Publication

Preprints

  1. N/A

Peer-reviewed papers

  1. Cao J, Wang X, Powley TL, Liu Z, “Gastric neurons in the nucleus tractus solitarius are selective to the orientation of gastric electrical stimulation,” Journal of Neural Engineering, in press.
  2. Zhang Y, Choi M, Han K, Liu Z, “Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning,” Advances in Neural Information Processing Systems (NeurIPS), 2021, to appear.
  3. Gamesan K, Plass J, Beltz AM, Liu Z, Grabowecky M, Suzuki S, Stacey WC, Wasade VS, Towle VL, Tao JX, Wu S, Issa NP, Brang D, “Visual speech differentially modulates beta, theta, and high gamma bands in auditory cortex,” European Journal of Neuroscience, DOI: 10.1111/ejn.15482, 2021.
  4. Liu Z, He B, “Converging frontiers in functional brain imaging,” Current Opinion in Biomedical Engineering, 19: 100325, 2021.
  5. Kim J-H, Zhang Y, Han K, Wen Z, Choi M, Liu Z., “Representation learning of resting state fMRI with variational auto-encoder,” NeuroImage, 241: 118423, 2021. 
  6. Lu K-H, Liu Z, Jaffey D, Wo J, Mosier K, Cao J, Wang X, Powley TL, “Automated assessment of human gastric motility and emptying from dynamic 3D magnetic resonance imaging,” Neurogastroenterology and Motility, e14239, 2021. 
  7. Race NS, Andrews KD, Lungwitz EA, Vega Alvarez SM, Warner TR, Acosta G, Cao J, Lu K-H, Liu Z, Dietrich AD, Majumdar S, Shekhar A, Truitt WA, Shi R, “Psychosocial impairment following mild blast-induced traumatic brain injury in rats,” Behavioral Brain Research, 412: 113405, 2021.
  8. Zhang Y, Kim J-H, Brang D, Liu Z, “Naturalistic stimuli: a paradigm for multi-scale functional characterization of the human brain”, Current Opinion in Biomedical Engineering, 19:100298, 2021. 
  9. Cheng LK, Nagahawatte ND, Avci Recep, Du P, Liu Z., Paskaranandavadivel N, “Strategies to refine gastric stimulation and pacing protocols: experimental and modeling approaches,” Frontiers in Neuroscience, 15:645472, 2021.
  10. Zhang Y, Han K, Worth RM, Liu Z., “Connecting concepts in the brain by mapping cortical representations of semantic relations,” Nature Communications, 11:1877, 2020.
  11. Lu K-H, Cao J, Phillips RJ, Powley TL, Liu Z, “Acute effects of vagus nerve stimulation parameters on gastric motility assessed with magnetic resonance imaging,” Neurogastroenterology and Motility, 32(7):e13853, 2020.
  12. Oleson ST, Lu K-H, Liu Z, Sivasankar PM, Durkes AC, “In vivo magnetic resonance imaging of the rat vocal folds after systematic dehydration and rehydration”, Journal of Speech, Language, and Hearing Research, 63(1): 135-142, 2020.
  13. Han K, Wen H, Shi J, Lu K-H, Zhang Y, Di F, Liu Z., “Variational auto-encoder: an unsupervised model for encoding and decoding fMRI activity in visual cortex,” NeuroImage, 198: 125-136, 2019.
  14. Cao J, Lu K-H, Oleson ST, Phillips RJ, Jaffey DM, Hendren C, Powley TL, Liu Z, “Gastric stimulation drives fast BOLD responses of neural origin,” NeuroImage, 197: 200-211, 2019.
  15. Mandal R, Babaria N, Cao J, Liu Z., “Adaptive and wireless recordings of electrophysiological signals during concurrent magnetic resonance imaging,” IEEE Transactions on Biomedical Engineering, 66(6): 1649-1657, 2019 (featured article).
  16. Han K, Wen H, Zhang Y, Fu D, Culurciello E, Liu Z., “Deep predictive coding network with local recurrent processing for object recognition,” Advances in Neural Information Processing Systems (NeurIPS), 2018.
  17. Lynch L, Lu K-H, Wen H, Zhang Y, Saykin AJ, Liu Z., “Task-evoked functional connectivity does not explain functional connectivity differences between rest and task conditions,” Human Brain Mapping, 39: 4939-4948, 2018. 
