Acta Psychiatr Scand 2015: 132: 400–407 All rights reserved DOI: 10.1111/acps.12429
© 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd ACTA PSYCHIATRICA SCANDINAVICA
Reduced interhemispheric resting-state functional connectivity in unmedicated bipolar II disorder Wang Y, Zhong S, Jia Y, Zhou Z, Zhou Q, Huang L. Reduced interhemispheric resting-state functional connectivity in unmedicated bipolar II disorder. Objective: Abnormalities in structural and functional brain connectivity have been increasingly reported in patients with bipolar disorder (BD) by recent neuroimaging studies. However, relatively little is known about the changes in functional interaction between the cerebral hemispheres in BD. The present study aimed to examine the interhemispheric functional connectivity of the whole brain in patients with BD II during resting state. Method: Twenty-six patients with unmedicated BD II depression and 40 normal controls underwent the resting-state functional magnetic resonance imaging. The functional connectivity between any pair of symmetrical interhemispheric voxels (i.e., functional homotopy) was measured by voxel-mirrored homotopic connectivity (VMHC). Results: The patients with BD II showed lower VMHC than normal controls in the medial prefrontal cortex and inferior temporal gyrus. No regions of increased VMHC were detected in patients. There were no significant correlations between the VMHC values in these regions and clinical severity of BD symptoms. Conclusion: These findings suggest substantial impairment of interhemispheric coordination in BD II.
Y. Wang1,2 , S. Zhong3 , Y. Jia3 ,
Z. Zhou2, Q. Zhou2, L. Huang2
1 Clinical Experimental Center, First Affiliated Hospital of Jinan University, 2Medical Imaging Center, First Affiliated Hospital of Jinan University, and 3Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
Key words: bipolar disorder; functional magnetic resonance imaging; voxel-mirrored homotopic connectivity; medial prefrontal cortex Ying Wang, Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China. E-mail: [email protected] and Li Huang, Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China. E-mail: [email protected]
Accepted for publication April 9, 2015
Significant outcomes
• This is the first study to demonstrate disrupted interhemispheric functional connectivity between the bilateral medial prefrontal cortex and inferior temporal gyrus in BD II.
• These findings suggest that impairment of interhemispheric coordination may be important in the pathophysiology of BD II.
Limitations
• The study sample is relatively small. • Future research such as voxel-based morphometry and diffusion tensor is necessary to identify the unknown structural basis for voxel-mirrored homotopic connectivity (VMHC) alterations.
Introduction
Bipolar disorder (BD) is a chronic, severe and fluctuating psychiatric disorder and remains a leading worldwide cause of disability, morbidity, and mortality from suicide and associated medical conditions, such as diabetes mellitus and cardiovascular 400
and neurovascular disease (1, 2). The disease is characterized by vacillations in mood from the lows of depression to the highs of mania with relatively normal mood in between. Although numerous structural and functional neuroimaging studies have revealed abnormalities in connections and specific brain areas in BD, the
Homotopic connection in bipolar disorder neurobiology of BD is still incompletely understood. The ability of the left and right hemispheres to interact and cooperate in the processing of information is important for normal brain functioning. Recently, interhemispheric connectivity abnormalities in BD are receiving increasing attention. Its evaluation may be of interest in studying pathophysiological characteristics of BD. Structural magnetic resonance imaging (MRI) studies have found area and shape changes in the corpus callosum (CC) in BD (3). The CC, the largest white matter structure connecting between the two cerebral hemispheres, plays a critical role in interhemispheric communication and coordination, particularly in the integration of emotional, cognitive, motor, and sensory information. It is recognized that the CC provides connections between homologous cortical areas (4). Several studies have also found decreased CC signal intensity in adult (5) and pediatric (6) BD I and II, reflecting an increase in water content in the CC in early-onset BD. In addition, diffusion tensor imaging (DTI) and tractography studies have found reduced fractional anisotropy (FA) in the genu, body, and splenium of the CC in patients with BD relative to controls (7–9), suggesting that disruption of the organization of fiber tracts may be related to efficiency of interhemispheric signal transfer in the case of the CC. A recent study reported impaired interhemispheric but relatively preserved intrahemispheric integration in BD using DTI and graph theoretical analysis (10). Unfortunately, relatively little is known about the alterations in functional interactions between the bilateral cerebral hemispheres in patients with BD. Few electroencephalogram (EEG) and functional MRI (fMRI) studies have demonstrated altered interhemispheric EEG coherence (11) and imbalanced task-related activity in homologous regions between hemispheres (12, 13) in BD. Resting-state fMRI (rs-fMRI), which is a noninvasive imaging technique to measure the spontaneous brain activity as low-frequency fluctuations in blood oxygen level-dependent (BOLD) signals in the resting brain (14), provides fresh insights intra- and interhemispheric functional connectivity. The majority of rs-fMRI studies conducted in BD have employed either seed-based or amplitude of low-frequency fluctuation (ALFF) analyses (15). While informative, the seed-based approach is always limited by the inherent bias introduced by predefining regions of interest (the seed region) for connectivity analyses. By contrast, ALFF is a useful tool for identifying between group
differences in local BOLD signal frequency fluctuations, but is not a direct measure of functional connectivity. Kenny et al. (16). have also emphasized that affective disorders are more likely due to aberrations at the circuit level rather than at a localized brain region. Homotopic resting-state functional connectivity is one of the most salient characteristics of the brain’s intrinsic functional architecture (17), likely reflecting the importance of interhemispheric communication to integrated brain function underlying coherent cognition and behaviour (18). It demonstrates the high degree of synchrony in spontaneous activity between homotopic (geometrically corresponding) regions in each hemisphere (17, 19). Voxel-mirrored homotopic connectivity (VMHC) is a novel approach which quantifies functional homotopy by providing a voxelwise measure of connectivity between hemispheres (20). This method measures the resting-state functional connectivity between each voxel in one hemisphere and its mirrored counterpart in the opposite hemisphere. Recent work has demonstrated that VMHC is a reliable and reproducible rs-fMRI metric (21). Using VMHC analysis, several studies have revealed aberrant interhemispheric functional connectivity in neuropsychiatric disorders, such as schizophrenia (22, 23), cocaine addiction (18), and migraine (24). Some recent studies found that VMHC decreased in some brain regions in major depressive disorder (MDD) (25–28). Although these findings were not exactly consistent, suggested functional coordination between homotopic brain regions impaired in MDD. These studies demonstrated the feasibility of using VMHC as an interhemispheric interaction index to show group differences between healthy controls and a number of different clinical populations. However, there are no studies to investigate possible impairment of homotopic resting-state functional connectivity in patients with BD. Additionally, sample populations such as psychotropic medication, types of BD, different mood state (manic, depressed, mixed, or euthymic phase), and the history of psychosis may have contributed to discrepant results of structural and/or functional neuroimaging. A recent systematic review of 8 rs-fMRI studies in BD suggested that the effect of psychotropic medication is an important source of possible bias in the final results of functional neuroimaging (15). Therefore, to better understand the brain primary functional changes in patients with BD, these confounding variables need to be controlled in research. In addition, most neuroimaging studies have involved bipolar I samples, but comparatively few studies have focused on bipolar II disorder. 401
Wang et al. Aims of the study
In the current study, we collected rs-fMRI data from patients with unmedicated BD II depression and healthy controls and compared interhemispheric resting-state functional connectivity using a VMHC analysis. We hypothesized that patients with BD II might show reduced VMHC values compared with controls, which would suggest an impairment of interhemispheric functional coordination. We believe such data will contribute to our improved understanding of the pathophysiology of BD.
