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1Resting-state functional connectivity of the vermal and hemispheric subregions of

2the cerebellum with both the cerebral cortical networks and subcortical structures

3LiQ1 Sang

a,1

, Wen Qin

a,1

, Yong Liu

, Wei Han

, Yunting Zhang

, Tianzi Jiang

⁎, Chunshui Yu

a,c,

⁎⁎

Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China

LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

School of Medical Imaging, Tianjin Medical University, Tianjin 300052, China

abstractarticle info

9Article history:

10 Accepted 6 April 2012

11 Available online xxxx

1213

15 Keywords:

16 Cerebellum

17 Subregions

18 Functional connectivity

19 Resting-state

20 Magnetic resonance imaging

21The human cerebellum is a heterogeneous structure, and the pattern of resting-state functional connectivity

22(rsFC) of each subregion has not yet been fully characterized. We aimed to systematically investigate rsFC

23pattern of each cerebellar subregion in 228 healthy young adults. Voxel-based analysis revealed that several

24subregions showed similar rsFC patterns, reﬂecting functional integration; however, different subregions dis-

25played distinct rsFC patterns, representing functional segregation. The same vermal and hemispheric subre-

26gions showed either different patterns or different strengths of rsFCs with the cerebrum, and different

27subregions of lobules VII and VIII displayed different rsFC patterns. Region of interest (ROI)-based analyses

28also conﬁrmed these ﬁndings. Speciﬁcally, strong rsFCs were found: between lobules I–VI and vermal VIIb–

29IX and the visual network; between hemispheric VI, VIIb, VIIIa and the auditory network; between lobules

30I–VI, VIII and the sensorimotor network; between lobule IX, vermal VIIIb and the default-mode network; be-

31tween lobule Crus I, hemispheric Crus II and the fronto-parietal network; between hemispheric VIIb, VIII and

32the task-positive network; between hemispheric VI, VIIb, VIII and the salience network; between most cere-

33bellar subregions and the thalamus; between lobules V, VIIb and the midbrain red nucleus; between hemi-

34spheric Crus I, Crus II, vermal VIIIb, IX and the caudate nucleus; between lobules V, VI, VIIb, VIIIa and the

35pallidum and putamen; and between lobules I–V, hemispheric VIII, IX and the hippocampus and amygdala.

36These results conﬁrm the existence of both functional integration and segregation among cerebellar subre-

37gions and largely improve our understanding of the functional organization of the human cerebellum.

3940

43 Introduction

44 The human cerebellum is thought to be a heterogeneous struc-

45 ture consisting of the vermis and two hemispheres, and it has been

46 anatomically divided into lobules designated I–X(Schmahmann

47 et al., 1999). Traditionally, the cerebellum has been regarded as a

48 part of the motor system, serving motor-related functions such as

49 posture maintenance (Ouchi et al., 1999, 2001) and motor control

50 (Kasahara et al., 2010; Spencer et al., 2007). Recently, evidence

51 from neuroimaging and clinical studies has supported the idea that

52 the cerebellum is also involved in cognitive (Kirschen et al., 2008;

53 Marien et al., 2001) and emotional functions (Gundel et al., 2003;

54 Scheuerecker et al., 2007).

55Most of our knowledge about the functions of cerebellar subre-

56gions comes from task-based neuroimaging studies. For example, in

57the cerebellar vermis, lobules I–V are involved in motor-related pro-

58cessing (Brown et al., 2006; Debaere et al., 2001; Ouchi et al., 1999,

592001); lobules VI and VII participate in controlling eye movements

60(Jenkinson and Miall, 2010); lobules III–V and VIII are activated dur-

61ing pain-related processes (Dimitrova et al., 2003, 2004; Maschke

62et al., 2002); and lobules IX–X are involved in spatial orientation

63and balance (Walker et al., 2010; Yakusheva et al., 2008). In the

64cerebellar hemispheres, sensorimotor function is represented in

65lobules I–V(Grodd et al., 2001; Salmi et al., 2010) and occasionally

66in lobules VI and VIII (Stoodley and Schmahmann, 2009, 2010); cog-

67nitive processing is subserved by lobules VI–VIII (Stoodley and

68Schmahmann, 2009, 2010); lobule IX is found to be activated during

69the experiences of thirst (Parsons et al., 2000) and the sensation of

70acupuncture stimulation (Hui et al., 2005); and lobule X contributes

71to controlling gaze and balance (Shaikh et al., 2011).

72However, task-based studies can only reveal a subset of regions in

73a functional network (Finn et al., 2010; Jenkins and Ranganath, 2010).

74For example, a working memory task can only activate a subset of

75brain regions of the memory network, while an episodic memory

NeuroImage xxx (2012) xxx–xxx

⁎Correspondence to: T. Jiang, LIAMA Center for Computational Medicine, National

Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences,

Beijing 100190, China. Fax: +86 10 6255 1993.

⁎⁎ Correspondence to: C. Yu, Department of Radiology, Tianjin Medical University

General Hospital, No. 154, Anshan Road, Heping District, Tianjin 300052, China.

Fax: +86 22 63062290.

E-mail addresses: jiangtz@nlpr.ia.ac.cn (T. Jiang), chunshuiyu@yahoo.cn (C. Yu).

These authors contributed equally to this work.

YNIMG-09398; No. of pages: 14; 4C:

doi:10.1016/j.neuroimage.2012.04.011

Contents lists available at SciVerse ScienceDirect

NeuroImage

journal homepage: www.elsevier.com/locate/ynimg

Please cite this article as: Sang, L., et al., Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum

with both the cerebral cortical networks and subcortical structures, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.04.011

UNCORRECTED PROOF

76 task can activate another subset of brain regions of the memory net-

77 work. Recently, resting-state functional connectivity (rsFC) analysis, a

78 technique with the potential to capture the full distribution of regions

79 belonging to a functional network, has been used to parcellate hetero-

80 geneous brain structures (Anwander et al., 2007; Deen et al., 2011)

81 and to investigate speciﬁc rsFC patterns of each subregion (Margulies

82 et al., 2009; Yu et al., 2011; Zhang and Li, 2012). These ﬁndings have

83 greatly improved our understanding of the functional organization of

84 certain brain structures.

