Abnormal spontaneous brain activity in minimal hepatic encephalopathy: resting-state fMRI study

Abstract

PURPOSE

We aimed to assess the abnormality of baseline spontaneous brain activity in minimal hepatic encephalopathy (MHE) by amplitude of low frequency fluctuation (ALFF) and fraction ALFF (fALFF).

METHODS

A total of 14 MHE patients and 14 healthy controls were included in our study. Both ALFF and fALFF of functional magnetic resonance imaging were calculated for statistical analysis.

RESULTS

Compared with healthy controls, patients with MHE had significantly decreased ALFF in the bilateral medial prefrontal cortex (MPFC), left superior frontal gyrus, right precentral gyrus, left opercular part of inferior frontal gyrus, left gyrus rectus, bilateral precuneus, and the posterior lobe of right cerebellum; and they had significantly decreased fALFF in the bilateral MPFC, right middle frontal gyrus, right superior temporal gyrus, and the posterior lobe of left cerebellum.

CONCLUSION

ALFF and fALFF changes in many brain regions demonstrate abnormality of the spontaneous neuronal activity in MHE. Especially the impairment of right precuneus and left MPFC may play a critical role in manifestation of MHE. Changes of ALFF and fALFF in the precuneus and the MPFC can be used as a potential marker for MHE.

Diagn Interv Radiol 2016; 22:196200

Turkish Society of Radiology 2015

NEURORADIOLOGY

ORIGINAL ARTICLE

Abnormal spontaneous brain activity in minimal hepatic encephalopathy: resting-state fMRI study

Wei-Jia Zhong* Zhi-Ming Zhou* Jian-Nong Zhao Wei Wu Da-Jing Guo

PURPOSE

We aimed to assess the abnormality of baseline spontaneous brain activity in minimal hepatic encephalopathy (MHE) by amplitude of low frequency uctuation (ALFF) and fraction ALFF (fALFF).

METHODS

A total of 14 MHE patients and 14 healthy controls were included in our study. Both ALFF and fALFF of functional magnetic resonance imaging were calculated for statistical analysis.

RESULTS

Compared with healthy controls, patients with MHE had signicantly decreased ALFF in the bilateral medial prefrontal cortex (MPFC), left superior frontal gyrus, right precentral gyrus, left opercular part of inferior frontal gyrus, left gyrus rectus, bilateral precuneus, and the posterior lobe of right cerebellum; and they had signicantly decreased fALFF in the bilateral MPFC, right middle frontal gyrus, right superior temporal gyrus, and the posterior lobe of left cerebellum.

CONCLUSION

ALFF and fALFF changes in many brain regions demonstrate abnormality of the spontaneous neuronal activity in MHE. Especially the impairment of right precuneus and left MPFC may play a critical role in manifestation of MHE. Changes of ALFF and fALFF in the precuneus and the MPFC can be used as a potential marker for MHE.

Minimal hepatic encephalopathy (MHE), as an early stage of hepatic encephalopathy (HE), shows only mild attention decit, visual motor dysfunction, cognitive control impairment and working memory network disorder, without any obvious

neurologic manifestations (e.g., confusion, hepatic coma). As a transitional stage, 20%80% of MHE cases develop from liver cirrhosis (1). Patients usually have weaker capabilities of handling an emergency situation and higher risk of accident (2). MHE is potentially reversible, because of the minor damage to the neurons (3).

Previously, diusion tensor imaging and magnetic resonance spectrum were used to get an insight into HE. These modalities found neuron swelling or interstitial edema and abnormal metabolism in related brain regions (48).

Currently, blood oxygenation level dependent-functional magnetic resonance imaging (BOLD-fMRI), which has the ability to detect brain dysfunction, is a focus in the eld of HE research. Some task-related fMRI studies found impairments in multiple cognitive and spatial memory functional regions of the brain (9, 10). Dierent from task-related fMRI, resting-state fMRI demonstrates spontaneous neuronal activity. Using resting-state fMRI, studies found decreased regional homogeneity in brain regions that are related to cognition and memory function, and the changes of regional homogeneity in the precuneus were closely related to the development of MHE (11, 12). Functional connectivity was also used in HE studies, which revealed disturbed brain networks (1318).

