Regional homogeneity in depression and its relationship with separate depressive symptom clusters: A resting-state fMRI study

Journal of Affective Disorders 115 (2009) 430 – 438 www.elsevier.com/locate/jad

Research report

Regional homogeneity in depression and its relationship with separate depressive symptom clusters: A resting-state fMRI study☆ Zhijian Yao a,b,⁎, Li Wang b , Qing Lu c , Haiyan Liu b , Gaojun Teng a,⁎ a

Department of Radiology, Zhong Da Hospital, School of Clinical Medicine, Southeast University, Nanjing, Jiangsu, China b Department of Psychiatry, Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China c Key Laboratory of Child Development and Learning Science, Ministry of Education Learning Science Research Center, Southeast University, Nanjing, Jiangsu, China Received 1 April 2008; received in revised form 7 October 2008; accepted 7 October 2008 Available online 12 November 2008

Abstract Background: Using a newly reported regional homogeneity (ReHo) approach, we were to explore the features of brain activity of patients with major depressive disorder (MDD) in resting state, and further to examine the relationship between abnormal brain activity of depressed patients and specific symptom clusters derived from ratings on the Hamilton Rating Scale for Depression (HRSD). Methods: 22 patients with MDD and 22 gender-, age-, and education-matched healthy subjects participated in the fMRI scans. Results: 1. Compared with healthy controls, decreased ReHo were found in depressed patients in the right orbitofrontal cortex, the right fusiform gyrus, the right ventral anterior cingulate gyrus, the left dorsal anterior cingulate gyrus, the right posterior cingulate gyrus, the left lentiform nucleus and the right insula (p b 0.005, uncorrected). 2. Anxiety severity was positively correlated with the ReHo in the right insula; Cognitive disturbance severity was positively correlated with the ReHo in the right orbitofrontal cortex and the left dorsal anterior cingulate gyrus; Retardation severity was positively correlated with the ReHo in the right posterior cingulate gyrus and the right insula; Sleep disturbance severity was positively correlated with the ReHo in the left dorsal anterior cingulate gyrus; Hopelessness severity was positively correlated with the ReHo in the right ventral anterior cingulate gyrus and the right insula (p b 0.05). Limitation: The influence of antidepressant medication to the brain activity of depressed patients was not fully excluded. Conclusions: Our findings indicated abnormal brain activity was distributed extensively in depressed patients during resting state, and some symptom domains of depression are separately related to specific abnormal patterns of brain activity. © 2008 Elsevier B.V. All rights reserved. Keywords: Depressive disorders; fMRI; Regional homogeneity; Hamilton Rating Scale for Depression; Resting state

☆ Sponsorship: The National Natural Science Foundation of China (30500179), The National High-tech Research and Development Program (863 Program) (2008AA02Z410), the Natural Science Foundation of Jiangsu Province (BK2005427), and the Key Medical Developing Program of Nanjing (IKX05003) supported this work. ⁎ Corresponding authors. Yao is to be contacted at Department of Psychiatry, Nanjing Brain Hospital, Nanjing Medical University, Guangzhoulu 264, Gulou District, Nanjing 210029, Jiangsu, China. Teng, School of Clinical Medicine, Southeast University, Nanjing, 210009, China. Tel.: +86 25 83700011x6224; fax: +86 25 83719457. E-mail addresses: [email protected] (Z. Yao), [email protected] (G. Teng).

0165-0327/$ - see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.jad.2008.10.013