85 rsFC analysis has made important contributions to the understand-

86 ing of neural circuitry, including: revealing strong rsFCs between the

87 dentate nucleus and the parietal and prefrontal cortices (Allen et al.,

88 2005); identifying 4 topographically distinct fronto-cerebellar circuits

89 (Krienen and Buckner, 2009); subdividing the cerebellum into a primary

90 sensorimotor zone and a supramodal zone (O'Reilly et al., 2010); catego-

91 rizing cerebellar subregions into different functional networks (Habas

92 et al., 2009); and mapping the organization of cerebro-cerebellar circuits

93 (Buckner et al., 2011). However, several questions regarding rsFC pat-

94 terns of cerebellar subregions have not yet been addressed: (1) What

95 are the rsFC patterns of the vermal subregions? (2) Do the rsFC patterns

96 differ among vermal, paravermal, and lateral hemispheric subregions?

97 (3) What are the rsFCs of cerebellar subregions with the intrinsic con-

98 nectivity networks (ICNs) and deep subcortical nuclei?

99 In the present study, we aimed to address these questions by an-

100 alyzing resting-state functional magnetic resonance imaging (fMRI)

101 data in 228 healthy young adults. We ﬁrst compared rsFCs between

102 paravermal and lateral hemispheric subregions (lobules VI, Crus I

103 and Crus II) with large horizontal diameters and found subtle differ-

104 ences. We therefore deﬁned lateral hemispheric subregions as re-

105 gions of interest (ROIs) of the cerebellar hemisphere. We then

106 analyzed rsFC patterns of 10 vermal subregions and compared them

107 with corresponding hemispheric ROIs using voxel-based rsFC analy-

108 sis. Finally, we used ROI-based rsFC analysis to investigate rsFCs of

109 cerebellar subregions with the 9 ICNs and several deep subcortical

110 nuclei.

111 Subjects and methods

112 Subjects

113 A total of 228 healthy young adults (126 females and 102 males;

114 mean age 22.9±2.3 years) were selected from 324 subjects who

115 participated in an imaging genetic study. All subjects were right-

116 handed (Oldﬁeld, 1971) native Chinese speakers who did not suffer

117 from any neurologic or psychiatric illnesses or exhibit visible lesions

118 on conventional brain MR images. Each subject signed a written in-

119 formed consent form that was approved by the Medical Research

120 Ethics Committee of Tianjin Medical University. Ninety-six subjects

121 were excluded from further analysis by a series of screening steps

122 to avoid confounding factors. Speciﬁcally, 74 subjects were excluded

123 due to excessive head motion during the fMRI scan, 3 subjects were

124 excluded due to a lack of correspondence between cerebellar ROIs

125 and structural images of the cerebellum in individual space, and

126 19 subjects were excluded due to either visible deformation of the

127 cerebellum in fMRI images or lack of correspondence between cere-

128 bellar ROIs and functional images of the cerebellum.

129 MR image acquisition

130 MR images were acquired using a 3.0 Tesla MR scanner (Signa

131 Excite HDx; GE Healthcare, Milwaukee, WI). Tight but comfortable

132 foam padding was used to minimize head motion, and earplugs

133 were used to reduce scanner noise. Functional MR images were col-

134 lected using an echo-planar imaging (EPI) sequence with the fol-

135 lowing scan parameters: repetition time (TR)/echo time (TE) =

136 2000/30 ms; ﬁeld of view (FOV)=240 mm× 240 mm; matrix =

13764×64; ﬂip angle (FA)= 90°, slice thickness= 4 mm without gap;

13840 transversal slices; 180 volumes. During fMRI scans, all subjects

139were instructed to keep their eyes closed, to stay as motionless as

140possible, to think of nothing in particular and not to fall asleep. Sagittal

141T1-weighted images were acquired with a brain volume (BRAVO)

142sequence (TR/TE= 8.1/3.1 ms; inversion time=450 ms; FA=13°;

143FOV=256 mm×256 mm; matrix= 256×256; slice thickness=1 mm

144without gap; 176 sagittal slices).

145Data preprocessing

146Preprocessing was carried out using statistical parametric map-

147ping (SPM8, http://www.ﬁl.ion.ucl.ac.uk/spm). The ﬁrst 10 volumes

148of each functional time series were discarded to allow longitudinal

149magnetization to reach a steady state and to allow participants to

150acclimate to the scanning environment. The 170 remaining images

151were ﬁrst corrected for within-scan acquisition time differences

152between slices and realigned to the ﬁrst volume to correct for

153inter-scan movements. The realigned T1 images were spatially nor-

154malized using a uniﬁed segmentation approach that included the

155following steps: (i) individual structural images were coregistered

156to the mean functional image after motion correction; (ii) the trans-

157formed structural images were segmented into gray mater, white

158matter, and cerebrospinal ﬂuid using a uniﬁed segmentation algo-

159rithm; and (iii) the motion corrected functional volumes were spa-

160tially normalized to Montreal Neurological Institute (MNI) space

161using the normalized parameters estimated during segmentation,

162and functional images were then re-sampled into a voxel size of

1632-mm

. After normalization, images were smoothed using a Gauss-

164ian kernel of 4-mm

full-width at half maximum. We controlled

165for head motion using a threshold of 1.0 mm translation in any car-

166dinal direction and 1.0° rotation in each of the orthogonal x, y and z

167axes. Several sources of spurious variances including the estimated

168motion parameters, linear drift, global average Blood Oxygenation

169Level-Dependent (BOLD) signals, and average BOLD signals in ven-

170tricular and white matter regions were removed from the data

171through linear regression. Finally, temporal band-pass ﬁltering

172(0.01–0.08 Hz) was performed on the time series of each voxel to

173reduce the effects of low-frequency drift and high-frequency noise

174(Greicius et al., 2003).

175Deﬁnition of cerebellar ROIs

176Seed regions were deﬁned using the probabilistic MR Atlas of the

177human cerebellum (Diedrichsen, 2006; Diedrichsen et al., 2009).

178Modiﬁcations were performed in the deﬁnition of lobules I–IV and V

179because the probabilistic atlas integrated the vermis and hemispheres

180into a single subregion for these two lobules. We manually extracted

181the vermal and hemispheric subregions for lobules I–IV and V using

182the probabilistic MR Atlas and MRIcroN software (www.mricro.

183com). A total of 10 cerebellar subregions (lobules I–IV, V, VI, Crus I,

184Crus II, VIIb, VIIIa, VIIIb, IX, and X) were extracted and each subregion

185was further divided into vermal and hemispheric subdivisions

186(Fig. 1). After the 20 subdivisions were deﬁned, the tripartite division

187of the cerebellum (Luft et al., 1998) was used to subdivide the hemi-

188spheres into paravermal and lateral hemispheric subregions.