Material and methods Subjects
In total, 30 right-handed, out- or in-patients with BD II were recruited from the psychiatry department of First Affiliated Hospital of Jinan University, Guangzhou, China. The patients were aged from 18 to 55 years. All patients met DSM-IV criteria for bipolar II disorder according to the diagnostic assessment by the Structured Clinical Interview for DSM-IV Patient Edition (SCID-P). Exclusion criteria included the presence of (i) any current psychiatric disorder (with the exception of BD and anxiety disorders), (ii) a history of electroconvulsive therapy, (iii) any history of moderate/ severe head injury, head trauma, neurological disorder, or mental retardation, (iv) alcohol/substance abuse or dependence, (v) the presence of a concurrent significant physical illness, and (vi) pregnancy or any contraindication to MRI scanning. Clinical state was assessed using the 24-item Hamilton Depression Rating Scale (HDRS) and the Young Mania Rating Scale (YMRS) during the 7-day period prior to the imaging session. All patients with BD were suffering from depression (HDRS-24 score ≥ 18). At the time of testing, all patients were either medication-na€ıve or were unmedicated for at least 5 months. A total of 41 right-handed healthy control subjects were recruited via local advertisements. They were carefully screened through a diagnostic interview, the Structured Clinical Interview for DSMIV Nonpatient Edition (SCID-NP), to rule out the presence of current or past psychiatric illness. Further exclusion criteria for healthy controls were any history of psychiatric illness in first-degree relatives, current or past significant medical or neurological illness. The study was approved by the Ethics Committee of First Affiliated Hospital of Jinan University, China. All subjects signed a written informed 402
consent form after a full written and verbal explanation of the study. Two senior clinical psychiatrists confirmed that all subjects had the ability to consent to participate in the examination. MRI data acquisition and preprocessing
MRI data were acquired on a 3.0 T MR system (Discovery MR 750 System, GE Healthcare, Milwaukee, WI) with an 8-channel phased array head coil. Subjects were scanned in a supine, head-first position with symmetrically placed cushions on both sides of the head to decrease motion. During the scanning, participants were instructed to relax with their eyes closed without falling asleep; after the experiment, each participant confirmed not having fallen asleep. The rs-fMRI data were acquired using gradientecho echo-planar imaging sequence with the following parameters: time repetition (TR)/time echo (TE) = 2000/25 ms, slice thickness/gap = 3.0/ 1.0 mm, voxel size = 3.75 9 3.75 9 3 mm3, field of view (FOV) = 240 9 240 mm, flip angle = 90°, matrix = 64 9 64, number of slices = 35, and NEX = 1. A 7-min scan (210 volumes) was obtained for each subject. In addition, a threedimensional brain volume imaging (3D-BRAVO) sequence covering the whole brain was used for structural data acquisition with: TR/TE = 8.2/ 3.2 ms, slice thickness/gap = 1.0/0 mm, matrix = 256 9 256, FOV = 240 9 240 mm, NEX = 1, flip angle = 12o, bandwidth = 31.25 Hz, and acquisition time = 3 min 45 s. Routine MRI examination images were also collected for excluding anatomic abnormality, such as T1, T2, DWI, and T2FLAIR images. All participants were found by two experienced radiologists to have no abnormalities on routine MRI. Functional image preprocessing
The preprocessing was carried out using Data Processing Assistant for Resting-State fMRI (DPARSF) (29) which is based on Statistical Parametric Mapping (SPM8, http://www.fil.ion.ucl. ac.uk/spm) and rs-fMRI Data Analysis Toolkit (REST, http://www.restfmri.net) (30). For each individual, the first 10 images were discarded to ensure steady-state longitudinal magnetization. The remaining images were slice-time corrected and realigned to the first image in the first series. All subjects should have no more than 1 mm maximum displacement in x, y, or z and 1° of angular motion. The individual T1 images were coregistered to functional images. The coregistered T1 structural images were segmented (gray matter,
Homotopic connection in bipolar disorder white matter, and cerebrospinal fluid) using the unified segmentation algorithm and were then transformed into standard Montreal Neurological Institute (MNI) space. The functional images were also spatially normalized to MNI space by applying the parameters of structural image normalization and were resampled to 3 9 393 mm3 resolution. The generated images were spatially smoothed with a Gaussian kernel of 6 mm at fullwidth at half-maximum. Subsequently, the data were removed linear trend and band-pass filtered (0.01–0.08 Hz). Several sources of spurious covariates and their temporal derivatives were then removed using linear regression, including the six head motion parameters obtained by rigid body correction, global mean, white matter, and cerebrospinal fluid. Then, the images of each subject were registered to a symmetrical MNI template and were used to compute the homotopic functional connectivity. Voxel-mirrored homotopic connectivity
framewise displacement (FD) values for each subject. The mean FD was applied as a covariate in the group comparisons of VMHC. Once significant group differences were observed in any brain regions, we further computed Pearson’s correlation coefficients between these VMHC values and the clinical severity of BD symptoms.
Results Sample characteristics
Table 1 shows the demographic and clinical data of all study participants. Four patients with BD and one normal control were excluded from further analyses due to excessive head motion during the image acquisition. Finally, the participants included 26 patients with bipolar II depression and 40 healthy control subjects. There were no significant differences in sex, age, years of education, and FD parameter between the BD II group and the healthy control group.
VMHC analysis was performed using DPARSF software. For each subject, the homotopic restingstate functional connectivity was computed as the Pearson correlation (Fisher Z-transformed) between each voxel’s residual time series and that of its mirrored interhemispheric counterpart. The resultant values generated the VMHC maps and were used for subsequent group-level analyses. We also calculated the global VMHC for each subject and compared it between groups. Global VMHC was calculated by averaging VMHC values across all brain voxels.
Although the control and bipolar II depression groups did not differ on the global VMHC (control subjects = 0.59 0.07; patients = 0.57 0.08; t = 1.45, P = 0.151), the patient group showed lower VMHC values than the control group in the medial prefrontal cortex (mPFC) and inferior temporal gyrus (ITG) (Fig. 1, Table 2). No region showed greater VMHC in the patient group than in the control group. There were no significant correlations between the VMHC values in these
Statistical analysis
Table 1. Demographic and clinical data and (standard deviations) by group
Independent-sample t-tests and chi-squared tests were used to compare demographic data between the BD and HC groups with SPSS 17.0 software (SPSS, Chicago, IL, USA). All tests were twotailed, and P < 0.05 was considered statistically significant. The two-sample t-test was performed to determine the significant differences in VMHC between patients with BD and controls. The statistical threshold was set at corrected P < 0.05 (combination of P < 0.01 for single voxel and a minimum cluster volume >918 mm3), which was determined by Monte Carlo simulations using the AFNI AlphaSim program (http://afni.nimh.nih.gov/pub/dist/doc/manual/AlphaSim.pdf). Individual’s age and gender were included as nuisance covariates. In addition, because micromotions from volume to volume can influence resting-state functional connectivity results, we computed
VMHC: group differences
Number of subjects Age (years) Gender (male/female) Education (years) Age at onset (years) Number of episodes 24-item HDRS score (points) 24-item HDRS score range (points) YMRS score (points) YMRS score range (points) Duration of illness (months) Duration of illness range (months) FD values (mm)
Bipolar II disorder
Control
26 26.12 (10.30) 15/11 14.64 (5.86) 22.40 (10.34) 2.12 (1.51) 28.08 (5.62) 19–38 2.05 (1.66) 0–5 31.24 (7.61) 1–72 0.08 (0.04)
40 28.97 (9.17) 22/18 15.56 (2.44) n/a n/a n/a
P value
0.317* 0.830† 0.428*
n/a n/a 0.08 (0.03)
0.501*
Means (with standard deviations in parentheses) are reported unless otherwise noted. HDRS, Hamilton Depression Rating Scale; YMRS, Young Mania Rating Scale; FD, framewise displacement for in-scanner head motion. *The P values were obtained by independent-sample t-tests. †The P value for gender distribution was obtained by chi-square test.
