1302 Clinical neuroscience
Altered spontaneous neural activity in first-episode, unmedicated patients with major depressive disorder Ting Shena,*, Meihui Qiua,*, Chao Lia, Jie Zhanga, Zhiguo Wua, Biao Wanga, Kaida Jiangb and Daihui Penga Abnormal brain function is presumed to be a pathophysiological aspect of major depressive disorder (MDD). However, the underlying patterns of spontaneous neural activity have been poorly characterized and replicated to date. In this study, we applied a novel approach of fractional amplitude of low-frequency fluctuation (fALFF) to investigate the alteration of spontaneous neural activity in MDD. Sixteen first-episode, unmedicated patients with MDD and 16 healthy controls were recruited and subjected to resting-state fMRI scans to measure the fALFF across the whole brain. Compared with healthy controls, MDD patients exhibited decreased fALFF in the right angular gyrus, left middle temporal gyrus, left superior temporal gyrus, right putamen, right precuneus, and the right superior temporal gyrus. Differences in fALFF between MDD patients and controls indicated that altered spontaneous neural activity was distributed across a number of specific brain regions among MDD patients. These atypical functional regions may
Introduction Major depressive disorder (MDD) is generally characterized by negative mood and other specific symptoms, such as cognitive deficits (e.g. dysfunctional visual attention or memory) [1–3] and somatic symptoms (e.g. insomnia, lack of appetite, and lower libido) [4]. Although these symptoms are well documented, the underlying neurobiological mechanisms are not well understood, and as a consequence, clinicians are forced to rely predominately on symptom-based assessments [5]. One promising avenue for improving this deficit is functional MRI (fMRI), a novel approach used to measure neurobiological patterns. In the human brain, low-frequency fluctuation (LFF; < 0.08 Hz) of fMRI signals can be observed in the resting state [6,7], which may reflect the spontaneous neuronal activity of brain regions [8]. Two methods to measure the fluctuation amplitude from the changes in oxygen levels are used to detect regional spontaneous activity in the resting-state. Biswal et al. [7] reported that the amplitude of LFF (ALFF) might reflect the absolute intensity of spontaneous brain activity by measuring the total power within the low-frequency range from 0.01 to 0.08 Hz [9]. Among patients with depression, previous studies found that some have abnormal ALFF [10–13], but a few of these results have withstood replication. For instance, Guo et al. [10] reported that patients with early onset 0959-4965 © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins
help explain some of the neural processes underlying the clinical symptoms accompanying MDD. NeuroReport 25:1302–1307 © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. NeuroReport 2014, 25:1302–1307 Keywords: depression, fractional amplitude of low-frequency fluctuation, functional MRI, resting state a Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine and bHuashan Hospital, Fudan University, Shanghai, China
Correspondence to Daihui Peng, MD, Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China Tel: + 86 21 64387250 x73529; fax: + 86 2164387986; e-mail: [email protected] *Ting Shen and Meihui Qiu are joint first authors. Received 22 April 2014 accepted 21 August 2014
MDD showed lower ALFF in the left superior/inferior temporal gyrus, right middle occipital gyrus, and left lingual gyrus, as well as higher ALFF in the left medial and bilateral superior frontal gyrus; however, recent studies using a similar depressed sample could not reproduce these findings [13,14], nor could studies using different depressed samples [11,12]. The fractional ALFF (fALFF) approach was further developed by defining the ratio of the power spectrum of the lowfrequency range (0.01–0.08 Hz) to that of the entire detectable frequency range without filtering, which has greater sensitivity and specificity for detecting spontaneous neural activities [8]. Again though, several previous studies on fALFF among depressed patients did not observe the same findings [15,16]. The general disparity between these study findings indicates a lack of consensus on the spontaneous activity of MDD at the brain region level. Abnormal neural activity is likely a pathophysiological aspect of MDD. Whether or not this is an accurate assessment is debatable – the aforementioned studies alone illustrate how conflicting the findings across different studies can be. Further studies using accepted techniques must be conducted to gain a clearer overall picture. In view of fALFF as a novel approach that has had some promising, albeit conflicting, results, we measured spontaneous neural activity and hypothesized that DOI: 10.1097/WNR.0000000000000263
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Altered spontaneous neural activity in MDD Shen et al. 1303
patients with MDD will show abnormal patterns of fALFF within specific brain regions. To test this hypothesis, while avoiding as many confounding factors as possible (e.g. medication effects and illness duration), we carried out fALFF analysis of resting-state fMRI data in unmedicated patients with MDD during the earlier period of the first episode and compared these findings with those from healthy controls.
Methods Participants
Patients with MDD were recruited from outpatient clinics at Shanghai Mental Health Centre and the Huashan Hospital in Shanghai. In total, 16 patients who met the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV) diagnosis criteria for MDD were enrolled, on the basis of the following conditions (inclusion criteria): age 25–50 years, no other diagnosed axis I or II disorder from DSM-IV, a 24-item Hamilton Depression Scale (HAMD) score greater than 20 [17], a 14-item Hamilton anxiety scale (HAMA) score less than 7, no evidence of having received any psychological treatment before or medication over the past 4 weeks, and no observed or diagnosed medical or neurological illness. Exclusion criteria were as follows: evidence of a current suicide attempt, substance dependence (except nicotine) during the past year, alcohol drinking in the prior week, or pregnancy or breastfeeding. Sixteen healthy controls were recruited through advertisement in the two psychiatry services. Inclusion criteria for health controls were as follows: no history of any DSM-IV axis I or II disorder and no first degree relative with a family history of major psychiatric or neurological illness. Exclusion criteria for health controls were as follows: current administration of any prescription medication, consumption of alcohol in the prior week, and pregnancy or breastfeeding. Two health controls were later excluded because of excessive head motion during the fMRI scan (details in the following section). The remaining health controls did not differ significantly from the MDD patients in terms of age and sex distribution (sex: seven male/nine female in the MDD group and six male/eight female in the control group, χ2 = 0.002, P = 0.961; age: 34.44 ± 6.72 years in the MDD group, 32.36 ± 5.30 years in the control group, t = 0.931, P = 0.324). In the MDD group, the mean age of onset was 33.25 ± 6.98 years and the mean duration of illness was 2.63 ± 1.14 months. The MDD group had significantly higher HAMD (30.88 ± 7.69 for the MDD group, 2.63 ± 1.96 for healthy controls) and HAMA scores (5.62 ± 0.72 for the MDD group, 3.31 ± 0.87 for healthy controls) compared with the control group (P < 0.05). All the participants were right-handed, with no metallic implants or any other factors that could affect MRI scanning. All participants provided written informed consent before their enrollment in the study. All
protocols of this study were approved by the Investigational Review Board of Shanghai Mental Health Center, China. MRI acquisition
Image data were acquired using a 3.0 T magnetic resonance scanner (General Electric, Milwaukee, Wisconsin, USA) with a standard whole-head coil. A high-resolution T1-weighted structural image was obtained using the spoiled GRASS gradient sequence with the following parameters: repeat time (TR) = 5.9 ms, echo time (TE) = 1.4 ms, flip angle (FA) = 15°, resolution = 1 × 1 × 1 mm3, without gap. The fMRI images were obtained using an echo planar imaging sequence with the following parameters: TR/TE = 3000 ms/30 ms, flip angle = 90°, resolution = 3.75 × 3.75 × 5.0 mm3, without gap, 22 axial slices. For each participant, the entire scan lasted 300 s and comprised 100 volumes. Imaging data preprocessing
