| Literature DB >> 26688237 |
Matteo De Marco1, Francesca Meneghello2, Davide Duzzi3, Jessica Rigon2, Cristina Pilosio2, Annalena Venneri4.
Abstract
A cognitive-stimulation tool was created to regulate functional connectivity within the brain Default-Mode Network (DMN). Computerized exercises were designed based on the hypothesis that repeated task-dependent coactivation of multiple DMN regions would translate into regulation of resting-state network connectivity. Forty seniors (mean age: 65.90 years; SD: 8.53) were recruited and assigned either to an experimental group (n=21) who received one month of intensive cognitive stimulation, or to a control group (n=19) who maintained a regime of daily-life activities explicitly focused on social interactions. An MRI protocol and a battery of neuropsychological tests were administered at baseline and at the end of the study. Changes in the DMN (measured via functional connectivity of posterior-cingulate seeds), in brain volumes, and in cognitive performance were measured with mixed models assessing group-by-timepoint interactions. Moreover, regression models were run to test gray-matter correlates of the various stimulation tasks. Significant associations were found between task performance and gray-matter volume of multiple DMN core regions. Training-dependent up-regulation of functional connectivity was found in the posterior DMN component. This interaction was driven by a pattern of increased connectivity in the training group, while little or no up-regulation was seen in the control group. Minimal changes in brain volumes were found, but there was no change in cognitive performance. The training-dependent regulation of functional connectivity within the posterior DMN component suggests that this stimulation program might exert a beneficial impact in the prevention and treatment of early AD neurodegeneration, in which this neurofunctional pathway is progressively affected by the disease.Entities:
Keywords: Alzheimer’s disease; Brain networks; Mild cognitive impairment; Resting state; fMRI
Mesh:
Year: 2015 PMID: 26688237 DOI: 10.1016/j.brainresbull.2015.12.001
Source DB: PubMed Journal: Brain Res Bull ISSN: 0361-9230 Impact factor: 4.077