重度抑郁障碍患者丘脑皮层环路的动态功能连接异常

郑炜豪; 张芹; 赵子阳; 张鹏飞; 赵磊磊; 王晓敏; 杨淞宇; 张静; 姚志军; 胡斌

doi:10.1631/jzus.B2300401

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Research Article | Updated：2024-05-14

重度抑郁障碍患者丘脑皮层环路的动态功能连接异常
Aberrant dynamic functional connectivity of thalamocortical circuitry in major depressive disorder
浙江大学学报（英文版）（B辑：生物医学和生物技术） 2024年页码：1-21
Affiliations：

1.Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
2.Second Clinical School, Lanzhou University, Lanzhou 730030, China
3.Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China
4.Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China
5.School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
6.CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
7.Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of Semiconductors, Chinese Academy of Sciences, Lanzhou 730000, China
Funds：

the Science and Technology Innovation 2030-Major Projects(2021ZD0202000;2021ZD0200800;2021ZD0200701);the National Key Research and Development Program of China(2019YFA0706200);the National Natural Science Foundation of China(62227807;62202212;U21A20520;U22A2033);the Science and Technology Program of Gansu Province(23YFGA0004)
DOI：10.1631/jzus.B2300401
中图分类号：
CSTR：
网络出版日期： 2024-04-07 ，

收稿日期： 2023-06-05 ，

修回日期： 2023-09-24 ，

郑炜豪,张芹,赵子阳等.重度抑郁障碍患者丘脑皮层环路的动态功能连接异常[J].浙江大学学报（英文版）（B辑：生物医学和生物技术）,

Weihao ZHENG, Qin ZHANG, Ziyang ZHAO, et al. Aberrant dynamic functional connectivity of thalamocortical circuitry in major depressive disorder[J/OL]. Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology), 2024,1-21.
郑炜豪,张芹,赵子阳等.重度抑郁障碍患者丘脑皮层环路的动态功能连接异常[J].浙江大学学报（英文版）（B辑：生物医学和生物技术）, DOI：10.1631/jzus.B2300401.

Weihao ZHENG, Qin ZHANG, Ziyang ZHAO, et al. Aberrant dynamic functional connectivity of thalamocortical circuitry in major depressive disorder[J/OL]. Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology), 2024,1-21. DOI： 10.1631/jzus.B2300401.

摘要

丘脑皮层环路对情绪和认知具有重大影响。研究表明，重度抑郁障碍患者存在丘脑皮层功能连接异常，主要表现为区域依赖性的低连接或超连接。然而，重度抑郁障碍患者丘脑皮层环路动态功能连接的潜在异常目前尚不清楚。因此，基于48名重度抑郁障碍患者和57名健康对照的静息态功能磁共振成像数据，本研究评估了10个丘脑亚区和大脑皮层之间的动态功能连接变化，进而探究重度抑郁障碍患者丘脑皮层环路的动态交互模式。利用动态偏侧性分析探究了丘脑皮层系统的功能偏侧性随时间的动态变化。此外，还计算了丘脑皮层环路的动态功能连接特征与临床量表评分之间的相关性。本研究确定了4个反复出现的丘脑皮层功能连接状态。与健康对照组相比，重度抑郁障碍患者在与初级皮层网络具有较强负相关的连接状态下，时间分数和状态转换概率显著降低。此外，重度抑郁障碍患者丘脑皮层系统的功能偏侧性表现出更大的波动。丘脑-子网络分析进一步发现重度抑郁障碍患者中丘脑与高阶皮层网络之间连接的变异性异常增加，并且与背侧注意网络和默认模式网络相关的丘脑皮层功能连接变异性与患者的症状严重程度之间存在显著的相关性。本研究综合探究了重度抑郁障碍患者丘脑皮层环路的动态功能连接变化模式。研究结果表明，丘脑与初级和高阶皮层网络之间动态功能连接的异质性改变可能有助于表征重度抑郁障碍患者的感觉和认知处理缺陷。