Image data were preprocessed using the Data Processing Assistant for Resting-State fMRI software (DPARSF, http://rfmri.org/DPARSF) [18]. The first 10 volumes were removed to allow for magnetization equilibrium and then the remaining volumes from each participant were sliced and realigned. Examination of the image data revealed that two healthy controls had to be excluded because of excessive head motion (exclusion criteria: movement by more than 2.0 mm or greater than 2.0° head motion). The remaining data were then normalized to the standard Montreal Neurological Institute (MNI) space and resampled with a resolution of 3 × 3 × 3 mm3 using echo planar imaging templates. Next, the images were smoothed to a Gaussian kernel of 4-mm full-width at half-maximum and the linear trend was removed to continue subsequent analysis with band-pass filtering (0.01–0.08 Hz) [6,7]. fALFF calculation
The fALFF analysis was carried out using DPARSF software as follows [15,16]: (i) by acquiring the power spectrum after transforming the time series of each voxel into the frequency domain without band-pass filtering using a Fast Fourier Transform; (ii) obtaining the average square root across 0.01–0.08 Hz at each voxel after it was calculated at each frequency of the power spectrum; (iii) extracting the ratio of the amplitude across 0.01–0.08 Hz to the whole frequency range as the fALFF [8]. For standardization, the fALFF of each voxel was divided by the global mean fALFF value within a whole brain mask [19]. Statistical analyses
All demographic data and clinical variables were analyzed using SPSS 16.0 (SPSS Inc., Chicago, Illinois, USA). Differences in fALFF between the MDD and control groups were evaluated using a two sample t-test with the
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REST software (http://restfmri.net/forum). Corrected threshold values were set at P = 0.01 and cluster size greater than 324 mm3 (12 voxels), as measured by AlphaSim and confined within a whole brain mask; this corresponded to a corrected P-value less than 0.01 for statistical significance. To evaluate the correlations between clinical symptoms and aberrant brain activity, the mean fALFF values of brain regions showing significant differences between the two groups were extracted. Pearson correlation analysis was carried out between the mean fALFF values in MDD patients and the total HAMD score, age of onset, and duration of disease, with P less than 0.05 considered statistically significant.
Results Sixteen patients with MDD and 14 healthy controls completed the analysis of fMRI data. Compared with the healthy controls, patients with MDD showed significantly decreased fALFF in the right angular gyrus, left middle temporal gyrus, left superior temporal gyrus, right putamen, right precuneus, and the right superior temporal gyrus. No significantly increased fALFF was found in the patients group. Details of the group differences are shown in Table 1 and Fig. 1. There was no significant correlation between the mean fALFF values of the different brain regions and clinical characteristics, including total HAMD score, age of onset, and duration of disease (P >0.05).
Discussion This study showed a decreased fALFF in the right angular gyrus, left middle temporal gyrus, bilateral superior temporal gyrus, right putamen, and right precuneus among patients with MDD (Table 1, Fig. 1). These results are partially consistent with those of recent studies reporting a decreased fALFF [15,16] and ALFF among MDD patients [10–13], but with some marked differences. The previous studies reported a significantly Table 1 Regions showing significant differences in fALFF between the patients with MDD and healthy controls MNI coordinate Brain regions NC > MDD Angular gyrus Middle temporal gyrus/ Superior temporal gyrus Putamen Precuneus Superior temporal gyrus
L/R Cluster size BA R L
77 59
L R R R
39 37/
x
y
z
t-value
51 − 48
− 66 − 69
42 12
4.69 5.38
27 3 63
9 − 72 − 54
6 24 15
4.21 3.76 5.17
22 34 24 21
22
BA, Brodmann area; L, left; MDD, major depressive disorder; MNI, Montreal Neurological Institute; NC, healthy control; R, right. Corrected P < 0.01.
increased fALFF in some brain regions of MDD patients (i.e. the right precentral gyrus, right inferior temporal gyrus, and bilateral fusiform gyrus [15], as well as the right putamen and the right ventral median frontal gyrus) [16]. These inconsistencies may be partially explained by differences in the analytical method, sample heterogeneity, and/or sample size between these studies, especially as the clinical participants scanned in this study were unmedicated during the early period of illness. Presuming that fALFF is a potential index of spontaneous neural activity [8], our findings suggest that there may be atypical neural activity distributed in specific brain regions of patients with MDD. To assess the abnormal spontaneous activity in MDD, it is important to note three main findings of the brain regions with significantly different fALFF in MDD patients from that among the healthy controls. First, the putamen showed decreased fALFF among our MDD patients without medication. Generally, the putamen has been confirmed to have reduced volume among patients with depression [20]. During processing of emotional stimuli, the putamen was found to increase the strength of responses to negative information and, conversely, decrease that to positive information [21]. Moreover, the putamen is a core region of the ‘hate neural circuit’ on the basis of the report of Tao et al. [22]. The depressed patients are supposed to have abnormal ‘hate neural circuit’ constructed of some specific brain areas, and accordingly can not reduce their cognition control over negative feelings [22]. Alterations in both structure and function have previously been shown to be associated with the putamen and negative regulation of mood in MDD. Given these factors, the decreased fALFF in the putamen found in this study may provide a foundation for further exploring how negative mood emerges in patients with MDD. Another finding of this study is that patients with MDD exhibited decreased fALFF in the left middle temporal gyrus and bilateral superior temporal gyrus. These findings are consistent with those from previous studies reporting decreased regional homogeneity within the temporal lobe [20,23–25], which is a similar index used to measure spontaneous neural activity. Besides the essential functions of auditory processing and language development, the superior temporal gyrus plays important roles in mood regulation in depressive disorders [26]. Moreover, this gyrus is responsible for the processing of emotions in facial stimuli [27,28]. Because of this specific function, the temporal gyrus should likely be involved in the processing of cognition related to mood [27]. Previous studies seem to concur with this conclusion, as patients with depression tend to have temporal lobes of a smaller volume [29,30]. The decreased regional homogeneity within this region is thought to be related to the altered temporal structure in MDD patients [23]. Likewise, the decrease in fALFF within the temporal gyrus may
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Altered spontaneous neural activity in MDD Shen et al. 1305
Fig. 1
R
L
+4.86 +4.54 +4.18 −6
−2
+2
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+3.83 +3.47 +3.12 +2.76 −2.76 −3.20
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−3.63 −4.07 −4.51 −4.94 −5.38
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T-statistic maps of fractional amplitude of low-frequency fluctuation (fALFF) between the patients with major depression disorder (MDD) and healthy controls. Color bars refer to the T-value: warm color bars indicate increased fALFF and cold color bars indicate decreased fALFF in the patients with MDD relative to healthy controls. The numbers below the images refer to the z coordinates of the Montreal Neurological Institute (MNI) template. The threshold was set at P < 0.01 and cluster size greater than 12 voxel.
