Author name cluster

Xingwei An

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

5 papers

1 author row

YNIMG Journal 2026 Journal Article

An fMRI-based study of the effect of audiovisual stimulus temporal pacing on brain responses

Lu Wang
Xingwei An
Liang Zhao
Shuang Liu
Dong Ming

Research on the effect of stimulus temporal pacing on brain states is a central topic in neuroscience and psychology. Studies of audiovisual integration (AVI) in the fields of Brain-Computer Interfaces (BCIs) and neuropsychology have often yielded inconsistent findings, potentially due to variations in stimulus temporal pacing. Although a number of psychological experiments have investigated the effects of stimulus temporal pacing on brain activity, the underlying neural mechanisms remain poorly understood. This study aims to investigate how stimulus temporal pacing modulates the dynamic reconfiguration of brain activity and connectivity using functional magnetic resonance imaging (fMRI). A multimodal audiovisual oddball paradigm was employed, presenting stimuli at two temporal pacing conditions (rapid and slow) across three sensory modalities (visual, auditory, and audiovisual) to compare brain activation and functional connectivity across conditions. Results showed that in the unimodal condition, rapid stimuli preferentially engaged primary sensory cortices, indicating efficient perceptual encoding under high temporal pressure. In contrast, slow stimuli shifted processing toward higher-order cognitive regions, suggesting greater engagement in higher-order cognitive regions and enhance global network efficiency. For audiovisual condition, both rapid and slow stimuli elicit comparable functional connectivity patterns, whereas slow stimuli showed stronger connectivity in specific regions (e.g., occipital-motor areas, STG-DMN nodes), suggesting that the core audiovisual network and the extended whole-brain networks act in concert, forming a dual-layer processing mechanism. These findings provide a neural basis for understanding how stimulus temporal pacing acts as a modulator, shaping the dynamic balance between localized sensory analysis and integrated global processing.

Details DOI

YNIMG Journal 2026 Journal Article

The individual alpha bandwidth: A trait-like neural marker associated with sensory processing and executive function

Zeliang Jiang
Pan Zhang
Hanlin Wang
Wenxiao Zhong
Xingwei An
Zhijie Zhang

Alpha oscillations are a fundamental rhythm of human brain activity, yet most studies have emphasized the peak alpha frequency (IAF) while overlooking the width of the alpha band. Here, we examined the individual alpha bandwidth (IAB) as a complementary marker across four EEG datasets. Using a unified preprocessing pipeline, we assessed its reliability and functional relevance. Test-retest analyses showed good-to-excellent reliability, supporting its trait-like stability. Importantly, IAB estimated with the Savitzky-Golay filter (SGF) method-but not with FOOOF or amplitude-difference-was significantly related to sensory and cognitive processes, whereas IAF showed no such associations. In perception, wider parieto-occipital IAB during eyes-closed rest was associated with larger P2 amplitudes in visual and auditory evoked potentials. In cognition, wider parieto-occipital IAB during eyes-open rest was linked to smaller flanker interference effects and enhanced N450 amplitudes. Mediation analysis further revealed a significant indirect effect of N450 on the IAB-inhibitory control relationship, whereas the direct effect was not significant. These findings suggest that IAB reflects both perceptual and executive processes, but its functional relevance is constrained by methodological and experimental factors. Specifically, associations were method-dependent (emerging only with SGF), state-dependent (perception during eyes-closed rest, cognition during eyes-open rest), and in the cognitive domain, also frequency-window dependent (significant only within 6-14 Hz). Overall, this study establishes IAB as a reliable neural marker of individual differences in sensory and executive function while underscoring key methodological considerations for future research.

Details DOI

YNIMG Journal 2025 Journal Article

Sleep indicators and staging: A functional near-infrared spectroscopy study in healthy young adults

Yong Cao
Xingwei An
Wenxiao Zhong
Jin Jiang
Hongzuo Chu
Xuejun Jiao
Xiaoping Chen
Yufeng Ke

