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Journal of Zhejiang University SCIENCE B 2018 Vol.19 No.12 P.924-934


Interhemispheric functional connectivity for Alzheimer’s disease and amnestic mild cognitive impairment based on the triple network model

Author(s):  Zheng-Luan Liao, Yun-Fei Tan, Ya-Ju Qiu, Jun-Peng Zhu, Yan Chen, Si-Si Lin, Ming-Hao Wu, Yan-Ping Mao, Jiao-Jiao Hu, Zhong-Xiang Ding, En-Yan Yu

Affiliation(s):  Department of Psychiatry, Zhejiang Provincial People’s Hospital, Hangzhou 310014, China; more

Corresponding email(s):   hangzhoudzx73@126.com, yuenyan@aliyun.com

Key Words:  Voxel-mirrored homotopic connectivity, Alzheimer’, s disease, Amnestic mild cognitive impairment, Default mode network, Salience network, Executive control network

Zheng-Luan Liao, Yun-Fei Tan, Ya-Ju Qiu, Jun-Peng Zhu, Yan Chen, Si-Si Lin, Ming-Hao Wu, Yan-Ping Mao, Jiao-Jiao Hu, Zhong-Xiang Ding, En-Yan Yu. Interhemispheric functional connectivity for Alzheimer’s disease and amnestic mild cognitive impairment based on the triple network model[J]. Journal of Zhejiang University Science B, 2018, 19(12): 924-934.

@article{title="Interhemispheric functional connectivity for Alzheimer’s disease and amnestic mild cognitive impairment based on the triple network model",
author="Zheng-Luan Liao, Yun-Fei Tan, Ya-Ju Qiu, Jun-Peng Zhu, Yan Chen, Si-Si Lin, Ming-Hao Wu, Yan-Ping Mao, Jiao-Jiao Hu, Zhong-Xiang Ding, En-Yan Yu",
journal="Journal of Zhejiang University Science B",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Interhemispheric functional connectivity for Alzheimer’s disease and amnestic mild cognitive impairment based on the triple network model
%A Zheng-Luan Liao
%A Yun-Fei Tan
%A Ya-Ju Qiu
%A Jun-Peng Zhu
%A Yan Chen
%A Si-Si Lin
%A Ming-Hao Wu
%A Yan-Ping Mao
%A Jiao-Jiao Hu
%A Zhong-Xiang Ding
%A En-Yan Yu
%J Journal of Zhejiang University SCIENCE B
%V 19
%N 12
%P 924-934
%@ 1673-1581
%D 2018
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B1800381

T1 - Interhemispheric functional connectivity for Alzheimer’s disease and amnestic mild cognitive impairment based on the triple network model
A1 - Zheng-Luan Liao
A1 - Yun-Fei Tan
A1 - Ya-Ju Qiu
A1 - Jun-Peng Zhu
A1 - Yan Chen
A1 - Si-Si Lin
A1 - Ming-Hao Wu
A1 - Yan-Ping Mao
A1 - Jiao-Jiao Hu
A1 - Zhong-Xiang Ding
A1 - En-Yan Yu
J0 - Journal of Zhejiang University Science B
VL - 19
IS - 12
SP - 924
EP - 934
%@ 1673-1581
Y1 - 2018
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.B1800381

The purpose of this study was to explore the differences in interhemispheric functional connectivity in patients with alzheimer’;s disease (AD) and amnestic mild cognitive impairment (aMCI) based on a triple network model consisting of the default mode network (DMN), salience network (SN), and executive control network (ECN). The technique of voxel-mirrored homotopic connectivity (VMHC) analysis was applied to explore the aberrant connectivity of all patients. The results showed that: (1) the statistically significant connections of interhemispheric brain regions included DMN-related brain regions (i.e. precuneus, calcarine, fusiform, cuneus, lingual gyrus, temporal inferior gyrus, and hippocampus), SN-related brain regions (i.e. frontoinsular cortex), and ECN-related brain regions (i.e. frontal middle gyrus and frontal inferior); (2) the precuneus and frontal middle gyrus in the AD group exhibited lower VMHC values than those in the aMCI and healthy control (HC) groups, but no significant difference was observed between the aMCI and HC groups; and (3) significant correlations were found between peak VMHC results from the precuneus and Mini Mental State Examination (MMSE) and Montreal Cognitive Scale (MOCA) scores and their factor scores in the AD, aMCI, and AD plus aMCI groups, and between the results from the frontal middle gyrus and MOCA factor scores in the aMCI group. These findings indicated that impaired interhemispheric functional connectivity was observed in AD and could be a sensitive neuroimaging biomarker for AD. More specifically, the DMN was inhibited, while the SN and ECN were excited. VMHC results were correlated with MMSE and MOCA scores, highlighting that VMHC could be a sensitive neuroimaging biomarker for AD and the progression from aMCI to AD.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]Anderson JS, Druzgal TJ, Froehlich A, et al., 2011. Decreased interhemispheric functional connectivity in autism. Cereb Cortex, 21(5):1134-1146.