  18. Wen H., Han K., Shi J., Zhang Y., Culurciello E., Liu Z., “Deep predictive coding network for object recognition,” International Conference on Machine Learning (ICML), Proceedings of Machine Learning Research, 80: 5263-5272, 2018
  19. Lu K-H, Cao J, Oleson ST, Ward MP, Phillips RL, Powley TL, Liu Z., “Vagus nerve stimulation promotes gastric emptying by increasing pyloric opening measured with magnetic resonance imaging,” Neurogastroenterology and Motility, 30(10): e13380, 2018. (cover article)
  20. Wen H, Shi J, Chen W, Liu Z, “Transferring and generalizing deep-learning-based neural encoding models across subjects,” NeuroImage, 176: 152-163, 2018.
  21. Wen H, Shi J, Chen W, Liu Z. “Deep residual network predicts cortical representation and organization of visual features for rapid categorization,” Scientific Reports, 8(1): 3752, 2018.
  22. Shi J., Wen H., Zhang Y, Han K., Liu Z., “Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision,” Human Brain Mapping, 39(5): 2269-2282, 2018.
  23. He B., Sobrabpour A., Brown E., Liu Z., “Electrophysiological source imaging: a non-invasive window to brain dynamics,” Annual Review of Biomedical Engineering, 20: 171-196, 2018.
  24. Somann J., Albors G., Neihouser K., Lu K-H, Liu Z., Durkes A., Robinson J., Powley T.L., Irazoqui, P., “Chronic cuffing of cervical vagus nerve inhibits efferent fiber integrity in rat model,” Journal of Neural Engineering, 15(3): 036018, 2018.
  25. Oleson ST, Lu K-H, Liu Z., Durkes AC, Sivasankar PM, “Proton density weighted laryngeal MRI in systemically dehydrated rats,” Laryngoscope, 128(6): E222-E227, 2018.
  26. Wen H., Shi J., Zhang Y., Lu K-H, Cao J, Liu Z., “Neural encoding and decoding with deep learning for dynamic natural vision,” Cerebral Cortex, 28(2): 4136-4160, 2018.
  27. Cao J., Lu K-H., Powley T.L., Liu Z., “Vagal nerve stimulation triggers widespread responses and alters large-scale functional connectivity in the rat brain,” PLoS ONE, 12(2): e0189518, 2017.
  28. Zhang Y., Chen G., Wen H., Lu K-H, Liu Z., “Musical imagery involves Wernicke’s area in bilateral and anti-correlated network interactions in musicians,” Scientific Reports, 7: 17066, 2017.
  29. Lu K-H, Cao J, Oleson ST, Powley TL, Liu Z., “Contrast enhanced magnetic resonance imaging of gastric emptying and motility in rats,” IEEE Transactions on Biomedical Engineering, 64(11): 2546-2554, 2017 (featured article).
  30. Lu K-H, Jeong J-H, Wen H., Liu Z., “Spontaneous activity in the visual cortex is organized by visual streams,” Human Brain Mapping, 38(9): 4613-4630, 2017.
  31. Marussich L., Lu K-H, Wen H., Liu Z., “Mapping white-matter functional organization at rest and during naturalistic visual perception,” NeuroImage, 146: 1128-1141, 2017.
  32. Lu K-H, Hung S., Wen H., Marussich L., Liu Z., “Influences of high-level features, gaze, and scene transitions on the reliability of BOLD responses to natural movie stimuli,” PLoS ONE, 11(8): e0161797, 2016.
  33. Wen H., Liu Z., “Broadband electrophysiological dynamics contribute to global resting-state fMRI signal,” Journal of Neuroscience, 36(22): 6030-6040, 2016.
  34. Wen H., Liu Z., “Separating fractal and oscillatory components in the power spectrum of neurophysiological signal,” Brain Topography, 29(1): 13-26, 2016.
  35. Liu Z., de Zwart J.A., van Gelderen P., Duan Q., Chang C. Duyn J.H., “Neuroelectrical decomposition of spontaneous brain activity patterns measured with functional magnetic resonance imaging,” Cerebral Cortex, 24(11): 3080-3089, 2014.
  36. De Zwart J.A., van Gelderen P., Liu Z., Duyn J.H., “Independent sources of spontaneous BOLD fluctuation along the visual pathway,” Brain Topography, 26(4): 525-537, 2013.
  37. Chang C., Liu Z., Chen M.C., Liu X., Duyn J.H., “EEG correlates of time-varying BOLD functional connectivity,” NeuroImage, 15(72): 227-236, 2013.
  38. Liu Z., de Zwart J.A., Yao B., van Gelderen P., Kuo L., Duyn J.H., “Finding thalamic BOLD correlates to posterior alpha EEG,” NeuroImage, 63(3): 1060-1069, 2012.
