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Clinical Article
Changes of cerebral functional hierarchy in AD patients based on cerebral-cerebellar connectivity gradients
HE Meirong  MO Xian  YOU Wanfang  SUN Ang  ZHANG Junran 

Cite this article as HE M R, MO X, YOU W F, et al. Changes of cerebral functional hierarchy in AD patients based on cerebral-cerebellar connectivity gradients[J]. Chin J Magn Reson Imaging, 2024, 15(5): 1-7. DOI:10.12015/issn.1674-8034.2024.05.001.


[Abstract] Objective To analyze the functional hierarchy of Alzheimer's disease (AD) cerebral cortex along the brain-cerebellar connectivity gradient and its altered interaction with the cerebellum and the association with cognitive dysfunction using a gradient-based approach.Materials and Methods A total of 33 AD patients and 46 age, sex matched healthy controls (HC) were included based on the publicly available database ANDI. The cerebral-cerebellar functional connectivity gradient of each subject was obtained by nonlinearly decomposing the cerebral-cerebellar resting-state functional connectivity matrix of all subjects, using gradient computation method. Two-sample t-tests were performed to analyze differences of cerebral-cerebellar gradient scores between groups, as well as group's comparisons of functional connectivity between abnormal regions of gradients and cerebellar , and correlation analyses were used to assess the correlation of abnormal gradient scores and connectivity values with scores on clinical scales.Results Compared with healthy controls, AD patients had locally altered gradient scores in the right inferior temporal gyrus (RITG) (t=4.71, P<0.001) which involved in higher cognitive functions, and further functional connectivity analyses based on the gradient-abnormal cerebral region as a seed point showed functional connectivity of RITG to the bilateral Crus Ⅱ region and extending to the Ⅶ B region of the cerebellum (right: t=-4.89, P<0.001; left: t=-4.98, P<0.001) was reduced. Clinical scale correlation analyses showed that connectivity gradient scores in gradient-abnormal brain regions were strongly correlated with Functional Activity Questionnaire (FAQ) scores (r=0.40, P=0.025) in AD patients.Conclusions The abnormal changes in the functional hierarchy of locoregional areas involved in higher cognitive function in AD patients and their reduced functional connectivity with bilateral cerebellar CrusⅡ and Ⅶ B regions may be one of the potential factors for cognitive impairment.
[Keywords] Alzheimer's disease;cerebral-cerebellar connection gradient;resting-state functional connectivity;magnetic resonance imaging;functional hierarchy

HE Meirong1, 2   MO Xian1   YOU Wanfang1   SUN Ang1   ZHANG Junran1*  

1 College of Electrical Engineering, Sichuan University, Chengdu 610065, China

2 College of Electrical Engineering, Northwest Minzu University, Lanzhou 730070, China

Corresponding author: ZHANG J R, E-mail: zhangjunran@126.com

Conflicts of interest   None.

Received  2023-11-02
Accepted  2024-04-30
DOI: 10.12015/issn.1674-8034.2024.05.001
Cite this article as HE M R, MO X, YOU W F, et al. Changes of cerebral functional hierarchy in AD patients based on cerebral-cerebellar connectivity gradients[J]. Chin J Magn Reson Imaging, 2024, 15(5): 1-7. DOI:10.12015/issn.1674-8034.2024.05.001.