Abstract

Thalamocortical circuitry has a substantial impact on emotion and cognition. Previous studies have demonstrated alterations in thalamocortical functional connectivity (FC)

characterized by region-dependent hypo- or hyper-connectivity

among individuals with major depressive disorder (MDD). However

the dynamical reconfiguration of the thalamocortical system over time and potential abnormalities in dynamic thalamocortical connectivity associated with MDD remain unclear. Hence

we analyzed dynamic FC (dFC) between ten thalamic subregions and seven cortical subnetworks from resting-state functional magnetic resonance images of 48 patients with MDD and 57 healthy controls (HCs) to investigate time-varying changes in thalamocortical FC in patients with MDD. Moreover

dynamic laterality analysis was conducted to examine the changes in functional lateralization of the thalamocortical system over time. Correlations between the dynamic measures of thalamocortical FC and clinical assessment were also calculated. We identified four dynamic states of thalamocortical circuitry wherein patients with MDD exhibited decreased fractional time and reduced transitions within a negative connectivity state that showed strong correlations with primary cortical networks

compared with the HCs. In addition

MDD patients also exhibited increased fluctuations in functional laterality in the thalamocortical system across the scan duration. The thalamo-subnetwork analysis unveiled abnormal dFC variability involving higher-order cortical networks in the MDD cohort. Significant correlations were found between increased dFC variability with dorsal attention and default mode networks and the severity of symptoms. Our study comprehensively investigated the pattern of alteration of the thalamocortical dFC in MDD patients. The heterogeneous alterations of dFC between the thalamus and both primary and higher-order cortical networks may help characterize the deficits of sensory and cognitive processing in MDD.

关键词

重度抑郁障碍静息态功能磁共振成像丘脑皮层环路动态功能连接动态偏侧性

Keywords

Major depressive disorderResting-state functional magnetic resonance imagingThalamocortical circuitryDynamic functional connectivityDynamic laterality

references

Aggarwal CC, Hinneburg A, Keim DA, 2001. On the surprising behavior of distance metrics in high dimensional space. Database Theory—ICDT 2001, Berlin, Heidelberg. Springer Berlin Heidelberg, p.420-434. https://doi.org/10.1007/3-540-44503-X_27https://doi.org/10.1007/3-540-44503-X_27

Allen EA, Damaraju E, Plis SM, et al., 2014. Tracking whole-brain connectivity dynamics in the resting state. Cereb Cortex, 24(3):663-676. https://doi.org/10.1093/cercor/bhs352https://doi.org/10.1093/cercor/bhs352

Arbabshirani MR, Damaraju E, Phlypo R, et al., 2014. Impact of autocorrelation on functional connectivity. NeuroImage, 102(Part 2):294-308. https://doi.org/10.1016/j.neuroimage.2014.07.045https://doi.org/10.1016/j.neuroimage.2014.07.045

Avants B, Tustison NJ, Song G, 2009. Advanced Normalization Tools: V1.0. Insight J, July-December. https://doi.org/10.54294/uvnhinhttps://doi.org/10.54294/uvnhin

Behrens TEJ, Johansen-Berg H, Woolrich MW, et al., 2003. Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nat Neurosci, 6(7):750-757. https://doi.org/10.1038/nn1075https://doi.org/10.1038/nn1075

Bos DJ, Oranje B, Achterberg M, et al., 2017. Structural and functional connectivity in children and adolescents with and without attention deficit/hyperactivity disorder. J Child Psychol Psychiatry, 58(7):810-818. https://doi.org/10.1111/jcpp.12712https://doi.org/10.1111/jcpp.12712

Brown EC, Clark DL, Hassel S, et al., 2017. Thalamocortical connectivity in major depressive disorder. J Affect Disord, 217:125-131. https://doi.org/10.1016/j.jad.2017.04.004https://doi.org/10.1016/j.jad.2017.04.004

Bruder GE, Stewart JW, McGrath PJ, 2017. Right brain, left brain in depressive disorders: clinical and theoretical implications of behavioral, electrophysiological and neuroimaging findings. Neurosci Biobehav Rev, 78:178-191. https://doi.org/10.1016/j.neubiorev.2017.04.021https://doi.org/10.1016/j.neubiorev.2017.04.021

Calhoun VD, Miller R, Pearlson G, et al., 2014. The chronnectome: time-varying connectivity networks as the next frontier in fMRI data discovery. Neuron, 84(2):262-274. https://doi.org/10.1016/j.neuron.2014.10.015https://doi.org/10.1016/j.neuron.2014.10.015

Chen FF, Lv XY, Fang JL, et al., 2021. Body-mind relaxation meditation modulates the thalamocortical functional connectivity in major depressive disorder: a preliminary resting-state fMRI study. Transl Psychiatry, 11:546. https://doi.org/10.1038/s41398-021-01637-8https://doi.org/10.1038/s41398-021-01637-8

