Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, The Netherlands.
Department of Clinical Neurophysiology and MEG, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, The Netherlands.
J Alzheimers Dis. 2022;87(1):317-333. doi: 10.3233/JAD-215464.
In Alzheimer's disease (AD), oscillatory activity of the human brain slows down. However, oscillatory slowing varies between individuals, particularly in prodromal AD. Cortical oscillatory changes have shown suboptimal accuracy as diagnostic markers. We speculated that focusing on the hippocampus might prove more successful, particularly using magnetoencephalography (MEG) for capturing subcortical oscillatory activity.
We explored MEG-based detection of hippocampal oscillatory abnormalities in prodromal AD patients.
We acquired resting-state MEG data of 18 AD dementia patients, 18 amyloid-β-positive amnestic mild cognitive impairment (MCI, prodromal AD) patients, and 18 amyloid-β-negative persons with subjective cognitive decline (SCD). Oscillatory activity in 78 cortical regions and both hippocampi was reconstructed using beamforming. Between-group and hippocampal-cortical differences in spectral power were assessed. Classification accuracy was explored using ROC curves.
The MCI group showed intermediate power values between SCD and AD, except for the alpha range, where it was higher than both (p < 0.05 and p < 0.001). The largest differences between MCI and SCD were in the theta band, with higher power in MCI (p < 0.01). The hippocampi showed several unique group differences, such as higher power in the higher alpha band in MCI compared to SCD (p < 0.05). Classification accuracy (MCI versus SCD) was best for absolute theta band power in the right hippocampus (AUC = 0.87).
In this MEG study, we detected oscillatory abnormalities of the hippocampi in prodromal AD patients. Moreover, hippocampus-based classification performed better than cortex-based classification. We conclude that a focus on hippocampal MEG may improve early detection of AD-related neuronal dysfunction.
在阿尔茨海默病（AD）中，人脑的振荡活动会减慢。然而，个体之间的振荡减慢情况存在差异，尤其是在 AD 的前驱期。皮质振荡变化作为诊断标志物的准确性并不理想。我们推测，关注海马体可能会更成功，特别是使用脑磁图（MEG）来捕捉皮质下的振荡活动。
我们探索了基于 MEG 的前驱期 AD 患者海马体振荡异常的检测。
我们采集了 18 名 AD 痴呆患者、18 名淀粉样蛋白-β阳性遗忘型轻度认知障碍（MCI，前驱期 AD）患者和 18 名淀粉样蛋白-β阴性主观认知下降（SCD）患者的静息状态 MEG 数据。使用波束形成重建了 78 个皮质区域和两个海马体的振荡活动。评估了组间和海马体-皮质间的频谱功率差异。使用 ROC 曲线探索分类准确性。
MCI 组的功率值在 SCD 和 AD 之间处于中间水平，除了在阿尔法频段，其功率值高于两者（p<0.05 和 p<0.001）。MCI 和 SCD 之间最大的差异出现在 theta 频段，MCI 的功率较高（p<0.01）。海马体还显示出一些独特的组间差异，例如 MCI 比 SCD 具有更高的高 alpha 频段功率（p<0.05）。MCI 与 SCD 相比，右侧海马体的绝对 theta 频段功率的分类准确性（AUC=0.87）最佳。
在这项 MEG 研究中，我们检测到前驱期 AD 患者的海马体振荡异常。此外，基于海马体的分类比基于皮质的分类表现更好。我们得出结论，关注海马体的 MEG 可能会提高 AD 相关神经元功能障碍的早期检测能力。