A dierent approach from regional homogeneity and functional connectivity, amplitude of low frequency uctuation (ALFF) analysis, which detects the alternation of spontaneous brain activity by measuring the energy of low frequency oscillation, was rst used by Zang et al. (19) in a study of patients with attention decit hyperactivity disorder, becoming a new method to study the brain function. Recently, Chen et al. (20) and Qi et al. (21) used it in MHE and revealed aberrant brain activity and continuous impairment. Based on the ALFF, the fraction ALFF (fALFF) proposed by Zou et al. (22) not only gets rid of physiological noise

* Wei-Jia Zhong and Zhi-Ming Zhou contributed equally to this work.

From the Department of Radiology (J.N.Z. [email protected]), the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Received 31 May 2015; revision requested 5 July 2015; last revision received 1 August 2015; accepted 6 August 2015.

Published online 5 January 2016. DOI 10.5152/dir.2015.15208

196

eectively, but also has a higher sensitivity and specicity compared with the ALFF. But until now, few studies employed the ALFF to investigate MHE and even fewer employed the fALFF. Moreover, study of MHE by means of ALFF and fALFF continues to be regarded as controversial. In this study, we used the ALFF and fALFF to investigate alternations of spontaneous brain activity in MHE.

Table 1. Summary of demographic information and neuropsychologic tests

Patients with MHE Healthy controls

Variables (n=14) (n=14) P

M/F ratio 7/7 7/7 0.334

Age (years) 54.5710.57 50.869.38

Education (years) 10.43.50 11.002.39 0.618

NCT-A (seconds) 57.6330.96 21.333.80 0.001

DST (raw score) 23.2910.99 48.8610.29 0.001

MHE, minimal hepatic encephalopathy; M/F, male/female; NCT-A, number connection test A; DST, digit-symbol test.

Methods

Subjects

This study was approved by the Institutional Ethics Committee and written informed consent was obtained from all participants. In total, 25 patients with nonalcoholic liver cirrhosis and 19 healthy control subjects were recruited in our study. All participants were right-handed and had no alcohol or drug abuse history, related neurologic or/ and psychiatric illness, or MRI contraindications. Healthy control subjects had no history of liver disease. Nonalcoholic liver cirrhosis was diagnosed through clinical manifestations, signs, and examinations (biochemical laboratory examinations and radiologic examinations such as computed tomography, MRI, and ultrasonography). The neuropsycho-logic tests including the number connection test A and digit-symbol test and fMRI were performed in all participants. MHE was diagnosed by two senior gastroenterologists based on the nal report of the working party of 11th World Congress of Gastroenterology in Vienna in 1998 (23); nonalcoholic liver cirrhosis patients with abnormal neuropsycho-logical test scores (more than one standard deviation beyond for number connection test A or under the mean value for digit-symbol test) were regarded as MHE. The normal

values of neuropsychiatric tests were determined in a sample of 120 healthy volunteers in a prior study (24). We excluded four cases of MHE and two healthy control subjects with intolerable motion (translation of more than 1.0 mm or rotation of more than 1.0), one case of MHE with bad registration, two cases of MHE with dentures artifact and four cases of MHE and three healthy control subjects with intracranial complications in the data preprocessing. Finally 14 MHE and 14 healthy control subjects were included in our study.

MRI data acquisition and preprocessing

MRI data was acquired on a 3.0 T scanner (Achieva Intera, Phillips Medical System) using an eight-channel head coil. The functional image was acquired by using an echo-planar imaging sequence (repetition time, 2000 ms; echo time, 30 ms; ip angle, 90; matrix, 6464; eld of view, 240 mm240 mm; section thickness, 4.0 mm; number of sections, 34; dynamics, 180). All participants were instructed to keep their head still and eyes closed. We provided the participants with earplugs and xed their head with sponges of dierent thickness before MRI scanning.

Preprocessing was performed by the data processing assistant for resting-state fMRI (DPARSF) (http://www.restfmri.net). The procedures included removing the rst 10 time points (for adaption to the scanning noise and the steady state of machine), slice-timing correction, realign correction, spatial normalization, smoothing (full width at half maximum, 4 mm), linear detrend and band-pass ltering (0.010.08 Hz).