Chen QL, Beaty RE, Cui ZX, et al., 2019. Brain hemispheric involvement in visuospatial and verbal divergent thinking. NeuroImage, 202:116065. https://doi.org/10.1016/j.neuroimage.2019.116065https://doi.org/10.1016/j.neuroimage.2019.116065

Chen SY, Langley J, Chen XC, et al., 2016. Spatiotemporal modeling of brain dynamics using resting-state functional magnetic resonance imaging with Gaussian Hidden Markov model. Brain Connect, 6(4):326-334. https://doi.org/10.1089/brain.2015.0398https://doi.org/10.1089/brain.2015.0398

Choe AS, Nebel MB, Barber AD, et al., 2017. Comparing test-retest reliability of dynamic functional connectivity methods. NeuroImage, 158:155-175. https://doi.org/10.1016/j.neuroimage.2017.07.005https://doi.org/10.1016/j.neuroimage.2017.07.005

Choi J, Jeong B, Lee SW, et al., 2013. Aberrant development of functional connectivity among resting state-related functional networks in medication-naive ADHD children. PLoS ONE, 8(12):e83516. https://doi.org/10.1371/journal.pone.0083516https://doi.org/10.1371/journal.pone.0083516

Ding YD, Yang R, Yan CG, et al., 2021. Disrupted hemispheric connectivity specialization in patients with major depressive disorder: evidence from the REST-meta-MDD Project. J Affect Disord, 284:217-228. https://doi.org/10.1016/j.jad.2021.02.030https://doi.org/10.1016/j.jad.2021.02.030

Doron KW, Bassett DS, Gazzaniga MS, 2012. Dynamic network structure of interhemispheric coordination. Proc Natl Acad Sci USA, 109(46):18661-18668. https://doi.org/10.1073/pnas.1216402109https://doi.org/10.1073/pnas.1216402109

Du HH, Shen X, Du XY, et al., 2022. Altered visual cortical excitability is associated with psychopathological symptoms in major depressive disorder. Front Psychiatry, 13:844434. https://doi.org/10.3389/fpsyt.2022.844434https://doi.org/10.3389/fpsyt.2022.844434

Dupire A, Kant P, Mons N, et al., 2013. A role for anterior thalamic nuclei in affective cognition: interaction with environmental conditions. Hippocampus, 23(5):392-404. https://doi.org/10.1002/hipo.22098https://doi.org/10.1002/hipo.22098

Fischl B, 2012. FreeSurfer. NeuroImage, 62(2):774-781. https://doi.org/10.1016/j.neuroimage.2012.01.021https://doi.org/10.1016/j.neuroimage.2012.01.021

Fox MD, Snyder AZ, Vincent JL, et al., 2005. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci USA, 102(27):9673-9678. https://doi.org/10.1073/pnas.0504136102https://doi.org/10.1073/pnas.0504136102

Fox MD, Zhang DY, Snyder AZ, et al., 2009. The global signal and observed anticorrelated resting state brain networks. J Neurophysiol, 101(6):3270-3283. https://doi.org/10.1152/jn.90777.2008https://doi.org/10.1152/jn.90777.2008

Gotlib IH, Jonides J, Buschkuehl M, et al., 2011. Memory for affectively valenced and neutral stimuli in depression: evidence from a novel matching task. Cognit Emotion, 25(7):1246-1254. https://doi.org/10.1080/02699931.2010.538374https://doi.org/10.1080/02699931.2010.538374

Groh A, Krieger P, Mease RA, et al., 2018. Acute and chronic pain processing in the thalamocortical system of humans and animal models. Neuroscience, 387:58-71. https://doi.org/10.1016/j.neuroscience.2017.09.042https://doi.org/10.1016/j.neuroscience.2017.09.042

Güntürkün O, Ströckens F, Ocklenburg S, 2020. Brain lateralization: a comparative perspective. Physiol Rev, 100(3):1019-1063. https://doi.org/10.1152/physrev.00006.2019https://doi.org/10.1152/physrev.00006.2019

Hakimdavoodi H, Amirmazlaghani M, 2020. Using autoregressive-dynamic conditional correlation model with residual analysis to extract dynamic functional connectivity. J Neural Eng, 17(3):035008. https://doi.org/10.1088/1741-2552/ab965bhttps://doi.org/10.1088/1741-2552/ab965b