[1]
MESULAM M M. From sensation to cognition[J]. Brain, 1998, 121(6): 1013-1052. DOI: 10.1093/brain/121.6.1013.
[2]
EICKHOFF S B, YEO B T T, GENON S. Imaging-based parcellations of the human brain[J]. Nat Rev Neurosci, 2018, 19(11): 672-686. DOI: 10.1038/s41583-018-0071-7.
[3]
MOGHIMI P, DANG A T, NETOFF T I, et al. A review on MR based human brain parcellation methods[C/OL]. Medicine, Computer Science, 2021 [2023-11-02]. https://arxiv.org/abs/2107.03475. DOI: 10.48550/arXiv.2107.03475.
[4]
MARGULIES D S, GHOSH S S, GOULAS A, et al. Situating the default-mode network along a principal gradient of macroscale cortical organization[J]. Proc Natl Acad Sci U S A, 2016, 113(44): 12574-12579. DOI: 10.1073/pnas.1608282113.
[5]
HONG S J, VOS D W R, BETHLEHEMethlehem R A I, et al. Atypical functional connectome hierarchy in autism[J/OL]. Nat Commun, 2019, 3, 10(1): 1022 [2023-11-02]. https://www.nature.com/articles/s41467-019-08944-1. DOI: 10.1038/s41467-019-08944-1.
[6]
BAYRAK S, KHALIL A A, VILLRINGER K, et al. The impact of ischemic stroke on connectivity gradients[J/OL]. Neuroimage Clin, 2019, 24: 101947 [2023-11-02]. https://www.sciencedirect.com/science/article/pii/S2213158219302979. DOI: 10.1016/j.nicl.2019.101947.
[7]
DONG D, LUO C, GUELL X, et al. Compression of cerebellar functional gradients in schizophrenia[J]. Schizophr Bull, 2020, 46(5): 1282-1295. DOI: 10.1093/schbul/sbaa016.
[8]
DONG D, YAO D, WANG Y, et al. Altered sensorimotor-to-transmodal hierarchical organization in schizophrenia[J/OL]. bioRxiv, 2020, 3: 980607 [2023-11-02]. https://www.biorxiv.org/content/10.1101/2020.03.06.980607v2. DOI: 10.1101/2020.03.06.980607.
[9]
LI Q, TAVAKOL S, ROYER J, et al. Atypical neural topographies underpin dysfunctional pattern separation in temporal lobe epilepsy[J]. Brain, 2021, 144(8): 2486-2498. DOI: 10.1093/brain/awab121.
[10]
XIA M, LIU J, MECHELLIA, et al. Connectome gradient dysfunction in major depression and its association with gene expression profiles[J]. Mol Psychiatry, 2022, 3, 27(3): 1384-1393. DOI: 10.1101/2020.10.24.352153.
[11]
LEE C H, PARK H, LEE M J, et al. Whole‐brain functional gradients reveal cortical and subcortical alterations in patients with episodic migraine[J]. Human Brain Mapping, 2023, 44(6): 2224-2233. DOI: 10.1002/hbm.26204.
[12]
DAI Z, LIN Q, LI T, et al. Disrupted structural and functional brain networks in Alzheimer's disease[J]. Neurobiol Aging, 2019, 75: 71-82. DOI: 10.1016/j.neurobiolaging.2018.11.005.
[13]
QUEVENCO F C, PRETI M G, VAN B J M, et al. Memory performance-related dynamic brain connectivity indicates pathological burden and genetic risk for Alzheimer's disease[J/OL]. Alzheimers Res Ther, 2017, 9(1): 24 [2023-11-02]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5374623. DOI: 10.1186/s13195-017-0249-7.
[14]
SINGH N A, MARTIN P R, GRAFF R J, et al. Altered within- and between-network functional connectivity in atypical Alzheimer's disease[J/OL]. Brain Communications, 2023, 5(4): fcad184 [2023-11-02]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10331277. DOI: 10.1093/braincomms/fcad184.
[15]
SCHMAHMANN J D, GUELL X, STOODLEY C J, et al. The theory and neuroscience of cerebellar cognition[J]. Annu Rev Neurosci, 2019, 42(1): 337-364. DOI: 10.1146/annurev-neuro-070918-050258.
[16]
KLAUS J, SCHUTTER D. Functional topography of anger and aggression in the human cerebellum[J/OL]. Neuroimage, 2021, 226: 117582 [2023-11-02]. https://www.sciencedirect.com/science/article/pii/S1053811920310673?via%3Dihub. DOI: 10.1016/j.neuroimage.2020.117582.
[17]
OREILLY J X, BECKMANN C F, TOMASSINI V, et al. Distinct and overlapping functional zones in the cerebellum defined by resting state functional connectivity[J]. Cerebral Cortex, 2010, 20(4): 953-965. DOI: 10.1093/cercor/bhp157.
[18]
ZHOU Z, ZHU R, SHAO W, et al. Changes in resting-state functional connectivity of cerebellum in amnestic mild cognitive impairment and Alzheimer's disease: A case-control study[J/OL]. Front Syst Neurosci, 2021, 15: 596221 [2023-11-02]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006280. DOI: 10.3389/fnsys.2021.596221.
[19]
