Publications

PEER- REVIEWED PUBLICATIONS

†:  denote students/postdocs advised

1. Chen, H., Guo, D., Guo, Y., He, Y., Liu, D., Liu, L., Yin, Y., and Zhou, X.. (2025). Cooperative Differential Network Learning with Hub Detection for Multi-center Neuroimaging Data.  Annals of Applied Statistics. In press.

2. Sun,D.†,, Peng, L., Qiu, Z., Guo, Y., Manatunga, AK. (2024). Partial Quantile Tensor Regression. Journal of the American Statistical Association (JASA) Theory and Methods, pp.1-23.  Paper Link

3. Ran, J.†, Wang, Y. and Guo, Y.  (2024). Unveiling hidden sources of dynamic functional connectome through a novel regularized blind source separation approach. Imaging Neuroscience, 2, pp.1-30.Open Access

4. Yang, G. †,  Haley, R.W.,  Guo, Y., and Gopinath, K.S. (2024).  Comprehensive Examination of Resting State fMRI Connectomics Yield New Insights into Brain Function Deficits in Gulf War Illness After Accounting for Heterogeneity in Brain Impairment Across the ill Veteran Population, Neuroimage: Reports. 4(3), 100209.

5. Sefiz, E., Duan, K., Li, Y., Sholar, B., Evans, L., Pincus, J., Ammar, Z., Murphy, M., Klaiman, C., Saulnier, C., White, SP, Goldman-Yassen, A.E., Guo, Y., Walker, EF, Li, L., Mulle, JG, Shultz, S. (2024). Structural deviations of the posterior fossa and the cerebellum and their cognitive links in a neurodevelopmental deletion syndrome. Molecular Psychiatry, pp.1-17.

6. Verdijk, J. P. A. J., van de Mortel, L. A., Ten Doesschate, F., Pottkämper, J. C. M., Stuiver, S., Bruin, W. B., Abbott, C. C., Argyelan, M., Ousdal, O. T., Bartsch, H., Narr, K., Tendolkar, I., Calhoun, V., Lukemire, J., Guo, Y., Oltedal, L., van Wingen, G., & van Waarde, J. A. (2024). Longitudinal resting-state network connectivity changes in electroconvulsive therapy patients compared to healthy controls. Brain stimulation, 17(1), 140–147. 

7. Ree, A., Rapsas, B., Denmon, C., Vernon, M., Rauch, S. A., Guo, Y., Cui, X., Stevens, J. S., Krishnamurthy, V., Napadow, V., Turner, J. A., & Woodbury, A. (2024). A Randomized, Sham-Controlled Trial of Cranial Electrical Stimulation for Fibromyalgia Pain and Physical Function, Using Brain Imaging Biomarkers. Journal of visualized experiments : JoVE, (203), 10.3791/65790.

8. Kan,X. †, Li, Z., Cui, H., Yu, Y.,  Xu, R., Yu, S., Zhang, Z., Guo, Y. , Yang, C. (2023). R-Mixup: Riemannian Mixup for Biological Networks. KDD 2023, Proceedings of the ACM International Conference on Knowledge Discovery and Data Mining (KDD).

9. Lukemire, J.†, Pagnoni, G. and Guo, Y. (2023). Sparse Bayesian Modeling of Hierarchical ICA: Reliable Estimation of Individual Differences in Brain Networks. Biometrics,  79(4), pp.3599-3611. Paper Link.  Early version of the paper was the Runner-Up of 2021 ASA Statistics in Imaging Section student paper competition

10. Wang, Y.† and Guo, Y.. (2023).   LOCUS: A Novel Decomposition Method for Brain Network Connectivity Matrices using Low-rank Structure with Uniform Sparsity. Annals of Applied Statistics, 17(2): 1307-1332.  pdf   Code

11. Wei, B., Peng, L., Guo, Y., Manatunga, AK and Stevens, J. (2023), Tensor response quantile regression with neuroimaging data. Biometrics, 79(3), pp.1947-1958.  Paper Link. 

