Schizophrenia Research 160 (2014) 67–72
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Disruptive changes of cerebellar functional connectivity with the default mode network in schizophrenia Lubin Wang a,b,1, Feng Zou a,b,1, Yongcong Shao a,b, Enmao Ye a,b, Xiao Jin a,b, Shuwen Tan a,b, Dewen Hu c,⁎, Zheng Yang a,b,⁎⁎ a b c
Beijing Institute of Basic Medical Sciences, Beijing, PR China Cognitive and Mental Health Research Center, Beijing, PR China College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan, PR China
a r t i c l e
i n f o
Article history: Received 1 January 2014 Received in revised form 31 August 2014 Accepted 16 September 2014 Available online 30 October 2014 Keywords: Schizophrenia Cerebellum Default mode network Functional connectivity
a b s t r a c t The default mode network (DMN) plays an important role in the physiopathology of schizophrenia. Previous studies have suggested that the cerebellum participates in higher-order cognitive networks such as the DMN. However, the specific contribution of the cerebellum to the DMN abnormalities in schizophrenia has yet to be established. In this study, we investigated cerebellar functional connectivity differences between 60 patients with schizophrenia and 60 healthy controls from a public resting-state fMRI database. Seed-based correlation analysis was performed by using seeds from the left Crus I, right Crus I and Lobule IX, which have previously been identified as being involved in the DMN. Our results revealed that, compared with the healthy controls, the patients showed significantly reduced cerebellar functional connectivity with the thalamus and several frontal regions including the middle frontal gyrus, anterior cingulate cortex, and supplementary motor area. Moreover, the positive correlations between the strength of frontocerebellar and thalamocerebellar functional connectivity observed in the healthy subjects were diminished in the patients. Our findings implicate disruptive changes of the fronto-thalamo-cerebellar circuit in schizophrenia, which may provide further evidence for the “cognitive dysmetria” concept of schizophrenia. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Schizophrenia is a complex mental disorder characterized by a diverse range of symptoms, including hallucination, delusions, reduction in affect and behavior, and disorganization of thought and language (Liddle, 1987). Although the causes and neural mechanisms underlying schizophrenia are far from clear, a “disconnection” hypothesis has been proposed for the physiological explanation of the behavioral syndromes of this mental disorder (Friston and Frith, 1995). This hypothesis proposes that schizophrenia arises from dysfunctional integration of distributed brain regions or disruptive changes of neural circuitry, which may lead to an impairment in the fluid coordination of mental processes, sometimes referred to as “cognitive dysmetria” (Andreasen et al., 1998, 1999).
⁎ Correspondence to: D. Hu, College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan 410073, PR China. Tel./fax: + 86 731 8457 4992. ⁎⁎ Correspondence to: Z. Yang, Beijing Institute of Basic Medical Sciences, Cognitive and Mental Health Research Center, 27 Taiping Road, Beijing 100850, PR China. Tel./fax: +86 10 68213284. E-mail addresses: [email protected] (D. Hu), [email protected] (Z. Yang). 1 These authors contributed equally to this work.
http://dx.doi.org/10.1016/j.schres.2014.09.034 0920-9964/© 2014 Elsevier B.V. All rights reserved.
Previous neuroimaging studies have consistently found dysfunctions of the default mode network (DMN) in schizophrenia. The DMN is a distributed network of brain regions more active during rest than during performance of attention-demanding tasks, which subserves cognitive operations involving episodic memory retrieval, selfreferential thought, and stream-of-consciousness processing (Gusnard and Raichle, 2001; Raichle et al., 2001; Buckner and Carroll, 2007). Task-related fMRI studies have revealed atypical patterns of brain activity in the DMN in patients with schizophrenia during a broad range of cognitive tasks (Garrity et al., 2007; Pomarol-Clotet et al., 2008; Whitfield-Gabrieli et al., 2009; Schneider et al., 2011). Recent restingstate fMRI and diffusion tensor imaging studies have also shown aberrant DMN connectivity in schizophrenia, further supporting the “disconnection” hypothesis of the disease (Bluhm et al., 2007; Skudlarski et al., 2010; Camchong et al., 2011; Mingoia et al., 2012). Additionally, the DMN abnormalities were found to be associated with clinical symptoms as well as cognitive ability deficits in patients with schizophrenia (Park et al., 2009; Skudlarski et al., 2010; Camchong et al., 2011). These findings suggest that the DMN plays an important role in the physiopathology of schizophrenia. Recently, there is an increased recognition of the higher-order functions of the cerebellum. A meta-analysis of task-related neuroimaging studies of the cerebellum has documented its role in various cognitive
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and emotional processing (Stoodley and Schmahmann, 2009). A number of resting-state functional connectivity studies have also demonstrated that the cerebellum participates in higher-order networks such as the DMN (Habas et al., 2009; Krienen and Buckner, 2009; O'Reilly et al., 2010; Buckner et al., 2011; Bernard et al., 2012). The role of the cerebellum in schizophrenia has been highlighted by Andreasen's hypothesis of “cognitive dysmetria”, which suggests that dysfunctions in the cortico-cerebellar-thalamo-cortical circuit (CCTCC) could explain a variety of behavioral symptoms of this disease (Andreasen et al., 1998, 1999). Up to now, cerebellar abnormalities in schizophrenia have been supported by many clinical, cognitive, behavioral, and neuroimaging studies (Picard et al., 2008; Lungu et al., 2013). Notably, some researchers have begun to pay attention to abnormal functional connectivity associated with the cerebellum in schizophrenia (Shen et al., 2010; Collin et al., 2011). However, the potential contribution of the cerebellum to the DMN abnormalities in schizophrenia has yet to be established. Taking advantage of a large public resting-state fMRI dataset, this study investigated the potential contribution of the cerebellum to the abnormal functional connectivity of the DMN in schizophrenia. Using a seed-based correlation method, we first reconstructed the intrinsic connectivity of the left Crus I, right Crus I and Louble IX in the control group and patient group, respectively. These cerebellar regions have been found to be involved in the DMN by previous studies (Habas et al., 2009; Krienen and Buckner, 2009; Bernard et al., 2012). Then, we examined the differences in the cerebellar functional connectivity between the two groups. Based on previous studies, we hypothesized that patients with schizophrenia would have decreased cerebellar functional connectivity with brain regions in the CCTCC circuit compared with healthy individuals.
