypothesis, Hum. Brain Mapp. 26 (2005) 15–29. fluctuation effects could be aliased into the LFF and could reduce [12] K.J. Friston, The disconnection hypothesis, Schizophr. Res. 30 (1998) the specificity of the connectivity effect [19]. In future stud- 115–125. ies, these physiological effects may be estimated and removed [13] M.D. Greicius, B. Krasnow, A.L. Reiss, V.Menon, Functional connectivity by simultaneously recording the respiratory and cardiac cycles in the resting brain: a network analysis of the default mode hypothesis, Proc. during data acquisition. Natl. Acad. Sci. U. S. A. 100 (2003) 253–258. [14] R.E. Gur, P.E. Cowell, A. Latshaw, B.I. Turetsky, R.I. Grossman, S.E. In summary, the present study not only provides new evi- Arnold, W.B. Bliker, R.C. Gur, Reduced dorsal and orbital prefrontal dence for the improper functional integration in schizophrenia gray matter volumes in schizophrenia, Arch. Gen. Psychiatry 57 (2000) by investigating the resting-state functional connectivity of 761–768. DLPFC, but also suggests that this abnormality may relate in [15] K. Hill, L. Mann, K.R. Laws, C.M. Stephenson, I. Nimmo-Smith, P.J. part to the disturbed intrinsic brain activity in schizophrenia. McKenna, Hypofrontality in schizophrenia: a meta-analysis of functional imaging studies, Acta Psychiatr. Scand. 110 (2004) 243–256. [16] A. Jiang, D.N. Kennedy, J.R. Baker, R.M. Weisskoff, R.B. Tootell, R.P. Acknowledgements Woods, R.R. Benson, K.K. Kwong, T.J. Brady, B.R. Rosen, J.W. Belliveau, Motion detection and correction in functional MR imaging, Hum. Brain Mapp. 3 (1995) 224–235. This work was partially supported by the Natural Science [17] J.J. Kim, J.S. Kwon, H.J. Park, T. Youn, H. do Kang, M.S. Kim, D.S. Lee, Foundation of China, Grant Nos. 30425004, 30530290 and M.C. Lee, Functional disconnection between the prefrontal and parietal 60121302, and the National Key Basic Research and Devel- cortices during working memory processing in schizophrenia: a [15(O)] opment Program (973), Grant No. 2003CB716100. H2O PET study, Am. J. Psychiatry 160 (2003) 919–923. The authors are grateful to the anonymous referees for their [18] M. Liang, Y. Zhou, T. Jiang, Z. Liu, L. Tian, H. Liu, Y. Hao, Widespread functional disconnectivity in schizophrenia with resting-state constructive comments. The authors also thank Yihui Hao, Kun functional magnetic resonance imaging, Neuroreport 17 (2006) 209– Wang, Ming Song and Professor Xiaoping P.Hu for their helpful 213. discussions and Drs. Rhoda E. and Edmund F. Perozzi for editing [19] M.J. Lowe, B.J. Mock, J.A. Sorenson, Functional connectivity in single and and English language assistance. multislice echoplanar imaging using resting-state fluctuations, Neuroimage 7 (1998) 119–132. [20] M.J. Lowe, M.D. Phillips, J.T. Lurito, D. Mattson, M. Dzemidzic, V.P. References Mathews, Multiple sclerosis: low-frequency temporal blood oxygen level- dependent fluctuations indicate reduced functional connectivity initial [1] S. Achard, R. Salvador, B. Whitcher, J. Suckling, E. Bullmore, A results, Radiology 224 (2002) 184–192. resilient, low-frequency, small-world human brain functional network [21] D. Malaspina, J. Harkavy-Friedman, C. Corcoran, L. Mujica-Parodi, D. with highly connected association cortical hubs, J. Neurosci. 