OLIVITO G, SERRA L, MARRA C, et al. Cerebellar dentate nucleus functional connectivity with cerebral cortex in Alzheimer's disease and memory: a seed-based approach[J]. Neurobiol Aging, 2020, 89: 32-40. DOI: 10.1016/j.neurobiolaging.2019.10.026.
[20]
XIONG Y, YE C H , CHEN Y et al. Altered functional connectivity of basal ganglia in mild cognitive impairment and Alzheimer's disease[J/OL]. Brain Sciences, 2022, 12: 1555 [2023-11-02]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688931. DOI: 10.3390/brainsci12111555.
[21]
ZHENG W, LIUX, SONG H, et al. Altered functional connectivity of cognitive-related cerebellar subregions in Alzheimer's disease[J/OL]. Front Aging Neurosci, 2017, 9: 143 [2023-11-02]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5432635. DOI: 10.3389/fnagi.2017.00143.
[22]
QI Z, AN Y, ZHANG M, et al. Altered cerebro-cerebellar limbic network in AD spectrum: A resting-state fMRI study[J/OL]. Front Neural Circuits, 2019, 13: 72 [2023-11-02]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851020. DOI: 10.3389/fncir.2019.00072.
[23]
PAGEN L H G, VAN D V V G, GRONENSCHILD E, et al. Contributions of cerebro-cerebellar default mode connectivity patterns to memory performance in mild cognitive impairment[J]. J Alzheimers Dis, 2020, 75(2): 633-647. DOI: 10.3233/JAD-191127.
[24]
JIA X Z, WANG J, SUN H Y, et al. RESTplus: an improved toolkit for resting-state functional magnetic resonance imaging data processing[J]. Sci Bull, 2019, 64(14): 953-954. DOI: 10.1016/j.scib.2019.05.008.
[25]
TOMASI D, VOLKOW N D. Functional connectivity density mapping[J]. Proc Natl Acad Sci U S A, 2010, 107(21): 9885-9890. DOI: 10.1073/pnas.1001414107.
[26]
CHEN Z, ZHANG R, HUO H, et al. Functional connectome of human cerebellum[J/OL]. Neuroimage, 2022, 251: 119015 [2023-11-02]. https://www.sciencedirect.com/science/article/pii/S1053811922001446. DOI: 10.1016/j.neuroimage.2022.119015.
[27]
EKLUND A, NICHOLS T E, KNUTSSON H. Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates[J]. Proc Natl Acad Sci U S A, 2016, 113(28): 7900-7905. DOI: 10.1073/pnas.1602413113.
[28]
YAN C G, WANG X D, ZUO X N, et al. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging[J]. Neuroinformatics, 2016, 14(3): 339-351. DOI: 10.1007/s12021-016-9299-4.
[29]
LIN Y H, YOUNG I M, CONNER A K, et al. Anatomy and white matter connections of the inferior temporal gyrus[J]. World Neurosurg, 2020, 143: e656-e666 [2023-11-02]. https://doi.org/10.1016/j.wneu.2020.08.058. DOI: 10.1016/j.wneu.2020.08.058.
[30]
CONVIT A, CONVIT A, ASIS J M D, et al. Atrophy of the medial occipitotemporal, inferior, and middle temporal gyri in non-demented elderly predict decline to Alzheimer's disease[J]. Neurobiol Aging, 2000, 21: 19-26. DOI: 10.1016/s0197-4580(99)00107-4.
[31]
SNOWDEN S G, EBSHIANA A A, HYE A, et al. Neurotransmitter imbalance in the brain and Alzheimer's disease pathology[J]. J Alzheimers Dis, 2019, 72(1): 35-43. DOI: 10.3233/JAD-190577.
[32]
SCHEFF S W, PRICE D A, SCHMITT F A, et al. Synaptic loss in the inferior temporal gyrus in mild cognitive impairment and Alzheimer's disease[J]. J Alzheimers Dis, 2011, 24(3): 547-557. DOI: 10.3233/JAD-2011-101782.
[33]
LI H, JIA X, LI Y, et al. Aberrant amplitude of low-frequency fluctuation and degree centrality within the default mode network in patients with vascular mild cognitive impairment[J/OL]. Brain Sci, 2021, 11: 1534 [2023-11-02]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8615791. DOI: 10.3390/brainsci11111534.
[34]
WAN K, YIN W, TAN Y, et al. Brain gray matter volume mediated the correlation between plasma P-tau and cognitive function of early Alzheimer's disease in China: A cross-sectional observational study[J]. J Alzheimers Dis, 2023, 92(1): 1-13. DOI: 10.3233/JAD-221100.
[35]
DAI W Z, LIU L, ZHU M Z, et al. Morphological and structural network analysis of sporadic Alzheimer's disease brains based on the APOE4 gene[J]. J Alzheimers Dis, 2023, 91(3): 1035-1048. DOI: 10.3233/jad-220877.
[36]
WU Y Q, WANG Y N, ZHANG L J, et al. Regional homogeneity in patients with mild cognitive impairment: A resting-state functional magnetic resonance imaging study[J/OL]. Front Aging Neurosci, 2022, 14: 877281 [2023-11-02]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050296. DOI: 10.3389/fnagi.2022.877281.
