Keywords
Functional connectivity
Resting-state functional MRI
Graph theory
Independent component analysis
Submitted : 2025-07-20
Accepted : 2025-08-04
Published : 2025-08-19
Abstract
Background: Resting-state functional connectivity (FC) has been nominated as an effective method for elucidating the neural mechanisms underlying chronic pain. To date, whole-brain FC alterations in chronic knee osteoarthritis (KOA) remain largely unknown. Purpose: To investigate the functional connectivity patterns across the entire brain in patients with knee osteoarthritis (KOA) using resting-state functional magnetic resonance imaging (rs-fMRI). Methods: The current rs-fMRI analysis included 56 well-characterized KOA patients and 20 healthy controls (HCs), with data obtained from OpenNeuro. To identify aberrant topological organization in the brains of KOA patients, the study employed a graph theoretical approach. Additionally, the independent component analysis was conducted to characterize both intra-network and inter-network brain connectivity in these individuals. Results: Both the KOA cohort and healthy control cohort exhibited small-world characteristics in brain functional networks. Additionally, compared to HCs, KOA patients showed altered global properties, specifically characterized by reduced global efficiency and increased assortativity. At the nodal level, the KOA patients exhibited decreased degree centrality and betweenness centrality in the right thalamus. Furthermore, independent component analysis indicated abnormal FC within the anterior default mode network (DMN) and salience network (SN) in this patient cohort. The inter-network interactions did not show intergroup differences after multiple-test correction. Conclusion: The widespread functional abnormalities observed from a whole-brain network perspective in subjects with KOA pain may provide more comprehensive insights and reinforce the grasp of the neural mechanisms underpinning KOA.
References
Felson D, Lawrence R, Dieppe P, et al., 2000, Osteoarthritis: New Insights. Part 1: The Disease and Its Risk Factors. Ann Intern Med, 133: 635–646.
Loeser R, Goldring S, Scanzello C, et al., 2012, Osteoarthritis: A Disease of the Joint as an Organ. Arthritis Rheum, 64: 1697–1707.
Kloppenburg M, Berenbaum F, 2020, Osteoarthritis Year in Review 2019: Epidemiology and Therapy. Osteoarthritis Cartilage, 28: 242–248.
Helmick C, Felson D, Lawrence R, et al., 2008, Estimates of the Prevalence of Arthritis and Other Rheumatic Conditions in the United States: Part I. Arthritis Rheum, 58: 15–25.
Safiri S, Kolahi A, Smith E, et al., 2020, Global, Regional and National Burden of Osteoarthritis 1990–2017: A Systematic Analysis of the Global Burden of Disease Study 2017. Ann Rheum Dis, 79: 819–828.
Peat G, McCarney R, Croft P, 2001, Knee Pain and Osteoarthritis in Older Adults: A Review of Community Burden and Current Use of Primary Health Care. Ann Rheum Dis, 60: 91–97.
Neogi T, 2013, The Epidemiology and Impact of Pain in Osteoarthritis. Osteoarthritis Cartilage, 21: 1145–1153.
Baliki M, Baria A, Apkarian V, 2011, The Cortical Rhythms of Chronic Back Pain. J Neurosci, 31: 13981–13990.
Borsook D, Becerra L, Fava M, 2013, Use of Functional Imaging Across Clinical Phases in CNS Drug Development. Translational Psychiatry, 3: e282.
Ichesco E, Schmidt-Wilcke T, Bhavsar R, et al., 2014, Altered Resting State Connectivity of the Insular Cortex in Individuals With Fibromyalgia. J Pain, 15: 815–826.
Giménez M, Pujol J, López-Solà M, et al., 2014, Naproxen Effects on Brain Response to Painful Pressure Stimulation in Patients With Knee Osteoarthritis: A Double-Blind, Randomized, Placebo-Controlled, Single-Dose Study. J Rheumatol, 41: 2240–2248.
Hashmi J, Baliki M, Huang L, et al., 2013, Shape Shifting Pain: Chronification of Back Pain Shifts Brain Representation From Nociceptive to Emotional Circuits. Brain, 136: 2751–2768.
Cottam W, Iwabuchi S, Drabek M, et al., 2018, Altered Connectivity of the Right Anterior Insula Drives the Pain Connectome Changes in Chronic Knee Osteoarthritis. Pain, 159: 929–938.
Liao X, Mao C, Wang Y, et al., 2018, Brain Gray Matter Alterations in Chinese Patients With Chronic Knee Osteoarthritis Pain Based on Voxel-Based Morphometry. Medicine, 97: e0145.
Shirui C, Xiaohui D, Jun Z, et al., 2022, Alterations of the White Matter in Patients With Knee Osteoarthritis: A Diffusion Tensor Imaging Study With Tract-Based Spatial Statistics. Front Neurol, 13.