26 (2006) Printz, J.M. Gorman, R. Van Heertum, Resting neural activity distin- 63–72. guishes subgroups of schizophrenia patients, Biol. Psychiatry 56 (2004) [2] N.C. Andreasen, D.S. O’Leary, M. Flaum, P. Nopoulos, G.L. Watkins, L.L. 931–937. Boles Ponto, R.D. Hichwa, Hypofrontality in schizophrenia: distributed [22] J.A. Maldjian, P.J. Laurienti, R.A. Kraft, J.H. Burdette, An automated dysfunctional circuits in neuroleptic–naive patients, Lancet 349 (1997) method for neuroanatomic and cytoarchitectonic atlas-based interrogation 1730–1734. of fMRI data sets, NeuroImage 19 (2003) 1233–1239. [3] B. Biswal, F.Z. Yetkin, V.M. Haughton, J.S. Hyde, Functional connectivity [23] A.S. Meyer-Lindenberg, R.K. Olsen, P.D. Kohn, T. Brown, M.F. Egan, in the of resting human brain using echo-planar MRI, Magn. D.R. Weinberger, K.F. Berman, Regionally specific disturbance of dorso- Reson. Med. 34 (1995) 537–541. lateral prefrontal–hippocampal functional connectivity in schizophrenia, [4] W.E. Bunney, B.G. Bunney, Evidence for a compromised dorsolateral pre- Arch. Gen. Psychiatry 62 (2005) 379–386. frontal cortical parallel circuit in schizophrenia, Brain Res. Brain Res. Rev. [24] M. Petrides, D.N. Pandya, Projections to the frontal cortex from the pos- 31 (2000) 138–146. terior parietal region in the rhesus monkey, J. Comp. Neurol. 228 (1984) [5] J. Burns, D. Job, M. Basin, H. Whalley, T. MacGillivray, E.C. Johnstone, 105–116. S.M. Lawrie, Structural disconnectivity in schizophrenia: a diffusion tensor [25] M.E. Raichle, A.M. MacLeod, S.A.Z. nyder, W.J. Powers, D.A. Gusnard, magnetic resonance imaging study, Br. J. Psychiatry 182 (2003) 439–443. G.L. Shulman, A default mode of brain function, Proc. Natl. Acad. Sci. U. [6] D. Cordes, V.M. Haughton, K. Arfanakis, J.D. Carew, P.A. Turski, C.H. S. A. 98 (2001) 676–682. Moritz, M.A. Quigley, M.E. Meyerand, Frequencies contributing to func- [26] M.E. Raichle, M.A. Mintun, Brain work and brain imaging, Annu. Rev. tional connectivity in the in ‘resting-state’ data, AJNR Am. Neurosci. 29 (2006) 449–476. J. Neuroradiol. 22 (2001) 1326–1333. [27] R. Schlosser, T. Gesierich, B. Kaufmann, G. Vucurevic, S. Hunsche, J. [7] B. Crespo-Facorro, J. Kim, N.C. Andreasen, D.S. O’Leary, H.J. Bockholt, Gawehn, P. Stoeter, Altered effective connectivity during working memory V. Magnotta, abnormalities in schizophrenia: a structural performance in schizophrenia: a study with fMRI and structural equation magnetic resonance imaging study of first-episode patients, Schizophr. Res. modeling, Neuroimage 19 (2003) 751–763. 46 (2000) 35–43. [28] K. Schon, A. Atri, M.E. Hasselmo, M.D. Tricarico, M.L. LoPresti, C.E. [8] J.H. Fallon, I.O. Opole, S.G. Potkin, The neuroanatomy of schizophre- Stern, Scopolamine reduces persistent activity related to long-term encod- nia: circuitry and neurotransmitter systems, Clin. Neurosci. Res. 77 (2003) ing in the during delayed matching in humans, J. 77–107. Neurosci. 25 (2005) 9112–9123. 302 Y. Zhou et al. / Neuroscience Letters 417 (2007) 297–302

[29] S.A. Spence, P.F. Liddle, M.D. Stefan, J.S. Hellewell, T. Sharma, K.J. [31] L. Tian, T. Jiang, Y.Wang, Y.Zang, Y.He, M. Liang, M. Sui, Q. Cao, S. Hu, Friston, S.R. Hirsch, C.D. Frith, R.M. Murray, J.F. Deakin, P.M. Grasby, M. Peng, Y. Zhuo, Altered resting-state functional connectivity patterns of Functional anatomy of verbal fluency in people with schizophrenia and anterior cingulate cortex in adolescents with attention deficit hyperactivity those at genetic risk. Focal dysfunction and distributed disconnectivity disorder, Neurosci. Lett. 400 (2006) 39–43. reappraised, Br. J. Psychiatry 176 (2000) 52–60. [32] L. Wang, Y. Zang, Y. He, M. Liang, X. Zhang, L. Tian, T. Wu, T. Jiang, K. [30] K.E. Stephan, T. Baldeweg, K.J. Friston, Synaptic plasticity and dyscon- Li, Changes in hippocampal connectivity in the early stages of Alzheimer’s nection in schizophrenia, Biol. Psychiatry 59 (2006) 929–939. disease: evidence from resting state fMRI, Neuroimage 31 (2006) 496–504.