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1. Introduction Major depressive disorder (MDD) is a common mental disorder, which is characterized by persistent depressed mood, anxiety and dysphoria, psychomotor changes, alterations of motivation and social behavior, and sleep abnormalities (American Psychiatric Association, 1994). The pathogenesis of depression, however, remains unclear. In the last decades, neuroimaging studies have greatly advanced our understanding of the pathogenesis of depression. Structural magnetic resonance imaging (MRI) studies have shown the abnormalities in various brain areas in depression, and it was presumed that there was abnormality of limbic–cortical–striatal–pallidal– thalamic circuit in depression (Sheline, 2003). Positronemission tomography (PET) and signal photon emission computed tomography (SPECT) studies also identified the engagement of regions in that circuit in depression (Mayberg, 2003; Soares and Mann, 1997) within paradigms examining both emotional processes and cognitive functions such as attention, executive processing, working memory, or during resting state. However, the results of these studies were always, to some extent, different. This may be due to many factors. Among these, the variety of clinical manifestations may be an important factor, as has been indicated in previous studies (Soares and Mann, 1997; Périco et al., 2005). Exploring the relationships between the abnormality of brain activity and specific symptom clusters in depressed patients is necessary to explain the variety of results. More important, this exploration will be helpful in discovering the neural mechanisms underlying the specific symptoms, which may offer some cues for the diagnosis and treatment of depression. Many studies have examined the association between the brain activities and depressive symptoms induced in normal subjects. Most of these studies paid attention to anxiety and transient sadness which are important symptoms of depression. In these studies, the induced anxiety was found to be associated with increased activity in the anterior cingulate gyrus (Javanmard et al., 1999; Kimbrell et al., 1999), the anterior insula and the inferior frontal gyrus (Kimbrell et al., 1999; Liotti et al., 2000), the anterior temporal lobe (Kimbrell et al., 1999) and the ventral prefrontal cortex (Liotti et al., 2000). In addition, the induced sadness was found to be associated with increased activity in the anterior cingulate gyrus and the insula (Liotti et al., 2000; George et al., 1995), and the ventral prefrontal cortex (Pardo et al., 1993). Some studies have directly investigated the correlation between the brain activity of depressed patients and

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the depressive symptoms. Bench et al. (1993) reported a positive correlation between the anxiety severity and the regional cerebral blood flow (rCBF) in the bilateral posterior cingulate gyrus and the inferior parietal lobule, as well as a positive correlation between cognitive performance and the rCBF in the left medial prefrontal cortex; Conversely, depressed mood and psychomotor retardation were correlated negatively with the rCBF in the left dorsolateral prefrontal cortex and the left angular gyrus. Dolan et al. (1994) found a positive correlation between cognitive performance and the rCBF in the bilateral medial prefrontal cortex and the anterior cingulate gyrus. Graff-Guerrero et al. (2004) reported that some items of the Hamilton Rating Scale for Depression (HRSD), widely used to measure depression severity, were correlated with the rCBF of some regions such as the anterior prefrontal cortex, the temporal lobe, the cingulate cortex, and the insula. Périco et al. (2005) reported that depressive mood was correlated negatively with the rCBF in the left amygdala, the lentiform nucleus, and the parahippocampal gyrus, and correlated positively with the rCBF in the right postero-lateral parietal cortex; Anxiety severity was correlated positively with the rCBF in the right antero-lateral orbitofrontal cortex; Insomnia severity was correlated negatively with the rCBF in the right subgenual and the rostral anterior cingulate gyrus, the insula and the claustrum; Cognitive performance was correlated positively with the rCBF in the right postero-medial orbitofrontal cortex and the left lentiform nucleus. However, the imaging method these studies used was SPCET, and previous resting studies in depression mainly used PET and SPECT, both of which have some significant limitations including exposure to radioactive tracers and poor spatial resolution. FMRI overcomes these limitations to a large extent. Since the first study performed by Biswal et al. (1995), resting-state fMRI has attracted more attention. But to our knowledge, only two resting-state fMRI studies were conducted on depression. Anand et al. (2005) reported cortico-limbic low-frequency blood fluctuations correlations were decreased in depression in resting state. Greicius et al. (2007) reported resting-state subgenual cingulate and thalamic functional connectivity with the default-mode network were higher in depression. The method for data analysis these studies used was correlation analysis which can only measure the correlation of time series between brain areas. When correlation was found abnormal, one couldn't determine which area was out of norm. Also, no study has yet investigated the relationship between brain activity and depressive symptom clusters in resting state using fMRI.