Functional near-infrared spectroscopy(fNIRS)-based sleep staging has attracted considerable interest due to its portability and limited interference with sleep. However, few studies have systematically examined sleep indicators or formulated sleep staging models based on fNIRS features labelled by polysomnography(PSG). This study aimed to address these shortcomings and promote the application of fNIRS in sleep monitoring. 37 volunteers participated in our experiment, with 6-channel prefrontal fNIRS data and standard PSG data collected simultaneously. Sleep indicators were extracted from time-domain, frequency-domain, and entropy perspectives. Sleep staging was developed based on these indicators using human-scored PSG as reference. Our findings indicated deeper sleep was correlated with a decrease in amplitude of time-domain features, while entropy features showed a contrasting trend. The fNIRS-based sleep staging achieved a Cohen's kappa(κ) of 0.76±0.12, 0.72±0.09, 0.71±0.07, with accuracies of 94.2 ± 2.4 %, 87.8 ± 3.2 %, and 82.2 ± 4.1 %, for 2-class(Wake/Sleep), 3-class(Wake/NREM/REM), 4-class (Wake/N1+N2/N3/REM) classifications, respectively. Sleep statistics derived from fNIRS closely aligned with those from PSG, with differences in sleep onset latency, wake after sleep onset, total wake/sleep time within 5 min and sleep efficiency below 3 %. The substantial agreement in both detailed (epoch-by-epoch) and comprehensive (total) sleep statistics with PSG suggests fNIRS is a reliable tool for long-term sleep monitoring in everyday settings.

Details DOI

JBHI Journal 2024 Journal Article

An Efficient Multi-Task Synergetic Network for Polyp Segmentation and Classification

Miao Wang
Xingwei An
Zhengcun Pei
Ning Li
Li Zhang
Gang Liu
Dong Ming

Colonoscopy is considered the best diagnostic tool for early detection and resection of polyps, which can effectively prevent consequential colorectal cancer. In clinical practice, segmenting and classifying polyps from colonoscopic images have a great significance since they provide precious information for diagnosis and treatment. In this study, we propose an efficient multi-task synergetic network (EMTS-Net) for concurrent polyp segmentation and classification, and we introduce a polyp classification benchmark for exploring the potential correlations of the above-mentioned two tasks. This framework is composed of an enhanced multi-scale network (EMS-Net) for coarse-grained polyp segmentation, an EMTS-Net (Class) for accurate polyp classification, and an EMTS-Net (Seg) for fine-grained polyp segmentation. Specifically, we first obtain coarse segmentation masks by using EMS-Net. Then, we concatenate these rough masks with colonoscopic images to assist EMTS-Net (Class) in locating and classifying polyps precisely. To further enhance the segmentation performance of polyps, we propose a random multi-scale (RMS) training strategy to eliminate the interference caused by redundant information. In addition, we design an offline dynamic class activation mapping (OFLD CAM) generated by the combined effect of EMTS-Net (Class) and RMS strategy, which optimizes bottlenecks between multi-task networks efficiently and elegantly and helps EMTS-Net (Seg) to perform more accurate polyp segmentation. We evaluate the proposed EMTS-Net on the polyp segmentation and classification benchmarks, and it achieves an average mDice of 0. 864 in polyp segmentation and an average AUC of 0. 913 with an average accuracy of 0. 924 in polyp classification. Quantitative and qualitative evaluations on the polyp segmentation and classification benchmarks demonstrate that our EMTS-Net achieves the best performance and outperforms previous state-of-the-art methods in terms of both efficiency and generalization.

Details DOI

JBHI Journal 2024 Journal Article

EEG Characteristic Comparison of Motor Imagery Between Supernumerary and Inherent Limb: Sixth-Finger MI Enhances the ERD Pattern and Classification Performance

Zhuang Wang
Yuan Liu
Shuaifei Huang
Shiyin Qiu
Yujian Zhang
Huimin Huang
Xingwei An
Dong Ming

Adding supernumerary robotic limbs (SRLs) to humans and controlling them directly through the brain are main goals for movement augmentation. However, it remains uncertain whether neural patterns different from the traditional inherent limbs motor imagery (MI) can be extracted, which is essential for high-dimensional control of external devices. In this work, we established a MI neo-framework consisting of novel supernumerary robotic sixth-finger MI (SRF-MI) and traditional right-hand MI (RH-MI) paradigms and validated the distinctness of EEG response patterns between two MI tasks for the first time. Twenty-four subjects were recruited for this experiment involving three mental tasks. Event-related spectral perturbation was adopted to supply details about event-related desynchronization (ERD). Activation region, intensity and response time (RT) of ERD were compared between SRF-MI and RH-MI tasks. Three classical classification algorithms were utilized to verify the separability between different mental tasks. And genetic algorithm aims to select optimal combination of channels for neo-framework. A bilateral sensorimotor and prefrontal modulation was found during the SRF-MI task, whereas in RH-MI only contralateral sensorimotor modulation was exhibited. The novel SRF-MI paradigm enhanced ERD intensity by a maximum of 117% in prefrontal area and 188% in the ipsilateral somatosensory-association cortex. And, a global decrease of RT was exhibited during SRF-MI tasks compared to RH-MI. Classification results indicate well separable performance among different mental tasks (88. 1% maximum for 2-class and 88. 2% maximum for 3-class). This work demonstrated the difference between the SRF-MI and RH-MI paradigms, widening the control bandwidth of the BCI system.

Details DOI