12. Cui, H., Dai, W., Zhu, Y., Kan, X., Gu, A.A.C., Lukemire, J., Zhan, L., He, L., Guo, Y. and Yang, C., (2023). BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks. IEEE Transactions on Medical Imaging, 42(2):493-506, Open Access

13. Wu, B.†, Guo, Y. and Kang, J. (2023). Bayesian Spatial Blind Source Separation via the Thresholded Gaussian Process. Journal of the American Statistical Association (JASA) Theory and Methods, pp1-12.  Paper Link

14. Dong, L. Zhao, C; He, Y., Liu, L., Guo, Y.  and Zhang, X. (2023), Simultaneous Cluster Structure Learning and Estimation of Heterogeneous Graphs for Matrix-variate fMRI Data. Biometrics.  Paper Link

15. Liu, D., Zhao, C., He, Y., Liu, L., Guo, Y. and Zhang, X., (2023). Simultaneous cluster structure learning and estimation of heterogeneous graphs for matrix-variate fMRI data. Biometrics, 79(3), pp.2246-2259.

16. Murden, R., Zhang, Z., Guo, Y.  and Risk, B. (2022). Interpretive JIVE: Connections with CCA and an Application to Brain Connectivity. Frontiers in Neuroscience, 16.  Open Access

17. Kan, X.†, Dai, W, Cui, H., Zhang, Z., Guo, Y. and Yang, C. (2022). Brain Network Transformer. Proceedings of the Conference on Neural Information Processing Systems (NeurIPS).   Open Access

18. Yang, Y., Zhu, Y., Cui, H., Kan, X., He, L., Guo, Y. and Yang, C. (2022). Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning.  Proceedings of the ACM International Conference on Knowledge Discovery and Data Mining (KDD). Open Access

19. Kan, X. †, Kong, Y., Yu, T. and Guo, Y., (2022), Bracenet: Graph-embedded neural network for brain network analysis. Proceeding of IEEE International Conference on Big Data.  

20. Hu, Y.†, Zeydabadinezhad, M., Li, L. and Guo,Y. (2022).  A multimodal multilevel neuroimaging model for investigating brain connectome development. Journal of the American Statistical Association (JASA), 117(539), pp.1134-1148. Early version of the paper was the First Place Winner of 2021 ASA Statistics in Imaging Section student paper competition. pdf   Code 

21. Kan, X.†, Cui, H., Lukemire, J., Guo, Y., and Yang, C. (2022). FBNETGEN: Task-aware GNN-based fMRI analysis via functional brain network generation. Proceedings of the International Conference on Medical Imaging with Deep Learning (MIDL).  Selected for oral presentation.  Open Access

22. Wu,B. †, Pal, S., Kang,J. and Guo,Y. (2022).  Rejoinder to Discussions of "Distributional independent component analysis for diverse neuroimaging modalities", Biometrics, Open Access

23. Wu,B. †, Pal, S., Kang,J. and Guo,Y. (2022).  Distributional Independent Component Analysis for Diverse Neuroimaging Modalities.  Biometrics.  Selected as a Discussion Paper by Biometrics.   Featured as the Cover Image of the issue.   Open Access

24. Kan, X.†, Cui, H., Guo, Y. and Yang, C. (2021). Effective and Interpretable fMRI Analysis via Functional Brain Network Generation. Interpretable Machine Learning in Healthcare: The International Conference on Machine Learning (ICML-IMLH).

25. Patel, R.M, Lukemire, J., Shenvi, N., Arthur, C., Stowell, S.R. , Sola-Visner, M., Easley, K., Roback,J.D., Guo, Y. Josephson, C.D. (2021).  Association between Blood Donor Sex and Age with Outcomes in Transfused Very Low Birth Weight Infants.  JAMA Network Open; 2021; 4(9);e2123942. Featured in Transfusion News – Global Advances, Trends, and Current Events. 