Hamilton JP, Chen MC, Waugh CE, et al., 2015. Distinctive and common neural underpinnings of major depression, social anxiety, and their comorbidity. Soc Cogn Affect Neurosci, 10(4):552-560. https://doi.org/10.1093/scan/nsu084https://doi.org/10.1093/scan/nsu084

Hamilton M, 1967. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol, 6(4):278-296. https://doi.org/10.1111/j.2044-8260.1967.tb00530.xhttps://doi.org/10.1111/j.2044-8260.1967.tb00530.x

Hutchison RM, Womelsdorf T, Gati JS, et al., 2013. Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques. Hum Brain Mapp, 34(9):2154-2177. https://doi.org/10.1002/hbm.22058https://doi.org/10.1002/hbm.22058

Iglesias JE, Insausti R, Lerma-Usabiaga G, et al., 2018. A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology. NeuroImage, 183:314-326. https://doi.org/10.1016/j.neuroimage.2018.08.012https://doi.org/10.1016/j.neuroimage.2018.08.012

Kaiser RH, Andrews-Hanna JR, Wager TD, et al., 2015. Large-scale network dysfunction in major depressive disorder: a meta-analysis of resting-state functional connectivity. JAMA Psychiatry, 72(6):603-611. https://doi.org/10.1001/jamapsychiatry.2015.0071https://doi.org/10.1001/jamapsychiatry.2015.0071

Kang LJ, Zhang AX, Sun N, et al., 2018. Functional connectivity between the thalamus and the primary somatosensory cortex in major depressive disorder: a resting-state fMRI study. BMC Psychiatry, 18:339. https://doi.org/10.1186/s12888-018-1913-6https://doi.org/10.1186/s12888-018-1913-6

Klingner CM, Langbein K, Dietzek M, et al., 2014. Thalamocortical connectivity during resting state in schizophrenia. Eur Arch Psychiatry Clin Neurosci, 264(2):111-119. https://doi.org/10.1007/s00406-013-0417-0https://doi.org/10.1007/s00406-013-0417-0

Kong QM, Qiao H, Liu CZ, et al., 2018. Aberrant intrinsic functional connectivity in thalamo-cortical networks in major depressive disorder. CNS Neurosci Ther, 24(11):1063-1072. https://doi.org/10.1111/cns.12831https://doi.org/10.1111/cns.12831

Lenoski B, Baxter LC, Karam LJ, et al., 2008. On the perform

ance of autocorrelation estimation algorithms for fMRI analysis. IEEE J Sel Top Signal Process, 2(6):828-838. https://doi.org/10.1109/JSTSP.2008.2007819https://doi.org/10.1109/JSTSP.2008.2007819

Lindquist MA, Xu YT, Nebel MB, et al., 2014. Evaluating dynamic bivariate correlations in resting-state fMRI: a comparison study and a new approach. NeuroImage, 101:531-546. https://doi.org/10.1016/j.neuroimage.2014.06.052https://doi.org/10.1016/j.neuroimage.2014.06.052

Liu F, Wang YF, Li ML, et al., 2017. Dynamic functional network connectivity in idiopathic generalized epilepsy with generalized tonic-clonic seizure. Hum Brain Mapp, 38(2):957-973. https://doi.org/10.1002/hbm.23430https://doi.org/10.1002/hbm.23430

Liu PH, Tu HW, Zhang AX, et al., 2021. Brain functional alterations in MDD patients with somatic symptoms: a resting-state fMRI study. J Affect Disord, 295:788-796. https://doi.org/10.1016/j.jad.2021.08.143https://doi.org/10.1016/j.jad.2021.08.143

Liu X, Zhang NY, Chang C, et al., 2018. Co-activation patterns in resting-state fMRI signals. NeuroImage, 180:485-494. https://doi.org/10.1016/j.neuroimage.2018.01.041https://doi.org/10.1016/j.neuroimage.2018.01.041

Llinás RR, Paré D, 1991. Of dreaming and wakefulness. Neuroscience, 44(3):521-535. https://doi.org/10.1016/0306-4522(91)90075-Yhttps://doi.org/10.1016/0306-4522(91)90075-Y

Llinás RR, Ribary U, Jeanmonod D, et al., 1999. Thalamocortical dysrhythmia: a neurological and neuropsychiatric syndrome characterized by magnetoencephalography. Proc Natl Acad Sci USA, 96(26):15222-15227. https://doi.org/10.1073/pnas.96.26.15222https://doi.org/10.1073/pnas.96.26.15222