London, UK; http://www.fil.ion.ucl.ac.uk/spm). Prior to preprocessing, the first 5 volumes of each scan were discarded for magnetic saturation. The remaining 145 volumes were corrected by registering to the first volume to account for head motion. All subjects in this study had less than 2 mm translation and 2° of rotation in any of the x, y, and z axes. Then, the volumes were normalized to the standard EPI template in the Montreal Neurological Institute (MNI) space and resliced to 3 × 3 × 3 mm3. The resulting images were spatially smoothed with a Gaussian filter of 8 mm full-width half-maximum kernel. To avoid the blurring of fMRI signal across the cerebellar–cerebral boundary during spatial smoothing, the functional data in the cerebellum and cerebrum were extracted from the whole brain and smoothed separately. Subsequently, the data were temporally filtered with a band-pass filter (0.01–0.1 Hz), followed by linear detrending to remove any residual drift. Nine nuisance signals were further removed from the data via multiple regression, including the signals averaged from the white matter, the cerebrospinal fluid and the whole brain, and six parameters obtained by head motion correction. This regression procedure was utilized to reduce spurious variance unlikely to reflect neuronal activity.
2. Materials and methods
2.3. Functional connectivity analysis
2.1. Subjects and imaging protocols
A seed-based correlation method was used to identify the resting cerebellar functional connectivity patterns in the patients with schizophrenia and in the healthy controls. Seed regions were defined as 6mm-radius spheres centered on previously published foci. In this study, we selected 3 seed regions centered in the left Crus I (MNI: − 33, − 76, − 34), right Crus I (MNI: 33, − 76, − 34), and Lobule IX (MNI: 0, −55, −49), which have been found to contribute to the intrinsic connectivity of the DMN in healthy individuals (Habas et al., 2009; Krienen and Buckner, 2009; Bernard et al., 2012). The time series of each seed region were calculated by averaging the fMRI time series over all voxels within the sphere. For each subject, correlation maps were created by calculating the Pearson's correlation coefficients between the time series of the seed regions and that of each voxel in the brain. These correlation maps were converted to z-value maps using Fisher's r-to-z transformation, to improve the normality of the correlation coefficients. Group analyses were performed for the correlation maps of each seed region. First, correlation maps of the patients with schizophrenia and healthy controls were separately underwent a voxel-wise onesample t-test, to determine the brain regions with significant correlations to the cerebellar seed regions. Then, a voxel-wise two-sample ttest was conducted between the correlation maps of the patients and healthy subjects, to identify significant cerebellar functional connectivity changes in schizophrenia. The significance level was set at p b 0.001, uncorrected. Multiple comparisons were corrected at the cluster level (p b 0.05, false discovery rate).
Data analyzed in this study came from an open access resting-state fMRI dataset comprising 72 patients with schizophrenia and 74 healthy controls. This publicly available dataset is contributed by the Center for Biomedical Research Excellence (COBRE, http://fcon_1000.projects. nitrc.org/indi/retro/cobre.html), and has been previously studied by Anderson and Cohen (2013), Sui et al. (2013). All the subjects in the COBRE were screened and excluded if they had history of neurological disorder, history of mental retardation, history of severe head trauma with more than 5 minute loss of consciousness, history of substance abuse or dependence within the last 12 months. The patients were treated with atypical antipsychotic medications and were retrospective and prospective clinical stability. Diagnostic information was collected using the Structured Clinical Interview used for DSM Disorders. The subjects underwent resting-state scans on a 3-T SIEMENS MRI scanner with the following parameters: 33 axial slices, repetition time = 2000 ms, echo time = 29 ms, flip angle = 75°, slice thickness = 3.5 mm, slice gap = 1.05 mm, acquisition matrix = 64 × 64, field of view = 240 mm. A total of 150 volumes of functional images were obtained for all the subjects except one (this subject was excluded from the present study). Another 15 subjects were excluded because of serious head motion (more than 2 mm translation or 2° of rotation) or partial cerebellum coverage of their fMRI scans. To match subjects across the two groups for age and sex, 10 healthy controls were further excluded from this study. Finally, 60 patients with schizophrenia and 60 healthy controls were included in the present analyses. Characteristics of the patient group and control group are shown in Table 1.
Table 1 Characteristics of the patient and control groups in this study. Variable
Patient
Control
p-Value
Sample size Age (years) Gender (M/F) Handedness (L/R)b Diagnosis score
60 38.0 ± 13.9 48/12 9/49 295.4 ± 0.7
60 37.6 ± 11.6 47/13 1/57
0.86 0.82a 0.008a
a b
Pearson Chi-square test. Two subjects are ambidextrous in both the patient and control groups.