26. Chen, H., Guo, Y., He, Y., Ji, J., Liu, L., Shi, Y., Wang, Y., Yu, L., Zhang, X. (2021). Simultaneous Differential Network Analysis and Classification for Matrix-variate Data with Application to Brain Connectivity. Biostatistics,  Mar 26:kxab007. doi: 10.1093/biostatistics/kxab007. Epub ahead of print. PMID: 33769450.

27. Keilholz, S., Maltbie, E., Zhang, X., Yousefi, B., Pan, W., Xu, N., Nezafati, M., LaGrow, TJ, Guo, Y. (2020). Relationship between basic properties of BOLD fluctuations and calculated metrics of complexity in the Human Connectome Project. Frontiers in Neuroscience, 14: 939 .

28. Woodbury, A., Krishnamurthy, V., Gebre, M., Napadow, V., Bicknese, C., Liu, M., Lukemire, J. Kalangara, J., Cui, X., Guo, Y., Sniecinski, R. and Crosson, B. (2020), Feasibility of Auricular Field Stimulation in Fibromyalgia: Evaluation by Functional Magnetic Resonance Imaging. Pain Medicine. In Press.

29. Lukemire, J†, Kundu, S, Pagnoni, G and Guo, Y  (2020).  Bayesian Joint Modeling of Multiple Brain Functional Networks, JASA,   PubMed 

30. Lukemire, J.† , Wang, Y., Verma, A. and Guo, Y (2020).  HINT: A Hierarchical Independent Component Analysis Toolbox for Investigating Brain Functional Networks using Neuroimaging Data. Journal of Neuroscience Methods. 341: 108726.  PubMed   Code

31. Wei,B., Dai,T., Peng, L., Guo, Y., Manatunga, AK (2020), A New Functional Representation of Broad Sense Agreement. Statistics and Probability Letters, 158, p.108619. 

32. Mejia, A., Nebel, M.B., Wang, Y., Caffo, B. and Guo, Y (2019). Template independent component analysis: targeted and reliable estimation of subject-level brain networks using big data population priors. Journal of the American Statistical Association, Nov 20: 1-27.  PubMed

33. Higgins, IA†, Kundu, S., Choi, KS., Mayberg, H., Guo, Y (2019), A Differential Degree Test for Comparing Brain Networks. Human Brain Mapping, 1-19.    PubMed   Code

34. Hu, R., Qiu, D., Guo, Y., Zhao, Y., Leatherday, C., Wu, J., Oshinski, J. and Allen, J. (2019). Variability of Resting State Functional MRI Graph Theory Metrics Across 3T Platforms. Journal of Neuroimaging, 29(3), 283-417.   PubMed

35. Wang, Y. † and Guo, Y  (2019).  A hierarchical independent component analysis model for longitudinal neuroimaging studies. NeuroImage. 189: 380-400. An earlier version of the paper was one of the winners of the 2018 ENAR Distinguished Student Paper Award and the First-Place Winner of the 2018 Student Paper Competition of the American Statistical Association (ASA) Statistics in Imaging Section.   PubMed   Code

36. Qiu, Z†, Peng, L, Manatunga, AK, Guo, Y. (2019).  A Smooth Nonparametric Approach to Determining Cut-Points of a Continuous Scale. Computational Statistics and Data Analysis. 134, 186-210. 

37. Kundu, S., Lukemire, J., Wang, Y. and Guo, Y., 2019. A novel joint brain network analysis using longitudinal Alzheimer’s disease data. Scientific reports, 9(1), pp.1-18. Open Access

38. Xiao, C., Bruner, D.W., Dai, T., Guo, Y. and Hanlon, A., 2019. A comparison of missing-data imputation techniques in exploratory factor analysis. Journal of nursing measurement, 27(2), pp.313-334.