Llinás RR, Urbano FJ, Leznik E, et al., 2005. Rhythmic and dysrhythmic thalamocortical dynamics: GABA systems and the edge effect. Trends Neurosci, 28(6):325-333. https://doi.org/10.1016/j.tins.2005.04.006https://doi.org/10.1016/j.tins.2005.04.006

Long YC, Cao HY, Yan CG, et al., 2020. Altered resting-state dynamic functional brain networks in major depressive disorder: findings from the REST-meta-MDD consortium. NeuroImage Clin, 26:102163. https://doi.org/10.1016/j.nicl.2020.102163https://doi.org/10.1016/j.nicl.2020.102163

Lu FM, Chen YC, Cui Q, et al., 2023. Shared and distinct patterns of dynamic functional connectivity variability of thalamo-cortical circuit in bipolar depression and major depressive disorder. Cereb Cortex, 33(11):6681-6692. https://doi.org/10.1093/cercor/bhac534https://doi.org/10.1093/cercor/bhac534

Lui S, Wu QZ, Qiu LH, et al., 2011. Resting-state functional connectivity in treatment-resistant depression. Am J Psychiatry, 168(6):642-648. https://doi.org/10.1176/appi.ajp.2010.10101419https://doi.org/10.1176/appi.ajp.2010.10101419

Lund TE, Madsen KH, Sidaros K, et al., 2006. Non-white noise in fMRI: does modelling have an impact? NeuroImage, 29(1):54-66. https://doi.org/10.1016/j.neuroimage.2005.07.005https://doi.org/10.1016/j.neuroimage.2005.07.005

McLeod KR, Langevin LM, Goodyear BG, et al., 2014. Functional connectivity of neural motor networks is disrupted in children with developmental coordination disorder and attention-deficit/hyperactivity disorder. NeuroImage Clin, 4:566-575. https://doi.org/10.1016/j.nicl.2014.03.010https://doi.org/10.1016/j.nicl.2014.03.010

Miller KD, Pinto DJ, Simons DJ, 2001. Processing in layer 4 of the neocortical circuit: new insights from visual and somatosensory cortex. Curr Opin Neurobiol, 11(4):‍488-497. https://doi.org/10.1016/S0959-4388(00)00239-7https://doi.org/10.1016/S0959-4388(00)00239-7

Murata Y, Colonnese MT, 2018. Thalamus controls development and expression of arousal states in visual cortex. J Neurosci, 38(41):8772-8786. https://doi.org/10.1523/JNEUROSCI.1519-18.2018https://doi.org/10.1523/JNEUROSCI.1519-18.2018

Otte C, Gold SM, Penninx BW, et al., 2016. Major depressive disorder. Nat Rev Dis Primers, 2:16065. https://doi.org/10.1038/nrdp.2016.65https://doi.org/10.1038/nrdp.2016.65

Pratt JA, Morris BJ, 2015. The thalamic reticular nucleus: a functional hub for thalamocortical network dysfunction in schizophrenia and a target for drug discovery. J Psychopharmacol, 29(2):127-137. https://doi.org/10.1177/0269881114565805https://doi.org/10.1177/0269881114565805

Purdon PL, Weisskoff RM, 1998. Effect of temporal autocorrelation due to physiological noise and stimulus paradigm on voxel-level false-positive rates in fMRI. Hum Brain Mapp, 6(4):239-249. https://doi.org/10.1002/(SICI)1097-0193(1998)6:4<239::AID-HBM4>3.0.CO;2-4https://doi.org/10.1002/(SICI)1097-0193(1998)6:4<239::AID-HBM4>3.0.CO;2-4

Rosen AFG, Roalf DR, Ruparel K, et al., 2018. Quantitative assessment of structural image quality. NeuroImage, 169:407-418. https://doi.org/10.1016/j.neuroimage.2017.12.059https://doi.org/10.1016/j.neuroimage.2017.12.059

Saalmann YB, 2014. Intralaminar and medial thalamic influence on cortical synchrony, information transmission and cognition. Front Syst Neurosci, 8:83. https://doi.org/10.3389/fnsys.2014.00083https://doi.org/10.3389/fnsys.2014.00083

