WELDON SCHOOL OF BIOMEDICAL ENGINEERING

SCHOOL OF ELECTRICAL AND COMPUTER ENGINEERING

Preprints

  1. 1Han K, Wen H, Shi J, Lu K-H, Zhang Y, Liu Z., “Variational auto-encoder: an unsupervised model for modeling and decoding fMRI activity in visual cortex,” doi: 10.1101/214247, 2017.

  2. 2Wen H, Shi J, Chen W, Liu Z. “Deep residual network reveals a nested hierarchy of distributed cortical representation for visual categorization,” doi: 10.1101/151142, 2017.

  3. 3Wen H, Shi J, Chen W, Liu Z, “Transferring and generalizing deep-learning-based neural encoding models across subjects,” doi: 10.1101/171017, 2017.

  4. 4Shi J., Wen H., Zhang Y, Han K., Liu Z., “Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision,” doi: 10.1101/177196, 2017.


Journal Articles

  1. 5Cao 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, in press.

  2. 6He B., Sobrabpour A., Brown E., Liu Z., “Electrophysiological source imaging: a non-invasive window to brain dynamics,” Annual Review of Biomedical Engineering, in press.

  3. 7Somann 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, in press.

  4. 8Zhang 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.

  5. 9Wen 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, doi: 10.1093/cercor/bhx268, 2017.

  6. 10Oleson ST, Lu K-H, Liu Z., Durkes AC, Sivasankar PM, “Proton density weighted laryngeal MRI in systemically dehydrated rats,” Laryngoscope, doi: 10.1002/lary.26978, 2017.

  7. 11Lu K-H, Cao J, Oleson S, 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.

  8. 12Lu 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.

  9. 13Marussich 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.

  10. 14Lu 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.

  11. 15Wen H., Liu Z., “Broadband electrophysiological dynamics contribute to global resting-state fMRI signal,” Journal of Neuroscience, 36(22): 6030-6040, 2016.

  12. 16Wen H., Liu Z., “Separating fractal and oscillatory components in the power spectrum of neurophysiological signal,” Brain Topography, 29(1): 13-26, 2016.

  13. 17Liu 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.

  14. 18De 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.

  15. 19Chang 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.

  16. 20Liu 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.

  17. 21Liu 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.

  18. 22Liu 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.

  19. 23Yang L., Liu Z., He B., “EEG-fMRI reciprocal functional neuroimaging,” Clinical Neurophysiology, 121: 1240-1250, 2010 (Cover article).

  20. 24Liu 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. 

  21. 25Lee 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).

  22. 26Liu Z., Zhang N., Chen W., He B., “Mapping the bilateral visual integration by EEG and fMRI,” NeuroImage, 46(4): 989-997, 2009.

  23. 27Bai 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.

  24. 28He B., Liu Z., “Multimodal functional neuroimaging: integrating functional MRI and EEG/MEG,” IEEE Reviews in Biomedical Engineering, 1:23-40, 2008.

  25. 29Han 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.

  26. 30Wang 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.

  27. 31Liu Z., He B., “FMRI-EEG integrated cortical source imaging by use of time-variant spatial constraints,” NeuroImage, 39(3): 1198-1214, 2008.

  28. 32Zhang 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.

  29. 33Liu 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.

  30. 34Im 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.

  31. 35Liu 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.

  32. 36Liu 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.

  33. 37Liu 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.

  34. 38Yamawaki 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.

  35. 39Zhang 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.

  36. 40Kamousi 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.

Conference Proceedings (since 2014)

  1. 41Shi J, Wen H, Zhang Y, Han K, Liu Z, “Deep recurrent neural network reveals a hierarchy of temporal receptive windows in the visual cortex,” the Annual Meeting of the Organization for Human Brain Mapping, 2017. [Merit Abstract Award]

  2. 42Wen H, Shi J, Zhang Y, Han K, Liu Z, “Distributed cortical networks represent visual object categories,” the Annual Meeting of the Organization for Human Brain Mapping, 2017.

  3. 43Han K, Wen H, Shi J, Lu K-H, Liu Z., “Decoding cortical activity with a variational auto-encoder supports direct visual reconstruction,” the Annual Meeting of the Organization for Human Brain Mapping, 2017.

