面向以主体为中心的协同适应性脑电脑接口,基于向后最佳传输
Victoria Peterson1, Valeria Spagnolo2, Catalina María Galván3
1Instituto de Matematica Aplicada del Litoral, Ruta Nacional N° 168 Km 0, S3000, Santa Fe, 3000, ARGENTINA.
Journal of neural engineering
|May 21, 2025
概括
这项研究引入了一种新的方法,用于评估运动图像大脑-计算机接口 (MI-BCI) 在协同适应性学习期间的技能. 支持性向后适应 (SBA) 方法通过适应用户并提供实时技能反来提高BCI性能.
科学领域:
- 神经科学是一个神经科学.
- 生物医学工程 生物医学工程
- 机器学习 机器学习
背景情况:
- 运动成像脑电脑接口 (MI-BCI) 需要大量的练习,并且对电脑电图 (EEG) 数据的跨会话变化敏感.
- 协同适应的系统,即用户和BCI算法同时学习,对于改善MI-BCI控制至关重要.
- 实时评估用户自我调节技能对于有效的协同适应BCI培训至关重要.
研究的目的:
- 开发一种在线评估运动图像 (MI) 调制能力的方法.
- 为协同适应的BCI创建一个框架,以提高用户性能和系统准确性.
- 为用户提供关于其MI调制技能的实时反.
主要方法:
- 使用后向最佳传输来进行域调整,以便在不需要重新训练分类器的情况下跨会话使用MI-BCI.
- 定义了一种支持性向后适应 (SBA) 方法,以标签为指导.
- 提出了试验适应所需的模型努力,作为MI调制技能的在线指标.
- 在真实和模拟的EEG数据上使用Riemannian特异性指标验证了该指标.
主要成果:
- 来自SBA的模型努力指标有效地评估了与MI任务相关的EEG模式的可区分性.
- 这一指标与已建立的里曼特异性指标有显著的相关性.
- 证明了该指标能够提供关于EEG模式的可区分性和稳定性的信息.
结论:
- 引入了一种新的协同适应性BCI学习框架,该框架将数据适应与用户技能评估集成在一起.
- SBA 方法促进了会话间的调整,并提高了 MI-BCI 的性能.
- 拟议的方法使用户能够对其MI调制策略提供反,推进以用户为中心的BCI开发.
相关概念视频
01:35Long-term Potentiation
Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre- and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
02:47The Synapse
Neurons communicate with one another by passing on their electrical signals to other neurons. A synapse is the location where two neurons meet to exchange signals. At the synapse, the neuron that sends the signal is called the presynaptic cell, while the neuron that receives the message is called the postsynaptic cell. Note that most neurons can be both presynaptic and postsynaptic, as they both transmit and receive information.
01:01Neuroplasticity
Neuroplasticity reflects the brain's remarkable capacity to adapt and evolve, responding dynamically to learning, experiences, or injury by reorganizing its neural circuitry. This reorganization involves creating new neural connections and refining old ones through a series of biological processes that contribute to the brain's lifelong development and adaptability.
01:20Parallel Processing
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...