  39. Liu Z., de Zwart J.A., van Gelderen P., Kuo L., Duyn J.H., “Statistical feature extraction for artifact removal from concurrent fMRI-EEG recordings,” NeuroImage, 59(3): 2073-2087, 2012.
  40. Liu Z., Fukunaga M, de Zwart J.A., Duyn J.H., “Large-scale spontaneous fluctuations and correlations in brain electrical activity observed with magnetoencephalography,” NeuroImage, 51(1): 102-111, 2010.
  41. Yang L., Liu Z., He B., “EEG-fMRI reciprocal functional neuroimaging,” Clinical Neurophysiology, 121: 1240-1250, 2010 (Cover article).
  42. Liu Z., Zhang N., Rios C., Yang L., Chen W., He B., “Linear and nonlinear relationships between visual stimuli, EEG and BOLD fMRI signals,” NeuroImage, 50(3): 1054-1066, 2010. 
  43. Lee W.H., Liu Z., Mueller B., Lim K., He B., “Influence of white matter anisotropic conductivity on EEG source localization: comparison to fMRI in human primary visual cortex,” Clinical Neurophysiology, 120(12): 2071-2081, 2009 (Cover article).
  44. Liu Z., Zhang N., Chen W., He B., “Mapping the bilateral visual integration by EEG and fMRI,” NeuroImage, 46(4): 989-997, 2009.
  45. Bai X., Liu Z., Zhang N., Chen W. and He B., “Three-dimensional source imaging from simultaneously recorded ERP and BOLD-fMRI,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 17(2): 101-106, 2009.
  46. He B., Liu Z., “Multimodal functional neuroimaging: integrating functional MRI and EEG/MEG,” IEEE Reviews in Biomedical Engineering, 1:23-40, 2008.
  47. Han C., Liu Z., Zhang X., Pogwizd S.M., He B., “Noninvasive three-dimensional cardiac activation imaging from body surface potential maps: A computational and experimental study on a rabbit model,” IEEE Transactions on Medical Imaging, 27(11): 1622-1630, 2008.
  48. Wang K., Zhu S., Mueller B., Lim K., Liu Z., He B., “A new method to derive the white matter conductivity from diffusion tensor MRI,” IEEE Transactions on Biomedical Engineering, 55(10): 2481-2486, 2008.
  49. Liu Z., He B., “FMRI-EEG integrated cortical source imaging by use of time-variant spatial constraints,” NeuroImage, 39(3): 1198-1214, 2008.
  50. Zhang N., Liu Z., He B. and Chen W., “Non-invasive study of neurovascular coupling during brain suppression,” Journal of Cerebral Blood Flow and Metabolism, 28: 280-290, 2008.
  51. Liu Z., Liu C., He B., “Noninvasive reconstruction of three-dimensional ventricular activation sequence by the inverse solution of equivalent current density,” IEEE Transactions on Medical Imaging, 25(10): 1307-1318, 2006.
  52. Im C-H., Liu Z., Zhang N., Chen W., He B., “Functional cortical source imaging from simultaneously recorded ERP and fMRI,” Journal of Neuroscience Methods, 157(1): 118-123, 2006.
  53. Liu C., Zhang X., Liu Z., Pogwizd S.M., He B., “Three-dimensional myocardial activation imaging in a rabbit model,” IEEE Transactions on Biomedical Engineering, 53(9): 1813-1820, 2006.
  54. Liu Z., Kecman F., He B., “Effects of fMRI-EEG mismatches in cortical current density estimation integrating fMRI and EEG: a simulation study,” Clinical Neurophysiology, 117(7): 1610-1622, 2006.
  55. Liu Z., Ding L., He B., “Integration of EEG/MEG with MRI and fMRI in functional neuroimaging,” IEEE Engineering in Medicine and Biology Magazine, 25(4): 46-53, 2006.
  56. Yamawaki N., Wilke C., Liu Z., He B., “An enhanced time-frequency approach for motor imagery classification,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 14(2): 250-254, 2006.
  57. Zhang X., Ramachandra I., Liu Z., Muneer B., Pogwizd S.M., He B., “Noninvasive three-dimensional electrocardiographic imaging of ventricular activation sequence,” American Journal of Physiology – Heart and Circulatory Physiology, 289(6): 2724-2732, 2005.
  58. Kamousi B., Liu Z., He B., “Classification of motor imagery tasks for brain-computer interface applications by means of two equivalent dipoles analysis,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 13(2): 166-171, 2005.