[2]Blautzik J, Keeser D, Paolini M, et al., 2016. Functional connectivity increase in the default-mode network of patients with Alzheimer’s disease after long-term treatment with galantamine. Eur Neuropsychopharmacol, 26(3):602-613.

[3]Botvinick MM, Cohen JD, Carter CS, 2004. Conflict monitoring and anterior cingulate cortex: an update. Trends Cogn Sci, 8(12):539-546.

[4]Buckner RL, Snyder AZ, Shannon BJ, et al., 2005. Molecular, structural, and functional characterization of Alzheimer’s disease: evidence for a relationship between default activity, amyloid, and memory. J Neurosci, 25(34):7709-7717.

[5]Burns JM, Church JA, Johnson DK, et al., 2005. White matter lesions are prevalent but differentially related with cognition in aging and early Alzheimer disease. Arch Neurol, 62(12):1870-1876.

[6]Cai SP, Peng YL, Chong T, et al., 2017. Differentiated effective connectivity patterns of the executive control network in progressive MCI: a potential biomarker for predicting AD. Curr Alzheimer Res, 14(9):937-950.

[7]Chang YT, Huang CW, Chang YH, et al., 2015. Amyloid burden in the hippocampus and default mode network: relationships with gray matter volume and cognitive performance in mild stage Alzheimer disease. Medicine, 94(16):e763.

[8]Donchin O, Gribova A, Steinberg O, et al., 1998. Primary motor cortex is involved in bimanual coordination. Nature, 395(6699):274-278.

[9]Francx W, Oldehinkel M, Oosterlaan J, et al., 2015. The executive control network and symptomatic improvement in attention-deficit/hyperactivity disorder. Cortex, 73:62-72.

[10]Ho CSH, Zhang MWB, Ho RCM, 2016. Optical topography in psychiatry: a chip off the old block or a new look beyond the mind-brain frontiers? Front Psychiatry, 7:74.

[11]Hoptman MJ, Zuo XN, D'Angelo D, et al., 2012. Decreased interhemispheric coordination in schizophrenia: a resting state fMRI study. Schizophr Res, 141(1):1-7.

[12]Jiang ZY, 2005. Abnormal cortical functional connections in Alzheimer’s disease: analysis of inter- and intra-hemispheric EEG coherence. J Zhejiang Univ SCI, 6B(4):259-264.

[13]Joo SH, Lim HK, Lee CU, 2016. Three large-scale functional brain networks from resting-state functional MRI in subjects with different levels of cognitive impairment. Psychiatry Investig, 13(1):1-7.

[14]Kelly C, Zuo XN, Gotimer K, et al., 2011. Reduced interhemispheric resting state functional connectivity in cocaine addiction. Biol Psychiatry, 69(7):684-692.

[15]Lai CYY, Ho CSH, Lim CR, et al., 2017. Functional near-infrared spectroscopy in psychiatry. BJPsych Adv, 23(5):324-330.

[16]Lakmache Y, Lassonde M, Gauthier S, et al., 1998. Interhemispheric disconnection syndrome in Alzheimer’s disease. Proc Natl Acad Sci USA, 95(15):9042-9046.

[17]Lehmann M, Madison C, Ghosh PM, et al., 2015. Loss of functional connectivity is greater outside the default mode network in nonfamilial early-onset Alzheimer’s disease variants. Neurobiol Aging, 36(10):2678-2686.

[18]Li Q, Liu JR, Wang W, et al., 2018. Disrupted coupling of large-scale networks is associated with relapse behaviour in heroin-dependent men. J Psychiatry Neurosci, 43(1):48-57.

[19]Liu AK, Belliveau JW, Dale AM, 1998. Spatiotemporal imaging of human brain activity using functional MRI constrained magnetoencephalography data: Monte Carlo simulations. Proc Natl Acad Sci USA, 95(15):8945-8950.

