Department of Informatics, Ionian University, Corfu, Greece.
Trinity College Institute of Neurosciences, Trinity College, Dublin, Ireland.
Adv Exp Med Biol. 2023;1424:1-22. doi: 10.1007/978-3-031-31982-2_1.
Large-scale human brain networks interact across both spatial and temporal scales. Especially for electro- and magnetoencephalography (EEG/MEG), there are many evidences that there is a synergy of different subnetworks that oscillate on a dominant frequency within a quasi-stable brain temporal frame. Intrinsic cortical-level integration reflects the reorganization of functional brain networks that support a compensation mechanism for cognitive decline. Here, a computerized intervention integrating different functions of the medial temporal lobes, namely, object-level and scene-level representations, was conducted. One hundred fifty-eight patients with mild cognitive impairment underwent 90 min of training per day over 10 weeks. An active control (AC) group of 50 subjects was exposed to documentaries, and a passive control group of 55 subjects did not engage in any activity. Following a dynamic functional source connectivity analysis, the dynamic reconfiguration of intra- and cross-frequency coupling mechanisms before and after the intervention was revealed. After the neuropsychological and resting state electroencephalography evaluation, the ratio of inter versus intra-frequency coupling modes and also the contribution of β1 frequency was higher for the target group compared to its pre-intervention period. These frequency-dependent contributions were linked to neuropsychological estimates that were improved due to intervention. Additionally, the time-delays of the cortical interactions were improved in {δ, θ, α2, β1} compared to the pre-intervention period. Finally, dynamic networks of the target group further improved their efficiency over the total cost of the network. This is the first study that revealed a dynamic reconfiguration of intrinsic coupling modes and an improvement of time-delays due to a target intervention protocol.
大规模的人类大脑网络在空间和时间尺度上相互作用。特别是对于脑电图（EEG）和脑磁图（MEG），有许多证据表明，在准稳定的大脑时间框架内，存在着不同子网络以主导频率协同振荡的现象。皮质内整合反映了功能脑网络的重新组织，支持认知衰退的补偿机制。在这里，进行了一项整合内侧颞叶不同功能的计算机干预，即物体水平和场景水平的表示。158 名轻度认知障碍患者每天接受 90 分钟的训练，持续 10 周。50 名主动对照组（AC）患者观看纪录片，55 名被动对照组患者不参与任何活动。在进行动态功能源连接分析后，揭示了干预前后的内频和外频耦合机制的动态重构。在神经心理学和静息状态脑电图评估之后，与干预前相比，目标组的跨频和内频耦合模式的比值以及β1 频率的贡献更高。这些与β1 频率相关的频域贡献与由于干预而改善的神经心理学估计有关。此外，与干预前相比，{δ、θ、α2、β1}的皮质相互作用的时间延迟得到了改善。最后，目标组的动态网络进一步提高了其效率，总网络成本降低。这是第一项揭示由于目标干预方案而导致内在耦合模式动态重构和时间延迟改善的研究。