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In this resting-state fMRI study, we used a newly reported regional homogeneity (ReHo) method (Zang et al., 2004) to analyze the fMRI data. It had been used in the studies of other psychiatric disorders such as schizophrenia (Liu et al., 2006), and attention deficit hyperactivity disorder (Cao et al., 2006). In this method, Kendall's coefficient concordance (KCC) (Kendall and Gibbons, 1990) was used to measure the similarity of time series of a given voxel to those of its nearest voxels in a voxel-wise way based on the assumption that a voxel was temporally similar to those of its neighbors (Tononi et al., 1998). Using this method, we can measure the temporal homogeneity of regional Bloodoxygenation-level-dependent signal, which can reflect the temporal homogeneity of neural activity. For analysis of MDD symptoms, the 24-item Hamilton Rating Scale for Depression (HRDS) (Hamilton, 1960) was used, which grouped the MDD symptoms into 7 factors (Hamilton, 1967), these symptom factors were: anxiety (consisting of psychic anxiety, somatic anxiety, gastro-intestinal, hypochondriasis, and insight items), weight (only loss of weight item), cognitive disturbance (feeling of guilt, suicide, agitation, depersonalization or derealization, paranoid symptoms, and obsessional symptoms items), diurnal variation, retardation (consisting of depressed mood, work difficulty, interest difficulty, retardation, and loss of libido items), sleep disturbance (consisting of early, middle, and late insomnia items) and hopelessness (helplessness, hopelessness, and worthlessness). In the present study, we propose that abnormal brain activity existed in patients with MDD during resting state, and specific depressive symptoms might be related to the abnormal activity of specific brain regions in depressed patients. By comparing the resting-state, brain ReHo value between the patients with MDD and healthy controls, then analysing the correlations in the abnormal ReHo values of depressed patients with separate symptom factors, we were to investigate the features of brain activity of depressed patients, and the neural mechanisms underlying the depressive symptoms clusters, thereby offering more information to the understanding of the pathogenesis of depression. 2. Methods 2.1. Subjects All depressed patients were recruited from in-patient facilities at the Department of Psychiatry, Nanjing Brain Hospital of Nanjing Medical University, between January 2006 and February 2007. 22 patients with

unipolar MDD were recruited. Eligibility screening procedures included the Structured Clinical Interview for the DSM-IV (SCID) (First et al., 1997), the Brief Psychiatric Rating Scale (BPRS) (Overall and Gorham, 1961), the 24-item HDRS and common clinical laboratory tests. The initial diagnoses of MDD were made by the participants' treating psychiatrists and confirmed by an expert psychiatrist according to SCID. All of the patients were suffering in major depressive episode (include single episode and recurrent). All of the patients with major depression are typical. Patients were required to complete a minimum 2-week medication washout prior to MRI scans, and have a minimum score of 35 rated with the 24-item HDRS on the day of scanning. Patients with other psychiatric illnesses, and a history of electroconvulsive therapy were excluded. Healthy subjects were recruited by print advertisements from a roll of persons living in the same places or nearby as depressed patients. Each healthy subject was required to match a patient in gender, age, and education level. None had any current psychiatric illness or a history of psychiatric illness. Healthy subjects were also assessed with SCID and BPRS. All subjects were right-handed, and satisfied the criteria to undergo a MRI scan. Exclusion criteria for all subjects included: serious medical and neurological disorders, a family history of serious psychiatric or neurological illness in first degree relatives, age under 18 or above 55, abnormal clinical laboratory tests, acutely suicidal or homicidal tendencies, present or previous substance abuse and substance dependence, currently on prescription medication, currently pregnant or breastfeeding. After a complete description of the study to all subjects, written informed consents were obtained. The study was approved by the Research Ethics Review Board of the Nanjing Medical University. 2.2. MRI scan Imaging data were acquired using a GE Signa 1.5 T MRI scanner in the Nanjing Brain Hospital. All subjects were placed in a birdcage head coil and fitted to foam padding to reduce head motion. They were informed to hold still, keep their eyes closed and not think of anything in particular. The fMRI sequence was as follows: 1. Anatomic scan: T1-weighted axial images: repetition time / echo time (TR/TE) = 500/14 ms, thickness/gap = 1.0/0 mm, flip angle = 15°, inversion time = 400 ms, matrix = 256 × 128, field of view (FOV) = 240 × 240 mm2, in-plane resolution = 256 × 192.

Z. Yao et al. / Journal of Affective Disorders 115 (2009) 430–438 Table 1 Demographic and clinical characteristics of the sample.

