用声音化与量子模拟分析癫痫发作，探索真实数据与模型的差异。
Sonified Quantum Seizures. Sonification of time series in epileptic seizures and simulation of seizures via quantum modelling
- 将脑电图信号转为多声部音乐，直观呈现癫痫发作特征。
- 提出两种量子计算方法模拟癫痫发作过程，生成可听化结果。
- 适合神经科学、量子计算交叉研究者，提供新分析范式。
我们应用声音化策略和量子计算分析一次癫痫发作事件。首先对部分通道的实测皮层电图（ECoG）数据进行声音化处理，生成多声部音序。随后提出两种量子计算方法模拟类似的发作过程，并对模拟结果进行声音化。通过对比真实数据与模拟结果的声音表现，可识别两者间的相似性与差异，从而优化虚拟仿真模型。该研究是首个结合量子计算与声音化的癫痫分析方法，拓展了真实数据的探索视角，为癫痫分析与预测构建了新的测试平台。
原文摘要 · Abstract (English)
We apply sonification strategies and quantum computing to the analysis of an episode of seizure. We first sonify the signal from a selection of channels (from real ECoG data), obtaining a polyphonic sequence. Then, we propose two quantum approaches to simulate a similar episode of seizure, and we sonify the results. The comparison of sonifications can give hints on similarities and discrepancies between real data and simulations, helping refine the \textit{in silico} model. This is a pioneering approach, showing how the combination of quantum computing and sonification can broaden the perspective of real-data investigation, and helping define a new test bench for analysis and prediction of seizures.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。