3. Results
2.2. Data preprocessing
3.1. Functional connectivity of the cerebellar seed regions
Functional scans were preprocessed using the SPM8 software (Wellcome Department of Imaging Neuroscience, University College
Resting-state functional connectivity patterns of the left Crus I, right Crus I and Lobule IX are shown in Fig. 1. For the control group, the
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Fig. 1. Resting-state functional connectivity of the cerebellar default-mode seed regions. Correlation maps for healthy controls and patients with schizophrenia are displayed in the top row and bottom row, separately. The left side of the images represents the left hemisphere of the brain.
cerebellar seed regions were highly correlated with the major regions of the DMN, including the posterior cingulate cortex (PCC), precuneus, anterior cingulate cortex (ACC), lateral parietal cortex, medial prefrontal cortex (mPFC), and thalamus (top row of Fig. 1). Moreover, we observed that the left Crus I showed stronger functional connectivity with the right-hemisphere cerebral regions and vice versa, suggesting the contralateral lateralization of cerebellar connectivity in relation to cortex (Krienen and Buckner, 2009; O'Reilly et al., 2010). For the patient group, the cerebellar seed regions also showed high correlations with the posterior part of the DMN, such as the PCC, precuneus and lateral parietal cortex (bottom row of Fig. 1). However, it can be seen that the frontocerebellar and thalamocerebellar connectivity were reduced or disrupted in the patients.
3.2. Decreased cerebellar functional connectivity in schizophrenia Using two-sample t-test, we found that the patients with schizophrenia exhibited significantly reduced cerebellar functional connectivity with the thalamus and several frontal regions relative to the healthy controls (see Fig. 2 and Table 2). Specifically, the patients exhibited reduced functional connectivity between the left Crus I and areas of the bilateral thalamus, bilateral middle frontal gyri (MFG), and bilateral ACC; between the right Crus I and bilateral thalamus; between the Lobule IX and areas of the bilateral thalamus, bilateral MFG, and bilateral supplementary motor area (SMA). There was no brain area that exhibited significantly increased cerebellar functional connectivity in the patients compared with the healthy controls.
Fig. 2. Significantly reduced functional connectivity maps of the cerebellar seed regions in schizophrenia. Seed regions: left Crus I (A), right Crus I (B), and Lobule IX (C).
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Table 2 Brain areas exhibiting significantly decreased functional connectivity with the cerebellar seed regions in schizophrenia. Seed regions
Target region
BA
Side
Size
MNI (x, y, z)
T-value
L Crus I
Thalamus Middle frontal gyrus Middle frontal gyrus Anterior cingulate cortex Thalamus Thalamus Thalamus Middle frontal gyrus Supplementary motor area Middle frontal gyrus
N/A 10/46 10/46 24/32 N/A N/A N/A 9/46 6/8 46
L/R L R L/R L R L/R R L/R L
425 158 283 375 103 64 404 130 118 91
−9, −22, 2 −27, 32 23 27, 38, 20 6, 32, 20 −9, −22, 2 9, −19, 2 −9, −22, 5 24, 44, 17 0, 17, 59 −27, 35, 20
−6.2 −5.8 −5.1 −4.9 −5.4 −4.0 −5.5 −5.0 −4.2 −4.1
R Crus I Lobule IX
In this study, there were more left-handed subjects in the patient group than in the control group (p = 0.008). To test the potential effect of this confounding factor on our results, we calculated the average functional connectivity strength of the brain areas in Table 2. Comparison of the functional connectivity of these areas for the right-handed subjects also revealed significant group differences (p b 0.001, Fig. S1). Thus, the schizophrenia-related functional connectivity differences observed in this study did not stem from the larger number of lefthanded subjects in the patient group. 3.3. Correlation between frontal and thalamic connectivity In this study, the pattern of cerebellar functional connectivity abnormality in schizophrenia implicates a fronto-thalamo-cerebellar circuit.
To further quantify the regulating effect of the thalamus on the synchronized activity between the cerebellum and frontal regions in schizophrenia, we performed the Pearson's correlation analysis between the strength of the frontocerebellar and thalamocerebellar functional connectivity that exhibited significant schizophrenia-related alterations. A list of the correlation coefficients and their statistical significance are presented in Fig. 3. We found that the strength of functional connectivity in several frontal regions was positively associated with that in the thalamus only in the healthy subjects but not in the patients. For the left Crus I, the healthy controls showed significant positive correlations between the strength of connectivity in the thalamus and that in the left MFG (p b 0.022), right MFG (p b 1.4e− 3), and ACC (p b 2.3e − 7), whereas the patients only showed a significant positive correlation between the connectivity in the thalamus and that in the ACC (p b 0.013)
Fig. 3. Correlations between the strength of frontocerebellar and thalamocerebellar functional connectivity in healthy controls (red) and patients with schizophrenia (blue). MFG, middle frontal gyrus; ACC, anterior cingulate cortex; SMA, supplementary motor cortex.