Age Sex (men/women) Education level Number of previous episodes Duration of illness Drug history

Depressed patients (n = 22)

Healthy subjects (n = 22)

38.2 ± 10.2 10/12

38.8 ± 10.7 10/12

11.1 ± 2.4 years 3±2

12.0 ± 2.9years –

5.0 ± 4.5 years

–

Treatment naïve: 5 patients; Rest of the patients: 18–35 weeks

–

Unless otherwise indicated, data are expressed as mean ± SD, SD: standard deviation.

2. Resting-state functional scans: TR/TE = 3000 ms/40 ms, thickness/gap= 4.0/0 mm, flip angle = 15°, matrix = 64 × 64, FOV = 240 ×240 mm2, inplane resolution = 128 × 128, 27 sequence slices, time: 6 min and 39 s. 2.3. Image analysis 2.3.1. Image preprocessing The first 6 time points were discarded due to scanner calibration and adaptation of subject to the circumstance, 128 time points were left for further analysis. The format of imaging data was transferred by MRIcro software (http://www.mricro.com), then slice timing, head motion correction and spatial normalization were performed using statistical parametric mapping (SPM2, http:// www.fil.ion.ucl.ac.uk/spm). Through the above processes, images were normalized to the standard SPM2 echoplanar imaging template and interpolated to 3 × 3 × 3 mm cubic voxels. We calculated the maximum excursion movement values for each of planes of translation (x, y, and z) and each of planes of rotation (roll, pitch, and yaw) for every participant. Images of those patients, whose maximum values of each movement of three axia is less than 2 mm, and each degree of rotation of the three dimensions is less than 2°, were included. Then, using Analysis of Functional NeuroImages (AFNI, http://afni.nimh.nih.gov) software, images were bandpass filtered (0.01 Hz b f b 0.08 Hz) to reduce lowfrequency drift and physiological high frequency respiratory and cardiac noise (Biswal et al., 1995; Lowe et al., 1998), and remove linear trend to reduce the influence of the rising temperature of the MRI equipment. Final generated images went into ReHo analysis.

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2.3.2. ReHo analysis The ReHo analysis was done by ReHofMRI1.0 (http:// www.nlpr.ia.ac.cn/english/mic/YongHe/Research.htm). A KCC value (also called ReHo value) was calculated to measure the similarity of the time series of a given voxel to its nearest 26 voxels. The formula to calculate the KCC value has been expounded in previous studies (Zang et al., 2004; Liu et al., 2006). Through calculating the KCC value of every voxel in the whole brain, individual ReHo maps were generated. To reduce the influence of individual variations in the KCC value, normalization of ReHo maps was preformed through dividing the KCC among each voxel by averaged KCC of the whole brain. 2.3.3. Statistic analysis To explore the ReHo differences between the depressed group and control group, a second-level random-effect two-sample t-test was performed on the individual normalized ReHo maps in a voxel-by-voxel manner. Voxels with a p value b0.005 (uncorrected) and cluster size N270 mm3 (10 voxels) which have been used in previous ReHo analyses of functional imaging data (Cao et al., 2006; Yuan et al., 2008) were used to determine significant difference. The following analyses were performed with SPSS 11.5 software (SPSS Inc., Chicago, IL, USA). Firstly, we extracted the mean ReHo values of the clusters that had been shown differences between the depressed patients and healthy controls. Then Pearson correlation was used to measure the relationships between mean ReHo values of the clusters and 7 separate clinical factors, P b 0.05 (uncorrected) was used to determine significant correlation. 3. Results 3.1. Subjects 30 depressed patients and 30 healthy subjects completed the fMRI scans. 4 patients and 4 healthy subjects were excluded owing to excessive head motion, 4 Table 2 Scores for each factors and total score rated with 24-item HRSD. Factors in HRSD

Score (Mean ± SD)

1 Anxiety 2 Weight loss 3 Cognitive disturbance 4 Diurnal variation 5 Retardation 6 Sleep disturbance 7 Hopelessness Total score