underlie the potential neural activity responsible for the processing of negative mood and cognition in patients with MDD. One further finding that was worth noting is that of decreased fALFF in the right angular gyrus and right precuneus among MDD patients. The roles of the two regions may contribute to the default mode network (DMN) of the brain at resting state [19,31], which is mainly associated with cognition control and strategic/ executive functions [32]. The precuneus is located in the center of the DMN; thus, even if there is lack of consensus with regard to the nature of the DMN in depression, abnormal DMN functions is an established feature of MDD [33–35]. Zhu et al. [36] further demonstrated that decreased functional connectivity in the posterior regions of the DMN, especially in the precuneus and angular gyrus, is associated with deficits in
overgeneral autobiographical memory. Accordingly, patients with MDD tend to exhibit a variety of clinical symptoms related to cognitive deficits [1–3]. If accurate, decreased fALFF in the right angular gyrus and right precuneus found in the current MDD samples may also be one of the underlying neural patterns for these types of clinical symptoms. No significant correlations were found between the mean fALFF values of the different brain regions, and the clinical characteristics might conform to some previous findings [15,37]. However, other previous studies found a positive or negative relationship between the mean fALFF values and clinical indices among patients with MDD [16,38,39]. For example, the right precuneus in currently depressed patients with MDD showed positive correlations with the number of depressive episodes, the duration of disease, and the fALFF values, which further
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supports the fact that increased fALFF in the precuneus may be a state marker of MDD [16]. Compared with those studies that indicated a significant relationship between fALFF and clinical characteristics [16,38,39], the current findings may result from differences in sample characteristics, such as first-episode MDD and early period of the MDD disease course without medication. This might suggest that fALFF in these different brain regions leads to trait alteration in MDD, underlying the pathogenesis of MDD rather than functioning as a specific state marker to assess the symptom severity or other clinical characteristics. We should note two limitations of this study. First, the relatively small sample likely leads to some speculation on the nature of the clinical implications of abnormal fALFF in patients with MDD. Second, although we found abnormal spontaneous neural activity in some patients that could have contributed to the negative mood and cognitive deficits in MDD patients, we did not successfully confirm the relationship between specific brain regions and somatic symptoms using our fALFF approach. As mentioned by Biswal et al. [7], ALFF might reflect the absolute intensity of spontaneous brain activity. The structure or function has been reported to be abnormal in some specific brain regions in patients with MDD [10,13,16,40,41]. For example, ALFF values in the right middle temporal gyrus were reduced in patients with MDD [41], whereas reduced volume was found in the right middle temporal gyrus of patients with MDD [42]. This region, known to be a part of the extended dorsal attention system, is involved in cued attention and working memory [41,42], and decreased ALFF in this region should contribute to the cognitive deficits associated with MDD. Thus, we further speculate that altered fALFF might indicate abnormal function in specific brain regions of patients with MDD. We still need an additional index to examine the underlying neural activity, and we need to further define the physiological mechanism of fALFF in MDD through longitudinal studies with larger sample sizes.
and no. YG2012MS11) and Fund of Science and Technology Commission of Shanghai Municipality (grant no. 134119a6200). Conflicts of interest
There are no conflicts of interest.
References 1
2
3
4
5
6
7
8
9
10
11
12
13
14
Conclusion The present study describes the atypical patterns in unmedicated patients with MDD during their first episode, defined by decreased fALFF in the right angular gyrus, left middle temporal gyrus, bilateral superior temporal gyrus, right putamen, and right precuneus. All the regions may potentially be confirmed to have abnormal spontaneous activity on the basis of fALFF, which subsequently highlights the underlying neural mechanism behind the clinical symptoms that accompany MDD, such as negative mood and cognition deficits.