Sacchet MD, Ho TC, Connolly CG, et al., 2016. Large-scale hypoconnectivity between resting-state functional networks in unmedicated adolescent major depressive disorder. Neuropsychopharmacology, 41(12):2951-2960. https://doi.org/10.1038/npp.2016.76https://doi.org/10.1038/npp.2016.76

Sanacora G, Treccani G, Popoli M, 2012. Towards a glutamate hypothesis of depression: an emerging frontier of neuropsychopharmacology for mood disorders. Neuropharmacology, 62(1):63-77. https://doi.org/10.1016/j.neuropharm.2011.07.036https://doi.org/10.1016/j.neuropharm.2011.07.036

Schaefer A, Kong R, Gordon EM, et al., 2018. Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI. Cereb Cortex, 28(9):‍3095-3114. https://doi.org/10.1093/cercor/bhx179https://doi.org/10.1093/cercor/bhx179

Sendi MSE, Zendehrouh E, Sui J, et al., 2021. Abnormal dynamic functional network connectivity estimated from default mode network predicts symptom severity in major depressive disorder. Brain Connect, 11(10):838-849. https://doi.org/10.1089/brain.2020.0748https://doi.org/10.1089/brain.2020.0748

Sherman SM, 2007. The thalamus is more than just a relay. Curr Opin Neurobiol, 17(4):417-422. https://doi.org/10.1016/j.conb.2007.07.003https://doi.org/10.1016/j.conb.2007.07.003

Shine JM, 2019. Neuromodulatory influences on integration and segregation in the brain. Trends Cogn Sci, 23(7):‍572-583. https://doi.org/10.1016/j.tics.2019.04.002https://doi.org/10.1016/j.tics.2019.04.002

Steiner L, Federspiel A, Slavova N, et al., 2020. Functional topography of the thalamo-cortical system during development and its relation to cognition. NeuroImage, 223:117361. https://doi.org/10.1016/j.neuroimage.2020.117361https://doi.org/10.1016/j.neuroimage.2020.117361

Steriade M, 2001. Impact of network activities on neuronal properties in corticothalamic systems. J Neurophysiol, 86(1):1-39. https://doi.org/10.1152/jn.2001.86.1.1https://doi.org/10.1152/jn.2001.86.1.1

Sun WZ, Tan ZC, Mensh BD, et al., 2016. Thalamus provides layer 4 of primary visual cortex with orientation- and direction-tuned inputs. Nat Neurosci, 19(2):308-315. https://doi.org/10.1038/nn.4196https://doi.org/10.1038/nn.4196

Sweeney-Reed CM, Buentjen L, Voges J, et al., 2021. The role of the anterior nuclei of the thalamus in human memory processing. Neurosci Biobehav Rev, 126:146-158. https://doi.org/10.1016/j.neubiorev.2021.02.046https://doi.org/10.1016/j.neubiorev.2021.02.046

Tadayonnejad R, Yang SL, Kumar A, et al., 2015. Clinical, cognitive, and functional connectivity correlations of resting-state intrinsic brain activity alterations in unmedicated depression. J Affect Disord, 172:241-250. https://doi.org/10.1016/j.jad.2014.10.017https://doi.org/10.1016/j.jad.2014.10.017

Vaccarino AL, Sills TL, Evans KR, et al., 2009. Multiple pain complaints in patients with major depressive disorder. Psychosom Med, 71(2):159-162. https://doi.org/10.1097/psy.0b013e3181906572https://doi.org/10.1097/psy.0b013e3181906572

Wang R, Liu MX, Cheng XH, et al., 2021. Segregation, integration, and balance of large-scale resting brain networks configure different cognitive abilities. Proc Natl Acad Sci USA, 118(23):e2022288118. https://doi.org/10.1073/pnas.2022288118https://doi.org/10.1073/pnas.2022288118

Weeland CJ, Vriend C, van der Werf Y, et al., 2022a. Thalamic subregions and obsessive-compulsive symptoms in 2,500 children from the general population. J Am Acad Child Adolesc Psychiatry, 61(2):321-330. https://doi.org/10.1016/j.jaac.2021.05.024https://doi.org/10.1016/j.jaac.2021.05.024

Weeland CJ, Kasprzak S, de Joode NT, et al., 2022b. The thalamus and its subnuclei—a gateway to obsessive-compulsive disorder. Transl Psychiatry, 12:70. https://doi.org/10.1038/s41398-022-01823-2https://doi.org/10.1038/s41398-022-01823-2

