文章/Publications

Neuroimaging Analysis and Neural Engineering

• B. Y. Lei, N. N. Cheng, A. F. Frangi, Y. C. Wei, B. H. Yu, L. Y. Liang, W. Mai, G. X. Duan, X. C. Nong, C. Li, J. H. Su, T. F. Wang, L. H. Zhao*, D. M. Deng*, and Z. G. Zhang*, “Auto-weighted centralised multi-task learning via integrating functional and structural connectivity for subjective cognitive decline diagnosis,” Medical Image Analysis, in press, 2021.

• Z. Liang, R. S. Zhou, L. Zhang, L. L. Li, G. Huang, Z. G. Zhang* and Shin Ishii, “EEGFuseNet: Hybrid unsupervised deep feature characterization and fusion for high-dimensional EEG with an application to emotion recognition,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, in press. [* Corresponding Author]

• M. J. Du, L. Zhang, L. L. Li, E. N. Jie, X. Han, G. Huang, Z. Liang, L. Shi, H. C. Yang*, and Z. G. Zhang*, “Abnormal transitions of dynamic functional connectivity states in bipolar disorder: A whole-brain resting-state fMRI study,” Journal of Affective Disorders, vol. 289, pp. 7-15, Jun. 2021. [* Corresponding Author]

• L. Y. Liang, Y. M. Yuan, Y. C. Wei, B. H. Yu, W. Mai, G. X. Duan, X. C. Nong, C. Li, J. H. Su, L. H. Zhao*, Z. G. Zhang*, and D. M. Deng*, “Recurrent and concurrent patterns of regional BOLD dynamics and functional connectivity dynamics in cognitive decline”, Alzheimer's Research & Therapy, vol. 28, Article No.: 28, Jan., 2021. [* Corresponding Author]

• Q. Q. Lin, G. Huang, L. L. Li, L. Zhang, Z. Liang, A. Anter, and Z. G. Zhang*, “Designing individual-specific and trial-specific models to accurately predict the intensity of nociceptive pain from single-trial fMRI responses,” NeuroImage, Jan,. 2021. [* Corresponding Author]

• Z. Liang, F. C. Li, W. R. Hu, G. Huang, S. Oba, Z. G. Zhang*, and S. Ishii, “A generalized encoding system for alpha oscillations through visual saliency analysis,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Dec. 2020. [* Corresponding Author]

• T. J. Liu^#, G. Huang*, N. Jiang, L. Yao, Z. G. Zhang^#, “Reduce brain-computer interface inefficiency by combining sensory motor rhythm and movement-related cortical potential features,” Journal of Neural Engineering, vol. 77, no. 3, 035003, Jun. 2020. [^# Equal Contribution]

• A. M. Anter, G. Huang, L. L. Li, L. Zhang, Z. Liang, and Z. G. Zhang*, “A new type of fuzzy rule-based system with chaotic swarm intelligence for multi-classification of pain perception from fMRI”, IEEE Transactions on Fuzzy Systems, vol. 28, no. 6, pp. 1096-1109, Jun. 2020. [* Corresponding Author]

• F. Tang, H. C. Yang, L. L. Li, E. N. Ji, Z. N. Fu, and Z. G. Zhang*, “Fusion analysis of gray matter and white matter in bipolar disorder by multimodal CCA-joint ICA”, Journal of Affective Disorders, vol. 263, pp. 80-88, Feb. 2020. [* Corresponding Author]

• Y. M. Yuan, L. Zhang, L. L. Li, G. Huang, A. Anter, Z. Liang, and Z. G. Zhang*, “Distinct dynamic functional connectivity patterns of pain and touch thresholds: A resting-state fMRI study”, Behavioural Brain Research, vol. 375, Article No.:112142, Dec. 2019. [* Corresponding Author]

• A. M. Anter, Y. C. Wei, J. H. Su, Y. M. Yuan, B. Y. Lei, G. X. Duan, W. Mai, X. C. Nong, B. H. Yu, C. Li, Z. N. Fu, L. H. Zhao*, D. M. Deng*, and Z. G. Zhang*, “A robust swarm intelligence-based feature selection model for neuro-fuzzy recognition of mild cognitive impairment from resting-state fMRI”, Information Sciences, vol. 503, pp. 670-687, Nov. 2019. [* Corresponding Author]

