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.

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