[20]Liu JX, Zhu MY, Feng CY, et al., 2015. Bamboo leaf extract improves spatial learning ability in a rat model with senile dementia. J Zhejiang Univ-Sci B (Biomed & Biotechnol), 16(7):593-601.

[21]Lu HN, Ma SL, Wong SWH, et al., 2017. Aberrant interhemispheric functional connectivity within default mode network and its relationships with neurocognitive features in cognitively normal APOE ε 4 elderly carriers. Int Psychogeriatr, 29(5):805-814.

[22]Lustig C, Snyder AZ, Bhakta M, et al., 2003. Functional deactivations: change with age and dementia of the Alzheimer type. Proc Natl Acad Sci USA, 100(24):14504-14509.

[23]McKhann GM, Knopman DS, Chertkow H, et al., 2011. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the national institute on aging-Alzheimer’s association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement, 7(3):263-269.

[24]Menon V, 2011. Large-scale brain networks and psychopathology: a unifying triple network model. Trends Cogn Sci, 15(10):483-506.

[25]Menon V, Uddin LQ, 2010. Saliency, switching, attention and control: a network model of insula function. Brain Struct Funct, 214(5-6):655-667.

[26]Mueller-Bierl BM, Uludag K, Pereira PL, et al., 2007. Magnetic field distribution and signal decay in functional MRI in very high fields (up to 9.4 T) using Monte Carlo diffusion modeling. Int J Biomed Imaging, 2007:70309.

[27]Orgeta V, Qazi A, Spector A, et al., 2015. Psychological treatments for depression and anxiety in dementia and mild cognitive impairment: systematic review and meta-analysis. Br J Psychiatry, 207(4):293-298.

[28]Perri R, Monaco M, Fadda L, et al., 2014. Neuropsychological correlates of behavioral symptoms in Alzheimer’s disease, frontal variant of frontotemporal, subcortical vascular, and Lewy body dementias: a comparative study. J Alzheimers Dis, 39(3):669-677.

[29]Petersen RC, Doody R, Kurz A, et al., 2001. Current concepts in mild cognitive impairment. Arch Neurol, 58(12):1985-1992.

[30]Russo MJ, Campos J, Vázquez S, et al., 2017. Adding recognition discriminability index to the delayed recall is useful to predict conversion from mild cognitive impairment to Alzheimer’s disease in the Alzheimer’s disease neuroimaging initiative. Front Aging Neurosci, 9:46.

[31]Stein MB, Simmons AN, Feinstein JS, et al., 2007. Increased amygdala and insula activation during emotion processing in anxiety-prone subjects. Am J Psychiatry, 164(2):318-327.

[32]Wang L, Li K, Zhang QE, et al., 2013. Interhemispheric functional connectivity and its relationships with clinical characteristics in major depressive disorder: a resting state fMRI study. PLoS ONE, 8(3):e60191.

[33]Wang ZQ, Wang JL, Zhang H, et al., 2015. Interhemispheric functional and structural disconnection in Alzheimer’s disease: a combined resting-state fMRI and DTI study. PLoS ONE, 10(5):e0126310.

[34]Xu P, Xu SP, Wang KZ, et al., 2016. Cognitive-enhancing effects of hydrolysate of polygalasaponin in SAMP8 mice. J Zhejiang Univ-Sci B (Biomed & Biotechnol), 17(7):503-514.

[35]Yu EY, Liao ZL, Tan YF, et al., 2017. High-sensitivity neuroimaging biomarkers for the identification of amnestic mild cognitive impairment based on resting-state fMRI and a triple network model. Brain Imaging Behav, online first.

[36]Zhan YF, Ma JH, Xu KB, et al., 2016. Impaired episodic memory network in subjects at high risk for Alzheimer’s disease. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, Orlando, FL, USA, p.4017-4020.

[37]Zhong YF, Huang LY, Cai SP, et al., 2014. Altered effective connectivity patterns of the default mode network in Alzheimer’s disease: an fMRI study. Neurosci Lett, 578: 171-175.

[38]Zhou Y, Milham M, Zuo XN, et al., 2013. Functional homotopic changes in multiple sclerosis with resting-state functional MR imaging. AJNR Am J Neuroradiol, 34(6):1180-1187.

[39]Zhu D, Liu GY, Lv Z, et al., 2014. Inverse associations of outdoor activity and vitamin D intake with the risk of Parkinson’s disease. J Zhejiang Univ-Sci B (Biomed & Biotechnol), 15(10):923-927.

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