Acknowledgements This work was supported by the Science Fund of Shanghai Jiao Tong University (grant no. 11XJ21006
15
16
17 18 19
20
Li CT, Lin CP, Chou KH, Chen IY, Hsieh JC, Wu CL, et al. Structural and cognitive deficits in remitting and non-remitting recurrent depression: a voxelbased morphometric study. NeuroImage 2010; 50:347–356. Turner AD, Furey ML, Drevets WC, Zarate C Jr, Nugent AC. Association between subcortical volumes and verbal memory in unmedicated depressed patients and healthy controls. Neuropsychologia 2012; 50:2348–2355. Greer TL, Sunderajan P, Grannemann BD, Kurian BT, Trivedi MH. Does duloxetine improve cognitive function independently of its antidepressant effect in patients with major depressive disorder and subjective reports of cognitive dysfunction? Depress Res Treat 2014; 2014:627863. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. Washington, DC: American Psychiatric Association; 2013. Bagby RM, Ryder AG, Schuller DR, Marshall MB. The Hamilton Depression Rating Scale: Has the gold standard become a lead weight? Am J Psychiatry 2004; 161:2163–2177. Lowe MJ, Mock BJ, Sorenson JA. Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage 1998; 7:119–132. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995; 34:537–541. Zou QH, Zhu CZ, Yang Y, Zuo XN, Long XY, Cao QJ, et al. An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF. J Neurosci Methods 2008; 172:137–141. Zang YF, He Y, Zhu CZ, Cao QJ, Sui MQ, Liang M, et al. Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev 2007; 29:83–91. Guo WB, Liu F, Xun GL, Hu MR, Guo XF, Xiao CQ, et al. Reversal alterations of amplitude of low-frequency fluctuations in early and late onset, first-episode, drug-naive depression. Prog Neuropsychopharmacol Biol Psychiatry 2013; 40:153–159. Jiao Q, Ding J, Lu G, Su L, Zhang Z, Wang Z, et al. Increased activity imbalance in fronto-subcortical circuits in adolescents with major depression. PLoS One 2011; 6:e25159. Fan T, Wu X, Yao L, Dong J. Abnormal baseline brain activity in suicidal and non-suicidal patients with major depressive disorder. Neurosci Lett 2013; 534:35–40. Zhang X, Zhu X, Wang X, Zhu X, Zhong M, Yi J, et al. First-episode medication-naive major depressive disorder is associated with altered resting brain function in the affective network. PLoS One 2014; 9:e85241. Lord A, Horn D, Breakspear M, Walter M. Changes in community structure of resting state functional connectivity in unipolar depression. PLoS One 2012; 7:e41282. Wang L, Dai W, Su Y, Wang G, Tan Y, Jin Z, et al. Amplitude of lowfrequency oscillations in first-episode, treatment-naive patients with major depressive disorder: a resting-state functional MRI study. PLoS One 2012; 7:e48658. Jing B, Liu CH, Ma X, Yan HG, Zuo ZZ, Zhang Y, et al. Difference in amplitude of low-frequency fluctuation between currently depressed and remitted females with major depressive disorder. Brain Res 2013; 1540:74–83. Hamilton M. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol 1967; 6:278–296. Chao-Gan Y, Yu-Feng Z. DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI. Front Syst Neurosci 2010; 4:13. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc Natl Acad Sci USA 2001; 98:676–682. Yuan Y, Zhang Z, Bai F, Yu H, Shi Y, Qian Y, et al. Abnormal neural activity in the patients with remitted geriatric depression: a resting-state functional magnetic resonance imaging study. J Affect Disord 2008; 111:145–152.
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Altered spontaneous neural activity in MDD Shen et al. 1307
21
22 23
24
25
26
27
28
29
30
31
32
Fitzgerald PB, Laird AR, Maller J, Daskalakis ZJ. A meta-analytic study of changes in brain activation in depression. Hum Brain Mapp 2008; 29:683–695. Tao H, Guo S, Ge T, Kendrick KM, Xue Z, Liu Z, Feng J. Depression uncouples brain hate circuit. Mol Psychiatry 2013; 18:101–111. Peng DH, Jiang KD, Fang YR, Xu YF, Shen T, Long XY, et al. Decreased regional homogeneity in major depression as revealed by resting-state functional magnetic resonance imaging. Chin Med J (Engl) 2011; 124:369–373. Chen JD, Liu F, Xun GL, Chen HF, Hu MR, Guo XF, et al. Early and late onset, first-episode, treatment-naive depression: same clinical symptoms, different regional neural activities. J Affect Disord 2012; 143:56–63. Lai CH, Wu YT. Frontal regional homogeneity increased and temporal regional homogeneity decreased after remission of first-episode drug-naïve major depressive disorder with panic disorder patients under duloxetine therapy for 6 weeks. J Affect Disord 2012; 136:453–458. Anand A, Li Y, Wang Y, Wu J, Gao S, Bukhari L, et al. Activity and connectivity of brain mood regulating circuit in depression: a functional magnetic resonance study. Biol Psychiatry 2005; 57:1079–1088. Bigler ED, Mortensen S, Neeley ES, Ozonoff S, Krasny L, Johnson M, et al. Superior temporal gyrus, language function, and autism. Dev Neuropsychol 2007; 31:217–238. Radua J, Phillips ML, Russell T, Lawrence N, Marshall N, Kalidindi S, et al. Neural response to specific components of fearful faces in healthy and schizophrenic adults. Neuroimage 2010; 49:939–946. Caetano SC, Fonseca M, Hatch JP, Olvera RL, Nicoletti M, Hunter K, et al. Medial temporal lobe abnormalities in pediatric unipolar depression. Neurosci Lett 2007; 427:142–147. Williams M, Perera S, Pearce RKB, Hirsch SR, Maier M. Changes in grey matter thickness in the frontal, temporal and occipital lobes in schizophrenia and depression. Schizophr Res 2008; 98:151. Greicius MD, Krasnow B, Reiss AL, Menon V. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci USA 2003; 100:253–258. Buckner RL, Andrews-Hanna JR, Schacter DL. The brain’s default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci 2008; 1124:1–38.
33
34
35
36
37
38
39
40
41
42
Sheline YI, Price JL, Yan Z, Mintun MA. Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proc Natl Acad Sci USA 2010; 107:11020–11025. Greicius MD, Flores BH, Menon V, Glover GH, Solvason HB, Kenna H, et al. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry 2007; 62:429–437. Bluhm R, Williamson P, Lanius R, Théberge J, Densmore M, Bartha R, et al. Resting state default-mode network connectivity in early depression using a seed region-of-interest analysis: decreased connectivity with caudate nucleus. Psychiatry Clin Neurosci 2009; 63:754–761. Zhu X, Wang X, Xiao J, Liao J, Zhong M, Wang W, Yao S. Evidence of a dissociation pattern in resting-state default mode network connectivity in first-episode, treatment-naive major depression patients. Biol Psychiatry 2012; 71:611–617. Liu F, Guo W, Liu L, Long Z, Ma C, Xue Z, et al. Abnormal amplitude lowfrequency oscillations in medication-naive, first-episode patients with major depressive disorder: a resting-state fMRI study. J Affect Disord 2013; 146:401–406. Guo W, Liu F, Zhang J, Zhang Z, Yu L, Liu J, et al. Dissociation of regional activity in the default mode network in first-episode, drug-naive major depressive disorder at rest. J Affect Disord 2013; 151:1097–1101. Liu CH, Ma X, Wu X, Fan TT, Zhang Y, Zhou FC, et al. Resting-state brain activity in major depressive disorder patients and their siblings. J Affect Disord 2013; 149:299–306. Grieve SM, Korgaonkar MS, Koslow SH, Gordon E, Williams LM. Widespread reductions in gray matter volume in depression. Neuroimage Clin 2013; 3:332–339. Guo WB, Liu F, Xue ZM, Xu XJ, Wu RR, Ma CQ, et al. Alterations of the amplitude of low-frequency fluctuations in treatment-resistant and treatmentresponse depression: a resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry 2012; 37:153–160. Ma C, Ding J, Li J, Guo W, Long Z, Liu F, et al. Resting-state functional connectivity bias of middle temporal gyrus and caudate with altered gray matter volume in major depression. PloS One 2012; 7:e45263.