• G. Huang, J. Liu, L. L. Li, L. Zhang, Y. X. Zeng, L. J. Ren, S. Q. Ye, and Z. G. Zhang*, “A novel training-free externally-regulated neurofeedback (ER-NF) system using phase-guided visual stimulation for alpha modulation,” NeuroImage, ivol. 189, pp. 688-699, Apr. 2019. [* Corresponding Author]

• L. L. Li, E. N. Ji, X. Han, F. Tang, Y. H. Bai, D. H. Peng, Y. R. Yang, S. L. Zhang, Z. G. Zhang*, and H. C. Yang*, “Cortical thickness and subcortical volumes alterations in euthymic bipolar I patients treated with different mood stabilizers,” Brain Imaging and Behavior, vol.13, no. 5, pp. 1255-1264, Oct. 2019. [* Corresponding Author]

• L. L. Li, E. N. Ji, F. Tang, Y. H. Qiu, X. Han, S. L. Zhang, Z. G. Zhang*, and H. C. Yang*, “Abnormal brain activation during emotion processing of euthymic bipolar patients taking different mood stabilizers,” Brain Imaging and Behavior, vol. 13, no. 4, pp. 905-913, Aug. 2019. [* Corresponding Author]

• Q. Q. Lin, L. L. Li, J. Liu, W. X. Liu, G. Huang and Z. G. Zhang*, “Influence of individual differences in fMRI-based pain prediction models on between-individual prediction performance,” Frontiers in Neuroscience, vol. 12, Article 569, Aug. 2018. [* Corresponding Author]

• L. L. Li, G. Huang, Q. Q. Lin, J. Liu, S. L. Zhang, and Z. G. Zhang*, “Magnitude and temporal variability of inter-stimulus EEG modulate the linear relationship between laser-evoked potentials and fast-pain perception,” Frontiers in Neuroscience, vol. 12, Article 340, May 2018. [* Corresponding Author]

• Y. H. Tu, Z. N. Fu, A. Tan, G. Huang, L. Hu, Y. S. Hung, and Z.G. Zhang*, “A novel and effective fMRI decoding approach based on sliced inverse regression and its application to pain prediction,” Neurocomputing, vol. 273, pp. 373-384, Jan. 2018. [* Corresponding Author]

• Z. N. Fu, Y. H. Tu, X. Di, B. B. Biswal, V. D. Calhoun, and Z. G. Zhang*, “Associations between functional connectivity dynamics and bold dynamics are heterogeneous across brain networks,” Frontiers in Human Neuroscience, vol. 11, Article 293, Dec. 2017. [* Corresponding Author]

• A. Tan, L. Hu, R. Chen, Y. S. Hung, and Z. G. Zhang*, “N1 magnitude of auditory evoked potentials and spontaneous functional connectivity between bilateral Heschl’s gyrus are coupled at inter-individual level,” Brain Connectivity, vol. 6, no. 6, pp. 496-504, Jul. 2016. [* Corresponding Author]

• Y. H. Tu, A. Tan, Y. R. Bai, Y. S. Hung, and Z. G. Zhang*, “Decoding subjective intensity of nociceptive pain from pre-stimulus and post-stimulus brain activities,” Frontiers in Computational Neuroscience, vol. 10, article 32, Apr. 2016. [* Corresponding Author]

• Y. R. Bai, G. Huang, Y. H. Tu, A. Tan, Y. S. Hung, and Z. G. Zhang*, “Normalization of pain-evoked neural responses using spontaneous EEG improves the performance of EEG-based cross-individual pain prediction,” Frontiers in Computational Neuroscience, vol. 10, article 31, Apr. 2016. [* Corresponding Author]

• Y. H. Tu, Z. G. Zhang*, A. Tan, W. W. Peng, Y. S. Hung, M. Moayedi, G. D. Iannetti, and L. Hu*, “Alpha and gamma oscillation amplitudes synergistically predict the perception of forthcoming nociceptive stimuli,”Human Brain Mapping, vol. 37, no. 2, pp. 501-514, Feb. 2016. [* Corresponding Author]

• X. Di, Z. N. Fu, S. C. Chan, Y. S. Hung, B. B. Biswal*, and Z. G. Zhang*, “Task-related functional connectivity dynamics in a block-designed visual experiment,” Frontiers in Human Neuroscience, vol. 9, Article 543, Sep. 2015. [* Corresponding Author]