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Fig. 1. Axial MR images show significant differences in VMHC between patients with BD and healthy controls. Blue colors indicate reduced VMHC in BD, and the color bar indicates the T value from t-test between groups. Table 2. The areas of VMHC differences between patients with BD and normal controls Montreal Neurological Institute Coordinates Brain regions Medial Prefrontal Cortex Inferior Temporal Gyrus
Peak t Value
Cluster Size (mm3)
Brodman Area
X
10
3
63
9
3.70
1134
20
57
18
33
4.10
972
Y
Z
VMHC, voxel-mirrored homotopic connectivity.
regions and any clinical measure (including HDRS, YMRS scores, and disease duration). Discussion
The main finding of this study was the significant decrease in the homologous resting-state functional connectivity of the mPFC and ITG in patients with unmedicated bipolar II depression. To our best knowledge, this is the first study to directly evaluate altered interhemispheric functional connectivity in patients with BD, using a VMHC method based on the rs-fMRI data. The mPFC is widely connected to subcortical and limbic areas, suggesting its import to emotional regulation processes and in affective symptoms of BD (31). Moreover, the mPFC is also a core hub of the default mode network (DMN), which is typically more active during rest than during the performance of sensorimotor or cognitive tasks, and is thought to mediate internal mental activity and self-reflection (32). In this study, we found decreased VMHC of the mPFC in patients with bipolar II depression compared with the control subjects, suggesting impaired functional connectivity between the bilateral mPFC. Moreover, these findings further support the issue that the DMN dysconnectivity is important in the 404
pathogenesis of BD. With the same VMHC approach, recent two studies found that patients with first-episode, drug-naive MDD showed decreased VMHC in mPFC (25, 27). Moreover, Guo et al. (25) found significant positive correlation between VMHC in mPFC and persistent error response of Wisconsin Card Sorting Test in patients with MDD. Unfortunately, we did not find a significant correlation between the VMHC values and HDRS or YMRS. Previous studies also demonstrated structure and function of the mPFC were abnormal in BD, such as decreased gray matter volume (33, 34) and decreased activity (35). Particularly, some fMRI studies reported abnormal mPFC -limbic connectivity in BD (15), which might partly contribute to the emotional and cognitive symptoms seen in patients with BD. A recent DTI study found white matter microstructure differences (decreased FA) in the anterior genu of the CC in young people with BD (36), supporting our finding of disturbed functional coordination between the left and right mPFC in BD. Postmortem studies found reduced neuronal size, neuronal density, and glial cell density in the mPFC in BD, which suggested the presence of dendritic atrophy of neurons and the loss of oligodendroglial cells (37). Taken together, the present decreased VMHC in the mPFC provides novel evidence for functional and structural damage to the mPFC in BD II and therefore may be a key neurobiological feature of BD. The temporal cortex is involved in the processing of auditory information, language comprehension, semantic memory, visual perception, and multimodal sensory integration (38). In patients with BD II, the decreased VMHC was also found in the ITG, which suggests impaired interhemispheric functional connectivity, especially in long-range connections. However, the ITG has received little attention in structural and functional
Homotopic connection in bipolar disorder neuroimaging studies of BD. A recent study of structural MRI found reduced cortical thickness in the left superior, middle, and ITG in patients with BD II (39). Meanwhile, a task-based fMRI study reported that patients with BD showed decreases in the ITG activation during visuospatial processing (40). Some studies also reported gray matter losses in the bilateral ITG in both patients with schizophrenia (38) and their non-psychotic siblings (41), suggesting the ITG played important roles in the pathophysiology of schizophrenia. Additionally, the ITG is been found to be involved in visual working memory maintenance and associative long-term memory retrieval (42, 43). Thus, combined with our results suggests that the decreased VMHC values in ITG could be associated with deficits in cognitive function of BD, particularly in complex visual perception. Future studies should address interhemispheric synchronization deficits relative to specific aspects of cognitive dysfunction. Some possible biological mechanisms may underlie the VMHC alteration in BD II. Altered brain structures, including widespread white matter integrity, local gray matter volume, and cortical thickness, might disrupt the functional synchrony between homotopic regions. Particularly, impairment in white matter connectivity of the CC could disrupt functional integration and coordination because neural signals are not transmitted from one hemisphere to another. The disruptions of functional integration are associated with abnormal myelination, axonal density, axonal caliber, and fiber coherence. However, direct structural connectivity does not appear to be a strict determinant of the functional connectivity in healthy brains. The rs-fMRI studies of split-brain patients found that a normal complement of resting-state networks and intact functional coupling between bilateral hemispheres can emerge in the absence of the CC (44). These findings suggest that interhemispheric functional connectivity may thus arise from common subcortical drivers, or complex network-level synchronization, neither of which requires direct structural connectivity between cortical components. Therefore, combination of the functional and structural information would help elucidating the mechanism underlying the VMHC deficits in BD. Another possible factor underlying abnormal functional homotopy in BD II is asymmetry of hemispheric growth. The two hemispheres may show subtle differences or delays in the trajectory of growth (23). The strengths of the study include the homogeneous samples of unmedicated depressive patients with BD II. However, some potential limitations
of the present study should be taken into consideration. First, the human brain is not symmetrical. However, we applied a symmetrical template and smoothed the functional data to improve the functional correspondence between homotopic regions. Kelly et al. (18) found morphometric asymmetry could not account for altered VMHC, but the effects of methodological symmetry could not be completely eliminated. Thus, future research such as voxel-based morphometry and DTI is necessary to identify the unknown structural basis for VMHC alterations. Second, the sample size of this study was relatively small, and results will require replication in a larger study. Third, without a group of patients with BD in a euthymic episode, it is still not clear whether VMHC deficits are specific to the depression episode of BD or shared by all episodes of the disease. Further studies using a prospective design may clarify this issue. Finally, we did not collect neuropsychological data, especially tasks that required interhemispheric transfer of information. Thus, additional neuropsychological tests are needed, and we will investigate the associations between cognitive dysfunction and VMHC deficits in further work. In conclusion, the present findings are the first to reveal aberrant interhemispheric functional connectivity in the bilateral mPFC and IPG in patients with bipolar II depression. Our results suggest that disruption in functional coordination between the two hemispheres may be a key neurobiological feature of BD II. Homotopic interhemispheric resting-state functional connectivity may provide a useful and sensitive screening approach for evaluating BD where neural connectivity is implicated in the pathophysiology. Acknowledgements We would like to thank all the participants for their contribution to this study. This work was supported by the National Science Foundation of China (81471650), Natural Science Foundation of Guangdong Province, China (2014A030313 375), Planned Science and Technology Project of Guangdong Province, China (2013B021800160), Fundamental Research Funds for the Central Universities (21615476), Humanity and Social Science Foundation of Ministry of Education of China (13YJA190008). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Declarations of interest The other authors declare no conflict of interests.