10.77 ± 1.57 1.50 ± 0.60 11.68 ± 1.55 1.45 ± 0.59 10.77 ± 1.19 4.77 ± 1.02 8.36 ± 1.99 48.86 ± 4.89

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Table 3 Brain regions with decreased ReHo in depression and correlations between the ReHo value of these areas and the severity of symptom clusters of MDD (n = 22). Brain area a

Coordinates (x, y, z) b

Number of voxels c

Peak Z d

Cluster of symptom e

Direction of correlation

Correlation coefficient f

R orbitofrontal cortex (BA10)

30, 61, − 3

22

5.35

R fusiform gyrus (BA19) R ventral anterior cingulate gyrus (BA24) L dorsal anterior cingulate gyrus (BA32)

24, − 62, − 7 9, 2, 47 − 21, 30, 15

13 36 26

3.00 3.06 3.31

R posterior cingulate gyrus (BA31) L lentiform nucleus R insula (BA13)

21, − 33, 40 − 24, 3, − 8 39, − 5, 25

18 18 15

3.32 3.23 3.75

Cognitive disturbance Total score None Hopelessness Cognitive disturbance Sleep disturbance Retardation None Anxiety Retardation Hopelessness

Positive Positive – Positive Positive Positive Positive – Positive Positive Positive

0.62 0.47 – 0.49 0.49 0.45 0.61 – 0.45 0.46 0.55

R, right; L, left; BA, Broadmann area. a Brain regions which showed lower ReHo value in depression patients than healthy controls, the threshold was set at P b 0.005 (corrected). b Coordinates of the voxel of maximal statistical significance within each brain regions, according to the atlas of Talairach and Tournoux (1988). c Total number of voxels in each cluster. d Z-scores for the voxel of maximal statistical significance in each cluster. e The symptom clusters of MDD which showed significant correlations (p b 0.05) with the ReHo value of the brain regions. f Correlation coefficients for the relationship between symptom factor scores and ReHo value.

patients and 4 healthy subjects were excluded because of no proper matches. The results were present for 22 patients and 22 healthy subjects. Basic characteristics of subjects are detailed in Table 1, the results of HRSD rating are shown in Table 2. The depressed group and control group didn't differ significantly in age (p = 0.90) or education level (p = 0.46), there were no significant differences in maximum excursion movement values in

each of planes of translation (x, y, and z) (p N 0.05), and in each of planes of rotation (roll, pitch, and yaw) (p N 0.05) between the two groups. 3.2. ReHo: depressed patients versus healthy subjects As shown in Table 3 and Fig. 1, the depressed group showed a significant ReHo decrease, but no increase, in

Fig. 1. Brain areas with decreased regional homogeneity in depression: A, orbitofrontal cortex; B, fusiform gyrus; C, ventral anterior cingulate cortex; D, dorsal anterior cingulate cortex; E, posterior cingulate gyrus; F, lentiform gyrus; J, insula.

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the right orbitofrontal cortex, the right fusiform gyrus, the right ventral anterior cingulate gyrus, the left dorsal anterior cingulate gyrus, the right posterior cingulate gyrus, the left lentiform nucleus and the right insula. 3.3. The correlations between ReHo values and symptom severity factors Anxiety severity was positively correlated with the ReHo in the right insula. Cognitive disturbance severity was positively correlated with the ReHo in the right orbitofrontal cortex and the left dorsal anterior cingulate gyrus. Retardation severity was positively correlated with the ReHo in the right posterior cingulate gyrus and the right insula. Sleep disturbance severity was positively correlated with the ReHo in the left dorsal anterior cingulate gyrus. Hopelessness severity was positively correlated with the ReHo in the right ventral anterior cingulate gyrus and the right insula (p b 0.05). 4. Discussion Using the ReHo approach, we found a diffuse ReHo decrease in the patients with MDDs during resting state, which was mainly distributed over frontal, limbic lobes and basal ganglia. MDDs showed abnormal ReHo areas in our study are involved in the limbic–cortical–striatal– pallidal–thalamic circuit, thus providing additional evidence for the hypothesis regarding the involvement of this circuit in the pathophysiology of depression. The correlation analysis indicated that the severity of anxiety, cognitive disturbance, retardation, sleep disturbance and hopelessness were related to the abnormal activities of specific brain regions in depressed patients. The orbitofrontal cortex is likely important for a wide range of functions, including emotional processing and memory, stimulus–reward association, reward-guided behavior, impulse control, and control of autonomic pathway (Price, 1999; Zald and Kim, 2001). Connectivity studies have found that the orbitofrontal cortex is connected with the hippocampal formation, the amygdala, the dorsolateral prefrontal cortex, the thalamic nucleus, the posterior cingulate cortex and the anterior cingulate cortex (Carmichael and Price, 1995a,b). Hyperactivity of the orbitofrontal cortex has been reported during negative mood induced in normal subjects(Baker et al., 1997), and in depressed patients (Drevets et al., 1995). Périco et al. (2005) found direct correlation of rCBF in the orbitofrontal cortex with cognitive performance of MDD patients. The ReHo decrease in the orbitofrontal cortex and a correlation in the ReHo value of this region with cognitive disturbance