189To investigate whether the rsFC patterns were homogeneous

190along the horizontal axis, we divided hemispheric lobules VI, Crus I

191and Crus II into four equal parts along the horizontal axis. The reason

192for the selection of these hemispheric lobules was that their hori-

193zontal diameters were large enough to deﬁne 4 spherical ROIs

194(radius=3 mm) within each lobule. Each paravermal ROI was de-

195ﬁned as the medial quarter of the corresponding hemispheric lobule,

196and each lateral hemispheric ROI was deﬁned as the remaining lateral

197parts of the lobule (see Fig. S1 in Supplementary materials). We com-

198pared rsFC patterns between paravermal and lateral hemispheric

2L. Sang et al. / NeuroImage xxx (2012) xxx–xxx

Please cite this article as: Sang, L., et al., Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum

with both the cerebral cortical networks and subcortical structures, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.04.011

UNCORRECTED PROOF

199 ROIs for each of these three lobules and found that although rsFC

200 patterns were similar across the 4 ROIs, subtle differences existed be-

201 tween paravermal and lateral hemispheric ROIs (see Fig. S2 in Sup-

202 plementary materials). Therefore, we used the lateral three-quarters

203 of the hemispheric ROI for each hemispheric ROI (Fig. 1).

204 All seed ROIs were re-sampled into 2-mm

voxels. Each ROI was

205 projected onto the individual space using SUIT software (http://

206 www.icn.ucl.ac.uk/motorcontrol/imaging/suit.htm) to conﬁrm the

207 correspondence between the cerebellar ROIs and individual structural

208 images of the cerebellum.

209 Deﬁnition of ICNs

210 Group spatial ICA was conducted in the 228 participants using the

211 infomax algorithm (Bell and Sejnowski, 1995) implemented in MICA

212 software (http://www.nitrc.org/projects/cogicat/). Functional MRI

213 data were preprocessed using SPM5, including slice timing, head mo-

214 tion correction, spatial normalization and smoothing; and all subjects'

215 datasets were then temporally concatenated. Twenty independent

216 components were obtained from the multi-subject data. According

217 to the ICNs identiﬁed by Damoiseaux et al. (2006), we identiﬁed 9

218 ICA components to represent meaningful ICNs using a threshold of

219 t>12 and a cluster size of >200 voxels. A binary mask of each ICN

220was obtained by multiplying the corresponding ICA component and

221the cerebral mask which was created based on the automated ana-

222tomical labeling (AAL) Atlas (Tzourio-Mazoyer et al., 2002). The bina-

223ry masks were used as ROIs of these ICNs (Fig. 2).

224Deﬁnition of deep subcortical nuclei

225The masks of the thalamic subregions (primary motor, sensory,

226occipital, prefrontal, premotor, posterior parietal, temporal-connected

227thalamus), basal ganglia (caudate nucleus, putamen, and pallidum),

228hippocampus, and amygdala were created in MNI space using the

229Harvard–Oxford Subcortical Structural Atlas and Oxford Thalamic Con-

230nectivity Probability Atlas, which are available toolboxes in the FMRIB

231Software Library (FSL) (Oxford Centre of Functional MR imaging of

232the Brain, UK; http://www.fmrib.ox.ac.uk/fsl) (see Fig. S3 in Supple-

233mentary materials). The red nucleus was deﬁned as a spherical ROI

234(radius=3 mm) centered at the coordinate of (x=±6, y=−18, z=

235−10), which was determined by averaging the central coordinates of

236the red nucleus in MNI space in 20 randomly selected subjects. The den-

237tate nucleus was extracted using the MRI Atlas of the Human Cerebellar

238Nucleus (Dimitrova et al., 2002) and a spherical ROI (radius=3 mm)

239was centered at the coordinate of (x=±16, y =−58, z=−35) (see

240Fig. S3 in Supplementary materials).

Fig. 1. Locations of vermal and hemispheric ROIs of the cerebellum. ROIs are projected onto sagittal images from the Colin27 brain in different colors and are labeled with Roman

numerals. The notion “x=+2”denotes the x-axis coordinate in MNI space. Abbreviations: A, anterior; MNI, Montreal Neurological Institute; ROI, region of interest; P, posterior.

(For interpretation of the references to color in this ﬁgure legend, the reader is referred to the web version of this article.)

Fig. 2. Nine intrinsic connectivity networks derived from an independent component analysis with a threshold of t>12 and a cluster size of > 100 voxels. Abbreviations: ADMN,

anterior default-mode network; AN, auditory network; L, left; LFPN, left frontal–parietal network; PDMN, posterior default-mode network; R, right; RFPN, right frontal–parietal

network; SMN, sensorimotor network; SN, salience network; TPN, task-positive network; VN, visual network.

3L. Sang et al. / NeuroImage xxx (2012) xxx–xxx

Please cite this article as: Sang, L., et al., Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum

with both the cerebral cortical networks and subcortical structures, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.04.011

UNCORRECTED PROOF

241 Resting-state functional connectivity analysis

242 For each subject, correlation coefﬁcients between the mean time

243 series of each seed ROI and that of each voxel in the whole brain

244 were computed and converted to z-values using Fisher's r-to-ztrans-

245 formation to improve normality. Subsequently, individuals' z-values

246 were entered into a random-effect one-sample t-test in a voxel-wise

247 manner to identify brain regions that showed signiﬁcant positive or

248 negative correlations with the seed ROIs. To investigate rsFCs be-

249 tween cerebellar subregions and the cerebral cortex, we limited the

250 statistical analyses within a cerebral mask excluding the cerebellum

251 that was created based on the AAL Atlas (Tzourio-Mazoyer et al.,

252 2002). The signiﬁcant rsFC maps were corrected for multiple compar-

253 isons using the family-wise error (FWE, pb0.05) method with a clus-

254 ter size of >100 voxels. Only positive rsFCs were reported because

255 the debate on whether the negative rsFC is an artifact of global signal

256 regression (Murphy et al., 2009; Weissenbacher et al., 2009) or re-

257 ﬂects dynamic, anti-correlated functional networks (Hampson et al.,

258 2010) remains unsettled.

259 A one -sample t-test was also performed to investigate rsFC pat-

260 terns between each cerebellar ROI and each of the ICNs and deep sub-

261 cortical nuclei. The Bonferroni correction for multiple comparisons

262 was used in ROI-based rsFC analyses with a corrected threshold of

263 pb0.05. A paired-samples t-test was performed to quantitatively

264 compare differences in rsFCs between the vermal and hemispheric

265 ROIs and each subregion of lobules VII and VIII.

266 Results

267 Intrinsic connectivity networks

268 According to ICA, we extracted 9 meaningful ICNs (Fig. 2), which

269 is very similar to the results of previous studies (Damoiseaux et al.,

270 2006). These ICNs included the visual network (VN), auditory net-

271 work (AN), sensorimotor network (SMN), anterior default-mode

272 network (DMN), posterior DMN, left frontal–parietal network

273 (FPN) (Smith et al., 2009), right FPN, task-positive network (TPN)

274 (Veer et al., 2010), and salience network (SN) (Habas et al., 2009).