• J. P. Zhang, Y. Cui, J. R. Zhang, J. Zhang, Q. Zhou, Q. Liu, and Z. G. Zhang*, “Closely spaced MEG source localization and functional connectivity analysis using a new pre-whitening invariance of noise space algorithm,” Neural Plasticity, Article ID 4890497, Feb. 2016. [* Corresponding Author]

• Y. Wang^#, Z. G. Zhang^#, X. Li, H. Cui, X. Xie, K. D. Luk, and Y. Hu, “Usefulness of time-frequency patterns of somatosensory evoked potentials in identification of the location of spinal cord injury,” Journal of Clinical Neurophysiology, vol. 32., no. 4, pp. 341-345, Aug. 2015. [^# Equal Contribution]

• Y. H. Tu, Y. S. Hung, G. Huang, L. Hu, and Z. G. Zhang*, “An automated and fast approach to detect single-trial visual evoked potentials with application to brain–computer interface,” Clinical Neurophysiology, vol. 125, no. 12, pp. 2372-2383, Dec. 2014. [* Corresponding Author]

• Z. N. Fu, S. C. Chan, X. Di, B. B. Biswal, and Z. G. Zhang*, “Adaptive covariance estimation of non-stationary processes and its application to infer dynamic connectivity from fMRI,” IEEE Transactions on Biomedical Circuits and Systems, vol. 8, no. 2, pp. 228-239, Apr. 2014. [* Corresponding Author]

• L. Hu, P. Xiao, Z. G. Zhang*, A. Mouraux, and G. D. Iannetti, “Single-trial time-frequency analysis of electrocortical signals: Baseline correction and beyond,” NeuroImage, vol. 84, no. 1, pp. 876-887, Jan. 2014. [* Corresponding Author]

• G. Huang, P. Xiao, Y. S. Hung, G. D. Iannetti, Z. G. Zhang*, and L. Hu*, “A novel approach to predict subjective pain perception from single-trial laser-evoked potentials,” NeuroImage, vol. 81, no. 1, pp. 283-293, Nov. 2013. [* Corresponding Author]

• L. Hu^#, Z. G. Zhang^#, and Y. Hu, “A time-varying source connectivity approach to reveal human somatosensory information processing,” NeuroImage, vol. 62, no. 1, pp. 217-228, Aug. 2012. [^# Equal Contribution]

• Z. G. Zhang^#, L. Hu^#, Y. S. Hung, A. Mouraux, and G. D. Iannetti, “Gamma-band oscillations in the primary somatosensory cortex - a direct and obligatory correlate of subjective pain intensity,” Journal of Neuroscience, vol. 32, no. 22, pp. 7429-7438, May 2012. [^# Equal Contribution] ·

Medical Signal and Image Processing

• A. M. Anter, M. A. Elaziz, and Z. G. Zhang*, “Real-time epileptic seizure recognition using Bayesian genetic whale optimizer and adaptive machine learning,” Future Generation Computer Systems, in press, 2021.

• A. M. Anter, D. Oliva, A. Thakare, and Z. G. Zhang*, “AFCM-LSMA: New intelligent model based on Lévy slime mould algorithm and adaptive fuzzy C-means for identification of COVID-19 infection from chest X-ray images,” Advanced Engineering Informatics, vol. 49, 101317, Aug. 2021. [* Corresponding Author]

• A. M. Anter, S. Bhattacharyya, and Z. G. Zhang*, “Multi-stage fuzzy swarm intelligence for automatic hepatic lesion segmentation from CT scans”, Applied Soft Computing, doi: 10.1016/j.asoc.2020.106677, Nov. 2020. [* Corresponding Author]

• G. Huang, Z. E. Xian, F. Tang, L. L. Li, L. Zhang, and Z. G. Zhang*, “Low-density surface electromyographic patterns under electrode-shift: Characterization and NMF-based classification”, Biomedical Signal Processing and Control, vol. 59, 101890, May 2020. [* Corresponding Author]

• G. Huang, Z. E. Xian, Z. G. Zhang*, S. C. Li, X. Y. Zhu, “Divide-and-conquer muscle synergies: A new feature space decomposition approach for simultaneous multifunction myoelectric control,” Biomedical Signal Processing and Control, vol. 44, pp. 209-220, Jul. 2018. [* Corresponding Author]