Then the time courses were converted to the frequency domain by using a fast Fourier transform and the averaged square root of the spectrum across 0.010.08 Hz at each voxel was taken as the ALFF. The fALFF was calculated as ALFF divided by the value of the entire detectable frequency band. For

standardizing variability across the participants, mean ALFF was obtained as ALFF divided by the global mean ALFF; mean fALFF was also calculated in a similar manner. Finally, mean ALFF and mean fALFF maps of the whole brain of MHE and healthy control subjects, which reected the degree of the raw value relative to the global mean value, were used for statistical analysis.

ALFF and fALFF analysis

The two-sample t-test was performed by Resting-State fMRI Data Analysis Toolkit v1.8 (REST1.8) (http://http://www.restfmri.net/

Web End =www.restfmri.net ) to determine the mean ALFF and mean fALFF dierences within the whole-brain between the two groups.

We used the signicant regions of ALFF or fALFF respectively to make a new union mask. Pearsons correlation analysis was performed by REST1.8 software to nd the correlation between the ALFF or fALFF and poor neurocognitive performances within the union mask. The gray matter volume and age were added as covariants for excluding the related eects. The threshold was set at P < 0.05 (corrected by using the AlphaSim program) and the minimum cluster size was 54 voxels.

Main points

Minimal hepatic encephalopathy (MHE) is difficult to diagnose because of its mild brain dysfunction.

It is important to be aware of MHE, given its higher risk of accidents and morbidity and potentially reversible nature.

Amplitude of low frequency uctuation (ALFF) and fraction ALFF (fALFF) changes in many brain regions demonstrate abnormality of the spontaneous neuronal activity in MHE, especially in the right precuneus and the left medial prefrontal cortex (MPFC).

Changes of ALFF and fALFF in the precuneus and MPFC play a critical role in the manifestation of MHE.

Results

There were no signicant dierences in terms of age (P = 0.334) and education (P = 0.618) between MHE patients and healthy controls. The number connection test A and digit-symbol test showed signicant dierence between the two groups (P < 0.001) (Table 1).

Compared with healthy controls, MHE showed regions of increased ALFF in the right inferior temporal gyrus, right temporal pole/middle temporal gyrus, left insular, and the posterior lobe of right cerebellum. On the other hand, clusters of decreased

Abnormal spontaneous brain activity in minimal hepatic encephalopathy 197

rectus, bilateral precuneus, and the posterior lobe of right cerebellum; while they had decreased fALFF in the bilateral MPFC, right middle frontal gyrus, right superior temporal gyrus, and the posterior lobe of left cerebellum. These ndings suggest the presence of abnormal brain spontaneous activity in MHE at the baseline.

Our study revealed that the ALFF and fALFF changes of the MHE group happened mainly in the frontal lobes. As we know, the frontal lobe is the most advanced part of the brain and it is closely related to working memory and cognition (25, 26). The prefrontal cortex is responsible for spatial memory (10, 25, 26). As the integration and processing center of spatial working memory, it has functions of noticing, inhibiting, coding, integrating, storing, extracting and processing the information from the outside (25). Decreased ALFF and increased fALFF in the frontal lobe reect decreased brain spontaneous activity, which may lead to brain dysfunction and result in cognition decits such as distracted attention, decreased memory, and slow reaction of MHE patients. A MHE study by Liao et al. (10) also suggested the impairment of prefrontal lobes as the mechanism of dysfunction of spatial working memory.

As we know, default mode network includes the precuneus and cuneus, post cingulum cortex, MPFC, bilateral inferior parietal lobule, and the lateral temporal lobes. It attends the basic functional activities in the resting state, such as processing the episodic memory, monitoring the cognitive control, and switching the state of external stimuli and internal brain activity (2729). The precuneus mainly participates in the process of visual spatial information integration (30). Our study showed that patients with MHE had lower ALFF in the bilateral precuneus and MPFC, while they had lower fALFF in the bilateral MPFC and higher fALFF in the precuneus. This nding indicates decreased neuronal activity in those regions led by reduced cerebral oxygen consumption and cerebral blood ow (31). Previous MHE studies showed decreased regional homogeneity in the cuneus and precuneus (11, 12) and weakened functional connectivity among the default mode network (14, 15) suggesting an abnormal connection among these regions. As members of the default mode network, the precuneus and MPFC are responsible for cognition. Decreased neuronal activity and consequent abnormal functional