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Altered spontaneous neural activity in first-episode, unmedicated patients with major depressive disorder Ting Shena,*, Meihui Qiua,*, Chao Lia, Jie Zhanga, Zhiguo Wua, Biao Wanga, Kaida Jiangb and Daihui Penga Abnormal brain function is presumed to be a pathophysiological aspect of major depressive disorder (MDD). However, the underlying patterns of spontaneous neural activity have been poorly characterized and replicated to date. In this study, we applied a novel approach of fractional amplitude of low-frequency fluctuation (fALFF) to investigate the alteration of spontaneous neural activity in MDD. Sixteen first-episode, unmedicated patients with MDD and 16 healthy controls were recruited and subjected to resting-state fMRI scans to measure the fALFF across the whole brain. Compared with healthy controls, MDD patients exhibited decreased fALFF in the right angular gyrus, left middle temporal gyrus, left superior temporal gyrus, right putamen, right precuneus, and the right superior temporal gyrus. Differences in fALFF between MDD patients and controls indicated that altered spontaneous neural activity was distributed across a number of specific brain regions among MDD patients. These atypical functional regions may
Introduction Major depressive disorder (MDD) is generally characterized by negative mood and other specific symptoms, such as cognitive deficits (e.g. dysfunctional visual attention or memory) [1–3] and somatic symptoms (e.g. insomnia, lack of appetite, and lower libido) [4]. Although these symptoms are well documented, the underlying neurobiological mechanisms are not well understood, and as a consequence, clinicians are forced to rely predominately on symptom-based assessments [5]. One promising avenue for improving this deficit is functional MRI (fMRI), a novel approach used to measure neurobiological patterns. In the human brain, low-frequency fluctuation (LFF; < 0.08 Hz) of fMRI signals can be observed in the resting state [6,7], which may reflect the spontaneous neuronal activity of brain regions [8]. Two methods to measure the fluctuation amplitude from the changes in oxygen levels are used to detect regional spontaneous activity in the resting-state. Biswal et al. [7] reported that the amplitude of LFF (ALFF) might reflect the absolute intensity of spontaneous brain activity by measuring the total power within the low-frequency range from 0.01 to 0.08 Hz [9]. Among patients with depression, previous studies found that some have abnormal ALFF [10–13], but a few of these results have withstood replication. For instance, Guo et al. [10] reported that patients with early onset 0959-4965 © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins
help explain some of the neural processes underlying the clinical symptoms accompanying MDD. NeuroReport 25:1302–1307 © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. NeuroReport 2014, 25:1302–1307 Keywords: depression, fractional amplitude of low-frequency fluctuation, functional MRI, resting state a Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine and bHuashan Hospital, Fudan University, Shanghai, China
Correspondence to Daihui Peng, MD, Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China Tel: + 86 21 64387250 x73529; fax: + 86 2164387986; e-mail: [email protected] *Ting Shen and Meihui Qiu are joint first authors. Received 22 April 2014 accepted 21 August 2014
MDD showed lower ALFF in the left superior/inferior temporal gyrus, right middle occipital gyrus, and left lingual gyrus, as well as higher ALFF in the left medial and bilateral superior frontal gyrus; however, recent studies using a similar depressed sample could not reproduce these findings [13,14], nor could studies using different depressed samples [11,12]. The fractional ALFF (fALFF) approach was further developed by defining the ratio of the power spectrum of the lowfrequency range (0.01–0.08 Hz) to that of the entire detectable frequency range without filtering, which has greater sensitivity and specificity for detecting spontaneous neural activities [8]. Again though, several previous studies on fALFF among depressed patients did not observe the same findings [15,16]. The general disparity between these study findings indicates a lack of consensus on the spontaneous activity of MDD at the brain region level. Abnormal neural activity is likely a pathophysiological aspect of MDD. Whether or not this is an accurate assessment is debatable – the aforementioned studies alone illustrate how conflicting the findings across different studies can be. Further studies using accepted techniques must be conducted to gain a clearer overall picture. In view of fALFF as a novel approach that has had some promising, albeit conflicting, results, we measured spontaneous neural activity and hypothesized that DOI: 10.1097/WNR.0000000000000263
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Altered spontaneous neural activity in MDD Shen et al. 1303
patients with MDD will show abnormal patterns of fALFF within specific brain regions. To test this hypothesis, while avoiding as many confounding factors as possible (e.g. medication effects and illness duration), we carried out fALFF analysis of resting-state fMRI data in unmedicated patients with MDD during the earlier period of the first episode and compared these findings with those from healthy controls.
Methods Participants
Patients with MDD were recruited from outpatient clinics at Shanghai Mental Health Centre and the Huashan Hospital in Shanghai. In total, 16 patients who met the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV) diagnosis criteria for MDD were enrolled, on the basis of the following conditions (inclusion criteria): age 25–50 years, no other diagnosed axis I or II disorder from DSM-IV, a 24-item Hamilton Depression Scale (HAMD) score greater than 20 [17], a 14-item Hamilton anxiety scale (HAMA) score less than 7, no evidence of having received any psychological treatment before or medication over the past 4 weeks, and no observed or diagnosed medical or neurological illness. Exclusion criteria were as follows: evidence of a current suicide attempt, substance dependence (except nicotine) during the past year, alcohol drinking in the prior week, or pregnancy or breastfeeding. Sixteen healthy controls were recruited through advertisement in the two psychiatry services. Inclusion criteria for health controls were as follows: no history of any DSM-IV axis I or II disorder and no first degree relative with a family history of major psychiatric or neurological illness. Exclusion criteria for health controls were as follows: current administration of any prescription medication, consumption of alcohol in the prior week, and pregnancy or breastfeeding. Two health controls were later excluded because of excessive head motion during the fMRI scan (details in the following section). The remaining health controls did not differ significantly from the MDD patients in terms of age and sex distribution (sex: seven male/nine female in the MDD group and six male/eight female in the control group, χ2 = 0.002, P = 0.961; age: 34.44 ± 6.72 years in the MDD group, 32.36 ± 5.30 years in the control group, t = 0.931, P = 0.324). In the MDD group, the mean age of onset was 33.25 ± 6.98 years and the mean duration of illness was 2.63 ± 1.14 months. The MDD group had significantly higher HAMD (30.88 ± 7.69 for the MDD group, 2.63 ± 1.96 for healthy controls) and HAMA scores (5.62 ± 0.72 for the MDD group, 3.31 ± 0.87 for healthy controls) compared with the control group (P < 0.05). All the participants were right-handed, with no metallic implants or any other factors that could affect MRI scanning. All participants provided written informed consent before their enrollment in the study. All
protocols of this study were approved by the Investigational Review Board of Shanghai Mental Health Center, China. MRI acquisition
Image data were acquired using a 3.0 T magnetic resonance scanner (General Electric, Milwaukee, Wisconsin, USA) with a standard whole-head coil. A high-resolution T1-weighted structural image was obtained using the spoiled GRASS gradient sequence with the following parameters: repeat time (TR) = 5.9 ms, echo time (TE) = 1.4 ms, flip angle (FA) = 15°, resolution = 1 × 1 × 1 mm3, without gap. The fMRI images were obtained using an echo planar imaging sequence with the following parameters: TR/TE = 3000 ms/30 ms, flip angle = 90°, resolution = 3.75 × 3.75 × 5.0 mm3, without gap, 22 axial slices. For each participant, the entire scan lasted 300 s and comprised 100 volumes. Imaging data preprocessing