Wei Q, Bai TJ, Brown EC, et al., 2020. Thalamocortical connectivity in electroconvulsive therapy for major depressive disorder. J Affect Disord, 264:163-171. https://doi.org/10.1016/j.jad.2019.11.120https://doi.org/10.1016/j.jad.2019.11.120

Williams JBW, 1988. A structured interview guide for the Hamilton Depression Rating Scale. Arch Gen Psychiatry, 45(8):742-747. https://doi.org/10.1001/archpsyc.1988.01800320058007https://doi.org/10.1001/archpsyc.1988.01800320058007

Wu XR, Kong XZ, Vatansever D, et al., 2022. Dynamic changes in brain lateralization correlate with human cognitive performance. PLoS Biol, 20(3):e3001560. https://doi.org/10.1371/journal.pbio.3001560https://doi.org/10.1371/journal.pbio.3001560

Xue SW, Wang D, Tan Z, et al., 2019. Disrupted brain entropy and functional connectivity patterns of thalamic subregions in major depressive disorder. Neuropsychiatr Dis Treat, 15:2629-2638. https://doi.org/10.2147/ndt.s220743https://doi.org/10.2147/ndt.s220743

Yan CG, Zang YF, 2010. DPARSF: a MATLAB toolbox for “pipeline” data analysis of resting-state fMRI. Front Syst Neurosci, 4:13. https://doi.org/10.3389/fnsys.2010.00013https://doi.org/10.3389/fnsys.2010.00013

Yao ZJ, Shi J, Zhang Z, et al., 2019a. Altered dynamic functional connectivity in weakly-connected state in major depressive disorder. Clin Neurophysiol, 130(11):2096-2104. https://doi.org/10.1016/j.clinph.2019.08.009https://doi.org/10.1016/j.clinph.2019.08.009

Yao ZJ, Zou Y, Zheng WH, et al., 2019b. Structural alterations of the brain preceded functional alterations in major depressive disorder patients: evidence from multimodal connectivity. J Affect Disord, 253:107-117. https://doi.org/10.1016/j.jad.2019.04.064https://doi.org/10.1016/j.jad.2019.04.064

Yu YM, Zheng WH, Tan XF, et al., 2021. Microstructural profiles of thalamus and thalamocortical connectivity in patients with disorder of consciousness. J Neurosci Res, 99(12):3261-3273. https://doi.org/10.1002/jnr.24921https://doi.org/10.1002/jnr.24921

Yuan R, Di X, Taylor PA, et al., 2016. Functional topography of the thalamocortical system in human. Brain Struct Funct, 221(4):1971-1984. https://doi.org/10.1007/s00429-015-1018-7https://doi.org/10.1007/s00429-015-1018-7

Zhang DY, Snyder AZ, Shimony JS, et al., 2010. Noninvasive functional and structural connectivity mapping of the human thalamocortical system. Cereb Cortex, 20(5):‍1187-1194. https://doi.org/10.1093/cercor/bhp182https://doi.org/10.1093/cercor/bhp182

Zhao ZY, Zhang YH, Chen N, et al., 2022. Altered temporal reachability highlights the role of sensory perception systems in major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry, 112:110426. https://doi.org/10.1016/j.pnpbp.2021.110426https://doi.org/10.1016/j.pnpbp.2021.110426

Zheng WH, Tan XF, Liu TT, et al., 2021. Individualized thalamic parcellation reveals alterations in shape and microstructure of thalamic nuclei in patients with disorder of consciousness. Cereb Cortex Commun, 2(2):tgab024. https://doi.org/10.1093/texcom/tgab024https://doi.org/10.1093/texcom/tgab024

Zhi DM, Calhoun VD, Lv LX, et al., 2018. Aberrant dynamic functional network connectivity and graph properties in major depressive disorder. Front Psychiatry, 9:339. https://doi.org/10.3389/fpsyt.2018.00339https://doi.org/10.3389/fpsyt.2018.00339

Zhu FR, Liu F, Guo WB, et al., 2018. Disrupted asymmetry of inter- and intra-hemispheric functional connectivity in patients with drug-naive, first-episode schizophrenia and their unaffected siblings. eBioMedicine, 36:429-435. https://doi.org/10.1016/j.ebiom.2018.09.012https://doi.org/10.1016/j.ebiom.2018.09.012

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