References 1. Merikangas KR, Akiskal HS, Angst J et al. Lifetime and 12-month prevalence of bipolar spectrum disorder in the
405
Wang et al.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
406
National Comorbidity Survey replication. Arch Gen Psychiatry 2007;64:543–552. Prieto ML, Cuellar-Barboza AB, Bobo WV et al. Risk of myocardial infarction and stroke in bipolar disorder: a systematic review and exploratory meta-analysis. Acta Psychiatr Scand 2014;130:342–353. Marlinge E, Bellivier F, Houenou J. White matter alterations in bipolar disorder: potential for drug discovery and development. Bipolar Disord 2014;16:97–112. Siffredi V, Anderson V, Leventer RJ, Spencer-Smith MM. Neuropsychological profile of agenesis of the corpus callosum: a systematic review. Dev Neuropsychol 2013;38: 36–57. Brambilla P, Nicoletti M, Sassi RB et al. Corpus callosum signal intensity in patients with bipolar and unipolar disorder. J Neurol Neurosurg Psychiatry 2004;75:221–225. Caetano SC, Silveira CM, Kaur S et al. Abnormal corpus callosum myelination in pediatric bipolar patients. J Affect Disord 2008;108:297–301. Emsell L, Leemans A, Langan C et al. Limbic and callosal white matter changes in euthymic bipolar I disorder: an advanced diffusion magnetic resonance imaging tractography study. Biol Psychiatry 2013;73:194–201. Sarrazin S, Poupon C, Linke J et al. A multicenter tractography study of deep white matter tracts in bipolar I disorder: psychotic features and interhemispheric disconnectivity. JAMA Psychiatry 2014;71:388–396. Wang F, Kalmar JH, Edmiston E et al. Abnormal corpus callosum integrity in bipolar disorder: a diffusion tensor imaging study. Biol Psychiatry 2008;64:730–733. Leow A, Ajilore O, Zhan L et al. Impaired inter-hemispheric integration in bipolar disorder revealed with brain network analyses. Biol Psychiatry 2013;73:183–193. Bjork MH, Sand T, Brathen G et al. Quantitative EEG findings in patients with acute, brief depression combined with other fluctuating psychiatric symptoms: a controlled study from an acute psychiatric department. BMC Psychiatry 2008;8:89. Bearden CE, Hoffman KM, Cannon TD. The neuropsychology and neuroanatomy of bipolar affective disorder: a critical review. Bipolar Disord 2001;3:106–150 discussion 151–153. Caligiuri MP, Brown GG, Meloy MJ et al. A functional magnetic resonance imaging study of cortical asymmetry in bipolar disorder. Bipolar Disord 2004;6:183–196. 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. Vargas C, Lopez-Jaramillo C, Vieta E. A systematic literature review of resting state network–functional MRI in bipolar disorder. J Affect Disord 2013;150:727–735. Kenny ER, O’Brien JT, Cousins DA et al. Functional connectivity in late-life depression using resting-state functional magnetic resonance imaging. Am J Geriatr Psychiatry 2010;18:643–651. Stark DE, Margulies DS, Shehzad ZE et al. Regional variation in interhemispheric coordination of intrinsic hemodynamic fluctuations. J Neurosci 2008;28:13754–13764. Kelly C, Zuo XN, Gotimer K et al. Reduced interhemispheric resting state functional connectivity in cocaine addiction. Biol Psychiatry 2011;69:684–692. Salvador R, Suckling J, Coleman MR et al. Neurophysiological architecture of functional magnetic resonance images of human brain. Cereb Cortex 2005;15:1332–1342. Zuo XN, Kelly C, Di Martino A et al. Growing together and growing apart: regional and sex differences in the
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
lifespan developmental trajectories of functional homotopy. J Neurosci 2010;30:15034–15043. Zuo XN, Xing XX. Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: a systems neuroscience perspective. Neurosci Biobehav Rev 2014;45:100–118. Hoptman MJ, Zuo XN, D’Angelo D et al. Decreased interhemispheric coordination in schizophrenia: a resting state fMRI study. Schizophr Res 2012;141:1–7. Li HJ, Xu Y, Zhang KR, Hoptman MJ, Zuo XN. Homotopic connectivity in drug-naive, first-episode, early-onset schizophrenia. J Child Psychol Psychiatry 2015;56:432– 443. Yuan K, Qin W, Liu P et al. Reduced fractional anisotropy of corpus callosum modulates inter-hemispheric resting state functional connectivity in migraine patients without aura. PLoS ONE 2012;7:e45476. Guo W, Liu F, Dai Y et al. Decreased interhemispheric resting-state functional connectivity in first-episode, drugnaive major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2013;41:24–29. Guo W, Liu F, Xue Z et al. Decreased interhemispheric coordination in treatment-resistant depression: a restingstate fMRI study. PLoS ONE 2013;8:e71368. Lai CH, Wu YT. Decreased inter-hemispheric connectivity in anterior sub-network of default mode network and cerebellum: significant findings in major depressive disorder. Int J Neuropsychopharmacol 2014;13:1–8. Wang L, Li K, Zhang QE et al. Interhemispheric functional connectivity and its relationships with clinical characteristics in major depressive disorder: a resting state fMRI study. PLoS ONE 2013;8:e60191. Chao-Gan Y, Yu-Feng Z. DPARSF: A MATLAB toolbox for “Pipeline” data analysis of resting-state fMRI. Front Syst Neurosci 2010;4:13. Song XW, Dong ZY, Long XY et al. REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PLoS ONE 2011;6:e25031. Favre P, Baciu M, Pichat C et al. fMRI evidence for abnormal resting-state functional connectivity in euthymic bipolar patients. J Affect Disord 2014;165:182–189. 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. Lijffijt M, Rourke ED, Swann AC et al. Illness-course modulates suicidality-related prefrontal gray matter reduction in women with bipolar disorder. Acta Psychiatr Scand 2014;130:374–387. Selvaraj S, Arnone D, Job D et al. Grey matter differences in bipolar disorder: a meta-analysis of voxel-based morphometry studies. Bipolar Disord 2012;14:135– 145. Keener MT, Phillips ML. Neuroimaging in bipolar disorder: a critical review of current findings. Curr Psychiatry Rep 2007;9:512–520. Lagopoulos J, Hermens DF, Hatton SN et al. Microstructural white matter changes in the corpus callosum of young people with Bipolar Disorder: a diffusion tensor imaging study. PLoS ONE 2013;8:e59108. Savitz JB, Price JL, Drevets WC. Neuropathological and neuromorphometric abnormalities in bipolar disorder: view from the medial prefrontal cortical network. Neurosci Biobehav Rev 2014;42:132–147. Onitsuka T, Shenton ME, Salisbury DF et al. Middle and inferior temporal gyrus gray matter volume abnormalities in chronic schizophrenia: an MRI study. Am J Psychiatry 2004;161:1603–1611.
Homotopic connection in bipolar disorder 39. Elvsashagen T, Westlye LT, Boen E et al. Bipolar II disorder is associated with thinning of prefrontal and temporal cortices involved in affect regulation. Bipolar Disord 2013;15:855–864. 40. Singh MK, Chang KD, Kelley RG et al. Reward processing in adolescents with bipolar I disorder. J Am Acad Child Adolesc Psychiatry 2013;52:68–83. 41. Gogtay N, Greenstein D, Lenane M et al. Cortical brain development in nonpsychotic siblings of patients with childhood-onset schizophrenia. Arch Gen Psychiatry 2007;64:772–780.
42. Ranganath C. Working memory for visual objects: complementary roles of inferior temporal, medial temporal, and prefrontal cortex. Neuroscience 2006;139:277–289. 43. Ranganath C, Cohen MX, Dam C, D’Esposito M. Inferior temporal, prefrontal, and hippocampal contributions to visual working memory maintenance and associative memory retrieval. J Neurosci 2004;24:3917–3925. 44. Tyszka JM, Kennedy DP, Adolphs R, Paul LK. Intact bilateral resting-state networks in the absence of the corpus callosum. J Neurosci 2011;31:15154–15162.