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(Fig. 3, top row). For the Louble IX, there was only a significant positive correlation between the connectivity in the thalamus and that in the right MFG in the healthy controls (p b 7.7e−3) (Fig. 3, bottom row). Discussion Using seeds from cerebellar regions previously identified as being involved in the DMN, we found that patients with schizophrenia showed significantly reduced cerebellar functional connectivity with the thalamus and several frontal regions during the resting state. Furthermore, the positive correlations between the strength of frontocerebellar and thalamocerebellar connectivity observed in the healthy subjects were diminished in the patients. Therefore, this study suggests disruptive changes of the fronto-thalamo-cerebellar circuit in schizophrenia, and may provide further evidence for the “cognitive dysmetria” concept of schizophrenia (Andreasen et al., 1998, 1999). In this study, we found overlapping and distinct functional connectivity patterns of the cerebellum with the DMN in healthy individuals and patients with schizophrenia. Recently, increased attention has been placed on the higher-order functions of the cerebellum and its abnormalities in psychiatric disorders. Our results are consistent with previous studies that demonstrated the involvement of the Crus I and Lobule IX in the spontaneous brain activity of the DMN (Habas et al., 2009; Krienen and Buckner, 2009; Bernard et al., 2012). Previous neuroimaging studies, such as morphometry (Loeber et al., 2001), taskrelated brain activity (Honey et al., 2005), and resting-state functional connectivity (Shen et al., 2010; Collin et al., 2011), have found that cerebellar abnormalities occur in schizophrenia. It is also suggested that a cerebellar dysfunction could account for some of the psychiatric, neurological, or cognitive symptoms present in this disease (Picard et al., 2008). Based on previous studies, disruptive changes of the cerebellar functional connectivity with the DMN may underlie the symptoms and deficits associated with schizophrenia. More specifically, we found that the cerebellar functional connectivity was disrupted with several frontal regions (the MFG, ACC and SMA) in schizophrenia. Previous neuroimaging studies have consistently found that the MFG and ACC show abnormal activation and disrupted integration with other brain regions in patients with schizophrenia across a range of cognitive paradigms, including working memory (Pomarol-Clotet et al., 2008; Whitfield-Gabrieli et al., 2009), cognitive interference (Heckers et al., 2004), stroop (Weiss et al., 2007), verbal encoding/retrieval (Wolf et al., 2007), response inhibition (Laurens et al., 2003), and auditory oddball task (Garrity et al., 2007). Therefore, disruptive changes of the resting cerebellar connectivity with the MFG and ACC may be associated with difficulty in coordinating the processing, prioritization, retrieval, and expression of information in schizophrenia. In addition, we found that patients with schizophrenia showed reduced connectivity between the Lobule IX and SMA. This finding is not surprising, given that the Lobule IX is considered essential for the visual guidance of movement (Glickstein et al., 1994), and lesion of the Louble IX could result in balance and gait impairments (Ilg et al., 2008). The observation of impaired connectivity of the Louble IX with the SMA may result in deficits of motor function in schizophrenia (Honey et al., 2005; Exner et al., 2006), suggesting that the functional deficit in schizophrenia is not confined to the DMN, but also affects integration in other regions. We also found that the functional connectivity between the cerebellum and thalamus was reduced in schizophrenia. The thalamus is believed to play a key role in the establishment of oscillatory dynamics that integrate brain functions (Jones, 2009). Previous studies have demonstrated that patients with schizophrenia exhibit decreased task-related thalamic activation (Andrews et al., 2006; Bor et al., 2011) and reduced thalamocortical connectivity (Welsh et al., 2010; Marenco et al., 2012). In this study, we further provide evidence of functional thalamocerebellar disconnection in schizophrenia. Moreover, we
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found positive correlations between the strength of frontocerebellar and thalamocerebellar functional connectivity only in healthy individuals but not in patients with schizophrenia. The correlations observed in healthy individuals are supported by previously findings that the cerebellum is anatomically connected to the prefrontal cortex through polysynaptic projections via the thalamus (Schmahmann, 1996; Middleton and Strick, 2001; Kelly and Strick, 2003). This relationship is diminished in patients with schizophrenia, suggesting the dysfunction of the thalamus in mediating the synchronized activity between the cerebellum and prefrontal cortex in schizophrenia. Therefore, our findings may help to shed light on the neural basis underlying the widespread disturbances in information transmission and processing in schizophrenia. It should be noted that all the patients in this study were treated with atypical antipsychotic medications. Evidence has indicated that antipsychotic treatment in schizophrenia can affect both the structure (Smieskova et al., 2009) and function (Abbott et al., 2013) of the brain. Recently, a few studies have also attempted to probe functional connectivity changes with antipsychotic treatment, which produced inconsistent results. Sambataro et al. (2010) showed that treatment with olanzapine was associated with increases in DMN connectivity with the medial prefrontal cortex. Hadley et al. (2014) found that functional connectivity deficits between the midbrain and thalamus in schizophrenia were restored after one week of risperidone treatment. However, another resting-state fMRI study showed that antipsychotic treatment in schizophrenia could lead to a widespread attenuation in functional connectivity (Lui et al., 2010). The effects of antipsychotic medications on functional brain systems are complex, and we ca nnot exclude the possibility that antipsychotic treatment contributed to our findings. Several other potential limitations of this study should also be noted. The phenotypic characterization of subjects in the COBRE database did not provide information regarding cognitive and behavioral variables, and the diagnosis scores were in a narrow range across the patients (290.3–296.4). Thus, we were unable to assess the associations between cerebellar functional connectivity changes and schizophrenia symptoms and severity. Moreover, we only examined the specific contribution of the cerebellum to the DMN abnormalities in schizophrenia. Previous studies have suggested that functional resting-state networks are differentially affected in schizophrenia (Woodward et al., 2011). In further study, we intend to perform comparisons of schizophreniarelated functional connectivity changes at different cerebellar regions to complement our results. In conclusion, this study found reduced cerebellar-DMN couplings in schizophrenia. Moreover, the associations between the strength of frontocerebellar and thalamocerebellar connectivity observed in healthy individuals were diminished in patients with schizophrenia. Our results provide further evidence for demonstrating the disruptive changes of the fronto-thalamo-cerebellar circuit in schizophrenia, which is believed to be of critical importance for schizophrenic pathophysiology. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.schres.2014.09.034.
Role of funding source This work was supported by the National Science Foundation of China (81271470, 31300840), the Beijing Natural Science Foundation (4144092), and the National Key Project of China (AWS12J003). The funding sources 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.
Contributors Zheng Yang and Dewen Hu designed the study. Xiao Jin managed the literature searches and analyses. Lubin Wang, Yongcong Shao, and Enmao Ye undertook the statistical analysis. Lubin Wang wrote the first draft of the manuscript, and Feng Zou and Shuwen Tan revised the manuscript. All authors contributed to and have approved the final manuscript.
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Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgment We thank the COBRE for publicly sharing the data, and Xueyan Zhang for proofreading the manuscript.