275 The VN is composed of the primary, secondary and high-level visual

276 cortices. The AN consists of the primary and secondary auditory cor-

277 tices and the superior temporal gyrus. The SMN extracted by ICA

278 represents the lateral part of the SMN and is mainly composed of

279 the precentral and postcentral gyri, premotor cortex, and a small

280 part of the supplementary motor area (SMA). The DMN includes

281 the medial prefrontal, lateral parietal, and precuneus/posterior cin-

282 gulate cortices. The FPN mainly includes the dorsolateral prefrontal

283 cortex and inferior parietal lobule. The TPN mainly consists of the

284 superior parietal and occipito-temporal cortices. The SN includes

285 the dorsal anterior cingulate and fronto-insular cortices.

286 Voxel-based rsFC analyses of vermal subregions

287 rsFC patterns of the vermal subregions are shown in Fig. 3.Lobules

288 I–V were similarly correlated with the VN, SMN, thalamus, amygdala,

289 and the hippocampal region. Lobule VI was also correlated with the

290 VN, SMN, thalamus, and the hippocampal region to a smaller spatial

291 extent. Crus I was correlated with the SMA, DMN, FPN, thalamus, cau-

292 date nucleus, and hippocampus. Crus II was correlated with the SMA,

293 thalamus, caudate nucleus, and hippocampus. Vermal VIIb showed

294 similar rsFC patterns with Crus II but had a larger spatial extent in

295 the VN, SMN, insula, thalamus, and basal ganglia. Vermal VIIIa showed

296 similar rsFC patterns with VIIb; however, vermal VIIIb showed similar

297 rsFC patterns with vermal IX, which were correlated with the VN,

298 DMN, FPN, thalamus, basal ganglia, hippocampus, and amygdala.

299 Vermal X was correlated with the SMA, DMN, and the hippocampal

300 region.

301Voxel-based rsFC analyses of hemispheric subregions

302rsFC patterns of the hemispheric subregions are shown in Fig. 4.

303Lobules I–V were similarly correlated with the VN, SMN, insula, thal-

304amus, amygdala, and the hippocampal region. Lobule VI was correlat-

305ed with the VN, AN, SMN, TPN, SN, thalamus, basal ganglia, amygdala,

306and the hippocampal region. rsFC maps of Crus I and Crus II were sim-

307ilar and mainly correlated with the SMN, DMN, FPN, thalamus, cau-

308date nucleus, and hippocampus. Lobules VIIb, VIIIa and VIIIb showed

309similar rsFC patterns but with different spatial extents, displaying

310correlations with the AN, SMN, FPN, TPN, SN, and thalamus. Lobule

311IX was correlated with the DMN, FPN, thalamus, and the hippocampal

312region. Lobule X was correlated with the SMN, prefrontal cortex, pa-

313rietal cortex, and the hippocampal region.

314Differences in rsFCs between vermal and hemispheric subregions

315Differences in rsFCs between the vermal and hemispheric subre-

316gions are shown in Fig. 5. Compared with the hemispheric subregions,

317vermal I–IV showed weaker correlations with the hippocampus and

318amygdala. Vermal V demonstrated weaker rsFCs with the SMN, pos-

319terior insula, hippocampus, and amygdala but stronger rsFCs with

320the SMA and thalamus. Vermal VI showed weaker rsFCs with the

321VN, AN, SMN, TPN, SN, and amygdala but stronger rsFCs with the

322SMA, DMN, thalamus, and hippocampus. Vermal and hemispheric

323Crus I displayed similar rsFC patterns but the former showed weaker

324rsFCs with the anterior DMN and left FPN. Vermal Crus II showed

325weaker rsFCs with the DMN, FPN, and caudate nucleus and a stronger

326rsFC with the thalamus. Vermal VIIb and VIIIa showed weaker rsFCs

327with the AN, SMN, FPN, TPN, SN and stronger rsFCs with the VN, thal-

328amus, hippocampus, and amygdala. Vermal and hemispheric VIIIb

329showed completely different rsFC patterns; the former was correlated

330with the VN, DMN, FPN, thalamus, basal ganglia, hippocampus, and

331amygdala, whereas the latter was correlated with the AN, SMN,

332TPN, and SN. Vermal IX showed weaker rsFCs with the prefrontal

333and parietal cortices and stronger rsFCs with the VN, DMN, left FPN,

334and amygdala. Similarly, vermal X displayed weaker rsFCs with the

335SMA, prefrontal, and parietal cortices.

336Differences in rsFC patterns between subregions within lobules VII

337and VIII

338Differences in rsFC patterns of subregions within lobules VII and

339VIII are shown in Fig. 6. In the vermal subregions of lobule VII, Crus I

340was the only subregion that was correlated with the DMN and FPN.

341Vermal VIIb was correlated with the lateral part of the SMN, and all

342three subregions were correlated with the SMA. Crus I showed the

343weakest and the VIIb showed the strongest rsFCs with the VN, AN,

344thalamus and basal ganglia. In the hemispheric subregions of lobule

345VII, Crus I and Crus II were similarly correlated with the DMN, FPN,

346and caudate nuclei. This pattern was completely different from that

347seen in VIIb, which showed correlations with the AN, SMN, TPN, SN,

348and thalamus. The most prominent difference in the rsFC patterns

349between vermal VIIIa and VIIIb was that the former was correlated

350with the SMN, but the latter was correlated with the DMN. How-

351ever, hemispheric VIIIa and VIIIb showed similar rsFC patterns but

352with different strengths.

353ROI-based rsFC analysis

354We extracted 9 ICNs and several subcortical nuclei to investigate

355rsFC patterns between these ROIs and cerebellar subregions (Fig. 7).