Image data were preprocessed using the Data Processing Assistant for Resting-State fMRI software (DPARSF, http://rfmri.org/DPARSF) [18]. The first 10 volumes were removed to allow for magnetization equilibrium and then the remaining volumes from each participant were sliced and realigned. Examination of the image data revealed that two healthy controls had to be excluded because of excessive head motion (exclusion criteria: movement by more than 2.0 mm or greater than 2.0° head motion). The remaining data were then normalized to the standard Montreal Neurological Institute (MNI) space and resampled with a resolution of 3 × 3 × 3 mm3 using echo planar imaging templates. Next, the images were smoothed to a Gaussian kernel of 4-mm full-width at half-maximum and the linear trend was removed to continue subsequent analysis with band-pass filtering (0.01–0.08 Hz) [6,7]. fALFF calculation
The fALFF analysis was carried out using DPARSF software as follows [15,16]: (i) by acquiring the power spectrum after transforming the time series of each voxel into the frequency domain without band-pass filtering using a Fast Fourier Transform; (ii) obtaining the average square root across 0.01–0.08 Hz at each voxel after it was calculated at each frequency of the power spectrum; (iii) extracting the ratio of the amplitude across 0.01–0.08 Hz to the whole frequency range as the fALFF [8]. For standardization, the fALFF of each voxel was divided by the global mean fALFF value within a whole brain mask [19]. Statistical analyses
All demographic data and clinical variables were analyzed using SPSS 16.0 (SPSS Inc., Chicago, Illinois, USA). Differences in fALFF between the MDD and control groups were evaluated using a two sample t-test with the
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REST software (http://restfmri.net/forum). Corrected threshold values were set at P = 0.01 and cluster size greater than 324 mm3 (12 voxels), as measured by AlphaSim and confined within a whole brain mask; this corresponded to a corrected P-value less than 0.01 for statistical significance. To evaluate the correlations between clinical symptoms and aberrant brain activity, the mean fALFF values of brain regions showing significant differences between the two groups were extracted. Pearson correlation analysis was carried out between the mean fALFF values in MDD patients and the total HAMD score, age of onset, and duration of disease, with P less than 0.05 considered statistically significant.
Results Sixteen patients with MDD and 14 healthy controls completed the analysis of fMRI data. Compared with the healthy controls, patients with MDD showed significantly decreased fALFF in the right angular gyrus, left middle temporal gyrus, left superior temporal gyrus, right putamen, right precuneus, and the right superior temporal gyrus. No significantly increased fALFF was found in the patients group. Details of the group differences are shown in Table 1 and Fig. 1. There was no significant correlation between the mean fALFF values of the different brain regions and clinical characteristics, including total HAMD score, age of onset, and duration of disease (P >0.05).
Discussion This study showed a decreased fALFF in the right angular gyrus, left middle temporal gyrus, bilateral superior temporal gyrus, right putamen, and right precuneus among patients with MDD (Table 1, Fig. 1). These results are partially consistent with those of recent studies reporting a decreased fALFF [15,16] and ALFF among MDD patients [10–13], but with some marked differences. The previous studies reported a significantly Table 1 Regions showing significant differences in fALFF between the patients with MDD and healthy controls MNI coordinate Brain regions NC > MDD Angular gyrus Middle temporal gyrus/ Superior temporal gyrus Putamen Precuneus Superior temporal gyrus
L/R Cluster size BA R L
77 59
L R R R
39 37/
x
y
z
t-value
51 − 48
− 66 − 69
42 12
4.69 5.38
27 3 63
9 − 72 − 54
6 24 15
4.21 3.76 5.17
22 34 24 21
22
BA, Brodmann area; L, left; MDD, major depressive disorder; MNI, Montreal Neurological Institute; NC, healthy control; R, right. Corrected P < 0.01.
increased fALFF in some brain regions of MDD patients (i.e. the right precentral gyrus, right inferior temporal gyrus, and bilateral fusiform gyrus [15], as well as the right putamen and the right ventral median frontal gyrus) [16]. These inconsistencies may be partially explained by differences in the analytical method, sample heterogeneity, and/or sample size between these studies, especially as the clinical participants scanned in this study were unmedicated during the early period of illness. Presuming that fALFF is a potential index of spontaneous neural activity [8], our findings suggest that there may be atypical neural activity distributed in specific brain regions of patients with MDD. To assess the abnormal spontaneous activity in MDD, it is important to note three main findings of the brain regions with significantly different fALFF in MDD patients from that among the healthy controls. First, the putamen showed decreased fALFF among our MDD patients without medication. Generally, the putamen has been confirmed to have reduced volume among patients with depression [20]. During processing of emotional stimuli, the putamen was found to increase the strength of responses to negative information and, conversely, decrease that to positive information [21]. Moreover, the putamen is a core region of the ‘hate neural circuit’ on the basis of the report of Tao et al. [22]. The depressed patients are supposed to have abnormal ‘hate neural circuit’ constructed of some specific brain areas, and accordingly can not reduce their cognition control over negative feelings [22]. Alterations in both structure and function have previously been shown to be associated with the putamen and negative regulation of mood in MDD. Given these factors, the decreased fALFF in the putamen found in this study may provide a foundation for further exploring how negative mood emerges in patients with MDD. Another finding of this study is that patients with MDD exhibited decreased fALFF in the left middle temporal gyrus and bilateral superior temporal gyrus. These findings are consistent with those from previous studies reporting decreased regional homogeneity within the temporal lobe [20,23–25], which is a similar index used to measure spontaneous neural activity. Besides the essential functions of auditory processing and language development, the superior temporal gyrus plays important roles in mood regulation in depressive disorders [26]. Moreover, this gyrus is responsible for the processing of emotions in facial stimuli [27,28]. Because of this specific function, the temporal gyrus should likely be involved in the processing of cognition related to mood [27]. Previous studies seem to concur with this conclusion, as patients with depression tend to have temporal lobes of a smaller volume [29,30]. The decreased regional homogeneity within this region is thought to be related to the altered temporal structure in MDD patients [23]. Likewise, the decrease in fALFF within the temporal gyrus may
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Altered spontaneous neural activity in MDD Shen et al. 1305
Fig. 1
R
L
+4.86 +4.54 +4.18 −6
−2
+2
+6
+3.83 +3.47 +3.12 +2.76 −2.76 −3.20
+10
+14
+18
+22
−3.63 −4.07 −4.51 −4.94 −5.38
+26
+30
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+38
T-statistic maps of fractional amplitude of low-frequency fluctuation (fALFF) between the patients with major depression disorder (MDD) and healthy controls. Color bars refer to the T-value: warm color bars indicate increased fALFF and cold color bars indicate decreased fALFF in the patients with MDD relative to healthy controls. The numbers below the images refer to the z coordinates of the Montreal Neurological Institute (MNI) template. The threshold was set at P < 0.01 and cluster size greater than 12 voxel.