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Disruptive changes of cerebellar functional connectivity with the default mode network in schizophrenia Lubin Wang a,b,1, Feng Zou a,b,1, Yongcong Shao a,b, Enmao Ye a,b, Xiao Jin a,b, Shuwen Tan a,b, Dewen Hu c,⁎, Zheng Yang a,b,⁎⁎ a b c
Beijing Institute of Basic Medical Sciences, Beijing, PR China Cognitive and Mental Health Research Center, Beijing, PR China College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan, PR China
a r t i c l e
i n f o
Article history: Received 1 January 2014 Received in revised form 31 August 2014 Accepted 16 September 2014 Available online 30 October 2014 Keywords: Schizophrenia Cerebellum Default mode network Functional connectivity
a b s t r a c t The default mode network (DMN) plays an important role in the physiopathology of schizophrenia. Previous studies have suggested that the cerebellum participates in higher-order cognitive networks such as the DMN. However, the specific contribution of the cerebellum to the DMN abnormalities in schizophrenia has yet to be established. In this study, we investigated cerebellar functional connectivity differences between 60 patients with schizophrenia and 60 healthy controls from a public resting-state fMRI database. Seed-based correlation analysis was performed by using seeds from the left Crus I, right Crus I and Lobule IX, which have previously been identified as being involved in the DMN. Our results revealed that, compared with the healthy controls, the patients showed significantly reduced cerebellar functional connectivity with the thalamus and several frontal regions including the middle frontal gyrus, anterior cingulate cortex, and supplementary motor area. Moreover, the positive correlations between the strength of frontocerebellar and thalamocerebellar functional connectivity observed in the healthy subjects were diminished in the patients. Our findings implicate disruptive changes of the fronto-thalamo-cerebellar circuit in schizophrenia, which may provide further evidence for the “cognitive dysmetria” concept of schizophrenia. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Schizophrenia is a complex mental disorder characterized by a diverse range of symptoms, including hallucination, delusions, reduction in affect and behavior, and disorganization of thought and language (Liddle, 1987). Although the causes and neural mechanisms underlying schizophrenia are far from clear, a “disconnection” hypothesis has been proposed for the physiological explanation of the behavioral syndromes of this mental disorder (Friston and Frith, 1995). This hypothesis proposes that schizophrenia arises from dysfunctional integration of distributed brain regions or disruptive changes of neural circuitry, which may lead to an impairment in the fluid coordination of mental processes, sometimes referred to as “cognitive dysmetria” (Andreasen et al., 1998, 1999).
⁎ Correspondence to: D. Hu, College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan 410073, PR China. Tel./fax: + 86 731 8457 4992. ⁎⁎ Correspondence to: Z. Yang, Beijing Institute of Basic Medical Sciences, Cognitive and Mental Health Research Center, 27 Taiping Road, Beijing 100850, PR China. Tel./fax: +86 10 68213284. E-mail addresses: [email protected] (D. Hu), [email protected] (Z. Yang). 1 These authors contributed equally to this work.
http://dx.doi.org/10.1016/j.schres.2014.09.034 0920-9964/© 2014 Elsevier B.V. All rights reserved.
Previous neuroimaging studies have consistently found dysfunctions of the default mode network (DMN) in schizophrenia. The DMN is a distributed network of brain regions more active during rest than during performance of attention-demanding tasks, which subserves cognitive operations involving episodic memory retrieval, selfreferential thought, and stream-of-consciousness processing (Gusnard and Raichle, 2001; Raichle et al., 2001; Buckner and Carroll, 2007). Task-related fMRI studies have revealed atypical patterns of brain activity in the DMN in patients with schizophrenia during a broad range of cognitive tasks (Garrity et al., 2007; Pomarol-Clotet et al., 2008; Whitfield-Gabrieli et al., 2009; Schneider et al., 2011). Recent restingstate fMRI and diffusion tensor imaging studies have also shown aberrant DMN connectivity in schizophrenia, further supporting the “disconnection” hypothesis of the disease (Bluhm et al., 2007; Skudlarski et al., 2010; Camchong et al., 2011; Mingoia et al., 2012). Additionally, the DMN abnormalities were found to be associated with clinical symptoms as well as cognitive ability deficits in patients with schizophrenia (Park et al., 2009; Skudlarski et al., 2010; Camchong et al., 2011). These findings suggest that the DMN plays an important role in the physiopathology of schizophrenia. Recently, there is an increased recognition of the higher-order functions of the cerebellum. A meta-analysis of task-related neuroimaging studies of the cerebellum has documented its role in various cognitive
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and emotional processing (Stoodley and Schmahmann, 2009). A number of resting-state functional connectivity studies have also demonstrated that the cerebellum participates in higher-order networks such as the DMN (Habas et al., 2009; Krienen and Buckner, 2009; O'Reilly et al., 2010; Buckner et al., 2011; Bernard et al., 2012). The role of the cerebellum in schizophrenia has been highlighted by Andreasen's hypothesis of “cognitive dysmetria”, which suggests that dysfunctions in the cortico-cerebellar-thalamo-cortical circuit (CCTCC) could explain a variety of behavioral symptoms of this disease (Andreasen et al., 1998, 1999). Up to now, cerebellar abnormalities in schizophrenia have been supported by many clinical, cognitive, behavioral, and neuroimaging studies (Picard et al., 2008; Lungu et al., 2013). Notably, some researchers have begun to pay attention to abnormal functional connectivity associated with the cerebellum in schizophrenia (Shen et al., 2010; Collin et al., 2011). However, the potential contribution of the cerebellum to the DMN abnormalities in schizophrenia has yet to be established. Taking advantage of a large public resting-state fMRI dataset, this study investigated the potential contribution of the cerebellum to the abnormal functional connectivity of the DMN in schizophrenia. Using a seed-based correlation method, we first reconstructed the intrinsic connectivity of the left Crus I, right Crus I and Louble IX in the control group and patient group, respectively. These cerebellar regions have been found to be involved in the DMN by previous studies (Habas et al., 2009; Krienen and Buckner, 2009; Bernard et al., 2012). Then, we examined the differences in the cerebellar functional connectivity between the two groups. Based on previous studies, we hypothesized that patients with schizophrenia would have decreased cerebellar functional connectivity with brain regions in the CCTCC circuit compared with healthy individuals.