356Under a strict correction method (Bonferroni) for multiple compari-

357sons, the VN was correlated with lobules V and VI, and vermal I–IV,

358and VIIb–IX. The AN was correlated with vermal VIIb and hemispheric

359V, VI, VIIb, VIIIa, and VIIIb. The SMN was correlated with hemispheric

4L. Sang et al. / NeuroImage xxx (2012) xxx–xxx

Please cite this article as: Sang, L., et al., Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum

with both the cerebral cortical networks and subcortical structures, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.04.011

UNCORRECTED PROOF

360 VI, VIIb, and VIIIa. The anterior DMN was correlated with vermal Crus

361 I, VIIIb, and IX and hemispheric Crus I, Crus II, and IX. The posterior

362 DMN was correlated with vermal Crus I, VIIIb, and IX and hemispheric

363 IX. The FPN was correlated with hemispheric Crus I and Crus II. The

364 TPN was correlated with hemispheric VIIb, VIIIa, VIIIb, and X. The SN

365was correlated with hemispheric VIIb and VIIIa. The dentate nucleus

366was correlated with most of the cerebellar subregions except vermal

367Crus I. The thalamus was correlated with most of the cerebellar subre-

368gions except vermal X, and hemispheric VIIIa, VIIIb, and X. The red

369nucleus was correlated with vermal I–V, Crus II, VIIb, VIIIa, and VIIIb

Fig. 3. The rsFC maps of the vermal subregions using a signiﬁcance threshold of pb0.05 (FWE correction) and a cluster size of >100 voxels. Abbreviations: FWE, family-wise error;

L, left; R, right; rsFC, resting-state functional connectivity.

5L. Sang et al. / NeuroImage xxx (2012) xxx–xxx

Please cite this article as: Sang, L., et al., Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum

with both the cerebral cortical networks and subcortical structures, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.04.011

UNCORRECTED PROOF

370 and hemispheric V, VI, VIIb, and IX. The caudate nucleus was correlated

371 with vermal VI, Crus I, Crus II, VIIIa, VIIIb, and IX, and hemispheric Crus I

372 and Crus II. The pallidum was correlated with vermal I–VI, Crus II, VIIb,

373 and VIIIa and hemispheric V, VI, VIIb, and VIIIa. The putamen was corre-

374 lated with vermal V, VIIb, and VIIIa and hemispheric V, VI, VIIb, and VIIIa.

375 The hippocampus was correlated with vermal I–VI, Crus II–X, and

376hemispheric I–VI, Crus II, IX, and X. The amygdala was correlated with

377vermal I–V, VIIb, VIIIa, VIIIb, and IX, and hemispheric I–VI and VIIb. We

378also adopted three more liberal thresholds of pb0.001 (uncorrected),

379pb0.01 (uncorrected), and pb0.05 (uncorrected) to calculate the rsFC

380between cerebellar ROIs and ICNs. As lower pvalues were selected,

381more pairs of the weak rsFC were found (Fig. S4).

Fig. 4. The rsFC maps of hemispheric cerebellar subregions using a signiﬁcance threshold of pb0.05 (FWE correction) and a cluster size of >100 voxels. Abbreviations: FWE, family-

wise error; L, left; R, right; rsFC, resting-state functional connectivity.

6L. Sang et al. / NeuroImage xxx (2012) xxx–xxx

Please cite this article as: Sang, L., et al., Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum

with both the cerebral cortical networks and subcortical structures, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.04.011

UNCORRECTED PROOF

382 rsFC patterns between cerebellar and thalamic subregions

383 rsFCs between the cerebellar and thalamic subregions are shown

384 in Fig. 8. All of the thalamic subregions were connected with vermal

385I–VI, Crus II–IX, hemispheric I–V, and IX; however, none of the tha-

386lamic subregions were connected with hemispheric X. Vermal Crus I

387was only correlated with the temporal and prefrontal-connected thal-

388amus. Vermal X and hemispheric Crus I were only correlated with the

Fig. 5. Quantitative comparisons between rsFC maps of the vermal and hemispheric subregions using a paired t-test. FWE correction was used to account for multiple comparisons

(pb0.05; cluster size> 100 voxels). The warm color represents that the rsFCs in the vermal subregions are stronger than those in the hemispheric subregions. The cold color denotes

that the rsFCs in the vermal subregions are weaker than those observed in the hemispheric subregions. Abbreviations: FWE, family-wise error; L, left; R, right; rsFC, resting-state

functional connectivity. (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the web version of this article.)

7L. Sang et al. / NeuroImage xxx (2012) xxx–xxx

Please cite this article as: Sang, L., et al., Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum

with both the cerebral cortical networks and subcortical structures, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.04.011

UNCORRECTED PROOF

389 temporal-connected thalamus. Hemispheric VI and VIIb were corre-

390 lated with all of the thalamic subregions except for the temporal-

391 connected thalamus. Hemispheric Crus II was correlated with the

392 occipital, temporal, and prefrontal-connected thalamus. Hemispheric

393 VIIIa was correlated with the sensory, primary motor, premotor, and

394 posterior parietal-connected thalamus. Hemispheric VIIIb was cor-

395 related with the sensory and posterior parietal-connected thalamus.

396 The correspondence between the connectivity-based thalamic sub-

397 regions and the cytoarchitectonically deﬁned thalamic nuclei are

398 shown in the legend of Fig. S3 in Supplementary materials.

399 Discussion

400 In the present study, we systematically mapped rsFC patterns of

401 subregions of the human cerebellum. We found that rsFC patterns

402of vermal and hemispheric subregions were a reﬂection of both func-

403tional integration and segregation in the cerebellum. The functional

404integration is characterized by several subregions involved in the

405same functional network, whereas the functional segregation refers

406to different subregions involved in different functional networks.

407Cerebellum and SMN

408Consistent with previous ﬁndings, cerebellar lobules I–VI and VIII,

409particularly the hemispheric regions, were involved in the SMN. Ana-

410tomically, most of these subregions belong to the spinocerebellum,

411which receives afferents from the spinal cord and directs efferents

412mainly to the brainstem and motor cortex (Gomi and Kawato,

4131992). Animal studies indicate that the ventral and lateral spinocere-

414bellar tracts terminate in lobules II–VI (Furue et al., 2011). Converging

Fig. 6. Quantitative comparisons between rsFC maps within cerebellar lobules VII (Crus I, Crus II and VIIb) and VIII (VIIIa and VIIIb) using a paired t-test. FWE correction was used to

account for multiple comparisons (pb0.05; cluster size >100 voxels). A warm color represents that the rsFC of the former subregion is stronger than that of the latter subregion. A

cold color denotes that the rsFC of the former subregion is weaker than that of the latter subregion. Abbreviations: FWE, family-wise error; L, left; R, right; rsFC, resting-state func-

tional connectivity. (For interpretation of the references to color in this ﬁgure legend, the reader is referred to the web version of this article.)