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in depressed patients shown in our study were consistent with the results of previous studies, thereby providing more evidences as to the involvement of the orbitofrontal cortex in cognitive deficits of depression. The variety of functional roles and the patterns of interconnections of the orbitofrontal cortex with other cortical and subcortical structures may explain the relationship between the ReHo of the orbitofrontal cortex and the total score in depressed patients shown in our study. The fusiform gyrus is thought to be important for facial processing (Kanwisher et al., 1997). Facial expression is an important signal revealing individual emotional state. Accurate recognition of facial expressions is crucial for social functioning. In depression, Surguladze et al. (2005) reported that depressed patients but not healthy subjects demonstrated an increase of the response in the right fusiform gyrus to expressions of increasing sadness, and a negative correlation in depressive severity with neural response of the right fusiform gyrus to happy expressions, while healthy subjects demonstrated a increase in response of the bilateral fusiform gyrus to expressions of increasing happiness. Our study showed the abnormality of the right fusiform gyrus in MDD patients during resting state, together with the earlier study, indicated a participation of dysfunction of the fusiform gyrus in the negative cognitive models (Beck, 1976). On the other hand, we didn't find a correlation in the activity of this region with any symptom factors. As we know, previous studies also didn't found significant correlation between the fusiform gyrus and any depressive symptoms (Périco et al., 2005; Graff-Guerrero et al., 2004), which indicated that the involvement of the fusiform gyrus in depression or the abnormality of fusiform gyrus can't be used to predict the severity of depressive symptoms. In our study, ReHo decreases in the right ventral anterior cingulate gyrus and the left dorsal anterior cingulate gyrus were found in depressed patients. The ReHo of the right ventral anterior cingulate gyrus was correlated with the severity of hopelessness, while the left dorsal anterior cingulate gyrus was correlated with the severity of cognitive and sleep disturbance. It is thought that the anterior cingulate gyrus plays a critical role in the cognition and emotional regulation, the ventral anterior cingulate gyrus is involved in emotion, mood and autonomic functions (Mayberg et al., 2002), while the dorsal anterior cingulate gyrus has been found to be associated with specific motor, attention and cognitive functions (MacDonald et al., 2000). In depression, an inability of response of the anterior cingulate gyrus to the stimulus was shown in some cognitive tasks (George et al., 1997; Elliott et al., 1997).