198 MarchApril 2016 Diagnostic and Interventional Radiology Zhong et al.

a b

Figure 1. a, b. Axial T1-weighted images (a, b) show minimal hepatic encephalopathy (MHE) group with decreased amplitude of low frequency uctuation (ALFF) in bilateral precuneus, medial prefrontal cortex (MPFC) (a) and the posterior lobe of right cerebellum (R-PLC) (b) compared with the healthy controls. (REST1.8, http://www.restfmri.net)

Table 2. Regions showing signicant dierences in ALFF between MHE patients and healthy controls

MNI coordinates

Regions BA Voxels (x, y, z ) Peak t value

ALFF increased in MHE

L-Insula 34 54 (-27, 3, -15) 4.4098

R-ITG 20 76 (54, -48, -27) 4.3602

R-Temporal pole/MTG 21 60 (39, 9, -39) 3.8904

R-PLC 58 (45, -45, -42) 3.6982

ALFF decreased in MHE

L-Oper/IFG 48 77 (-42, 9, 21) -4.6821

L-SFG 10 54 (-33, 63, 3) -4.0135

L-Gyrus rectus 47 80 (-15, 15, -15) -3.4602

R-PLC 54 (9, -90, -33) -4.5152

R-PrCG 4 59 (36, -21, 51) -3.4411

B-MPFC 6 121 (3, 33, 39) -3.5014

B-Precuneus 7 71 (3, -42, 45) -3.5021

ALFF, amplitude of low frequency uctuation; MHE, minimal hepatic encephalopathy; BA, Brodmanns area; MNI (x, y, z), Montreal Neurologic Institute (x, y, z); L, left; R, right; ITG, inferior temporal gyrus; MTG, middle temporal gyrus; PLC, posterior lobe of cerebellum; Oper/IFG, opercular part of inferior frontal gyrus; SFG, superior frontal gyrus; PrCG, precentral gyrus; B, bilateral; MPFC, medial prefrontal cortex.

ALFF were located in the bilateral frontal lobes including the bilateral medial pre-frontal cortex (MPFC), left superior frontal gyrus, right precentral gyrus, left opercular part of inferior frontal gyrus, left gyrus rectus, bilateral precuneus, and the posterior lobe of right cerebellum (Fig. 1, Table 2).

Compared with healthy controls, MHE showed regions of increased fALFF in the right middle cingulum gyrus/middle and inferior frontal gyrus, left triangular part of inferior frontal gyrus, left middle frontal gyrus, left gyrus rectus, left precentral gyrus, right precuneus/post cingulum cortex, right insula, right lentiform nucleus, left pallidum and pons/the anterior lobe of left cerebellum. On the other hand, clusters of

decreased fALFF were found in the bilateral MPFC, right middle frontal gyrus, right superior temporal gyrus, and the posterior lobe of left cerebellum (Fig. 2, Table 3).

There were no correlations between ALFF or fALFF changes and poor neurocognitive performances in the MHE group.

Discussion

In this study, ALFF and fALFF were used to detect the abnormal brain activity in MHE. We found that patients with MHE had decreased ALFF in the frontal lobes including the bilateral MPFC, left superior frontal gyrus, right precentral gyrus, left opercular part of inferior frontal gyrus, left gyrus

a b

Figure 2. a, b. Axial T1-weighted images (a, b) show MHE group with increased fraction amplitude of low frequency uctuation (fALFF) in right precuneus (a) and decreased fALFF in the posterior lobe of left cerebellum (L-PLC) (b) compared with the healthy controls. (REST1.8, http://www.restfmri.net)

Table 3. Regions showing signicant dierences in fALFF between MHE patients and healthy controls