Zhou J, Zeng F, Cheng S, et al., 2023, Modulation Effects of Different Treatments on Periaqueductal Gray Resting State Functional Connectivity in Knee Osteoarthritis Knee Pain Patients. CNS Neurosci Ther, 29: 1965–1980.
Biswal B, Zerrin F, Haughton V, et al., 1995, Functional Connectivity in the Motor Cortex of Resting Human Brain Using Echo‐Planar MRI. Magn Reson Med, 34: 537–541.
Zhou J, Zeng F, Cheng S, et al., 2023, Modulation Effects of Different Treatments on Periaqueductal Gray Resting State Functional Connectivity in Knee Osteoarthritis Knee Pain Patients. CNS Neurosci Ther, 29: 1965–1980.
Kang B, Ma J, Shen J, et al., 2022, Altered Brain Activity in End-Stage Knee Osteoarthritis Revealed by Resting-State Functional Magnetic Resonance Imaging. Brain and Behavior, 12.
Farmer M, Baliki M, Apkarian A, 2012, A Dynamic Network Perspective of Chronic Pain. Neurosci Lett, 520: 197–203.
Heuvel M, Pol H, 2010, Exploring the Brain Network: A Review on Resting-State fMRI Functional Connectivity. Eur Neuropsychopharmacol, 20: 519–534.
Kucyi A, Davis K, 2017, The Neural Code for Pain: From Single-Cell Electrophysiology to the Dynamic Pain Connectome. Neuroscientist, 23: 397–414.
Bullmore E, Sporns O, 2009, Complex Brain Networks: Graph Theoretical Analysis of Structural and Functional Systems. Nat Rev Neurosci, 10: 186–198.
Hou Y, Feng F, Zhang L, et al., 2022, Disrupted Topological Organization of Resting-State Functional Brain Networks in Parkinson’s Disease Patients With Glucocerebrosidase Gene Mutations. Neuroradiology, 65: 361–370.
Guye M, Bettus G, Bartolomei F, et al., 2010, Graph Theoretical Analysis of Structural and Functional Connectivity MRI in Normal and Pathological Brain Networks. Magn Reson Mater Phy, 23: 409–421.
Zhang F, Li F, Jia Z, et al., 2022, Altered Brain Topological Property Associated With Anxiety in Experimental Orthodontic Pain. Front Neurosci, 16: 907216.
Keown C, Datko M, Chen C, et al., 2017, Network Organization Is Globally Atypical in Autism: A Graph Theory Study of Intrinsic Functional Connectivity. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2: 66–75.
Pauw R, Meeus M, Coppieters I, et al., 2020, Hub Disruption in Patients With Chronic Neck Pain: A Graph Analytical Approach. Pain, 161: 729–741.
Zhang J, Wang J, Wu Q, et al., 2011, Disrupted Brain Connectivity Networks in Drug-Naive, First-Episode Major Depressive Disorder. Biol Psychiatry, 70: 334–342.
Du Y, Fan Y, 2013, Group Information Guided ICA for fMRI Data Analysis. Neuroimage, 69: 157–197.
Wang D, Qin W, Liu Y, et al., 2014, Altered Resting-State Network Connectivity in Congenital Blind. Hum Brain Mapp, 35: 2573–2581.
Buckner R, Vincent J, 2007, Unrest at Rest: Default Activity and Spontaneous Network Correlations. Neuroimage, 37: 1091–1096.
Fox M, Raichle M, 2007, Spontaneous Fluctuations in Brain Activity Observed With Functional Magnetic Resonance Imaging. Nat Rev Neurosci, 8: 700–711.
Tétreault P, Mansour A, Vachon-Presseau E, et al., 2016, Brain Connectivity Predicts Placebo Response Across Chronic Pain Clinical Trials. PLoS Biol, 14: 1–22.
Tzourio-Mazoyer N, Papathanassiou D, Crivello F, et al., 2002, Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain. Neuroimage, 15: 273–289.
Mingrui X, Jinhui W, Yong H, 2013, BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics. PLoS One, 8: e68910.
Kim J, Criaud M, Cho S, et al., 2017, Abnormal Intrinsic Brain Functional Network Dynamics in Parkinson’s Disease. Brain, 140: 2955–2967.
Zhang J, Wu Q, Huang X, et al., 2011, Disrupted Brain Connectivity Networks in Drug-Naive, First-Episode Major Depressive Disorder. Biol Psychiatry, 70: 334–342.
Yu X, Yu J, Li Y, et al., 2023, Aberrant Intrinsic Functional Brain Networks in Patients With Functional Constipation. Neuroradiology: A Journal Dedicated to Neuroimaging and Interventional Neuroradiology, 65: 337–348.