  4. 44Kim J-H, Wen H, Zhang Y, Liu Z., “Development of new EEG-fMRI source imaging method for continuous task paradigm,” the Annual Meeting of the Organization for Human Brain Mapping, 2017.

  5. 45Zhang Y, Wen H, Lu K-H, Liu Z, “Common and distributed cortical network bases of musical perception and imagery,” the Annual Meeting of the Organization for Human Brain Mapping, 2017.

  6. 46Lu K-H, Jeong JY, Wen H, Liu Z., “Spontaneous activity patterns reveal non-retinotopic functional parcellation and organization of human visual cortex,” the Scientific Meeting of the International Society of Magnetic Resonance for Medicine, 2017. [Summa Cum Laude Award]

  7. 47Lu K-H, Cao J, Marussich L, Hu TC, Liu Z., “Mapping abdominal inflammatory response using manganese-enhanced MRI (MEMRI),” the Scientific Meeting of the International Society of Magnetic Resonance for Medicine, 2017. [Magna Cum Laude Award]

  8. 48Mandal R., Babaria N., Liu Z., “Multimodal imaging: MR-compatible gradient free wireless recording system integrated with MR-scanner for simultaneous EEG and fMRI acquisition,” the Scientific Meeting of the International Society of Magnetic Resonance for Medicine, 2017. [Magna Cum Laude Award; Power-Pitch Highlight]

  9. 49Wen H., Shi J., Han K., Liu Z., “Distributed and overlapping cortical networks represent visual categories,” the Scientific Meeting of the International Society of Magnetic Resonance for Medicine, 2017.

  10. 50Cao J, Lu K-H, Ward MP, Powley TP, Liu Z., “Neural and physiological responses to vagus nerve stimulation in rats,” the Scientific Meeting of the International Society of Magnetic Resonance for Medicine, 2017. [Magna Cum Laude Award]

  11. 51Lu K-H, Wen H, Liu Z, “Sources of reliable fMRI responses to natural movie stimuli,” Human Brain Mapping Conference, 2016.

  12. 52Wen H, Jeong JY, Liu Z, “Intrinsic functional networks within visual cortex supports naturalistic visual perception,” Human Brain Mapping Conference, 2016.

  13. 53Shi J, Wen H, Liu Z, “Mapping neural representations of hierarchical visual features during natural movie stimuli,” Human Brain Mapping Conference, 2016.

  14. 54Wen H, Shi J, Lu K-H, Zhang Y, Marussich L, Liu Z, “Decode cortical fMRI activity to reconstruct naturalistic movie via deep learning,” Human Brain Mapping Conference, 2016. [Merit Abstract Award]

  15. 55Marussich L, Lu K-H, Wen H, Liu Z, “Hierarchical clusters of white-matter fMRI are coupled with cortical visual networks,” Human Brain Mapping Conference, 2016.

  16. 56Marussich L, Jeong JY, Lu K-H, Hung S-C, Liu Z, “Natural vision task partially reorganizes resting state networks,” Human Brain Mapping Conference, 2015.

  17. 57Jeong JY, Druzbicki J, Lu K-H, Wen H, Liu Z, “Functional relevance of spatial ICA and k-means clustering,” Intl. Soc. Magn. Reson. Med. Annual Scientific Meeting, 2015.

  18. 58Wen H., Liu Z, “Distinct neurophysiological correlates of global vs. local resting state fMRI networks,” Intl. Soc. Magn. Reson. Med. Annual Scientific Meeting, 2015. [Power-Pitch Highlight]

  19. 59Liu. Z, Cheng H., “System for integrated neural imaging, recording and stimulation,” Biomedical Engineering Society Annual Conference, 2014.

  20. 60Wen H., Liu Z., “Functional networks observed with scale-free and oscillatory cortical activity,” Resting State Brain Connectivity Conference, 2014.

  21. 61Evan J., Kundu P., Liu Z., Horovitz S., Bandettini P., “Validation of slow signal detection in multi-echo fMRI using simultaneous EEG,” Human Brain Mapping Conference, 2014.

Laboratory of Integrated Brain Imaging

Home    People    Research    Publication    Links    Resource    News    Internal