MNI coordinates

Regions BA Voxels (x, y, z ) Peak t value

fALFF increased in MHE

L-Tri/IFG 48 93 (-27, 33, 6) 4.4042

Pons/L-ALC 81 (-21, -48, -33) 4.6300

L-MFG 11 76 (-21, 42, -6) 3.5792

L-Pallidum 60 (-18, -3, 3) 3.9015

L-PrCG 24 58 (-15, -18, 42) 4.7522

L-Gyrus rectus 11 54 (-15, 33, -27) 5.5160

R-MCC-M/IFG 31/6 315 (18, 0, 48) 4.6569

R-Precuneus/PCC 29/23 64 (9, -48, 12) 4.2656

R-Insula 72 (24, -15, 15) 4.9575

R-Lentiform nucleus 73 (21, -3, 21) 4.0159

fALFF decreased in MHE

B-MPFC 8 121 (-1, 30, 48) -4.1249

R-MFG 9 62 (42, 9, 48) -3.5478

L-PLC 61 (-30, -84, -30) -3.9211

R-STG 48 54 (51, -6, 0) -4.3696

fALFF, fraction amplitude of low frequency uctuation; MHE, minimal hepatic encephalopathy; BA, Brodmanns area; MNI (x, y, z), Montreal Neurologic Institute (x, y, z); L, left; Tri/IFG, triangular part of inferior frontal gyrus; ALC, anterior lobe of cerebellum; MFG, middle frontal gyrus; PrCG, precentral gyrus; R, right; MCC, middle cingulum cortex; M/IFG, middle and inferior frontal gyrus; PCC, post cingulum cortex; B, bilateral; MPFC, medial prefrontal cortex; PLC, posterior lobe of cerebellum; STG, superior temporal gyrus.

connection cause cognitive dysfunction in MHE. We speculate that the dysfunction of precuneus and MPFC are manifestations of MHE, and changes in those two regions could provide a potential marker to detect MHE.

Previous studies suggested opposite patterns of changes in the cerebellum: decreased ALFF in the posterior lobe of left cerebellum in low-grade HE (20) and increased ALFF in the posterior lobe of left cerebellum in HE (21). Our results showed more complicated changes in the cerebel-

lum in MHE (increased or decreased ALFF in dierent regions of the posterior lobe of right cerebellum, while increased and decreased fALFF in the anterior lobe and the posterior lobe of left cerebellum, respectively). As a regulator of the whole brain, the cerebellum inuences several regions of prefrontal cortex via the thalamus (32). The anterior lobe of cerebellum is responsible for communication between cerebral and spinal motor systems, while the posterior lobe attends the cognitive control and emotion regulation (33, 34). Our complicat-

ed ndings in the cerebellum may be interpreted as impairments and compensations happening in dierent regions of the cerebellum at the same time. Further study is needed to clarify these ndings.

Interestingly, we detected increased ALFF in the right inferior temporal gyrus, right temporal pole/middle temporal gyrus, and left insula and increased fALFF in the right insula, right lentiform nucleus, and left pallidum in MHE, suggesting an increased spontaneous neuronal activity in those regions. We speculate that this may reect the compensation of brain dysfunction in MHE.

This study has some limitations. First, although we instructed all participants to keep their head still and eyes closed during the scan, we cannot completely exclude uncontrolled factors such as the noise during the scanning aecting our results. Second, our sample size was small. Although we found signicant dierences in ALFF and fALFF in our study, further research with larger sample size is needed to conrm our ndings.

In conclusion, we found ALFF and fALFF changes in many brain regions in MHE, demonstrating abnormality of the spontaneous neuronal activity. Especially, impairment of the right precuneus and left MPFC may represent the underlying manifestations in MHE. ALFF and fALFF can be used as potential markers for MHE.

Financial disclosure

This research was supported by grants from the National Natural Science Foundation of China (Grant No 81071126 to Jian-Nong Zhao and Grant No 30800262 to Wei-Jia Zhong).

Acknowledgements

We gratefully thank all the stas of Hepatology Treatment and Research Center of the Second Afliated Hospital of Chongqing Medical University, Chongqing, China for their valuable help.

Conict of interest disclosure

The authors declared no conicts of interest.

References

1. Cordoba J. New assessment of hepatic encephalopathy. J Hepatol 2011; 54:10301040. http://dx.doi.org/10.1016/j.jhep.2010.11.015

Web End =[CrossRef]

2. Roman E, Cordoba J, Torrens M, et al. Minimal hepatic encephalopathy is associated with falls. Am J Gastroenterol 2011; 106:476482. http://dx.doi.org/10.1038/ajg.2010.413

Web End =[CrossRef]

3. Shavakhi A, Hashemi H, Tabesh E, Derakhshan Z, Farzamnia S. Multistrain probiotic and lactulose in the treatment of minimal hepatic encephalopathy. J Res Med Sci 2014; 19:703 708.