Yang H, Chen X, Chen Z, et al., 2021, Disrupted Intrinsic Functional Brain Topology in Patients With Major Depressive Disorder. Mol Psychiatry, 26: 7363–7371.
Watts D, Strogatz S, 1998, Collective Dynamics of ‘Small-World’ Networks. Nature, 393: 440.
He Y, Chen Z, Evans A, 2008, Structural Insights Into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer’s Disease. J Neurosci, 28: 4756–4766.
Sophie A, Ed B, 2007, Efficiency and Cost of Economical Brain Functional Networks. PLoS Comput Biol, 3: e17.
Bassett D, Weinberger D, Meyer-Lindenberg A, et al., 2008, Hierarchical Organization of Human Cortical Networks in Health and Schizophrenia. J Neurosci, 28: 9239–9248.
Calhoun V, McGinty V, Watson T, et al., 2001, fMRI Activation in a Visual-Perception Task: Network of Areas Detected Using the General Linear Model and Independent Components Analysis. Neuroimage, 14: 1080–1088.
Stam C, 2010, Characterization of Anatomical and Functional Connectivity in the Brain: A Complex Networks Perspective. Int J Psychophysiol, 77: 186–194.
Barroso J, Galhardo V, Baliki M, et al., 2021, Reorganization of Functional Brain Network Architecture in Chronic Osteoarthritis Pain. Hum Brain Mapp, 42: 1206–1222.
Lin G, Lan F, Liu Y, et al., 2022, Resting-State Functional Connectivity Alteration in Elderly Patients With Knee Osteoarthritis and Declined Cognition: An Observational Study. Front Aging Neurosci, 14.
Cao M, Wang Z, He Y, 2015, Connectomics in Psychiatric Research: Advances and Applications. Neuropsychiatr Dis Treat, 11: 2801–2810.
Agosta F, Sala S, Valsasina P, et al., 2013, Brain Network Connectivity Assessed Using Graph Theory in Frontotemporal Dementia. Neurology, 81: 134–143.
Moreira N, Taylor P, Cowie C, et al., 2020, Investigating Brain Network Changes and Their Association With Cognitive Recovery After Traumatic Brain Injury: A Longitudinal Analysis. Front Neurol, 11.
Keown C, Datko M, Chen C, et al., 2017, Network Organization Is Globally Atypical in Autism: A Graph Theory Study of Intrinsic Functional Connectivity. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2: 66–75.
Termenon M, Delon-Martin C, Jaillard A, et al., 2016, Reliability of Graph Analysis of Resting State fMRI Using Test-Retest Dataset From the Human Connectome Project. Neuroimage, 142: 172–187.
Sven V, Jae-Jin S, Dirk R, 2018, Thalamocortical Dysrhythmia Detected by Machine Learning. Nature Communications, 9: 1–13.
Li H, Li X, Feng Y, et al., 2020, Deficits in Ascending and Descending Pain Modulation Pathways in Patients With Postherpetic Neuralgia. Neuroimage, 221.
Groh A, Krieger P, Mease R, et al., 2018, Acute and Chronic Pain Processing in the Thalamocortical System of Humans and Animal Models. Neuroscience, 387: 58–71.
Tu Y, Mao C, Gollub R, et al., 2020, Distinct Thalamocortical Network Dynamics Are Associated With the Pathophysiology of Chronic Low Back Pain. Nature Communications, 11.
Mao C, Yang H, Dong T, et al., 2024, Thalamocortical Dysconnectivity Is Associated With Pain in Patients With Knee Osteoarthritis. Eur J Neurosci, 60(8): 5831–5848.
Kucyi A, Salomons T, Davis K, 2013, Mind Wandering Away From Pain Dynamically Engages Antinociceptive and Default Mode Brain Networks. Proc Natl Acad Sci USA, 110: 18692–18697.
Otti A, Henningsen P, Noll-Hussong M, et al., 2010, I Know the Pain You Feel—How the Human Brain’s Default Mode Predicts Our Resonance to Another’s Suffering. Neuroscience, 169: 143–148.
Baliki M, Mansour A, Baria A, et al., 2014, Functional Reorganization of the Default Mode Network Across Chronic Pain Conditions. PLoS One, 9: 1–13.
Baliki M, Geha P, Apkarian A, et al., 2008, Beyond Feeling: Chronic Pain Hurts the Brain, Disrupting the Default-Mode Network Dynamics. J Neurosci, 28: 1398–1403.
Cauda F, Sacco K, Duca S, et al., 2009, Altered Resting State in Diabetic Neuropathic Pain. PLoS One, 4: 1–9.