London, UK; http://www.fil.ion.ucl.ac.uk/spm). Prior to preprocessing, the first 5 volumes of each scan were discarded for magnetic saturation. The remaining 145 volumes were corrected by registering to the first volume to account for head motion. All subjects in this study had less than 2 mm translation and 2° of rotation in any of the x, y, and z axes. Then, the volumes were normalized to the standard EPI template in the Montreal Neurological Institute (MNI) space and resliced to 3 × 3 × 3 mm3. The resulting images were spatially smoothed with a Gaussian filter of 8 mm full-width half-maximum kernel. To avoid the blurring of fMRI signal across the cerebellar–cerebral boundary during spatial smoothing, the functional data in the cerebellum and cerebrum were extracted from the whole brain and smoothed separately. Subsequently, the data were temporally filtered with a band-pass filter (0.01–0.1 Hz), followed by linear detrending to remove any residual drift. Nine nuisance signals were further removed from the data via multiple regression, including the signals averaged from the white matter, the cerebrospinal fluid and the whole brain, and six parameters obtained by head motion correction. This regression procedure was utilized to reduce spurious variance unlikely to reflect neuronal activity.
2. Materials and methods
2.3. Functional connectivity analysis
2.1. Subjects and imaging protocols
A seed-based correlation method was used to identify the resting cerebellar functional connectivity patterns in the patients with schizophrenia and in the healthy controls. Seed regions were defined as 6mm-radius spheres centered on previously published foci. In this study, we selected 3 seed regions centered in the left Crus I (MNI: − 33, − 76, − 34), right Crus I (MNI: 33, − 76, − 34), and Lobule IX (MNI: 0, −55, −49), which have been found to contribute to the intrinsic connectivity of the DMN in healthy individuals (Habas et al., 2009; Krienen and Buckner, 2009; Bernard et al., 2012). The time series of each seed region were calculated by averaging the fMRI time series over all voxels within the sphere. For each subject, correlation maps were created by calculating the Pearson's correlation coefficients between the time series of the seed regions and that of each voxel in the brain. These correlation maps were converted to z-value maps using Fisher's r-to-z transformation, to improve the normality of the correlation coefficients. Group analyses were performed for the correlation maps of each seed region. First, correlation maps of the patients with schizophrenia and healthy controls were separately underwent a voxel-wise onesample t-test, to determine the brain regions with significant correlations to the cerebellar seed regions. Then, a voxel-wise two-sample ttest was conducted between the correlation maps of the patients and healthy subjects, to identify significant cerebellar functional connectivity changes in schizophrenia. The significance level was set at p b 0.001, uncorrected. Multiple comparisons were corrected at the cluster level (p b 0.05, false discovery rate).
Data analyzed in this study came from an open access resting-state fMRI dataset comprising 72 patients with schizophrenia and 74 healthy controls. This publicly available dataset is contributed by the Center for Biomedical Research Excellence (COBRE, http://fcon_1000.projects. nitrc.org/indi/retro/cobre.html), and has been previously studied by Anderson and Cohen (2013), Sui et al. (2013). All the subjects in the COBRE were screened and excluded if they had history of neurological disorder, history of mental retardation, history of severe head trauma with more than 5 minute loss of consciousness, history of substance abuse or dependence within the last 12 months. The patients were treated with atypical antipsychotic medications and were retrospective and prospective clinical stability. Diagnostic information was collected using the Structured Clinical Interview used for DSM Disorders. The subjects underwent resting-state scans on a 3-T SIEMENS MRI scanner with the following parameters: 33 axial slices, repetition time = 2000 ms, echo time = 29 ms, flip angle = 75°, slice thickness = 3.5 mm, slice gap = 1.05 mm, acquisition matrix = 64 × 64, field of view = 240 mm. A total of 150 volumes of functional images were obtained for all the subjects except one (this subject was excluded from the present study). Another 15 subjects were excluded because of serious head motion (more than 2 mm translation or 2° of rotation) or partial cerebellum coverage of their fMRI scans. To match subjects across the two groups for age and sex, 10 healthy controls were further excluded from this study. Finally, 60 patients with schizophrenia and 60 healthy controls were included in the present analyses. Characteristics of the patient group and control group are shown in Table 1.
Table 1 Characteristics of the patient and control groups in this study. Variable
Patient
Control
p-Value
Sample size Age (years) Gender (M/F) Handedness (L/R)b Diagnosis score
60 38.0 ± 13.9 48/12 9/49 295.4 ± 0.7
60 37.6 ± 11.6 47/13 1/57
0.86 0.82a 0.008a
a b
Pearson Chi-square test. Two subjects are ambidextrous in both the patient and control groups.