underlie the potential neural activity responsible for the processing of negative mood and cognition in patients with MDD. One further finding that was worth noting is that of decreased fALFF in the right angular gyrus and right precuneus among MDD patients. The roles of the two regions may contribute to the default mode network (DMN) of the brain at resting state [19,31], which is mainly associated with cognition control and strategic/ executive functions [32]. The precuneus is located in the center of the DMN; thus, even if there is lack of consensus with regard to the nature of the DMN in depression, abnormal DMN functions is an established feature of MDD [33–35]. Zhu et al. [36] further demonstrated that decreased functional connectivity in the posterior regions of the DMN, especially in the precuneus and angular gyrus, is associated with deficits in
overgeneral autobiographical memory. Accordingly, patients with MDD tend to exhibit a variety of clinical symptoms related to cognitive deficits [1–3]. If accurate, decreased fALFF in the right angular gyrus and right precuneus found in the current MDD samples may also be one of the underlying neural patterns for these types of clinical symptoms. No significant correlations were found between the mean fALFF values of the different brain regions, and the clinical characteristics might conform to some previous findings [15,37]. However, other previous studies found a positive or negative relationship between the mean fALFF values and clinical indices among patients with MDD [16,38,39]. For example, the right precuneus in currently depressed patients with MDD showed positive correlations with the number of depressive episodes, the duration of disease, and the fALFF values, which further
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supports the fact that increased fALFF in the precuneus may be a state marker of MDD [16]. Compared with those studies that indicated a significant relationship between fALFF and clinical characteristics [16,38,39], the current findings may result from differences in sample characteristics, such as first-episode MDD and early period of the MDD disease course without medication. This might suggest that fALFF in these different brain regions leads to trait alteration in MDD, underlying the pathogenesis of MDD rather than functioning as a specific state marker to assess the symptom severity or other clinical characteristics. We should note two limitations of this study. First, the relatively small sample likely leads to some speculation on the nature of the clinical implications of abnormal fALFF in patients with MDD. Second, although we found abnormal spontaneous neural activity in some patients that could have contributed to the negative mood and cognitive deficits in MDD patients, we did not successfully confirm the relationship between specific brain regions and somatic symptoms using our fALFF approach. As mentioned by Biswal et al. [7], ALFF might reflect the absolute intensity of spontaneous brain activity. The structure or function has been reported to be abnormal in some specific brain regions in patients with MDD [10,13,16,40,41]. For example, ALFF values in the right middle temporal gyrus were reduced in patients with MDD [41], whereas reduced volume was found in the right middle temporal gyrus of patients with MDD [42]. This region, known to be a part of the extended dorsal attention system, is involved in cued attention and working memory [41,42], and decreased ALFF in this region should contribute to the cognitive deficits associated with MDD. Thus, we further speculate that altered fALFF might indicate abnormal function in specific brain regions of patients with MDD. We still need an additional index to examine the underlying neural activity, and we need to further define the physiological mechanism of fALFF in MDD through longitudinal studies with larger sample sizes.
and no. YG2012MS11) and Fund of Science and Technology Commission of Shanghai Municipality (grant no. 134119a6200). Conflicts of interest
There are no conflicts of interest.
References 1
2
3
4
5
6
7
8
9
10
11
12
13
14
Conclusion The present study describes the atypical patterns in unmedicated patients with MDD during their first episode, defined by decreased fALFF in the right angular gyrus, left middle temporal gyrus, bilateral superior temporal gyrus, right putamen, and right precuneus. All the regions may potentially be confirmed to have abnormal spontaneous activity on the basis of fALFF, which subsequently highlights the underlying neural mechanism behind the clinical symptoms that accompany MDD, such as negative mood and cognition deficits.
