通过随机共振增强瞬态运动开始的视觉诱发电位:单峰和跨峰噪声效应

IF 2.3 4区 医学 Q2 BIOCHEMICAL RESEARCH METHODS
Huanqing Zhang , Jun Xie , Hongwei Yu , Fangzhao Du , Zhiwei Jin , Yujie Chen
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引用次数: 0

摘要

运动诱发视觉诱发电位(mVEP)是一种由突发运动刺激触发的短暂脑反应,广泛应用于脑机接口(BCI)系统。然而,mVEP信号固有的微弱特性对实现可靠和准确的BCI性能构成了重大挑战。因此,提高mVEP响应的信号质量对于提高系统稳健性和可用性至关重要。新方法本研究引入了一种基于随机共振(SR)理论的新方法,其中适当的噪声水平可以提高非线性系统(如大脑)的性能。通过将不同强度的听觉和视觉噪声与mVEP刺激一起应用,研究了单模态SR和跨模态SR效应。该方法检验了这些噪声条件对mVEP-BCI中大脑激活和分类性能的影响。结果中等水平的听觉或视觉噪声可显著增强mVEP的P2分量振幅,提高脑机接口任务的分类准确率。相反,过多的噪声导致神经反应受到抑制,噪声强度与mVEP幅值之间形成倒u型关系。传统的mVEP增强技术通常依赖于空间滤波或特征提取等信号处理方法。相比之下,提出的噪声调制策略直接增强神经反应,提供了一种生物学启发和计算简单的替代方案,补充了现有的方法。结论单模态和跨模态SR均能有效提高mVEP反应和脑机接口性能。该策略为SR机制提供了新的见解,并支持开发更强大的mVEP-BCI系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing transient motion-onset visual evoked potentials via stochastic resonance: Unimodal and cross-modal noise effects

Background

Motion-onset visual evoked potential (mVEP) are transient brain responses triggered by sudden motion stimuli and are widely used in brain-computer interface (BCI) systems. However, the inherently weak nature of mVEP signals poses a significant challenge to achieving reliable and accurate BCI performance. Enhancing the signal quality of mVEP responses is therefore critical for improving system robustness and usability.

New method

This study introduces a novel approach based on stochastic resonance (SR) theory, where appropriate levels of noise can enhance the performance of nonlinear systems such as the brain. By applying auditory and visual noise of varying intensities alongside mVEP stimuli, both unimodal SR and cross-modal SR effects were investigated. The method examines the effects of these noise conditions on brain activation and classification performance in mVEP-BCI.

Results

The results show that moderate levels of auditory or visual noise significantly enhance the P2 component amplitude of mVEP and improve classification accuracy in BCI tasks. In contrast, excessive noise leads to suppression of neural responses, forming an inverted U-shaped relationship between noise intensity and mVEP amplitude.

Comparison with existing methods

Conventional mVEP enhancement techniques typically rely on signal processing methods such as spatial filtering or feature extraction. In comparison, the proposed noise modulation strategy directly enhances neural responses, offering a biologically inspired and computationally simple alternative that complements existing approaches.

Conclusions

Both unimodal and cross-modal SR effectively enhance mVEP responses and BCI performance. This strategy provides new insights into SR mechanisms and supports the development of more robust mVEP-BCI systems.
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来源期刊
Journal of Neuroscience Methods
Journal of Neuroscience Methods 医学-神经科学
CiteScore
7.10
自引率
3.30%
发文量
226
审稿时长
52 days
期刊介绍: The Journal of Neuroscience Methods publishes papers that describe new methods that are specifically for neuroscience research conducted in invertebrates, vertebrates or in man. Major methodological improvements or important refinements of established neuroscience methods are also considered for publication. The Journal''s Scope includes all aspects of contemporary neuroscience research, including anatomical, behavioural, biochemical, cellular, computational, molecular, invasive and non-invasive imaging, optogenetic, and physiological research investigations.
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