Bosl William, Enlow Michelle Bosquet, Nelson Charles
University of San Francisco.
Boston Children's Hospital.
Res Sq. 2024 Sep 18:rs.3.rs-4927086. doi: 10.21203/rs.3.rs-4927086/v1.
Neural circuits are often considered the bridge connecting genetic causes and behavior. Whereas prenatal neural circuits are believed to be derived from a combination of genetic and intrinsic activity, postnatal circuits are largely influenced by exogenous activity and experience. A dynamical neuroelectric field maintained by neural activity is proposed as the fundamental information processing substrate of cognitive function. Time series measurements of the neuroelectric field can be collected by scalp sensors and used to mathematically quantify the essential dynamical features of the neuroelectric field by constructing a digital twin of the dynamical system phase space. The multiscale nonlinear values that result can be organized into tensor data structures, from which latent features can be extracted using tensor factorization. These latent features can be mapped to behavioral constructs to derive digital biomarkers. This computational framework provides a robust method for incorporating neurodynamical measures into neuropsychiatric biomarker discovery.
神经回路通常被视为连接遗传因素与行为的桥梁。产前神经回路被认为源自遗传和内在活动的结合,而后天回路在很大程度上受外部活动和经验的影响。由神经活动维持的动态神经电场被认为是认知功能的基本信息处理基质。神经电场的时间序列测量可通过头皮传感器收集,并通过构建动态系统相空间的数字孪生,用于从数学上量化神经电场的基本动态特征。由此得到的多尺度非线性值可组织成张量数据结构,利用张量分解从中提取潜在特征。这些潜在特征可映射到行为结构上,以得出数字生物标志物。这一计算框架为将神经动力学测量纳入神经精神生物标志物发现提供了一种可靠方法。