Porcaro Camillo, Seppi Dario, Pellegrino Giovanni, Dainese Filippo, Kassabian Benedetta, Pellegrino Luciano, De Nardi Gianluigi, Grego Alberto, Corbetta Maurizio, Ferreri Florinda
Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy.
Institute of Cognitive Sciences and Technologies (ISTC) - National Research Council (CNR), Rome, Italy.
Front Neurosci. 2024 Jun 7;18:1401068. doi: 10.3389/fnins.2024.1401068. eCollection 2024.
An important challenge in epilepsy is to define biomarkers of response to treatment. Many electroencephalography (EEG) methods and indices have been developed mainly using linear methods, e.g., spectral power and individual alpha frequency peak (IAF). However, brain activity is complex and non-linear, hence there is a need to explore EEG neurodynamics using nonlinear approaches. Here, we use the Fractal Dimension (FD), a measure of whole brain signal complexity, to measure the response to anti-seizure therapy in patients with Focal Epilepsy (FE) and compare it with linear methods.
Twenty-five drug-responder (DR) patients with focal epilepsy were studied before (t1, named DR-t1) and after (t2, named DR-t2) the introduction of the anti-seizure medications (ASMs). DR-t1 and DR-t2 EEG results were compared against 40 age-matched healthy controls (HC).
EEG data were investigated from two different angles: frequency domain-spectral properties in δ, θ, α, β, and γ bands and the IAF peak, and time-domain-FD as a signature of the nonlinear complexity of the EEG signals. Those features were compared among the three groups.
The δ power differed between DR patients pre and post-ASM and HC (DR-t1 vs. HC, < 0.01 and DR-t2 vs. HC, < 0.01). The θ power differed between DR-t1 and DR-t2 ( = 0.015) and between DR-t1 and HC ( = 0.01). The α power, similar to the δ, differed between DR patients pre and post-ASM and HC (DR-t1 vs. HC, < 0.01 and DR-t2 vs. HC, < 0.01). The IAF value was lower for DR-t1 than DR-t2 ( = 0.048) and HC ( = 0.042). The FD value was lower in DR-t1 than in DR-t2 ( = 0.015) and HC ( = 0.011). Finally, Bayes Factor analysis showed that FD was 195 times more likely to separate DR-t1 from DR-t2 than IAF and 231 times than θ.
FD measured in baseline EEG signals is a non-linear brain measure of complexity more sensitive than EEG power or IAF in detecting a response to ASMs. This likely reflects the non-oscillatory nature of neural activity, which FD better describes.
Our work suggests that FD is a promising measure to monitor the response to ASMs in FE.
癫痫治疗中的一个重要挑战是确定治疗反应的生物标志物。许多脑电图（EEG）方法和指标主要是使用线性方法开发的，例如频谱功率和个体阿尔法频率峰值（IAF）。然而，大脑活动是复杂且非线性的，因此需要使用非线性方法来探索EEG神经动力学。在此，我们使用分形维数（FD），一种衡量全脑信号复杂性的指标，来测量局灶性癫痫（FE）患者对抗癫痫治疗的反应，并将其与线性方法进行比较。
对25名药物反应者（DR）局灶性癫痫患者在引入抗癫痫药物（ASM）之前（t1，称为DR-t1）和之后（t2，称为DR-t2）进行了研究。将DR-t1和DR-t2的EEG结果与40名年龄匹配的健康对照（HC）进行比较。
从两个不同角度研究EEG数据：δ、θ、α、β和γ频段的频域频谱特性以及IAF峰值，以及作为EEG信号非线性复杂性特征的时域FD。在三组之间比较这些特征。
DR患者在ASM治疗前后与HC之间的δ功率存在差异（DR-t1与HC比较，<0.01；DR-t2与HC比较，<0.01）。DR-t1和DR-t2之间以及DR-t1和HC之间的θ功率存在差异（=0.015和=0.01）。与δ类似，DR患者在ASM治疗前后与HC之间的α功率存在差异（DR-t1与HC比较，<0.01；DR-t2与HC比较，<0.01）。DR-t1的IAF值低于DR-t2（=0.048）和HC（=0.042）。DR-t1的FD值低于DR-t2（=0.015）和HC（=0.011）。最后，贝叶斯因子分析表明，FD区分DR-t1和DR-t2的可能性比IAF高195倍，比θ高231倍。
在基线EEG信号中测量的FD是一种非线性的大脑复杂性测量指标，在检测对ASM的反应方面比EEG功率或IAF更敏感。这可能反映了神经活动的非振荡性质，而FD能更好地描述这一性质。
我们的研究表明，FD是监测FE患者对ASM反应的一个有前景的指标。