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Reduced interhemispheric resting-state functional connectivity in unmedicated bipolar II disorder Wang Y, Zhong S, Jia Y, Zhou Z, Zhou Q, Huang L. Reduced interhemispheric resting-state functional connectivity in unmedicated bipolar II disorder. Objective: Abnormalities in structural and functional brain connectivity have been increasingly reported in patients with bipolar disorder (BD) by recent neuroimaging studies. However, relatively little is known about the changes in functional interaction between the cerebral hemispheres in BD. The present study aimed to examine the interhemispheric functional connectivity of the whole brain in patients with BD II during resting state. Method: Twenty-six patients with unmedicated BD II depression and 40 normal controls underwent the resting-state functional magnetic resonance imaging. The functional connectivity between any pair of symmetrical interhemispheric voxels (i.e., functional homotopy) was measured by voxel-mirrored homotopic connectivity (VMHC). Results: The patients with BD II showed lower VMHC than normal controls in the medial prefrontal cortex and inferior temporal gyrus. No regions of increased VMHC were detected in patients. There were no significant correlations between the VMHC values in these regions and clinical severity of BD symptoms. Conclusion: These findings suggest substantial impairment of interhemispheric coordination in BD II.
Y. Wang1,2 , S. Zhong3 , Y. Jia3 ,
Z. Zhou2, Q. Zhou2, L. Huang2
1 Clinical Experimental Center, First Affiliated Hospital of Jinan University, 2Medical Imaging Center, First Affiliated Hospital of Jinan University, and 3Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou, China
Key words: bipolar disorder; functional magnetic resonance imaging; voxel-mirrored homotopic connectivity; medial prefrontal cortex Ying Wang, Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China. E-mail: [email protected] and Li Huang, Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China. E-mail: [email protected]
Accepted for publication April 9, 2015
Significant outcomes
• This is the first study to demonstrate disrupted interhemispheric functional connectivity between the bilateral medial prefrontal cortex and inferior temporal gyrus in BD II.
• These findings suggest that impairment of interhemispheric coordination may be important in the pathophysiology of BD II.
Limitations
• The study sample is relatively small. • Future research such as voxel-based morphometry and diffusion tensor is necessary to identify the unknown structural basis for voxel-mirrored homotopic connectivity (VMHC) alterations.
Introduction
Bipolar disorder (BD) is a chronic, severe and fluctuating psychiatric disorder and remains a leading worldwide cause of disability, morbidity, and mortality from suicide and associated medical conditions, such as diabetes mellitus and cardiovascular 400
and neurovascular disease (1, 2). The disease is characterized by vacillations in mood from the lows of depression to the highs of mania with relatively normal mood in between. Although numerous structural and functional neuroimaging studies have revealed abnormalities in connections and specific brain areas in BD, the
Homotopic connection in bipolar disorder neurobiology of BD is still incompletely understood. The ability of the left and right hemispheres to interact and cooperate in the processing of information is important for normal brain functioning. Recently, interhemispheric connectivity abnormalities in BD are receiving increasing attention. Its evaluation may be of interest in studying pathophysiological characteristics of BD. Structural magnetic resonance imaging (MRI) studies have found area and shape changes in the corpus callosum (CC) in BD (3). The CC, the largest white matter structure connecting between the two cerebral hemispheres, plays a critical role in interhemispheric communication and coordination, particularly in the integration of emotional, cognitive, motor, and sensory information. It is recognized that the CC provides connections between homologous cortical areas (4). Several studies have also found decreased CC signal intensity in adult (5) and pediatric (6) BD I and II, reflecting an increase in water content in the CC in early-onset BD. In addition, diffusion tensor imaging (DTI) and tractography studies have found reduced fractional anisotropy (FA) in the genu, body, and splenium of the CC in patients with BD relative to controls (7–9), suggesting that disruption of the organization of fiber tracts may be related to efficiency of interhemispheric signal transfer in the case of the CC. A recent study reported impaired interhemispheric but relatively preserved intrahemispheric integration in BD using DTI and graph theoretical analysis (10). Unfortunately, relatively little is known about the alterations in functional interactions between the bilateral cerebral hemispheres in patients with BD. Few electroencephalogram (EEG) and functional MRI (fMRI) studies have demonstrated altered interhemispheric EEG coherence (11) and imbalanced task-related activity in homologous regions between hemispheres (12, 13) in BD. Resting-state fMRI (rs-fMRI), which is a noninvasive imaging technique to measure the spontaneous brain activity as low-frequency fluctuations in blood oxygen level-dependent (BOLD) signals in the resting brain (14), provides fresh insights intra- and interhemispheric functional connectivity. The majority of rs-fMRI studies conducted in BD have employed either seed-based or amplitude of low-frequency fluctuation (ALFF) analyses (15). While informative, the seed-based approach is always limited by the inherent bias introduced by predefining regions of interest (the seed region) for connectivity analyses. By contrast, ALFF is a useful tool for identifying between group
differences in local BOLD signal frequency fluctuations, but is not a direct measure of functional connectivity. Kenny et al. (16). have also emphasized that affective disorders are more likely due to aberrations at the circuit level rather than at a localized brain region. Homotopic resting-state functional connectivity is one of the most salient characteristics of the brain’s intrinsic functional architecture (17), likely reflecting the importance of interhemispheric communication to integrated brain function underlying coherent cognition and behaviour (18). It demonstrates the high degree of synchrony in spontaneous activity between homotopic (geometrically corresponding) regions in each hemisphere (17, 19). Voxel-mirrored homotopic connectivity (VMHC) is a novel approach which quantifies functional homotopy by providing a voxelwise measure of connectivity between hemispheres (20). This method measures the resting-state functional connectivity between each voxel in one hemisphere and its mirrored counterpart in the opposite hemisphere. Recent work has demonstrated that VMHC is a reliable and reproducible rs-fMRI metric (21). Using VMHC analysis, several studies have revealed aberrant interhemispheric functional connectivity in neuropsychiatric disorders, such as schizophrenia (22, 23), cocaine addiction (18), and migraine (24). Some recent studies found that VMHC decreased in some brain regions in major depressive disorder (MDD) (25–28). Although these findings were not exactly consistent, suggested functional coordination between homotopic brain regions impaired in MDD. These studies demonstrated the feasibility of using VMHC as an interhemispheric interaction index to show group differences between healthy controls and a number of different clinical populations. However, there are no studies to investigate possible impairment of homotopic resting-state functional connectivity in patients with BD. Additionally, sample populations such as psychotropic medication, types of BD, different mood state (manic, depressed, mixed, or euthymic phase), and the history of psychosis may have contributed to discrepant results of structural and/or functional neuroimaging. A recent systematic review of 8 rs-fMRI studies in BD suggested that the effect of psychotropic medication is an important source of possible bias in the final results of functional neuroimaging (15). Therefore, to better understand the brain primary functional changes in patients with BD, these confounding variables need to be controlled in research. In addition, most neuroimaging studies have involved bipolar I samples, but comparatively few studies have focused on bipolar II disorder. 401
Wang et al. Aims of the study
In the current study, we collected rs-fMRI data from patients with unmedicated BD II depression and healthy controls and compared interhemispheric resting-state functional connectivity using a VMHC analysis. We hypothesized that patients with BD II might show reduced VMHC values compared with controls, which would suggest an impairment of interhemispheric functional coordination. We believe such data will contribute to our improved understanding of the pathophysiology of BD.
