Hypersynchronization in mild cognitive impairment: the 'X' model

Brain. 2019 Dec 1;142(12):3936-3950. doi: 10.1093/brain/awz320.


Hypersynchronization has been proposed as a synaptic dysfunction biomarker in the Alzheimer's disease continuum, reflecting the alteration of the excitation/inhibition balance. While animal models have verified this idea extensively, there is still no clear evidence in humans. Here we test this hypothesis, evaluating the risk of conversion from mild cognitive impairment (MCI) to Alzheimer's disease in a longitudinal study. We compared the functional resting state eyes-closed magnetoencephalographic networks of 54 patients with MCI who were followed-up every 6 months. According to their clinical outcome, they were split into: (i) the 'progressive' MCI (n = 27) group; and (ii) the 'stable' MCI group (n = 27). They did not differ in gender or educational level. For all participants, two magnetoencephalographic recordings were acquired. Functional connectivity was evaluated using the phase locking value. To extract the functional connectivity network with significant changes between both magnetoencephalographic recordings, we evaluated the functional connectivity ratio, defined as functional connectivity post-/pre-condition, in a network-based statistical model with an ANCOVA test with age as covariate. Two significant networks were found in the theta and beta bands, involving fronto-temporal and fronto-occipital connections, and showing a diminished functional connectivity ratio in the progressive MCI group. These topologies were then evaluated at each condition showing that at baseline, patients with progressive MCI showed higher synchronization than patients with stable MCI, while in the post-condition this pattern was reversed. These results may be influenced by two main factors in the post-condition: the increased synchrony in the stable MCI patients and the network failure in the progressive MCI patients. These findings may be explained as an 'X' form model where the hypersynchrony predicts conversion, leading subsequently to a network breakdown in progressive MCI. Patients with stable MCI showed an opposite phenomenon, which could indicate that they were a step beyond in the Alzheimer's disease continuum. This model would be able to predict the risk for the conversion to dementia in MCI patients.

Keywords: classification; functional connectivity; longitudinal study; magnetoencephalography; stable and progressive mild cognitive impairment.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Alzheimer Disease / diagnostic imaging*
  • Brain / diagnostic imaging*
  • Cognitive Dysfunction / diagnostic imaging*
  • Disease Progression
  • Female
  • Humans
  • Magnetic Resonance Imaging
  • Magnetoencephalography
  • Male
  • Nerve Net / diagnostic imaging*
  • Neuroimaging
  • Neuropsychological Tests