Pascarella Annalisa, Bruni Vittoria, Armonaite Karolina, Porcaro Camillo, Conti Livio, Cecconi Federico, Paulon Luca, Vitulano Domenico, Tecchio Franca
Istituto per le Applicazioni del Calcolo 'Mauro Picone', National Research Council of Italy, Rome, Italy.
Department of Basic and Applied Science for Engineering (SBAI), University of Rome 'Sapienza', Rome, Italy.
Front Neurosci. 2024 Jan 25;17:1261701. doi: 10.3389/fnins.2023.1261701. eCollection 2023.
The formation and functioning of neural networks hinge critically on the balance between structurally homologous areas in the hemispheres. This balance, reflecting their physiological relationship, is fundamental for learning processes. In our study, we explore this functional homology in the resting state, employing a complexity measure that accounts for the temporal patterns in neurodynamics.
We used Normalized Compression Distance (NCD) to assess the similarity over time, neurodynamics, of the somatosensory areas associated with hand perception (S1). This assessment was conducted using magnetoencephalography (MEG) in conjunction with Functional Source Separation (FSS). Our primary hypothesis posited that neurodynamic similarity would be more pronounced within individual subjects than across different individuals. Additionally, we investigated whether this similarity is influenced by hemisphere or age at a population level.
Our findings validate the hypothesis, indicating that NCD is a robust tool for capturing balanced functional homology between hemispheric regions. Notably, we observed a higher degree of neurodynamic similarity in the population within the left hemisphere compared to the right. Also, we found that intra-subject functional homology displayed greater variability in older individuals than in younger ones.
Our approach could be instrumental in investigating chronic neurological conditions marked by imbalances in brain activity, such as depression, addiction, fatigue, and epilepsy. It holds potential for aiding in the development of new therapeutic strategies tailored to these complex conditions, though further research is needed to fully realize this potential.
神经网络的形成与功能关键取决于半球中结构同源区域之间的平衡。这种反映它们生理关系的平衡对于学习过程至关重要。在我们的研究中，我们采用一种考虑神经动力学时间模式的复杂性度量，探索静息状态下的这种功能同源性。
我们使用归一化压缩距离（NCD）来评估与手部感知相关的体感区域（S1）随时间的神经动力学相似性。这项评估是通过将脑磁图（MEG）与功能源分离（FSS）相结合来进行的。我们的主要假设是，神经动力学相似性在个体内部比在不同个体之间更为显著。此外，我们在群体水平上研究了这种相似性是否受半球或年龄的影响。
我们的研究结果验证了这一假设，表明NCD是捕捉半球区域间平衡功能同源性的有力工具。值得注意的是，我们观察到，与右侧相比，群体中左侧半球的神经动力学相似性程度更高。此外，我们发现，与年轻个体相比，老年个体的受试者内功能同源性表现出更大的变异性。
我们的方法可能有助于研究以大脑活动失衡为特征的慢性神经疾病，如抑郁症、成瘾、疲劳和癫痫。尽管需要进一步研究以充分实现这一潜力，但它在帮助开发针对这些复杂病症的新治疗策略方面具有潜力。