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Our study also supported the abnormality of the anterior cingulate gyrus in depression. The functional division of the anterior cingulate gyrus in cognition and emotion may account for the correlation in the activity of the right ventral anterior cingulate gyrus with the severity of hopelessness, as well as a correlation in the left dorsal anterior cingulate gyrus with the severity of cognitive and sleep disturbance. The posterior cingulate gyrus is related to episodic memory (Maddock et al., 2001). Moreover, it has been speculated that the posterior cingulate gyrus plays a role in the modulation of memory by emotionally arousing stimuli (Maddock, 1999). Maddock et al. (2003) have reported that the posterior cingulate gyrus of normal subjects showed relatively greater activity to thoughts about duties and obligations than to thoughts about hopes and aspirations. In depression, the activity of posterior cingulate gyrus was found increased in most studies and decreased in a few studies in resting state (Drevets, 2000). We found a decreased ReHo in the posterior cingulate gyrus, and its correlation with the severity of retardation in depressed patients. Along with the previous studies, we propose the abnormality of posterior cingulate gyrus might play a role in memory impairment and a persistent, emotionally-laden, self reflective tendency in depression. This may help to explain the correlation in the activity of posterior cingulate gyrus with severity of retardation. The basal ganglia are connected with the anterior cingulate gyrus, dorsolateral prefrontal cortex and cerebellum (Graybiel, 2000). This region is thought to be involved in cognitive processing (Middleton and Strick, 2000). In depression, reduced rCBF of the basal ganglia has been shown (Mayberg et al., 1994). We found the abnormality of the left lentiform gyrus in depressed patients, which offered more evidence to the participation of basal ganglia in depression. Yet we didn't find a correlation in this region with any symptom factors. This is inconsistent with the previous studies (Bench et al., 1993) showing a correlation in the activity of left lentiform gyrus and cognitive performance rated with Mini Mental State Examination (MMSE). We propose the difference of rating method might be a cause of the inconsistency. In addition, we found a decreased ReHo in the right insula in depression patients, which was correlated with severity of anxiety, retardation, and hopelessness. Reiman et al. (1997) reported that the recall-generated sadness was associated with greater rCBF in the anterior insular in normal subjects, which indicated the involvement of the insula in the emotional response to potentially distressing thoughts or interoceptive sensory

stimuli. An association was also found in induced anxiety with the increased activity in the insula in normal subjects (Liotti et al., 2000). In depression, GraffGuerrero et al. (2004) reported a significant correlation in the rCBF of the insula and the severity of agitation, which may support our findings. The role of the insula in sadness and anxiety may explain the correlation in the activity of the insula with severity of anxiety and hopelessness, which may be contributed to a correlation with retardation. None of the regions was shown to be abnormal bilaterally and this correlated accordingly in the depressed patients. Previous findings on brain lateralization in MDD have been conflicting. Some tended to right hemisphere (Flor-Henry and Koles, 1984), while some tended to left hemisphere (Vataja et al., 2004). The correlation analysis between the lateralization in brain function and specific symptom clusters in depression may be helpful for explaining the contradictions. Some limitations in our study are worth mentioning. Firstly, though all patients were required to complete a minimum 2-week medication washout prior to MRI scans, most of the patients have a history of antidepressant medication, in this case, we can't completely exclude the influence of medicine to brain activity. Obviously, the ideal study would have all depressed patients in an unmedicated state, but it would face some substantial practical and ethical problems. Another limitation we couldn't avoid is the slow sampling rate. It is known that with slow sampling rates (as in this study TR = 3 s), noise from the cardiac and respiratory cycle can alias into the resting-state low frequency ranges (Lowe et al., 1998). Since the influence extent is uncertain, we can't assume the influence of the respiratory and cardiac cycle artifacts on the resting-state low frequency ranges are same in the two groups. The respiratory and cardiac cycle artifacts may therefore be potential confounding factors. Since we couldn't exclude the interference of some potential confounding factors such as medication, and respiratory and cardiac cycle artifacts, we used a two sample t-test. In addition, the uncorrected p value we used was a liberal strategy and may limit the external validity of our results to some extent. As the application of uncorrected level may lead to a type I error, these findings should be considered preliminary due to this and should be treated with caution. In conclusion, our finding indicated abnormal brain activity was distributed extensively in depressed patients during resting state, and some separate symptom domains of depression are related to specific abnormal patterns of brain activity. Based on the previous works (Cao et al., 2006; Liu et al., 2006; Yuan et al., 2008), the

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ReHo approach shows some promise as a clinical indicator of functional deficit for mental disorders. Role of funding source Funding for this study was provided by the National Natural Science Foundation of China (30500179), The National High-tech Research and Development Program (863 Program) (2008AA02Z410), the Natural Science Foundation of Jiangsu Province (BK2005427) and the Key Medical Developing Program of Nanjing (IKX05003), which had no further role in study design, in the collection, analysis and interpretation of data, in the writing of the report, and in the decision to submit the paper for publication. Conflict of interest All authors declare that they have no conflicts of interest.

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