Material and methods Subjects
In total, 30 right-handed, out- or in-patients with BD II were recruited from the psychiatry department of First Affiliated Hospital of Jinan University, Guangzhou, China. The patients were aged from 18 to 55 years. All patients met DSM-IV criteria for bipolar II disorder according to the diagnostic assessment by the Structured Clinical Interview for DSM-IV Patient Edition (SCID-P). Exclusion criteria included the presence of (i) any current psychiatric disorder (with the exception of BD and anxiety disorders), (ii) a history of electroconvulsive therapy, (iii) any history of moderate/ severe head injury, head trauma, neurological disorder, or mental retardation, (iv) alcohol/substance abuse or dependence, (v) the presence of a concurrent significant physical illness, and (vi) pregnancy or any contraindication to MRI scanning. Clinical state was assessed using the 24-item Hamilton Depression Rating Scale (HDRS) and the Young Mania Rating Scale (YMRS) during the 7-day period prior to the imaging session. All patients with BD were suffering from depression (HDRS-24 score ≥ 18). At the time of testing, all patients were either medication-na€ıve or were unmedicated for at least 5 months. A total of 41 right-handed healthy control subjects were recruited via local advertisements. They were carefully screened through a diagnostic interview, the Structured Clinical Interview for DSMIV Nonpatient Edition (SCID-NP), to rule out the presence of current or past psychiatric illness. Further exclusion criteria for healthy controls were any history of psychiatric illness in first-degree relatives, current or past significant medical or neurological illness. The study was approved by the Ethics Committee of First Affiliated Hospital of Jinan University, China. All subjects signed a written informed 402
consent form after a full written and verbal explanation of the study. Two senior clinical psychiatrists confirmed that all subjects had the ability to consent to participate in the examination. MRI data acquisition and preprocessing
MRI data were acquired on a 3.0 T MR system (Discovery MR 750 System, GE Healthcare, Milwaukee, WI) with an 8-channel phased array head coil. Subjects were scanned in a supine, head-first position with symmetrically placed cushions on both sides of the head to decrease motion. During the scanning, participants were instructed to relax with their eyes closed without falling asleep; after the experiment, each participant confirmed not having fallen asleep. The rs-fMRI data were acquired using gradientecho echo-planar imaging sequence with the following parameters: time repetition (TR)/time echo (TE) = 2000/25 ms, slice thickness/gap = 3.0/ 1.0 mm, voxel size = 3.75 9 3.75 9 3 mm3, field of view (FOV) = 240 9 240 mm, flip angle = 90°, matrix = 64 9 64, number of slices = 35, and NEX = 1. A 7-min scan (210 volumes) was obtained for each subject. In addition, a threedimensional brain volume imaging (3D-BRAVO) sequence covering the whole brain was used for structural data acquisition with: TR/TE = 8.2/ 3.2 ms, slice thickness/gap = 1.0/0 mm, matrix = 256 9 256, FOV = 240 9 240 mm, NEX = 1, flip angle = 12o, bandwidth = 31.25 Hz, and acquisition time = 3 min 45 s. Routine MRI examination images were also collected for excluding anatomic abnormality, such as T1, T2, DWI, and T2FLAIR images. All participants were found by two experienced radiologists to have no abnormalities on routine MRI. Functional image preprocessing
The preprocessing was carried out using Data Processing Assistant for Resting-State fMRI (DPARSF) (29) which is based on Statistical Parametric Mapping (SPM8, http://www.fil.ion.ucl. ac.uk/spm) and rs-fMRI Data Analysis Toolkit (REST, http://www.restfmri.net) (30). For each individual, the first 10 images were discarded to ensure steady-state longitudinal magnetization. The remaining images were slice-time corrected and realigned to the first image in the first series. All subjects should have no more than 1 mm maximum displacement in x, y, or z and 1° of angular motion. The individual T1 images were coregistered to functional images. The coregistered T1 structural images were segmented (gray matter,
Homotopic connection in bipolar disorder white matter, and cerebrospinal fluid) using the unified segmentation algorithm and were then transformed into standard Montreal Neurological Institute (MNI) space. The functional images were also spatially normalized to MNI space by applying the parameters of structural image normalization and were resampled to 3 9 393 mm3 resolution. The generated images were spatially smoothed with a Gaussian kernel of 6 mm at fullwidth at half-maximum. Subsequently, the data were removed linear trend and band-pass filtered (0.01–0.08 Hz). Several sources of spurious covariates and their temporal derivatives were then removed using linear regression, including the six head motion parameters obtained by rigid body correction, global mean, white matter, and cerebrospinal fluid. Then, the images of each subject were registered to a symmetrical MNI template and were used to compute the homotopic functional connectivity. Voxel-mirrored homotopic connectivity
framewise displacement (FD) values for each subject. The mean FD was applied as a covariate in the group comparisons of VMHC. Once significant group differences were observed in any brain regions, we further computed Pearson’s correlation coefficients between these VMHC values and the clinical severity of BD symptoms.
Results Sample characteristics
Table 1 shows the demographic and clinical data of all study participants. Four patients with BD and one normal control were excluded from further analyses due to excessive head motion during the image acquisition. Finally, the participants included 26 patients with bipolar II depression and 40 healthy control subjects. There were no significant differences in sex, age, years of education, and FD parameter between the BD II group and the healthy control group.
VMHC analysis was performed using DPARSF software. For each subject, the homotopic restingstate functional connectivity was computed as the Pearson correlation (Fisher Z-transformed) between each voxel’s residual time series and that of its mirrored interhemispheric counterpart. The resultant values generated the VMHC maps and were used for subsequent group-level analyses. We also calculated the global VMHC for each subject and compared it between groups. Global VMHC was calculated by averaging VMHC values across all brain voxels.
Although the control and bipolar II depression groups did not differ on the global VMHC (control subjects = 0.59 0.07; patients = 0.57 0.08; t = 1.45, P = 0.151), the patient group showed lower VMHC values than the control group in the medial prefrontal cortex (mPFC) and inferior temporal gyrus (ITG) (Fig. 1, Table 2). No region showed greater VMHC in the patient group than in the control group. There were no significant correlations between the VMHC values in these
Statistical analysis
Table 1. Demographic and clinical data and (standard deviations) by group
Independent-sample t-tests and chi-squared tests were used to compare demographic data between the BD and HC groups with SPSS 17.0 software (SPSS, Chicago, IL, USA). All tests were twotailed, and P < 0.05 was considered statistically significant. The two-sample t-test was performed to determine the significant differences in VMHC between patients with BD and controls. The statistical threshold was set at corrected P < 0.05 (combination of P < 0.01 for single voxel and a minimum cluster volume >918 mm3), which was determined by Monte Carlo simulations using the AFNI AlphaSim program (http://afni.nimh.nih.gov/pub/dist/doc/manual/AlphaSim.pdf). Individual’s age and gender were included as nuisance covariates. In addition, because micromotions from volume to volume can influence resting-state functional connectivity results, we computed
VMHC: group differences
Number of subjects Age (years) Gender (male/female) Education (years) Age at onset (years) Number of episodes 24-item HDRS score (points) 24-item HDRS score range (points) YMRS score (points) YMRS score range (points) Duration of illness (months) Duration of illness range (months) FD values (mm)
Bipolar II disorder
Control
26 26.12 (10.30) 15/11 14.64 (5.86) 22.40 (10.34) 2.12 (1.51) 28.08 (5.62) 19–38 2.05 (1.66) 0–5 31.24 (7.61) 1–72 0.08 (0.04)
40 28.97 (9.17) 22/18 15.56 (2.44) n/a n/a n/a
P value
0.317* 0.830† 0.428*
n/a n/a 0.08 (0.03)
0.501*
Means (with standard deviations in parentheses) are reported unless otherwise noted. HDRS, Hamilton Depression Rating Scale; YMRS, Young Mania Rating Scale; FD, framewise displacement for in-scanner head motion. *The P values were obtained by independent-sample t-tests. †The P value for gender distribution was obtained by chi-square test.