Acknowledgements This work was supported by the Science Fund of Shanghai Jiao Tong University (grant no. 11XJ21006
15
16
17 18 19
20
Li CT, Lin CP, Chou KH, Chen IY, Hsieh JC, Wu CL, et al. Structural and cognitive deficits in remitting and non-remitting recurrent depression: a voxelbased morphometric study. NeuroImage 2010; 50:347–356. Turner AD, Furey ML, Drevets WC, Zarate C Jr, Nugent AC. Association between subcortical volumes and verbal memory in unmedicated depressed patients and healthy controls. Neuropsychologia 2012; 50:2348–2355. Greer TL, Sunderajan P, Grannemann BD, Kurian BT, Trivedi MH. Does duloxetine improve cognitive function independently of its antidepressant effect in patients with major depressive disorder and subjective reports of cognitive dysfunction? Depress Res Treat 2014; 2014:627863. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. Washington, DC: American Psychiatric Association; 2013. Bagby RM, Ryder AG, Schuller DR, Marshall MB. The Hamilton Depression Rating Scale: Has the gold standard become a lead weight? Am J Psychiatry 2004; 161:2163–2177. Lowe MJ, Mock BJ, Sorenson JA. Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage 1998; 7:119–132. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995; 34:537–541. Zou QH, Zhu CZ, Yang Y, Zuo XN, Long XY, Cao QJ, et al. An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF. J Neurosci Methods 2008; 172:137–141. Zang YF, He Y, Zhu CZ, Cao QJ, Sui MQ, Liang M, et al. Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev 2007; 29:83–91. Guo WB, Liu F, Xun GL, Hu MR, Guo XF, Xiao CQ, et al. Reversal alterations of amplitude of low-frequency fluctuations in early and late onset, first-episode, drug-naive depression. Prog Neuropsychopharmacol Biol Psychiatry 2013; 40:153–159. Jiao Q, Ding J, Lu G, Su L, Zhang Z, Wang Z, et al. Increased activity imbalance in fronto-subcortical circuits in adolescents with major depression. PLoS One 2011; 6:e25159. Fan T, Wu X, Yao L, Dong J. Abnormal baseline brain activity in suicidal and non-suicidal patients with major depressive disorder. Neurosci Lett 2013; 534:35–40. Zhang X, Zhu X, Wang X, Zhu X, Zhong M, Yi J, et al. First-episode medication-naive major depressive disorder is associated with altered resting brain function in the affective network. PLoS One 2014; 9:e85241. Lord A, Horn D, Breakspear M, Walter M. Changes in community structure of resting state functional connectivity in unipolar depression. PLoS One 2012; 7:e41282. Wang L, Dai W, Su Y, Wang G, Tan Y, Jin Z, et al. Amplitude of lowfrequency oscillations in first-episode, treatment-naive patients with major depressive disorder: a resting-state functional MRI study. PLoS One 2012; 7:e48658. Jing B, Liu CH, Ma X, Yan HG, Zuo ZZ, Zhang Y, et al. Difference in amplitude of low-frequency fluctuation between currently depressed and remitted females with major depressive disorder. Brain Res 2013; 1540:74–83. Hamilton M. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol 1967; 6:278–296. Chao-Gan Y, Yu-Feng Z. DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI. Front Syst Neurosci 2010; 4:13. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc Natl Acad Sci USA 2001; 98:676–682. Yuan Y, Zhang Z, Bai F, Yu H, Shi Y, Qian Y, et al. Abnormal neural activity in the patients with remitted geriatric depression: a resting-state functional magnetic resonance imaging study. J Affect Disord 2008; 111:145–152.
Copyright © Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Altered spontaneous neural activity in MDD Shen et al. 1307
21
22 23
24
25
26
27
28
29
30
31
32
Fitzgerald PB, Laird AR, Maller J, Daskalakis ZJ. A meta-analytic study of changes in brain activation in depression. Hum Brain Mapp 2008; 29:683–695. Tao H, Guo S, Ge T, Kendrick KM, Xue Z, Liu Z, Feng J. Depression uncouples brain hate circuit. Mol Psychiatry 2013; 18:101–111. Peng DH, Jiang KD, Fang YR, Xu YF, Shen T, Long XY, et al. Decreased regional homogeneity in major depression as revealed by resting-state functional magnetic resonance imaging. Chin Med J (Engl) 2011; 124:369–373. Chen JD, Liu F, Xun GL, Chen HF, Hu MR, Guo XF, et al. Early and late onset, first-episode, treatment-naive depression: same clinical symptoms, different regional neural activities. J Affect Disord 2012; 143:56–63. Lai CH, Wu YT. Frontal regional homogeneity increased and temporal regional homogeneity decreased after remission of first-episode drug-naïve major depressive disorder with panic disorder patients under duloxetine therapy for 6 weeks. J Affect Disord 2012; 136:453–458. Anand A, Li Y, Wang Y, Wu J, Gao S, Bukhari L, et al. Activity and connectivity of brain mood regulating circuit in depression: a functional magnetic resonance study. Biol Psychiatry 2005; 57:1079–1088. Bigler ED, Mortensen S, Neeley ES, Ozonoff S, Krasny L, Johnson M, et al. Superior temporal gyrus, language function, and autism. Dev Neuropsychol 2007; 31:217–238. Radua J, Phillips ML, Russell T, Lawrence N, Marshall N, Kalidindi S, et al. Neural response to specific components of fearful faces in healthy and schizophrenic adults. Neuroimage 2010; 49:939–946. Caetano SC, Fonseca M, Hatch JP, Olvera RL, Nicoletti M, Hunter K, et al. Medial temporal lobe abnormalities in pediatric unipolar depression. Neurosci Lett 2007; 427:142–147. Williams M, Perera S, Pearce RKB, Hirsch SR, Maier M. Changes in grey matter thickness in the frontal, temporal and occipital lobes in schizophrenia and depression. Schizophr Res 2008; 98:151. Greicius MD, Krasnow B, Reiss AL, Menon V. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci USA 2003; 100:253–258. Buckner RL, Andrews-Hanna JR, Schacter DL. The brain’s default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci 2008; 1124:1–38.
33
34
35
36
37
38
39
40
41
42
Sheline YI, Price JL, Yan Z, Mintun MA. Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proc Natl Acad Sci USA 2010; 107:11020–11025. Greicius MD, Flores BH, Menon V, Glover GH, Solvason HB, Kenna H, et al. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry 2007; 62:429–437. Bluhm R, Williamson P, Lanius R, Théberge J, Densmore M, Bartha R, et al. Resting state default-mode network connectivity in early depression using a seed region-of-interest analysis: decreased connectivity with caudate nucleus. Psychiatry Clin Neurosci 2009; 63:754–761. Zhu X, Wang X, Xiao J, Liao J, Zhong M, Wang W, Yao S. Evidence of a dissociation pattern in resting-state default mode network connectivity in first-episode, treatment-naive major depression patients. Biol Psychiatry 2012; 71:611–617. Liu F, Guo W, Liu L, Long Z, Ma C, Xue Z, et al. Abnormal amplitude lowfrequency oscillations in medication-naive, first-episode patients with major depressive disorder: a resting-state fMRI study. J Affect Disord 2013; 146:401–406. Guo W, Liu F, Zhang J, Zhang Z, Yu L, Liu J, et al. Dissociation of regional activity in the default mode network in first-episode, drug-naive major depressive disorder at rest. J Affect Disord 2013; 151:1097–1101. Liu CH, Ma X, Wu X, Fan TT, Zhang Y, Zhou FC, et al. Resting-state brain activity in major depressive disorder patients and their siblings. J Affect Disord 2013; 149:299–306. Grieve SM, Korgaonkar MS, Koslow SH, Gordon E, Williams LM. Widespread reductions in gray matter volume in depression. Neuroimage Clin 2013; 3:332–339. Guo WB, Liu F, Xue ZM, Xu XJ, Wu RR, Ma CQ, et al. Alterations of the amplitude of low-frequency fluctuations in treatment-resistant and treatmentresponse depression: a resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry 2012; 37:153–160. Ma C, Ding J, Li J, Guo W, Long Z, Liu F, et al. Resting-state functional connectivity bias of middle temporal gyrus and caudate with altered gray matter volume in major depression. PloS One 2012; 7:e45263.
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