Andreoli Luca, Bova Stefania Maria, Veggiotti Pierangelo
Neuroscience Research Centre, Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy.
Paediatric Neurology Unit, Buzzi Children's Hospital, Milan, Italy.
Dev Med Child Neurol. 2025 Oct;67(10):1250-1256. doi: 10.1111/dmcn.16361. Epub 2025 May 12.
The interplay between epilepsy and cognition is intricate and multifaceted, particularly in the context of childhood-onset epileptic disorders where epileptic activity can significantly interfere with and disrupt the delicate, highly plastic, and environment-related trajectories of neurodevelopment. Developmental and epileptic encephalopathy with spike-wave activation during slow sleep (D/EE-SWAS), a spectrum of conditions including Landau-Kleffner syndrome, could serve as a valuable model to explore these complexities. Research to date has primarily examined its distinctive features, including genetic and structural etiological factors, electroencephalographic patterns, and cognitive phenotypes, often interpreted through simplified cause-effect paradigms. The adoption of a network perspective that aligns with neurodevelopmental trajectories is essential to grasp the full complexity of this evolving condition. Advancing research requires the integration of multimodal data, while leveraging tools such as artificial intelligence to develop sophisticated models in order to achieve a holistic understanding of D/EE-SWAS.
癫痫与认知之间的相互作用错综复杂且具有多面性,在儿童期起病的癫痫性疾病背景下尤为如此,其中癫痫活动会显著干扰并破坏神经发育中微妙、高度可塑性且与环境相关的轨迹。慢波睡眠期棘波激活的发育性和癫痫性脑病(D/EE-SWAS),这一包括Landau-Kleffner综合征在内的一系列病症,可作为探索这些复杂性的宝贵模型。迄今为止的研究主要考察了其独特特征,包括遗传和结构病因因素、脑电图模式以及认知表型,这些往往通过简化的因果范式来解读。采用与神经发育轨迹相一致的网络视角对于全面理解这一不断演变的病症的复杂性至关重要。推进研究需要整合多模态数据,同时利用人工智能等工具来开发复杂模型,以便对D/EE-SWAS实现全面理解。