• X. Chen, H. Y. Wen, Q. L. Li, T. F. Wang, S. P. Chen, Y. P. Zheng, and Z. G. Zhang*, “Identifying transient patterns of in vivo muscle behaviors during isometric contraction by local polynomial regression,” Biomedical Signal Processing and Control, vol. 24, pp. 93-102, Feb. 2016. [* Corresponding Author]

• J. F. Wu, A. M. S. Ang, K. M. Tsui, H. C. Wu, Y. S. Hung, Y. Hu, J. N. F. Mak, S. C. Chan, and Z. G. Zhang*, “Efficient implementation and design of a new single-channel electrooculography-based human-machine interface system,” IEEE Transactions on Circuits and Systems II-Express Briefs, vol. 62., no. 2, pp. 179-183, Feb. 2015. [* Corresponding Author]

• X. Chen, Y. P. Zheng, J. Y. Guo, Z. Y. Zhu, S. C. Chan, and Z. G. Zhang*, “Sonomyographic responses during voluntary isometric ramp contraction of the human rectus femoris muscle,” European Journal of Applied Physiology, vol. 112, no. 7, pp. 2603-2614, Jul. 2012. [* Corresponding Author]

• Z. G. Zhang, K. D. K. Luk, and Y. Hu, “Identification of detailed time-frequency components in somatosensory evoked potentials,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 18, no. 3, pp. 245-254, Jun. 2010.

• Z. G. Zhang, H. T. Liu, S. C. Chan, K. D. K. Luk, and Y. Hu, “Time-dependent power spectral density estimation of surface electromyography during isometric muscle contraction: Methods and comparisons,”Journal of Electromyography and Kinesiology, vol. 20, no. 1, pp. 89-101, Feb. 2010.

• Z. G. Zhang, J. L. Yang, S. C. Chan, K. D. K. Luk, and Y. Hu, “Time-frequency component analysis of somatosensory evoked potentials in rats,” BioMedical Engineering OnLine, vol. 8, no. 4, DOI: 10.1186/1475-925X-8-4, Feb. 2009.

• Z. G. Zhang, V. W. Zhang, S. C. Chan, B. McPherson, and Y. Hu, “Time-frequency analysis of click-evoked otoacoustic emissions by means of a minimum variance spectral estimation-based method,” Hearing Research, vol. 243, no. 1-2, pp. 18-27, Sep. 2008.

• Z. G. Zhang, K. M. Tsui, S. C. Chan, W. Y. Lau, and M. Aboy, “A novel method for nonstationary power spectral density estimation of cardiovascular pressure signals based on a Kalman filter with variable number of measurements,” Medical & Biological Engineering & Computing, vol. 46, no. 8, pp. 789-797, Aug. 2008.

Signal Processing Methods and Engineering Applications

• L. Zhang^#, Z. N. Fu^#, W. W. Zhang*, G. Huang, Z. Liang, L. L. Li, B. B. Biswal, V. D. Calhoun, and Z. G. Zhang*, “Accessing dynamic functional connectivity using l0-regularized sparse-smooth inverse covariance estimation from fMRI,” Neurocomputing, vol. 443, no. 5, pp. 147-161, Jul, 2021. [* Corresponding Author]

• Z. G. Zhang and S. C. Chan, “Recursive parametric frequency/spectrum estimation for non-stationary signals with impulsive components using variable forgetting factor,” IEEE Transactions on Instrumentation and Measurement, vol. 62, no. 12, pp. 3251-3264, Dec. 2013.

• Z. G. Zhang, S. C. Chan, and C. Wang, “A new regularized adaptive windowed Lomb-periodogram for time-frequency analysis of nonstationary signals with impulsive components,” IEEE Transactions on Instrumentation and Measurement, vol. 61, no. 8, pp. 2283-2304, Aug. 2012.

• Z. G. Zhang, Y. S. Hung, and S. C. Chan, “Local polynomial modelling of time-varying autoregressive models with application to time-frequency analysis of event-related EEG,” IEEE Transactions on Biomedical Engineering, vol. 58, no. 3, pp. 557-566, Mar. 2011.

• Z. G. Zhang, S. C. Chan, and K. M. Tsui, “A recursive frequency estimator using linear prediction and a Kalman-filter-based iterative algorithm,” IEEE Transactions on Circuits and Systems II, vol. 55, no. 6, pp. 576-580, Jun. 2008.