8L. Sang et al. / NeuroImage xxx (2012) xxx–xxx

Please cite this article as: Sang, L., et al., Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum

with both the cerebral cortical networks and subcortical structures, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.04.011

UNCORRECTED PROOF

415 evidence from neuroimaging studies has revealed that the anterior

416 lobe (lobules I–V) and parts of the posterior lobe (lobules VI and

417 VIII) are sensorimotor components (Stoodley and Schmahmann,

418 2010). Lobule VII (Crus I, Crus II, and VIIb) has been shown to corre-

419 late with the SMA and parts of the lateral motor cortex, supporting

420 the idea that lobule VII is involved in complex movements (Schlerf

421 et al., 2010). These motor-related cerebellar subregions play an im-

422 portant role in maintaining upright posture (Ouchi et al., 1999,

423 2001) and in processing various dexterous motions, such as hand

424 movement (Chan et al., 2006; Nitschke et al., 2005) and ﬁnger

425 tapping (Aoki et al., 2005; Witt et al., 2008). A meta-analysis of func-

426 tional topography in the human cerebellum showed consistent acti-

427 vation in lobules V, VI and VIII during motor and somatosensory

428 tasks (Stoodley and Schmahmann, 2009). Additionally, patients

429 with lesions in these cerebellar subregions have been shown to dis-

430 play impairments in postural balance and gait (Ilg et al., 2008;

431 Konczak et al., 2005; Sullivan et al., 2010).

432 Cerebellum and VN and AN

433 We observed strong rsFCs between lobules I–VI, vermal VIIb–IX,

434 and the VN and between hemispheric VI, VIIb, VIIIa, and the AN.

435 These results are partially consistent with a previous rsFC study

436 (O'Reilly et al., 2010) and prior anatomical ﬁndings regarding the

437 visual and auditory cortico-cerebellar loops (Q2 Clarke, 1977; Pastor

438 et al., 2008; Sens and de Almeida, 2007). In these loops, visual or

439 auditory information can reach the cerebellum through the pontine

440 nuclei and return through the thalamus. The involvement of the

441 cerebellum in the processing of visual and auditory information

442 has been revealed in a plethora of previous neuroimaging studies

443 (Baumann and Mattingley, 2010; Pastor et al., 2008; Petacchi et al.,

444 2005), which suggests that the cerebellum plays a role in the integration

445of multi-modal sensory information (Gentile et al., 2011; Naumer et al.,

4462010) and sensorimotor information (Baumann and Greenlee, 2007;

447Bengtsson et al., 2009; Hagura et al., 2009). Such integration in the

448cerebellum is reﬂected in the ﬁnding that some cerebellar subregions

449(such as hemispheric VI) displayed strong rsFC with the visual-,

450auditory-, somatosensory-, and motor-related cerebral cortices. How-

451ever, these functional systems showed distinct rsFC patterns with

452other cerebellar subregions, which highlight the functional segregation

453of the cerebellum.

454Cerebellum and DMN

455Lobule IX and vermal VIIIb showed strong rsFCs with the DMN,

456which is consistent with previous rsFC studies (Habas et al., 2009;

457Krienen and Buckner, 2009; O'Reilly et al., 2010). The DMN has

458been suggested to play an important role in the sustenance of self-

459referential processing (Gusnard and Raichle, 2001), conscious aware-

460ness (Horovitz et al., 2009), mind wandering (Christoff et al., 2009),

461retrieval and manipulation of episodic memories and semantic

462knowledge (Greicius et al., 2003).

463Cerebellum and FPN

464Consistent with previous rsFC studies (Buckner et al., 2011; Habas

465et al., 2009; Krienen and Buckner, 2009; O'Reilly et al., 2010), we

466found that lobule Crus I and hemispheric Crus II were involved in

467the FPN, which is involved in memory, language, action control, and

468pain perception (Smith et al., 2009). As revealed by transneuronal

469tracing techniques, Crus I and Crus II have been found to show recip-

470rocal connections with the dorsolateral prefrontal cortex (Kelly and

471Strick, 2003). They are consistently activated during various cognitive

472tasks involving working memory (Chen and Desmond, 2005a,

4732005b), executive function (Stoodley and Schmahmann, 2009), and

474language (Ackermann et al., 2007).

475Cerebellum and TPN

476In contrast with the DMN, the TPN includes a set of brain regions

477that show increased activation during attentionally demanding cog-

478nitive tasks (Corbetta and Shulman, 2002; Fox et al., 2005). We

Fig. 7. A matrix map of the ROI-based rsFC analysis between cerebellar subregions

and the ICNs and subcortical nuclei. The x-axis denotes the cerebellar subregions

and the y-axis demonstrates ICNs and subcortical nuclei. Abbreviations: ADMN, ante-

rior default mode network; Amyg, amygdala; AN, auditory network; Caud, caudate;

DN, dentate nucleus; Hipp, hippocampus; ICNs, intrinsic connectivity networks;

LFPN, left frontal–parietal network; Pall, pallidum; PDMN, posterior default mode

network; Puta, putamen; RFPN, right frontal–parietal network; RN, red nucleus;

ROI, region of interest; rsFC, resting-state functional connectivity; SMN, sensorimotor

network; SN, salience network; Thal, thalamus; TPN, task-positive network; VN,

visual network. The colorbar indicates the z-value of the rsFC. (For interpretation of

the references to color in this ﬁgure legend, the reader is referred to the web version

of this article.)

Fig. 8. A matrix map of the ROI-based rsFC analysis between cerebellar and thalamic sub-

regions. The x-axis denotes thalamic subregions and the y-axis denotes cerebellar subre-

gions. Abbreviations: Occipital, occipital-connected thalamus; Prefrontal, prefrontal-

connected thalamus; Premotor, premotor-connected thalamus; Primary, primary motor-

connected thalamus; Posterior parietal, posterior parietal-connected thalamus; Sensory,

sensory-connected thalamus; Temporal, temporal-connected thalamus.

9L. Sang et al. / NeuroImage xxx (2012) xxx–xxx

Please cite this article as: Sang, L., et al., Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum

with both the cerebral cortical networks and subcortical structures, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.04.011

UNCORRECTED PROOF

479 found that hemispheric VIIb and VIII were strongly correlated with

480 the TPN, which suggests that these two cerebellar subregions may

481 be involved in the attention demanding cognitive tasks. This specu-

482 lation is supported by the ﬁndings that hemispheric VIIb and VIII are ac-

483 tivated by a variety of cognitive tasks (Stoodley and Schmahmann,

484 2010; Stoodley et al., 2012) and complex motor tasks (Nitschke et al.,

485 2005).

