A Pilot Study on Brain Plasticity of Functional Connectivity Modulated by Cognitive Training in Mild Alzheimer’s Disease and Mild Cognitive Impairment

Abstract

Alzheimer’s disease (AD) alters the functional connectivity of the default mode network (DMN) but also the topological properties of the functional connectome. Cognitive training (CT) is a tool to slow down AD progression and is likely to impact on functional connectivity. In this pilot study, we aimed at investigating brain functional changes after a period of CT and active control (AC) in a group of 26 subjects with mild AD (mAD), 26 with amnestic mild cognitive impairment (aMCI), and a control group of 29 healthy elderly (HE) people. They all underwent a CT and AC in a counterbalanced order following a crossover design. Resting-state functional MRI and neuropsychological testing were acquired before and after each period. We tested post-CT and post-AC changes of cognitive abilities, of the functional connectivity of the DMN, and of topological network properties derived from graph theory and network-based statistics. Only CT produced functional changes, increasing the functional connectivity of the posterior DMN in all three groups. mAD also showed functional changes in the medial temporal lobe and topological changes in the anterior cingulum, whereas aMCI showed more widespread topological changes involving the frontal lobes, the cerebellum and the thalamus. Our results suggest specific functional connectivity changes after CT for aMCI and mAD.

The Efficacy of Cognitive Intervention in Mild Cognitive Impairment (MCI): a Meta-Analysis of Outcomes on Neuropsychological Measures

“…Taken together, the moderate summary effects observed after multicomponent and multidomain interventions would be consistent with activation of compensatory mechanisms described by the STAC-r model such that multifaceted cognitive interventions may recruit alternate networks as neurocomputational support to aid primary functional networks process load demands (Barban et al 2017 ; Ciarmiello et al 2015 ; Onur et al 2016 ). As such, strategies which target both primary functional networks as well as alternate pathways simultaneously may be the most efficacious form of intervention for individuals with MCI.…”

“…are aggressively being sought to mitigate or slow illness progression (Cai and Abrahamson 2016 ; Curlik and Shors 2013 ; Kivipelto et al 2013 ; Lehert et al 2015 ; Simons et al 2016 ; Smith et al 2010 ). This may be especially important as cognitive training in MCI has been associated with increased activation in the hippocampus (Hampstead et al 2012b ; Rosen et al 2011 ), right inferior parietal lobe (Belleville et al 2011 ), frontoparietal network (Hampstead et al 2011 ), occipito-temporal areas (Onur et al 2016 ), and implicated in other processes (Barban et al 2017 ; Ciarmiello et al 2015 ; Maffei et al 2017 ). As such, identifying the cognitive interventions effective in MCI may, in turn, aid in targeting the neural networks with greater specificity at prodromal stages to alter illness trajectory away from more serious cognitive decline (Kim and Kim 2014 ; Shatenstein and Bargerger-Gateau 2015 ; Sitzer et al 2006 ).…”

“…Primary network engagement would also be suggested by moderate to large effect sizes with multicomponent or multidomain interventions. In this instance, training may act on primary networks and complementary processes simultaneously requiring integration of complex skillsets, including lifestyle changes, mitigating structural and functional declines by enhancing processing in specific centers and decreasing the neural burden on other areas (Barban et al 2017 ; Hosseini et al 2014 ; Suo et al 2016 ). Multidomain approaches may also target multiple neural regions for a more enriched and complex neural challenge (Ballesteros et al 2015 ; Li et al 2017 ).…”

Altered Patterns of Phase Position Connectivity in Default Mode Subnetwork of Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment

“…Interestingly, compared to patients with SCD, DMN subnetworks in aMCI group showed obvious differences in right SFGMP and left MFGOP belonging to FG. In previous studies, aMCI group showed more widespread topological changes involving the frontal lobes (Barban et al, 2017), and aberrant connectivity was also found in patients with SCD between DMN and FG due to cognitive impairment (Xue et al, 2019). Besides, an increasing trend of values of amplitude of low-frequency fluctuation (ALFF) and fractional ALFF were detected in FG (Yang et al, 2018).…”

Brain Network Modeling Based on Mutual Information and Graph Theory for Predicting the Connection Mechanism in the Development of Alzheimer's Disease

“…Thus, we anticipate that MINM may explain the connection mechanism for the formation of the brain network organization in AD patients.topological properties for evaluating the characteristics of human brain networks [8][9][10][11][12]. Taking the form of a graph, people can learn the alterations of brain network properties in terms of network connectivity, transitivity, efficiency, degree distribution, modularity, and small-world-ness between normal controls (NC) and AD patients [13][14][15]. Particularly, graph theory also provides numerous methods of network modeling for simulating the evolution processes of real complex networks [16][17][18][19].…”