Dynamics of the Brain Functional Network Associated With Subjective Cognitive Decline and Its Relationship to Apolipoprotein E €4 Alleles

Insomnia disorder characterized by probabilistic metastable substates using blood-oxygenation-level-dependent (BOLD) phase signals

PURPOSE

From a clinical point of view, how to force a transition from insomnia brain state to healthy brain state by external driven stimulation is of great interest. This needs to define brain state of insomnia disorder as metastable substates. The current study was to identify recurrent substates of insomnia disorder in terms of probability of occurrence, lifetime, and alternation profiles by using leading eigenvector dynamics analysis (LEiDA) method.

METHODS

We enrolled 32 patients with insomnia disorder and 30 healthy subjects. We firstly obtained the BOLD phase coherence matrix from Hilbert transform of BOLD signals and then extracted all the leading eigenvectors from the BOLD phase coherence matrix for all subjects across all time points. Lastly, we clustered the leading eigenvectors using a k-means clustering algorithm to find the probabilistic metastable substates (PMS) and calculate the probability of occurrence and associated lifetime for substates.

RESULTS

The resulting 3 clusters were optimal for brain state of insomnia disorder and healthy brain state, respectively. The occurred probabilities of the PMS were significantly different between the patients with insomnia disorder and healthy subjects, with 0.51 versus 0.44 for PMS-1 (p < 0.001), 0.25 versus 0.27 for PMS-2 (p = 0.051), and 0.24 versus 0.29 for PMS-3 (p < 0.001), as well as the lifetime (in TR) of 36.65 versus 33.15 for PMS-1 (p = 0.068), 14.36 versus 15.43 for PMS-2 (p = 0.117), and 14.80 versus 16.34 for PMS-3 (p = 0.042). The values of the diagonal of the transition matrix were much higher than the probabilities of switching states, indicating the metastable nature of substates.

CONCLUSION

The resulted probabilistic metastable substates hint the characteristic brain dynamics of insomnia disorder. The results may lay a foundation to help determine how to force a transition from insomnia brain state to healthy brain state by external driven stimulation.

Shared and unique effects of ApoEε4 and pathogenic gene mutation on cognition and imaging in preclinical familial Alzheimer's disease

BACKGROUND

Neuropsychology and imaging changes have been reported in the preclinical stage of familial Alzheimer's disease (FAD). This study investigated the effects of APOEε4 and known pathogenic gene mutation on different cognitive domains and circuit imaging markers in preclinical FAD.

METHODS

One hundred thirty-nine asymptomatic subjects in FAD families, including 26 APOEε4 carriers, 17 APP and 20 PS1 mutation carriers, and 76 control subjects, went through a series of neuropsychological tests and MRI scanning. Test scores and imaging measures including volumes, diffusion indices, and functional connectivity (FC) of frontostriatal and hippocampus to posterior cingulate cortex pathways were compared between groups and analyzed for correlation.

RESULTS

Compared with controls, the APOEε4 group showed increased hippocampal volume and decreased FC of fronto-caudate pathway. The APP group showed increased recall scores in auditory verbal learning test, decreased fiber number, and increased radial diffusivity and FC of frontostriatal pathway. All three genetic groups showed decreased fractional anisotropy of hippocampus to posterior cingulate cortex pathway. These neuropsychological and imaging measures were able to discriminate genetic groups from controls, with areas under the curve from 0.733 to 0.837. Circuit imaging measures are differentially associated with scores in various cognitive scales in control and genetic groups.

CONCLUSIONS

There are neuropsychological and imaging changes in the preclinical stage of FAD, some of which are shared by APOEε4 and known pathogenic gene mutation, while some are unique to different genetic groups. These findings are helpful for the early identification of Alzheimer's disease and for developing generalized and individualized prevention and intervention strategies.