486 Cerebellum and SN

487 The SN is composed of the dorsal anterior cingulate cortex and

488 fronto-insular cortex, and its function is to identify internal and

489 extra-personal stimuli to guide behavior (Seeley et al., 2007). Our

490 ﬁnding that hemispheric VI, VIIb, and VIII are involved in the SN is

491 partially consistent with a previous rsFC study (Habas et al., 2009)

492 and suggests that these cerebellar subregions serve the function of

493 identifying salient stimuli to guide behavior. This inference is sup-

494 ported by prior studies that implicate these cerebellar subregions in

495 pain-related processes (Dimitrova et al., 2003, 2004), interoceptive

496 awareness (Gray et al., 2007), and the experience of pleasure

497 (Turner et al., 2007).

498 Cerebellum and thalamus

499 The thalamus is an important node in the cerebro-ponto-

500 cerebellar-thalamo-cortical loop (Nagao, 2004). Inputs from the cere-

501 bral cortices terminate in the pontine nuclei then project to the cer-

502 ebellum, where feedback projections travel via the deep cerebellar

503 nuclei and terminate in the thalamus, which then sends projections

504 back to both motor and non-motor cerebral cortices (Hui et al.,

505 2005; Stoodley and Schmahmann, 2010). Through this circuit, infor-

506 mation can be freely exchanged between the cerebrum and cerebel-

507 lum to facilitate a variety of functions, such as movement, cognition

508 and emotional processing. As expected, we found that most of the

509 cerebellar subregions were correlated with the thalamus, suggesting

510 the importance of the thalamus in exchanging information between

511 the cerebrum and cerebellum. Unexpectedly, we did not ﬁnd rsFCs

512 between a few cerebellar subregions and the thalamus. It is possible

513 that the stringent threshold we employed in our analyses may ac-

514 count for this observation. In the rsFC analysis between thalamic

515 and cerebellar subregions, some of our ﬁndings were expected,

516 such as the observation that lobules I–VI and vermal VIIb–IX were

517 strongly correlated with the occipital–thalamus and the visual network

518 and that vermal lobules I–VI, VIIb, and VIII were correlated with primary

519 motor-, premotor-, and sensory-connected thalamus and the SMN.

520 However, several of our ﬁndings are unexpected, such as the strong

521 rsFC between lobule V and the prefrontal–thalamus. The relatively

522 large voxel size and potential methodological problems may account

523 for these unexpected ﬁndings.

524 Cerebellum and red nucleus

525 The red nucleus showed extensive rsFCs with the cerebellum in-

526 cluding vermal I–V, Crus II–VIIIb and hemispheric V, VI, VIIb, and IX.

527 According to our results, lobules I–VI and VIII are involved in the

528 SMN, lobules VIIb and VIII are involved in the SN and TPN, and lobule

529 IX is involved in the DMN. The rsFCs between these cerebellar sub-

530 regions and the red nucleus are consistent with diffusion tensor MRI

531 studies that show extensive projections from the prefrontal, pericen-

532 tral, temporal and occipital cortices, and subcortical nuclei to the red

533 nucleus (Habas and Cabanis, 2006, 2007). The results are partially con-

534 sistent with a study that found rsFCs between the red nucleus and the

535 cerebellum (hemispheric V), prefrontal and occipital cortices, SN,

536 DMN, and several subcortical nuclei (Nioche et al., 2009). These ﬁnd-

537 ings indicate that the red nucleus is involved in both motor coordina-

538 tion and cognitive functions, an idea that is supported by functional

539neuroimaging studies ﬁnding the red nucleus to be activated during

540sensory, motor, and cognitive tasks (Bhatt et al., 2009; Bingel et al.,

5412002; Dunckley et al., 2005; Liu et al., 2000; Williams et al., 2007).

542Cerebellum and basal ganglia

543Both the sensorimotor- and cognitive-related cerebellar subre-

544gions (lobules V, VII and VIII) were correlated with the basal ganglia,

545which is consistent with prior ﬁndings regarding the function of the

546basal ganglia in sensorimotor (Draganski et al., 2008), cognitive

547(Voytek and Knight, 2010) and emotional processing (Paulmann et

548al., 2011). The close relationship between the cerebellum and basal

549ganglia has also been conﬁrmed by functional neuroimaging ﬁnding

550co-activations in these structures during a variety of tasks

551(Harrington et al., 2004; Hofer et al., 2007; Lu et al., 2004; Winstein

552et al., 1997).

553Cerebellum and the hippocampal region

554Most cerebellar subregions were correlated with the hippocam-

555pal region, a center for memory processing (LeDoux, 2000; Maren,

5562001), suggesting a potential role for these cerebellar lobules in

557memory and navigation processing. The learning and memory pro-

558cess involves different brain regions including the hippocampus,

559cerebellum, amygdala, and other structures (Thompson and Kim,

5601996). The hippocampal region is particularly important for declar-

561ative memory (Squire et al., 2004). The cerebellar system is respon-

562sible for initiating speciﬁc behavioral responses and storing formed

563memories, and cerebellar activation has been observed in numerous

564studies using memory tasks (Groussard et al., 2010; Halsband,

5652006). Functional neuroimaging studies have identiﬁed a complex

566network that is involved in spatial navigation including the hippo-

567campus, cerebellum and other structures (Gordon, 2007). Both

568human and animal studies have indicated that cerebellar damage

569affects spatial navigation processing (Joyal et al., 1996; Rondi-Reig

570and Burguiere, 2005).

571Cerebellum and amygdala

572A novel ﬁnding in this study is that rsFCs exist between several

573cerebellar subregions and the amygdala, indicating the involvement

574of these lobules in emotional processing. Several cerebellar–cerebral

575pathways connect the cerebellum with various limbic structures in-

576cluding the hippocampus, amygdala, septal nuclei, mammillary bod-

577ies, and hypothalamus; these structures have been implicated in

578emotional behavior (Sacchetti et al., 2005). The vermis is involved

579in the processing of affective and fear-related responses such as

580anxiety (Reiman, 1997), grief (Gundel et al., 2003), and pain

581(Dimitrova et al., 2004). Many studies on cerebellar cognitive affec-

582tive syndrome (CCAS) have ascribed the emotional disorders in

583these patients to vermal lesions (Marien et al., 2009; Schmahmann,

5842004; Tavano and Borgatti, 2010). Neuroimaging studies have sug-

585gested that the cerebellum participates in affective circuits in which

586positive emotions are associated with the left cerebral hemisphere

587and negative emotions appear to be more aligned with the right

588hemisphere (Lee et al., 2004; Silberman and Weingartner, 1986).