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Fig. 1. Axial MR images show significant differences in VMHC between patients with BD and healthy controls. Blue colors indicate reduced VMHC in BD, and the color bar indicates the T value from t-test between groups. Table 2. The areas of VMHC differences between patients with BD and normal controls Montreal Neurological Institute Coordinates Brain regions Medial Prefrontal Cortex Inferior Temporal Gyrus
Peak t Value
Cluster Size (mm3)
Brodman Area
X
10
3
63
9
3.70
1134
20
57
18
33
4.10
972
Y
Z
VMHC, voxel-mirrored homotopic connectivity.
regions and any clinical measure (including HDRS, YMRS scores, and disease duration). Discussion
The main finding of this study was the significant decrease in the homologous resting-state functional connectivity of the mPFC and ITG in patients with unmedicated bipolar II depression. To our best knowledge, this is the first study to directly evaluate altered interhemispheric functional connectivity in patients with BD, using a VMHC method based on the rs-fMRI data. The mPFC is widely connected to subcortical and limbic areas, suggesting its import to emotional regulation processes and in affective symptoms of BD (31). Moreover, the mPFC is also a core hub of the default mode network (DMN), which is typically more active during rest than during the performance of sensorimotor or cognitive tasks, and is thought to mediate internal mental activity and self-reflection (32). In this study, we found decreased VMHC of the mPFC in patients with bipolar II depression compared with the control subjects, suggesting impaired functional connectivity between the bilateral mPFC. Moreover, these findings further support the issue that the DMN dysconnectivity is important in the 404
pathogenesis of BD. With the same VMHC approach, recent two studies found that patients with first-episode, drug-naive MDD showed decreased VMHC in mPFC (25, 27). Moreover, Guo et al. (25) found significant positive correlation between VMHC in mPFC and persistent error response of Wisconsin Card Sorting Test in patients with MDD. Unfortunately, we did not find a significant correlation between the VMHC values and HDRS or YMRS. Previous studies also demonstrated structure and function of the mPFC were abnormal in BD, such as decreased gray matter volume (33, 34) and decreased activity (35). Particularly, some fMRI studies reported abnormal mPFC -limbic connectivity in BD (15), which might partly contribute to the emotional and cognitive symptoms seen in patients with BD. A recent DTI study found white matter microstructure differences (decreased FA) in the anterior genu of the CC in young people with BD (36), supporting our finding of disturbed functional coordination between the left and right mPFC in BD. Postmortem studies found reduced neuronal size, neuronal density, and glial cell density in the mPFC in BD, which suggested the presence of dendritic atrophy of neurons and the loss of oligodendroglial cells (37). Taken together, the present decreased VMHC in the mPFC provides novel evidence for functional and structural damage to the mPFC in BD II and therefore may be a key neurobiological feature of BD. The temporal cortex is involved in the processing of auditory information, language comprehension, semantic memory, visual perception, and multimodal sensory integration (38). In patients with BD II, the decreased VMHC was also found in the ITG, which suggests impaired interhemispheric functional connectivity, especially in long-range connections. However, the ITG has received little attention in structural and functional
Homotopic connection in bipolar disorder neuroimaging studies of BD. A recent study of structural MRI found reduced cortical thickness in the left superior, middle, and ITG in patients with BD II (39). Meanwhile, a task-based fMRI study reported that patients with BD showed decreases in the ITG activation during visuospatial processing (40). Some studies also reported gray matter losses in the bilateral ITG in both patients with schizophrenia (38) and their non-psychotic siblings (41), suggesting the ITG played important roles in the pathophysiology of schizophrenia. Additionally, the ITG is been found to be involved in visual working memory maintenance and associative long-term memory retrieval (42, 43). Thus, combined with our results suggests that the decreased VMHC values in ITG could be associated with deficits in cognitive function of BD, particularly in complex visual perception. Future studies should address interhemispheric synchronization deficits relative to specific aspects of cognitive dysfunction. Some possible biological mechanisms may underlie the VMHC alteration in BD II. Altered brain structures, including widespread white matter integrity, local gray matter volume, and cortical thickness, might disrupt the functional synchrony between homotopic regions. Particularly, impairment in white matter connectivity of the CC could disrupt functional integration and coordination because neural signals are not transmitted from one hemisphere to another. The disruptions of functional integration are associated with abnormal myelination, axonal density, axonal caliber, and fiber coherence. However, direct structural connectivity does not appear to be a strict determinant of the functional connectivity in healthy brains. The rs-fMRI studies of split-brain patients found that a normal complement of resting-state networks and intact functional coupling between bilateral hemispheres can emerge in the absence of the CC (44). These findings suggest that interhemispheric functional connectivity may thus arise from common subcortical drivers, or complex network-level synchronization, neither of which requires direct structural connectivity between cortical components. Therefore, combination of the functional and structural information would help elucidating the mechanism underlying the VMHC deficits in BD. Another possible factor underlying abnormal functional homotopy in BD II is asymmetry of hemispheric growth. The two hemispheres may show subtle differences or delays in the trajectory of growth (23). The strengths of the study include the homogeneous samples of unmedicated depressive patients with BD II. However, some potential limitations
of the present study should be taken into consideration. First, the human brain is not symmetrical. However, we applied a symmetrical template and smoothed the functional data to improve the functional correspondence between homotopic regions. Kelly et al. (18) found morphometric asymmetry could not account for altered VMHC, but the effects of methodological symmetry could not be completely eliminated. Thus, future research such as voxel-based morphometry and DTI is necessary to identify the unknown structural basis for VMHC alterations. Second, the sample size of this study was relatively small, and results will require replication in a larger study. Third, without a group of patients with BD in a euthymic episode, it is still not clear whether VMHC deficits are specific to the depression episode of BD or shared by all episodes of the disease. Further studies using a prospective design may clarify this issue. Finally, we did not collect neuropsychological data, especially tasks that required interhemispheric transfer of information. Thus, additional neuropsychological tests are needed, and we will investigate the associations between cognitive dysfunction and VMHC deficits in further work. In conclusion, the present findings are the first to reveal aberrant interhemispheric functional connectivity in the bilateral mPFC and IPG in patients with bipolar II depression. Our results suggest that disruption in functional coordination between the two hemispheres may be a key neurobiological feature of BD II. Homotopic interhemispheric resting-state functional connectivity may provide a useful and sensitive screening approach for evaluating BD where neural connectivity is implicated in the pathophysiology. Acknowledgements We would like to thank all the participants for their contribution to this study. This work was supported by the National Science Foundation of China (81471650), Natural Science Foundation of Guangdong Province, China (2014A030313 375), Planned Science and Technology Project of Guangdong Province, China (2013B021800160), Fundamental Research Funds for the Central Universities (21615476), Humanity and Social Science Foundation of Ministry of Education of China (13YJA190008). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Declarations of interest The other authors declare no conflict of interests.