[37]
LAI Z, ZHANG Q, LIANG L, et al. Efficacy and mechanism of moxibustion treatment on mild cognitive impairment patients: An fMRI study using ALFF[J/OL]. Front Mol Neurosci, 2022, 15: 852882 [2023-11-02]. https://pubmed.ncbi.nlm.nih.gov/35620445/. DOI: 10.3389/fnmol.2022.852882.
[38]
DIEN J. The neurocognitive basis of reading single words as seen through early latency ERPs: A model of converging pathways[J]. Biological Psychology, 2009, 80(1): 10-22. DOI: 10.1016/j.biopsycho.2008.04.013.
[39]
LIUS H, SIEMERS E, PRICE K, et al. Cognitive impairment precedes and predicts functional impairment in mild Alzheimer's disease[J]. J Alzheimers Dis, 2015, 47(1): 205-214. DOI: 10.3233/JAD-142508.
[40]
TONIOLO S, SERRA L, OLIVITO G, et al. Cerebellar white matter disruption in Alzheimer's disease patients: A diffusion tensor imaging study[J]. J Alzheimers Dis, 2020, 74: 615-624. DOI: 10.3233/JAD-191125.
[41]
ZHANG L, NI H, YU Z, et al. Investigation on the alteration of brain functional network and its role in the identification of mild cognitive impairment[J/OL]. Front Neurosci, 2020, 14: 558434 [2023-11-02]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7556272. DOI: 10.3389/fnins.2020.558434.
[42]
BUCKNER R L, KRIENEN F M, CASTLLANOS A, et al. The organization of the human cerebellum estimated by intrinsic functional connectivity[J]. J Neurophysiol, 2011, 106(5): 2322-2345. DOI: 10.1152/jn.00339.2011.
[43]
HABAS C, KAMDAR N, NGUYEN D, et al. Distinct cerebellar contributions to intrinsic connectivity networks[J]. J Neurosci, 2009, 29(26): 8586-8594. DOI: 10.1523/JNEUROSCI.1868-09.2009.
[44]
SHELINE Y I, RAICHLE M E, SNYDER A Z, et al. Amyloid plaques disrupt resting state default mode network connectivity in cognitively normal elderly[J]. Biol Psychiatry, 2010, 67(6): 584-587. https://doi.org/10.1016/j.biopsych.2009.08.024. DOI: 10.1016/j.biopsych.2009.08.024.
[45]
GUO C C, TAN R, HODGES J R, et al. Network-selective vulnerability of the human cerebellum to Alzheimer's disease and frontotemporal dementia[J]. Brain, 2016, 139(Pt 5): 1527-1538. DOI: 10.1093/brain/aww003.
[46]
BUCKNER R L, ANDREWS H J R, SCHACTER D L. The brain's default network: Anatomy, function and relevance to disease[J]. Ann N Y Acad Sci, 2008, 1124(1): 1-38. DOI: 10.1196/annals.1440.011.
[47]
SCHMAHMANN J D, GUELL X, STOODLEY C J, et al. The theory and neuroscience of cerebellar cognition[J]. Annu Rev Neurosci, 2019, 42: 337-364. DOI: 10.1146/annurev-neuro-070918-050258.
[48]
HOFER A, SIEDENTOPF C M, ISCHEBECK A, et al. Sex differences in brain activation patterns during processing of positively and negatively valenced emotional words[J]. Psychol Med, 2007, 37(1): 109-119. DOI: 10.1017/S0033291706008919
[49]
LIE C H, SPECHT K, MARSHALL J C, et al. Using fMRI to decompose the neural processes underlying the Wisconsin Card Sorting Test[J]. Neuroimage, 2006, 30(3): 1038-1049. DOI: 10.1016/j.neuroimage.2005.10.031.
[50]
COOPERRIDER J, FURMAGA H, PLOW E, et al. Chronic deep cerebellar stimulation promotes long-term potentiation, microstructural plasticity, and reorganization of perilesional cortical representation in a rodent model[J]. J Neurosci, 2014, 34(27): 9040-9050. DOI: 10.1523/JNEUROSCI.0953-14.2014.
[51]
PASSOT J B, SHEYNIKHOVICH D, DUVELLE E, et al. Contribution of cerebellar sensorimotor adaptation to hippocampal spatial memory[J/OL]. PLoS One, 2012, 7(4): e32560 [2023-11-02]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3317659. DOI: 10.1371/journal.pone.0032560.
[52]
CATHERINE J S, JEREMY S D. Evidence for topographic organization in the cerebellum of motor control versus cognitive and affective processing[J]. Cortex, 2010, 46(7): 831-844. DOI: 10.1016/j.cortex.2009.11.008.
[53]
LI T, LIAO Z, MAO Y, et al. Temporal dynamic changes of intrinsic brain activity in Alzheimer's disease and mild cognitive impairment patients: a resting-state functional magnetic resonance imaging study[J/OL]. Ann Transl Med, 2021, 9(1): 63 [2023-11-02]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7859807. DOI: 10.21037/atm-20-7214.

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