Vallesi Antonino, Porcaro Camillo, Visalli Antonino, Fasolato Davide, Rossato Francesco, Bussè Cinzia, Cagnin Annachiara
Dipartimento di Neuroscienze, Università degli Studi di Padova, Italy; Padova Neuroscience Center, Università degli Studi di Padova, Italy.
Dipartimento di Neuroscienze, Università degli Studi di Padova, Italy; Padova Neuroscience Center, Università degli Studi di Padova, Italy; Institute of Cognitive Sciences and Technologies-National Research Council, Rome, Italy; Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, United Kingdom.
Clin Neurophysiol. 2024 Dec;168:43-51. doi: 10.1016/j.clinph.2024.10.004. Epub 2024 Oct 16.
Complex visual hallucinations (VH) are a core feature of dementia with Lewy bodies (DLB), though they may not occur in all patients. Power spectral density (PSD) analysis of resting-state EEG (rs-EEG) shows associations between some frequency bands (e.g., theta), individual alpha frequency (IAF) and VH. However, new tools that improve early differential diagnosis and symptom-based stratification with higher sensitivity and specificity, even within the DLB population, are desirable. We aimed to assess differences in rs-EEG data between DLB patients with VH (DLB-VH+) and without VH (DLB-VH-), comparing innovative non-linear approaches with more traditional linear ones.
We retrospectively analyzed rs-EEG recordings of DLB-VH+, DLB-VH-, Alzheimer's disease patients and age-matched healthy controls. EEG was analyzed using the nonlinear Higuchi's Fractal Dimension (FD) measure, and the results were compared with those of entropy and standard linear methods based on PSD and IAF.
Only the FD measure could discriminate between DLB-VH+ and DLB-VH-.
In conclusion, rs-EEG differences between DLB-VH+ and DLB-VH- are better characterized by FD analysis than by a more traditional power spectrum approach.
This suggests that the presence of complex VH is associated with less complex brain dynamics at rest, as reflected by the FD measure.
复杂视幻觉（VH）是路易体痴呆（DLB）的核心特征，尽管并非所有患者都会出现。静息态脑电图（rs-EEG）的功率谱密度（PSD）分析显示，某些频段（如θ波）、个体α频率（IAF）与VH之间存在关联。然而，即使在DLB患者群体中，也需要新的工具来提高早期鉴别诊断和基于症状的分层的敏感性和特异性。我们旨在评估有VH的DLB患者（DLB-VH+）和无VH的DLB患者（DLB-VH-）之间rs-EEG数据的差异，将创新的非线性方法与更传统的线性方法进行比较。
我们回顾性分析了DLB-VH+、DLB-VH-、阿尔茨海默病患者及年龄匹配的健康对照者的rs-EEG记录。使用非线性的 Higuchi 分形维数（FD）测量方法分析脑电图，并将结果与基于PSD和IAF的熵及标准线性方法的结果进行比较。
只有FD测量能够区分DLB-VH+和DLB-VH-。
总之，与更传统的功率谱方法相比，FD分析能更好地表征DLB-VH+和DLB-VH-之间的rs-EEG差异。
这表明，如FD测量所反映的，复杂VH的存在与静息时大脑动力学复杂性降低有关。