Čeko M, Shir Y, Ware M, et al., 2015, Partial Recovery of Abnormal Insula and Dorsolateral Prefrontal Connectivity to Cognitive Networks in Chronic Low Back Pain After Treatment. Hum Brain Mapp, 36: 2075–2092.
Kucyi A, Moayedi M, Weissman-Fogel I, et al., 2014, Enhanced Medial Prefrontal-Default Mode Network Functional Connectivity in Chronic Pain and Its Association With Pain Rumination. J Neurosci, 34: 3969–3975.
Chai X, Whitfield-Gabrieli S, Shinn A, et al., 2011, Abnormal Medial Prefrontal Cortex Resting-State Connectivity in Bipolar Disorder and Schizophrenia. Neuropsychopharmacology, 36: 2009–2017.
Liu C, Ma X, Li F, et al., 2012, Regional Homogeneity Within the Default Mode Network in Bipolar Depression: A Resting-State Functional Magnetic Resonance Imaging Study. PLoS One, 7: e48181.
Kragel P, Kano M, Oudenhove L, et al., 2018, Generalizable Representations of Pain, Cognitive Control, and Negative Emotion in Medial Frontal Cortex. Nat Neurosci, 21: 283–289.
Tang Y, Shi Y, Xu Z, et al., 2024, Altered Gray Matter Volume and Functional Connectivity in Lung Cancer Patients With Bone Metastasis Pain. J Neurosci Res, 102.
Kandilarova S, Stoyanov D, Sirakov N, et al., 2019, Reduced Grey Matter Volume in Frontal and Temporal Areas in Depression: Contributions from Voxel-Based Morphometry Study. Acta Neuropsychiatrica, 31: 252–257.
Bair M, Robinson R, Katon W, et al., 2003, Depression and Pain Comorbidity: A Literature Review. Arch Intern Med, 163: 2433–2445.
Ku J, Cho Y, Lee Y, et al., 2014, Functional Connectivity Alternation of the Thalamus in Restless Legs Syndrome Patients During the Asymptomatic Period: A Resting-State Connectivity Study Using Functional Magnetic Resonance Imaging. Sleep Med, 15: 289–294.
Johansson E, Xiong H, Polli A, et al., 2024, Towards a Real-Life Understanding of the Altered Functional Behaviour of the Default Mode and Salience Network in Chronic Pain: Are People with Chronic Pain Overthinking the Meaning of Their Pain? J Clin Med, 13: 1645.
Weeks C, Simmons A, Strigo I, et al., 2022, Distal Neuropathic Pain in HIV is Associated with Functional Connectivity Patterns in Default Mode and Salience Networks. Frontiers in Pain Research, 3.
Jalon I, Berger A, Shofty B, et al., 2023, Lesions to Both Somatic and Affective Pain Pathways Lead to Decreased Salience Network Connectivity. Brain: A Journal of Neurology, 146: 2153–2162.
Otti A, Guendel H, Wohlschläger A, et al., 2013, Frequency Shifts in the Anterior Default Mode Network and the Salience Network in Chronic Pain Disorder. BMC Psychiatry, 13: 1–9.
Qiu E, Xing X, Wang Y, et al., 2023, Altered Functional Connectivity of the Thalamus and Salience Network in Patients with Cluster Headache: A Pilot Study. Neurol Sci, 45: 269–276.
Cauda F, D’Agata F, Sacco K, et al., 2011, Functional Connectivity of the Insula in the Resting Brain. Neuroimage, 55: 8–23.
Torta D, Legrain V, Mouraux A, et al., 2017, Attention to Pain! A Neurocognitive Perspective on Attentional Modulation of Pain in Neuroimaging Studies. Cortex, 89: 120–134.
Joaquín S, Iván C, Nelson V, et al., 2023, Structural and Functional Brain Changes in People with Knee Osteoarthritis: A Scoping Review. PeerJ, 11: e16003.
Mandloi S, Syed M, Shoraka O, et al., 2023, The Role of the Insula in Chronic Pain Following Spinal Cord Injury: A Resting-State fMRI Study. J Neuroimaging, 33: 781–791.
Yoshino A, Otsuru N, Okada G, et al., 2021, Brain Changes Associated with Impaired Attention Function in Chronic Pain. Brain Cogn, 154.
Sanchis-Alfonso V, Beser-Robles M, Ten-Esteve A, et al., 2023, Brain Network Functional Connectivity Changes in Patients with Anterior Knee Pain: A Resting-State fMRI Exploratory Study. European Radiology Experimental, 7.
Guo H, Wang Y, Qiu L, et al., 2021, Structural and Functional Abnormalities in Knee Osteoarthritis Pain Revealed With Multimodal Magnetic Resonance Imaging. Front Hum Neurosci, 15.