39. Kemmer, P†, Wang, Y., Bowman, F.D., Mayberg, H. and Guo, Y  (2018).  Evaluating the strength of structural connectivity underlying brain functional networks. Brain Connectivity.  PubMed

40. Higgins, IA†, Kundu, S. and Guo, Y., (2018). Integrative Bayesian Analysis of Brain Functional Networks Incorporating  Anatomical Knowledge. NeuroImage, 181: 263-278.   PubMed   Code

41. Guo, Y, Wang Y., Marin, T., Easley, K., Patel, R.M., Josephson, C.D. (2018). Statistical Methods for Characterizing transfusion-related changes in regional oxygenation using Near-infrared spectroscopy (NIRS) in preterm infants. Statistical Methods in Medical Research.  PubMed

42. Kundu, S., Ming, J., Pierce, J. McDowell, J. and Guo, Y, (2018), Estimating Dynamic Brain Functional Networks Using Multi-subject fMRI Data, NeuroImage, 183: 635-649.   PubMed   Code

43. Dai, T†, Guo, Y, Peng, L., Manatunga, AK (2018). A local agreement pattern measure based on hazard functions for survival outcomes. Biometrics, 74(1):86-99.

44. Rahman, AF†, Manatunga, AK, Guo, Y, Peng, L., Warnock, M., Ressler, K.J., Jovanovic, T. (2018).  A Latent Class Analysis of PTSD Symptoms Among Inner City Primary Care Patients.  Journal of Psychiatric Research, 98:1-8.

45. Waldrop-Valverde, D., Murden, R.J., Guo, Y., Holstad, M., & Ownby, R.L. (2018). Racial disparities in HIV antiretroviral medication management are mediated by health literacy. Health Literacy Research and Practice, 2(4):e205-e213.

46. Marin, T., Patel, R., Josephson, C., Roback, J., Stowell, S., Guo, Y., Easley, K., Warnock, M. and Skvarich, J., Josephson, C.D. (2018). Does Red Blood Cell Irradiation and/or Anemia Trigger Intestinal Injury in Premature Infants with Birth Weight ≤ 1250 grams? An Observational Birth Cohort Study. BMC Pediatrics, 18:270.

47. Wheat, J., Myint, T., Guo, Y., Kemmer, P., Hage, C., Terry, C., Azar, M.M., Riddell, J., Ender, P., Chen, S. and Shehab, K., (2018). Central nervous system histoplasmosis: Multicenter retrospective study on clinical features, diagnostic approach and outcome of treatment. Medicine, 97(13).

48. Dai, T† and Guo, Y (2017). Predicting Individual Brain Functional Connectivity Using a Bayesian Hierarchical Model. NeuroImage.147(15): 772–787. An earlier version of the paper was the Second-Place winner of the 2016 Student Paper Competition, American Statistical Association (ASA) Statistics in Imaging Section.   PubMed

49. Rahman, AF†, Peng, L., Manatunga, AK, Guo, Y (2017). Nonparametric regression method for broad sense agreement. Journal of nonparametric statistics, 29(2):280-300.

50. Shi, R† and Guo, Y (2016). Investigating differences in brain functional networks using hierarchical covariate-adjusted independent component analysis. Annals of Applied Statistics. 10(4): 1930-1957. An earlier version of the paper was selected for the First-Place winner of the 2015 Student Paper Competition, American Statistical Association (ASA) Statistics in Imaging Section.   PubMed   Code

51. Peng, L., Manatunga, AK, Wang, M., Guo, Y. and Rahman AF (2016). A general approach to categorizing a continuous scale according to an ordinal outcome.  Journal of Statistical Planning and Inference, May 1;172:23-25. 

52. Wang, Y†, Kang J, Kemmer, PB and Guo, Y. (2016). An efficient and reliable statistical method for estimating functional connectivity in large-scale brain networks using partial correlation.  Frontiers in Neuroscience. 10:123. Open Access   Code

53. Cordova, J.S., Gurbani, S. S., Holder, C.A. Olson, J.J., Schreibmann, E., Shi, R., Guo, Y., Shu, H.G., Shim, H., Hadjipanayis, C.G. (2016) Semi-quantitative volumetric and morphological assessment of glioblastoma resection with fluorescence-guided surgery. Molecular Imaging and Biology, 18.3: 454–462. 

54. Darcy-Mahoney, A., Minter, B., Higgins, M., Guo, Y., Williams, B., Head, L. M., & Birth, K. (2016). Probability of an Autism Diagnosis by Gestational Age. Newborn and Infant Nursing Reviews: 16(4): 322-326.