4. Goel A, Yadav S, Saraswat V, et al. Cerebral oedema in minimal hepatic encephalopathy due to extrahepatic portal venous obstruction. Liver Int 2010; 30:11431151. http://dx.doi.org/10.1111/j.1478-3231.2010.02289.x

Web End =[CrossRef]

Abnormal spontaneous brain activity in minimal hepatic encephalopathy 199

5. Kale RA, Gupta RK, Saraswat VA, et al. Demonstration of interstitial cerebral edema with diffusion tensor MR imaging in type C hepatic encephalopathy. Hepatology 2006; 43:698706. http://dx.doi.org/10.1002/hep.21114

Web End =[CrossRef]

6. Kumar R, Gupta RK, Elderkin-Thompson V, et al. Voxel-based diusion tensor magnetic resonance imaging evaluation of low-grade hepatic encephalopathy. J Magn Reson Imaging 2008; 27:10611068. http://dx.doi.org/10.1002/jmri.21342

Web End =[CrossRef]

7. Singhal A, Nagarajan R, Hinkin CH, et al. Two-dimensional MR spectroscopy of minimal hepatic encephalopathy and neuropsychological correlates in vivo. J Magn Reson Imaging 2010; 32:3543.http://dx.doi.org/10.1002/jmri.22216

Web End = [CrossRef]

8. Mechtcheriakov S, Schocke M, Kugener A, et al. Chemical shift magnetic resonance spectroscopy of cingulate grey matter in patients with minimal hepatic encephalopathy. Neuroradiology 2005; 47:2734. http://dx.doi.org/10.1007/s00234-004-1298-8

Web End =[CrossRef]

9. Zaris O, Kircheis G, Rood HA, Boers F, Haussinger D, Zilles K. Neural mechanism underlying impaired visual judgement in the dys-metabolic brain: an fMRI study. Neuroimage 2004; 22:541552.http://dx.doi.org/10.1016/j.neuroimage.2004.01.038

Web End = [CrossRef]

10. Liao LM, Zhou LX, Le HB, Yin JJ, Ma SH. Spatial working memory dysfunction in minimal hepatic encephalopathy: an ethology and BOLD-fMRI study. Brain Res 2012; 1445:6272. http://dx.doi.org/10.1016/j.brainres.2012.01.036

Web End =[CrossRef]

11. Ni L, Qi R, Zhang LJ, et al. Altered regional homogeneity in the development of minimal hepatic encephalopathy: a resting-state functional MRI study. PLoS One 2012; 7:e42016. http://dx.doi.org/10.1371/journal.pone.0042016

Web End =[CrossRef]

12. Chen HJ, Zhu XQ, Yang M, et al. Changes in the regional homogeneity of resting-state brain activity in minimal hepatic encephalopathy. Neurosci Lett 2012; 507:59. http://dx.doi.org/10.1016/j.neulet.2011.11.033

Web End =[CrossRef]

13. Zhang LJ, Zheng G, Zhang L, et al. Altered brain functional connectivity in patients with cirrhosis and minimal hepatic encephalopathy: a functional MR imaging study. Radiology 2012; 265:528536. http://dx.doi.org/10.1148/radiol.12120185

Web End =[CrossRef]

14. Qi R, Zhang LJ, Xu Q, et al. Selective impairments of resting-state networks in minimal hepatic encephalopathy. PLoS One 2012; 7:e37400. http://dx.doi.org/10.1371/journal.pone.0037400

Web End =[CrossRef]

15. Chen HJ, Jiao Y, Zhu XQ, et al. Brain dysfunction primarily related to previous overt hepatic encephalopathy compared with minimal hepatic encephalopathy: resting-state functional MR imaging demonstration. Radiology 2013; 266:261270. http://dx.doi.org/10.1148/radiol.12120026

Web End =[CrossRef]

16. Qi R, Zhang LJ, Zhong J, et al. Altered eective connectivity network of the basal ganglia in low-grade hepatic encephalopathy: a resting-state fMRI study with Granger causality analysis. PLoS One 2013; 8:e53677. http://dx.doi.org/10.1371/journal.pone.0053677

Web End =[CrossRef]

17. Zhang LJ, Qi R, Zhong J, et al. Disrupted functional connectivity of the anterior cingulate cortex in cirrhotic patients without overt hepatic encephalopathy: a resting state fMRI study. PLoS One 2013; 8:e53206. http://dx.doi.org/10.1371/journal.pone.0053206

Web End =[CrossRef]

18. Qi R, Zhang LJ, Zhong J, et al. Disrupted thalamic resting-state functional connectivity in patients with minimal hepatic encephalopathy. Eur J Radiol 2013; 82:850856. http://dx.doi.org/10.1016/j.ejrad.2012.12.016