References 1. Merikangas KR, Akiskal HS, Angst J et al. Lifetime and 12-month prevalence of bipolar spectrum disorder in the
405
Wang et al.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
406
National Comorbidity Survey replication. Arch Gen Psychiatry 2007;64:543–552. Prieto ML, Cuellar-Barboza AB, Bobo WV et al. Risk of myocardial infarction and stroke in bipolar disorder: a systematic review and exploratory meta-analysis. Acta Psychiatr Scand 2014;130:342–353. Marlinge E, Bellivier F, Houenou J. White matter alterations in bipolar disorder: potential for drug discovery and development. Bipolar Disord 2014;16:97–112. Siffredi V, Anderson V, Leventer RJ, Spencer-Smith MM. Neuropsychological profile of agenesis of the corpus callosum: a systematic review. Dev Neuropsychol 2013;38: 36–57. Brambilla P, Nicoletti M, Sassi RB et al. Corpus callosum signal intensity in patients with bipolar and unipolar disorder. J Neurol Neurosurg Psychiatry 2004;75:221–225. Caetano SC, Silveira CM, Kaur S et al. Abnormal corpus callosum myelination in pediatric bipolar patients. J Affect Disord 2008;108:297–301. Emsell L, Leemans A, Langan C et al. Limbic and callosal white matter changes in euthymic bipolar I disorder: an advanced diffusion magnetic resonance imaging tractography study. Biol Psychiatry 2013;73:194–201. Sarrazin S, Poupon C, Linke J et al. A multicenter tractography study of deep white matter tracts in bipolar I disorder: psychotic features and interhemispheric disconnectivity. JAMA Psychiatry 2014;71:388–396. Wang F, Kalmar JH, Edmiston E et al. Abnormal corpus callosum integrity in bipolar disorder: a diffusion tensor imaging study. Biol Psychiatry 2008;64:730–733. Leow A, Ajilore O, Zhan L et al. Impaired inter-hemispheric integration in bipolar disorder revealed with brain network analyses. Biol Psychiatry 2013;73:183–193. Bjork MH, Sand T, Brathen G et al. Quantitative EEG findings in patients with acute, brief depression combined with other fluctuating psychiatric symptoms: a controlled study from an acute psychiatric department. BMC Psychiatry 2008;8:89. Bearden CE, Hoffman KM, Cannon TD. The neuropsychology and neuroanatomy of bipolar affective disorder: a critical review. Bipolar Disord 2001;3:106–150 discussion 151–153. Caligiuri MP, Brown GG, Meloy MJ et al. A functional magnetic resonance imaging study of cortical asymmetry in bipolar disorder. Bipolar Disord 2004;6:183–196. 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. Vargas C, Lopez-Jaramillo C, Vieta E. A systematic literature review of resting state network–functional MRI in bipolar disorder. J Affect Disord 2013;150:727–735. Kenny ER, O’Brien JT, Cousins DA et al. Functional connectivity in late-life depression using resting-state functional magnetic resonance imaging. Am J Geriatr Psychiatry 2010;18:643–651. Stark DE, Margulies DS, Shehzad ZE et al. Regional variation in interhemispheric coordination of intrinsic hemodynamic fluctuations. J Neurosci 2008;28:13754–13764. Kelly C, Zuo XN, Gotimer K et al. Reduced interhemispheric resting state functional connectivity in cocaine addiction. Biol Psychiatry 2011;69:684–692. Salvador R, Suckling J, Coleman MR et al. Neurophysiological architecture of functional magnetic resonance images of human brain. Cereb Cortex 2005;15:1332–1342. Zuo XN, Kelly C, Di Martino A et al. Growing together and growing apart: regional and sex differences in the
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
lifespan developmental trajectories of functional homotopy. J Neurosci 2010;30:15034–15043. Zuo XN, Xing XX. Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: a systems neuroscience perspective. Neurosci Biobehav Rev 2014;45:100–118. Hoptman MJ, Zuo XN, D’Angelo D et al. Decreased interhemispheric coordination in schizophrenia: a resting state fMRI study. Schizophr Res 2012;141:1–7. Li HJ, Xu Y, Zhang KR, Hoptman MJ, Zuo XN. Homotopic connectivity in drug-naive, first-episode, early-onset schizophrenia. J Child Psychol Psychiatry 2015;56:432– 443. Yuan K, Qin W, Liu P et al. Reduced fractional anisotropy of corpus callosum modulates inter-hemispheric resting state functional connectivity in migraine patients without aura. PLoS ONE 2012;7:e45476. Guo W, Liu F, Dai Y et al. Decreased interhemispheric resting-state functional connectivity in first-episode, drugnaive major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2013;41:24–29. Guo W, Liu F, Xue Z et al. Decreased interhemispheric coordination in treatment-resistant depression: a restingstate fMRI study. PLoS ONE 2013;8:e71368. Lai CH, Wu YT. Decreased inter-hemispheric connectivity in anterior sub-network of default mode network and cerebellum: significant findings in major depressive disorder. Int J Neuropsychopharmacol 2014;13:1–8. Wang L, Li K, Zhang QE et al. Interhemispheric functional connectivity and its relationships with clinical characteristics in major depressive disorder: a resting state fMRI study. PLoS ONE 2013;8:e60191. Chao-Gan Y, Yu-Feng Z. DPARSF: A MATLAB toolbox for “Pipeline” data analysis of resting-state fMRI. Front Syst Neurosci 2010;4:13. Song XW, Dong ZY, Long XY et al. REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PLoS ONE 2011;6:e25031. Favre P, Baciu M, Pichat C et al. fMRI evidence for abnormal resting-state functional connectivity in euthymic bipolar patients. J Affect Disord 2014;165:182–189. 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. Lijffijt M, Rourke ED, Swann AC et al. Illness-course modulates suicidality-related prefrontal gray matter reduction in women with bipolar disorder. Acta Psychiatr Scand 2014;130:374–387. Selvaraj S, Arnone D, Job D et al. Grey matter differences in bipolar disorder: a meta-analysis of voxel-based morphometry studies. Bipolar Disord 2012;14:135– 145. Keener MT, Phillips ML. Neuroimaging in bipolar disorder: a critical review of current findings. Curr Psychiatry Rep 2007;9:512–520. Lagopoulos J, Hermens DF, Hatton SN et al. Microstructural white matter changes in the corpus callosum of young people with Bipolar Disorder: a diffusion tensor imaging study. PLoS ONE 2013;8:e59108. Savitz JB, Price JL, Drevets WC. Neuropathological and neuromorphometric abnormalities in bipolar disorder: view from the medial prefrontal cortical network. Neurosci Biobehav Rev 2014;42:132–147. Onitsuka T, Shenton ME, Salisbury DF et al. Middle and inferior temporal gyrus gray matter volume abnormalities in chronic schizophrenia: an MRI study. Am J Psychiatry 2004;161:1603–1611.
Homotopic connection in bipolar disorder 39. Elvsashagen T, Westlye LT, Boen E et al. Bipolar II disorder is associated with thinning of prefrontal and temporal cortices involved in affect regulation. Bipolar Disord 2013;15:855–864. 40. Singh MK, Chang KD, Kelley RG et al. Reward processing in adolescents with bipolar I disorder. J Am Acad Child Adolesc Psychiatry 2013;52:68–83. 41. Gogtay N, Greenstein D, Lenane M et al. Cortical brain development in nonpsychotic siblings of patients with childhood-onset schizophrenia. Arch Gen Psychiatry 2007;64:772–780.
42. Ranganath C. Working memory for visual objects: complementary roles of inferior temporal, medial temporal, and prefrontal cortex. Neuroscience 2006;139:277–289. 43. Ranganath C, Cohen MX, Dam C, D’Esposito M. Inferior temporal, prefrontal, and hippocampal contributions to visual working memory maintenance and associative memory retrieval. J Neurosci 2004;24:3917–3925. 44. Tyszka JM, Kennedy DP, Adolphs R, Paul LK. Intact bilateral resting-state networks in the absence of the corpus callosum. J Neurosci 2011;31:15154–15162.
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