589The rsFCs between cerebellar subregions and the hippocampus and

590amygdala suggest a cerebellar involvement in emotional memory.

591Because the hippocampus is a center for memory processing and the

592amygdala is a center for processing emotional information (Davis and

593Whalen, 2001; Pape and Pare, 2010), these regions may work

594together to process emotional memory (Phelps, 2004). This functional

595organization may provide a basis for the cerebellum to participate in

596emotional processing.

10 L. Sang et al. / NeuroImage xxx (2012) xxx–xxx

Please cite this article as: Sang, L., et al., Resting-state functional connectivity of the vermal and hemispheric subregions of the cerebellum

with both the cerebral cortical networks and subcortical structures, NeuroImage (2012), doi:10.1016/j.neuroimage.2012.04.011

UNCORRECTED PROOF

597 Differences in rsFC patterns between vermal and hemispheric subregions

598 As phylogenetically old structures, lobules I–V and X showed sim-

599 ilar rsFC patterns between the vermis and the hemisphere. However,

600 in phylogenetically new lobules such as VI–VIII, much stronger rsFC

601 was found between the lateral hemispheres and the phylogenetically

602 new cortex (especially cognitive-related brain regions), compared to

603 those between the vermis and the cortex (see Figs. 3–5and Fig. S5).

604 The rich rsFC between the phylogenetically new cerebellar subre-

605 gions and the cerebral cortices may form a neural basis for the cere-

606 bellar hemisphere to be involved in many higher-level functions.

607 Our ﬁnding is also supported by other studies. An ICA study has

608 revealed that the hemispheric subregions of the cerebellum, not the

609 vermal subregions, were involved in the sensorimotor and cognitive

610 networks (Habas et al., 2009). In addition, the AN had strong rsFCs

611 with the hemispheric lobules VI, VIIb, and VIIIa but weak or even

612 absent rsFCs in the vermal lobules; these ﬁndings are consistent

613 with a meta-analysis showing that during auditory tasks, signiﬁcant

614 activation was found in the cerebellar hemispheres but was not pre-

615 sent in the vermis (Petacchi et al., 2005).

616 The lobule VIIIb showed quite a striking difference between the

617 lateral hemispheric region (which was connected to the TPN) and

618 the vermal region (which is connected to the DMN). This difference

619 may be also explained by the phylogenetical difference between

620 these two regions. The lateral hemispheric VIIIb is a phylogenetically

621 new structure and is involved in brain network involved in higher-

622 level functions, such as verbal working memory (Cooper et al.,

623 2012; Ravizza et al., 2006) and cognitive sequencing functions

624 (Leggio et al., 2008). However, the vermal VIIIb is a phylogenetically

625 old structure, which can explain why it is functionally associated

626 with the DMN, a phylogenetically old structure.

627 Differences in rsFC within lobules VII and VIII

628 Lobules VII and VIII account for the majority of the volume of the

629 cerebellum, and offer support for sensorimotor, cognitive and emo-

630 tional functions. It is interesting to investigate whether either lobule

631 VII or VIII will be a homogeneous structure. We found that vermal

632 Crus I and hemispheric Crus I and Crus II displayed stronger rsFCs

633 with the DMN and FPN; in contrast, lobule VIIb, especially hemi-

634 spheric VIIb, showed stronger rsFCs with the AN, SMN, TPN, and SN.

635 Although hemispheric VIIIa and VIIIb showed similar rsFC patterns,

636 vermal VIIIa and VIIIb exhibited completely different patterns. Vermal

637 VIIIa was correlated with the SMN but vermal VIIIb was correlated

638 with the DMN. These ﬁndings suggest that lobules VII and VIII are het-

639 erogeneous structures and can be subdivided into different subre-

640 gions with different rsFC patterns and different functions.

641 Limitations

642 Several limitations should be considered when interpreting our

643 ﬁndings. The sizes of some cerebellar subregions (such as vermal

644 and hemispheric X) were signiﬁcantly smaller than those of other

645 subregions (such as vermal VI and hemispheric VIIIb), which may

646 affect the resulting rsFC maps of these small subregions under the

647 same statistical threshold. We should be cautious when interpreting

648 the rsFCs between anterosuperior cerebellar subregions and the VN;

649 these regions are adjoining and we cannot exclude the possibility

650 that some rsFCs are artifacts resulting from the smoothing and reg-

651 istration steps. The cluster size threshold may also have affected our

652 reported results. We analyzed correlations between cerebellar subre-

653 gions (lobules I–IV, VIIb and IX) and the cerebral cortex using different

654 thresholds (cluster sizes of 50, 100, and 200 voxels) and found that the

655 results using different cluster sizes were very similar to each other (see

656 Fig. S6 and Fig. S7 in Supplementary materials). We thus adopted a

657 threshold of a 100-voxel cluster size to determine the rsFC maps of

658each cerebellar subregion. We also explored homogeneity in the rsFC

659patterns of hemispheric lobules VI, Crus I and Crus II along the horizon-

660tal axis and found subtle differences between paravermal and lateral

661hemispheric ROIs. Therefore, we used the lateral three-quarters of the

662hemispheric ROI as each hemispheric ROI. However, we did not investi-

663gate the rsFCs of the paravermal regions because it was difﬁcult to ex-

664tract some paravermal ROIs with an acceptable size. The poor spatial

665resolution (4-mm

) of the present study prevents us from drawing con-

666clusions about some smaller structures such as thalamic subregions. Fi-

667nally, some ICNs extracted with ICA only include a part of a complete

668functional network, such as the DMN and SMN, which may account

669for differences in rsFC patterns between voxel- and ROI-based rsFC

670analyses.

671Conclusion

672Unlike previous rsFC studies, we systematically studied the rsFC

673patterns of vermal subregions and found that the same vermal and

674hemispheric subregions showed either different patterns or different

675strengths in rsFCs with the cerebrum. We found that different subre-

676gions of lobules VII and VIII had different rsFCs, and we elucidated the

677rsFC patterns between cerebellar subregions and 9 ICNs, thalamic

678subregions, the red nucleus, the basal ganglia, the hippocampus, and

679the amygdala. Our results demonstrate both functional integration

680and segregation of cerebellar subregions and largely improve our un-

681derstanding of the functional organization of the human cerebellum.

682Acknowledgments

683This work was supported by the National Basic Research Program

684of China (973 program, No. 2011CB707801) and the Natural Science

685Foundation of China (Nos. 30870694 and 30730036).

686Appendix A. Supplementary data

687Supplementary data to this article can be found online at http://

688dx.doi.org/10.1016/j.neuroimage.2012.04.011.

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