3. Results
2.2. Data preprocessing
3.1. Functional connectivity of the cerebellar seed regions
Functional scans were preprocessed using the SPM8 software (Wellcome Department of Imaging Neuroscience, University College
Resting-state functional connectivity patterns of the left Crus I, right Crus I and Lobule IX are shown in Fig. 1. For the control group, the
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Fig. 1. Resting-state functional connectivity of the cerebellar default-mode seed regions. Correlation maps for healthy controls and patients with schizophrenia are displayed in the top row and bottom row, separately. The left side of the images represents the left hemisphere of the brain.
cerebellar seed regions were highly correlated with the major regions of the DMN, including the posterior cingulate cortex (PCC), precuneus, anterior cingulate cortex (ACC), lateral parietal cortex, medial prefrontal cortex (mPFC), and thalamus (top row of Fig. 1). Moreover, we observed that the left Crus I showed stronger functional connectivity with the right-hemisphere cerebral regions and vice versa, suggesting the contralateral lateralization of cerebellar connectivity in relation to cortex (Krienen and Buckner, 2009; O'Reilly et al., 2010). For the patient group, the cerebellar seed regions also showed high correlations with the posterior part of the DMN, such as the PCC, precuneus and lateral parietal cortex (bottom row of Fig. 1). However, it can be seen that the frontocerebellar and thalamocerebellar connectivity were reduced or disrupted in the patients.
3.2. Decreased cerebellar functional connectivity in schizophrenia Using two-sample t-test, we found that the patients with schizophrenia exhibited significantly reduced cerebellar functional connectivity with the thalamus and several frontal regions relative to the healthy controls (see Fig. 2 and Table 2). Specifically, the patients exhibited reduced functional connectivity between the left Crus I and areas of the bilateral thalamus, bilateral middle frontal gyri (MFG), and bilateral ACC; between the right Crus I and bilateral thalamus; between the Lobule IX and areas of the bilateral thalamus, bilateral MFG, and bilateral supplementary motor area (SMA). There was no brain area that exhibited significantly increased cerebellar functional connectivity in the patients compared with the healthy controls.
Fig. 2. Significantly reduced functional connectivity maps of the cerebellar seed regions in schizophrenia. Seed regions: left Crus I (A), right Crus I (B), and Lobule IX (C).
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Table 2 Brain areas exhibiting significantly decreased functional connectivity with the cerebellar seed regions in schizophrenia. Seed regions
Target region
BA
Side
Size
MNI (x, y, z)
T-value
L Crus I
Thalamus Middle frontal gyrus Middle frontal gyrus Anterior cingulate cortex Thalamus Thalamus Thalamus Middle frontal gyrus Supplementary motor area Middle frontal gyrus
N/A 10/46 10/46 24/32 N/A N/A N/A 9/46 6/8 46
L/R L R L/R L R L/R R L/R L
425 158 283 375 103 64 404 130 118 91
−9, −22, 2 −27, 32 23 27, 38, 20 6, 32, 20 −9, −22, 2 9, −19, 2 −9, −22, 5 24, 44, 17 0, 17, 59 −27, 35, 20
−6.2 −5.8 −5.1 −4.9 −5.4 −4.0 −5.5 −5.0 −4.2 −4.1
R Crus I Lobule IX
In this study, there were more left-handed subjects in the patient group than in the control group (p = 0.008). To test the potential effect of this confounding factor on our results, we calculated the average functional connectivity strength of the brain areas in Table 2. Comparison of the functional connectivity of these areas for the right-handed subjects also revealed significant group differences (p b 0.001, Fig. S1). Thus, the schizophrenia-related functional connectivity differences observed in this study did not stem from the larger number of lefthanded subjects in the patient group. 3.3. Correlation between frontal and thalamic connectivity In this study, the pattern of cerebellar functional connectivity abnormality in schizophrenia implicates a fronto-thalamo-cerebellar circuit.
To further quantify the regulating effect of the thalamus on the synchronized activity between the cerebellum and frontal regions in schizophrenia, we performed the Pearson's correlation analysis between the strength of the frontocerebellar and thalamocerebellar functional connectivity that exhibited significant schizophrenia-related alterations. A list of the correlation coefficients and their statistical significance are presented in Fig. 3. We found that the strength of functional connectivity in several frontal regions was positively associated with that in the thalamus only in the healthy subjects but not in the patients. For the left Crus I, the healthy controls showed significant positive correlations between the strength of connectivity in the thalamus and that in the left MFG (p b 0.022), right MFG (p b 1.4e− 3), and ACC (p b 2.3e − 7), whereas the patients only showed a significant positive correlation between the connectivity in the thalamus and that in the ACC (p b 0.013)
Fig. 3. Correlations between the strength of frontocerebellar and thalamocerebellar functional connectivity in healthy controls (red) and patients with schizophrenia (blue). MFG, middle frontal gyrus; ACC, anterior cingulate cortex; SMA, supplementary motor cortex.
