Abstract
Aberrant activity of local functional networks underlies memory and cognition deficits in Alzheimer’s disease (AD). Hyperactivity was observed in microcircuits of mice AD-models showing plaques, and also recently in early stage AD mutants prior to amyloid deposition. However, early functional effects of AD on cortical microcircuits remain unresolved. Using two-photon calcium imaging, we found altered temporal distributions (burstiness) in the spontaneous activity of layer II/III visual cortex neurons, in a mouse model of familial Alzheimer’s disease (5xFAD), before plaque formation. Graph theory (GT) measures revealed a distinct network topology of 5xFAD microcircuits, as compared to healthy controls, suggesting degradation of parameters related to network robustness. After treatment with acitretin, we observed a re-balancing of those network measures in 5xFAD mice; particularly in the mean degree distribution, related to network development and resilience, and post-treatment values resembled those of age-matched controls. Further, behavioral deficits, and the increase of excitatory synapse numbers in layer II/III were reversed after treatment. GT is widely applied for whole-brain network analysis in human neuroimaging, we here demonstrate the translational value of GT as a multi-level tool, to probe networks at different levels in order to assess treatments, explore mechanisms, and contribute to early diagnosis.
Highlights
Aberrant activity of local functional networks underlies memory and cognition deficits in Alzheimer’s disease (AD)
We provide evidence that acitretin stabilizes cortical microcircuit dynamics and rebalances network topology parameters related to network development and resilience in early-stage 5xFAD mice
In 5xFAD mice, it has been shown that Aβ depositions first appear in deep layers of the cortex and the subiculum, to later spread towards other cortical regions and hippocampus[37]
Summary
Aberrant activity of local functional networks underlies memory and cognition deficits in Alzheimer’s disease (AD). Since the brain’s structural and functional systems can be understood as complex n etworks[23], this approach has been rapidly translated to quantitative analysis of brain network organization with a vast number of studies investigating human AD imaging data[11,30,31,32,33]. In those studies, whole-brain network topology was shown to be disrupted in fMRI networks affecting their global efficiency and modularity – two of many parameters used for network topology assessment—in late[34] as well as in early stages of AD11,35
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