Web End =[CrossRef]

19. Zang YF, He Y, Zhu CZ, et al. Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev 2007; 29:8391.http://dx.doi.org/10.1016/j.braindev.2006.07.002

Web End = [CrossRef]

20. Chen HJ, Zhu XQ, Jiao Y, Li PC, Wang Y, Teng GJ. Abnormal baseline brain activity in low-grade hepatic encephalopathy: a resting-state fMRI study. J Neurol Sci 2012; 318:140145. http://dx.doi.org/10.1016/j.jns.2012.02.019

Web End =[CrossRef]

21. Qi R, Zhang L, Wu S, et al. Altered resting-state brain activity at functional MR imaging during the progression of hepatic encephalopathy. Radiology 2012; 264:187195. http://dx.doi.org/10.1148/radiol.12111429

Web End =[CrossRef]

22. Zou QH, Zhu CZ, Yang Y, et al. An improved approach to detection of amplitude of low-frequency uctuation (ALFF) for resting-state fMRI: fractional ALFF. J Neurosci Methods 2008; 172:137141. http://dx.doi.org/10.1016/j.jneumeth.2008.04.012

Web End =[CrossRef]

23. Ferenci P, Lockwood A, Mullen K, Tarter R, Weissenborn K, Blei AT. Hepatic encephalopathy: denition, nomenclature, diagnosis, and quantication: nal report of the working party at the 11th World Congresses of Gastroenterology, Vienna, 1998. Hepatology 2002; 35:716 721. http://dx.doi.org/10.1053/jhep.2002.31250

Web End =[CrossRef]

24. Bao ZJ, Qiu DK, Ma X, et al. The application of psychometric measures in diagnosis of minimal hepatic encephalopathy. Chin J Dig 2006; 26:606609.

25. Funahashi S. Prefrontal cortex and working memory processes. Neuroscience 2006; 139:251261. http://dx.doi.org/10.1016/j.neuroscience.2005.07.003

Web End =[CrossRef]

26. Wagner AD, Maril A, Bjork RA, Schacter DL. Prefrontal contributions to executive control: fMRI evidence for functional distinctions within lateral prefrontal cortex. Neuroimage 2001; 14:13371347. http://dx.doi.org/10.1006/nimg.2001.0936

Web End =[CrossRef]

27. Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc Natl Acad Sci USA 2001; 98:676682. http://dx.doi.org/10.1073/pnas.98.2.676

Web End =[CrossRef]

28. Mantini D, Perrucci MG, Del Gratta C, Romani GL, Corbetta M. Electrophysiological signatures of resting state networks in the human brain. Proc Natl Acad Sci USA 2007; 104:13170 13175. http://dx.doi.org/10.1073/pnas.0700668104

Web End =[CrossRef]

29. Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME. The human brain is intrinsically organized into dynamic, anticor-related functional networks. Proc Natl Acad Sci USA 2005; 102:96739678.http://dx.doi.org/10.1073/pnas.0504136102

Web End = [CrossRef]

30. Wenderoth N, Debaere F, Sunaert S, Swinnen SP. The role of anterior cingulate cortex and precuneus in the coordination of motor behaviour. Eur J Neurosci 2005; 22:235246. http://dx.doi.org/10.1111/j.1460-9568.2005.04176.x

Web End =[CrossRef]

31. Iversen P, Sorensen M, Bak LK. Low cerebral oxygen consumption and blood ow in patients with cirrhosis and an acute episode of hepatic encephalopathy. Gastroenterology 2009; 136:863871.http://dx.doi.org/10.1053/j.gastro.2008.10.057

Web End = [CrossRef]

32. Middleton FA, Strick PL. Cerebellar projections to the prefrontal cortex of the primate. J Neurosci 2001; 21:700712.

33. Stoodley CJ, Schmahmann JD. Evidence for topographic organization in the cerebellum of motor control versus cognitive and aective processing. Cortex 2010; 46:831844.http://dx.doi.org/10.1016/j.cortex.2009.11.008

Web End = [CrossRef]

34. Schmahmann JD, Caplan D. Cognition, emotion and the cerebellum. Brain 2006; 129:290292. http://dx.doi.org/10.1093/brain/awh729

Web End =[CrossRef]

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