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(Fig. 3, top row). For the Louble IX, there was only a significant positive correlation between the connectivity in the thalamus and that in the right MFG in the healthy controls (p b 7.7e−3) (Fig. 3, bottom row). Discussion Using seeds from cerebellar regions previously identified as being involved in the DMN, we found that patients with schizophrenia showed significantly reduced cerebellar functional connectivity with the thalamus and several frontal regions during the resting state. Furthermore, the positive correlations between the strength of frontocerebellar and thalamocerebellar connectivity observed in the healthy subjects were diminished in the patients. Therefore, this study suggests disruptive changes of the fronto-thalamo-cerebellar circuit in schizophrenia, and may provide further evidence for the “cognitive dysmetria” concept of schizophrenia (Andreasen et al., 1998, 1999). In this study, we found overlapping and distinct functional connectivity patterns of the cerebellum with the DMN in healthy individuals and patients with schizophrenia. Recently, increased attention has been placed on the higher-order functions of the cerebellum and its abnormalities in psychiatric disorders. Our results are consistent with previous studies that demonstrated the involvement of the Crus I and Lobule IX in the spontaneous brain activity of the DMN (Habas et al., 2009; Krienen and Buckner, 2009; Bernard et al., 2012). Previous neuroimaging studies, such as morphometry (Loeber et al., 2001), taskrelated brain activity (Honey et al., 2005), and resting-state functional connectivity (Shen et al., 2010; Collin et al., 2011), have found that cerebellar abnormalities occur in schizophrenia. It is also suggested that a cerebellar dysfunction could account for some of the psychiatric, neurological, or cognitive symptoms present in this disease (Picard et al., 2008). Based on previous studies, disruptive changes of the cerebellar functional connectivity with the DMN may underlie the symptoms and deficits associated with schizophrenia. More specifically, we found that the cerebellar functional connectivity was disrupted with several frontal regions (the MFG, ACC and SMA) in schizophrenia. Previous neuroimaging studies have consistently found that the MFG and ACC show abnormal activation and disrupted integration with other brain regions in patients with schizophrenia across a range of cognitive paradigms, including working memory (Pomarol-Clotet et al., 2008; Whitfield-Gabrieli et al., 2009), cognitive interference (Heckers et al., 2004), stroop (Weiss et al., 2007), verbal encoding/retrieval (Wolf et al., 2007), response inhibition (Laurens et al., 2003), and auditory oddball task (Garrity et al., 2007). Therefore, disruptive changes of the resting cerebellar connectivity with the MFG and ACC may be associated with difficulty in coordinating the processing, prioritization, retrieval, and expression of information in schizophrenia. In addition, we found that patients with schizophrenia showed reduced connectivity between the Lobule IX and SMA. This finding is not surprising, given that the Lobule IX is considered essential for the visual guidance of movement (Glickstein et al., 1994), and lesion of the Louble IX could result in balance and gait impairments (Ilg et al., 2008). The observation of impaired connectivity of the Louble IX with the SMA may result in deficits of motor function in schizophrenia (Honey et al., 2005; Exner et al., 2006), suggesting that the functional deficit in schizophrenia is not confined to the DMN, but also affects integration in other regions. We also found that the functional connectivity between the cerebellum and thalamus was reduced in schizophrenia. The thalamus is believed to play a key role in the establishment of oscillatory dynamics that integrate brain functions (Jones, 2009). Previous studies have demonstrated that patients with schizophrenia exhibit decreased task-related thalamic activation (Andrews et al., 2006; Bor et al., 2011) and reduced thalamocortical connectivity (Welsh et al., 2010; Marenco et al., 2012). In this study, we further provide evidence of functional thalamocerebellar disconnection in schizophrenia. Moreover, we
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found positive correlations between the strength of frontocerebellar and thalamocerebellar functional connectivity only in healthy individuals but not in patients with schizophrenia. The correlations observed in healthy individuals are supported by previously findings that the cerebellum is anatomically connected to the prefrontal cortex through polysynaptic projections via the thalamus (Schmahmann, 1996; Middleton and Strick, 2001; Kelly and Strick, 2003). This relationship is diminished in patients with schizophrenia, suggesting the dysfunction of the thalamus in mediating the synchronized activity between the cerebellum and prefrontal cortex in schizophrenia. Therefore, our findings may help to shed light on the neural basis underlying the widespread disturbances in information transmission and processing in schizophrenia. It should be noted that all the patients in this study were treated with atypical antipsychotic medications. Evidence has indicated that antipsychotic treatment in schizophrenia can affect both the structure (Smieskova et al., 2009) and function (Abbott et al., 2013) of the brain. Recently, a few studies have also attempted to probe functional connectivity changes with antipsychotic treatment, which produced inconsistent results. Sambataro et al. (2010) showed that treatment with olanzapine was associated with increases in DMN connectivity with the medial prefrontal cortex. Hadley et al. (2014) found that functional connectivity deficits between the midbrain and thalamus in schizophrenia were restored after one week of risperidone treatment. However, another resting-state fMRI study showed that antipsychotic treatment in schizophrenia could lead to a widespread attenuation in functional connectivity (Lui et al., 2010). The effects of antipsychotic medications on functional brain systems are complex, and we ca nnot exclude the possibility that antipsychotic treatment contributed to our findings. Several other potential limitations of this study should also be noted. The phenotypic characterization of subjects in the COBRE database did not provide information regarding cognitive and behavioral variables, and the diagnosis scores were in a narrow range across the patients (290.3–296.4). Thus, we were unable to assess the associations between cerebellar functional connectivity changes and schizophrenia symptoms and severity. Moreover, we only examined the specific contribution of the cerebellum to the DMN abnormalities in schizophrenia. Previous studies have suggested that functional resting-state networks are differentially affected in schizophrenia (Woodward et al., 2011). In further study, we intend to perform comparisons of schizophreniarelated functional connectivity changes at different cerebellar regions to complement our results. In conclusion, this study found reduced cerebellar-DMN couplings in schizophrenia. Moreover, the associations between the strength of frontocerebellar and thalamocerebellar connectivity observed in healthy individuals were diminished in patients with schizophrenia. Our results provide further evidence for demonstrating the disruptive changes of the fronto-thalamo-cerebellar circuit in schizophrenia, which is believed to be of critical importance for schizophrenic pathophysiology. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.schres.2014.09.034.
Role of funding source This work was supported by the National Science Foundation of China (81271470, 31300840), the Beijing Natural Science Foundation (4144092), and the National Key Project of China (AWS12J003). The funding sources 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.
Contributors Zheng Yang and Dewen Hu designed the study. Xiao Jin managed the literature searches and analyses. Lubin Wang, Yongcong Shao, and Enmao Ye undertook the statistical analysis. Lubin Wang wrote the first draft of the manuscript, and Feng Zou and Shuwen Tan revised the manuscript. All authors contributed to and have approved the final manuscript.
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Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgment We thank the COBRE for publicly sharing the data, and Xueyan Zhang for proofreading the manuscript.
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