55. Darcy-Mahoney, A., Minter, B., Higgins, M., Guo, Y., Zauche, L.H. and Hirst, J., (2016). Maternal and Neonatal Birth Factors Affecting the Age of ASD Diagnosis. Newborn and Infant Nursing Reviews, 16(4), pp.340-347.

56. Zuniga, J.A., Yoo-Jeong, M., Dai, T., Guo, Y. and Waldrop-Valverde, D., (2016). The role of depression in retention in care for persons living with HIV. AIDS patient care and STDs, 30(1), pp.34-3.

57. Kemmer PB†, Guo, Y , Wang Y and Pagnoni G. (2015). Network-based characterization of brain functional connectivity in Zen practitioners. Frontiers in Psychology, 6, 603.  Open Access

58. Ferranti, E. P. Narayan, K. M. V., Reilly, C. M., Foster, J., McCullough, M., Ziegler, T. R., Guo, Y., Dunbar, S. B. (2014). Dietary Self Efficacy predicts AHEI Diet Quality in Women with previous Gestational Diabetes. The Diabetes Educator. 40(5), 688-699.

59. Shim H, Wei L, Holder C, Guo, Y, Hu XP, Miller AH, Olson JJ. (2014). Use of high resolution volumetric MR spectroscopic imaging in assessing treatment response of GBM to an HDAC inhibitor. American Journal of Roentgenology, 203.2: W158-W165.

60. Cordova JS, Schreibmann, E., Hadjipanayis CG., Guo, Y, Shu H, Shim H.  and Holder C. (2014). Quantitative tumor segmentation for evaluation of extent of glioblastoma resection to facilitate multisite clinical trials. Translational Oncology. 7(1):40-7.

61. Waldrop-Valverde D., Guo, Y., Ownby R.L., Rodriguez A. and Jones D.L. Risk and Protective Factors for Retention in HIV Care. (2014). AIDS and Behavior. 18(8):1483-91.

62. Guo, Y and Tang Li. (2013). A hierarchical probabilistic model for group independent component analysis in fMRI studies. Biometrics. 69(4):970-81. PubMed 

63. Guo, Y, Li R, Peng L and Manatunga AK. (2013). A new agreement measures based on survival processes. Biometrics. 69(4):874-82.

64. Ross H, Guo, Y, Coleman K, Ousley O, Miller A. (2013). Association of IL-12p70 and IL-6:IL-10 ratio with autistic-like behavior in 22q11.2 deletion syndrome. Brain, Behavior and Immunity, 31:76-81.

65. Kung R.D, Reid AL, Maheshwari R, Fleischman W, Guo, Y, McMahon MM, Nesmith E, Patel M, Lennox JL, Wehbi MA, Ford RM. (2013). Colon Cancer Screening in HIV-infected Patients Age 50 and Older: Data from an outpatient HIV clinic. Practical Gastroenterology. pp32-42. 

66. Corwin, E.J., Guo, Y., Pajer, K., Lowe, N., McCarthy, D., Schmiege, S., Weber, M., Pace, T., & Stafford, B.(2013). Immune Dysregulation and Glucocorticoid Resistance in Minority and Low Income Pregnant Women. Psychoneuroendocrinology. 38(9):1786-96.

67. Lyles RH, Guo, Y and Greenland S. (2012).  Reducing bias and mean squared error associated with regression-based odds ratio estimators. Journal of Statistical Planning and Inference. 142: 3235-3241.

68. Peng L, Li R, Guo, Y, and Manatunga AK.(2011). Assessing Broad Sense Agreement between Ordinal and Continuous Measurements. Journal of American Statistician Association. 106: 1592-1601. Selected as JASA Featured Article. 

69. Guo, Y (2011). A general probabilistic model for group independent component analysis and its estimation methods. Biometrics.  67(4): 1532-1542. PubMed

70. Guo, Y (2010). A weighted cluster kernel PCA prediction model for multi-subject brain imaging data. Statistics And Its Interface. 3:103-111.

71. Guo, Y and Manatunga AK (2010).  A note on assessing agreement for frailty models. Statistics and Probability Letters.  80: 527-533.

72. Lyles, R, Guo, Y and Hill, A (2009). A Fresh Look at the Discriminant Function Approach for Estimating Crude or Adjusted Odds Ratios. The American Statistician, 63(4): 320-327.

73. Guo, Y and Manatunga AK (2009). Measuring agreement of multivariate discrete survival times using a modified weighted kappa coefficient. Biometrics, 65(1):125-34.

74. Guo, Y and Pagnoni G (2008). A unified framework for group independent component analysis for multi-subject fMRI data. NeuroImage 42: 1078-1093.   Listed in ScienceDirect’s Top 25 hottest articles of NeuroImage between July-Sep. 2008.   PubMed 

75. Guo, Y (2008). Group Independent Component Analysis of Multi-subject fMRI data: Connections and Distinctions between Two Methods.  IEEE Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics v2: 748-752.   

76. Guo, Y and Bowman FD (2008).  Modeling Dose-Dependent Neural Processing Responses Using Mixed Effects Spline Models. NeuroImage, 40: 698-711.  PubMed

77. Guo, Y, Bowman FD, Kilts C (2008). Predicting the brain response to treatment using a Bayesian Hierarchical model . Human Brain Mapping, 29(9): 1092-1109.  PubMed

78. Pagnoni G, Cekic M and Guo, Y (2008). “Thinking about not-thinking”: neural correlates of conceptual processing during Zen meditation. PLoS ONE, 3(9): e3083.   PubMed

79. Bruce EC, Guo, Y, Lawson KC, Manatunga AK, McDonald WM, Rushing N, Brown AR, Gilles N, Emery M, Bonsall R, Porquez J, Stowe Z, Nemeroff CB, Musselman DL (2008). Platelet Thromboxane A2 secretion in patients with major depression responsive to electroconvulsive therapy. Psychosomatic Medicine, 70:319–327.

80. Bowman FB, Guo, Y, and Derado G. (2007).  Statistical Approaches to Functional Neuroimaging data. Neuroimaging Clinics of North America: Imaging of the mind, 17(4): 441-458.  PubMed

81. Guo, Y and Manatunga AK (2007). Nonparametric estimation of the concordance correlation coefficient under univariate censoring. Biometrics, 63(1): 164-172.

82. Guo, Y , Musselman DL, Manatunga AK, Gilles N, Lawson  KC, Porter MR, McDaniel JS and Nemeroff CB (2006). The diagnosis of major depression in patients with cancer: a comparative approach.  Psychosomatics, 47: 376 - 384. 

83. Guo, Y, Manatunga AK, Chen S. and Marcus M (2006).  Modeling menstrual cycle length using a mixture distribution. Biostatistics, 7(1):100-114.

84. Wolf SL, O’Grady M, Easley KA, Guo, Y, Kressig RW and Kutner M (2006). The influence of intense Tai Chi training on functional performance and hemodynamic outcomes in transitionally frail, older adults.  The Journal of Gerontology: Medical Sciences, 61A (2): 184-189.

85. Musselman DL, Somerset WI, Porter M, Guo, Y, Manatunga AK, Penna S, Schatzberg A, Evans D and Nemeroff CB (2006). A double-blinded, multicenter, parallel group study of paroxetine, desipramine, or placebo in breast cancer patients (stages I, II, III & IV) with major depression. The Journal of Clinical Psychiatry, 67:288-296.

86. Guo, Y and Manatunga AK (2005).  Modeling the agreement of discrete bivariate survival times using kappa coefficient. Lifetime Data Analysis, 11(3): 309-332.

87. Guo, Y, Nilsson ME, Heiligenstein JH, Wilson MG and Emslie GJ. An exploratory factor analysis of the children’s depression rating scale-revised (2005). Journal of Child and Adolescent Psychopharmacology, 16 (4): 482-491.