| Autor: |
Farràs-Permanyer L; Departament de Psicologia Social i Psicologia Quantitativa, Facultat de Psicologia, Universitat de Barcelona, 08035 Barcelona, Spain.; UBICS Institute of Complex Systems & UB Institute of Neurosciences, 08035 Barcelona, Spain., Mancho-Fora N; Departament de Psicologia Social i Psicologia Quantitativa, Facultat de Psicologia, Universitat de Barcelona, 08035 Barcelona, Spain., Montalà-Flaquer M; Departament de Psicologia Social i Psicologia Quantitativa, Facultat de Psicologia, Universitat de Barcelona, 08035 Barcelona, Spain., Gudayol-Ferré E; Facultad de Psicología, Universidad Michoacana de San Nicolás Hidalgo, Morelia 58000, Mexico., Gallardo-Moreno GB; Instituto de Neurociencias, Guadalajara, Jalisco 44130, Mexico., Zarabozo-Hurtado D; CINDFA-Grupo Río, Guadalajara, Jalisco 44648, Mexico., Villuendas-González E; Facultad de Psicología, Universidad Michoacana de San Nicolás Hidalgo, Morelia 58000, Mexico., Peró-Cebollero M; Departament de Psicologia Social i Psicologia Quantitativa, Facultat de Psicologia, Universitat de Barcelona, 08035 Barcelona, Spain.; UBICS Institute of Complex Systems & UB Institute of Neurosciences, 08035 Barcelona, Spain., Guàrdia-Olmos J; Departament de Psicologia Social i Psicologia Quantitativa, Facultat de Psicologia, Universitat de Barcelona, 08035 Barcelona, Spain.; UBICS Institute of Complex Systems & UB Institute of Neurosciences, 08035 Barcelona, Spain. |
| Abstrakt: |
Mild cognitive impairment is defined as greater cognitive decline than expected for a person at a particular age and is sometimes considered a stage between healthy aging and Alzheimer's disease or other dementia syndromes. It is known that functional connectivity patterns change in people with this diagnosis. We studied functional connectivity patterns and functional segregation in a resting-state fMRI paradigm comparing 10 MCI patients and 10 healthy controls matched by education level, age and sex. Ninety ROIs from the automated anatomical labeling (AAL) atlas were selected for functional connectivity analysis. A correlation matrix was created for each group, and a third matrix with the correlation coefficient differences between the two matrices was created. Functional segregation was analyzed with the 3-cycle method, which is novel in studies of this topic. Finally, cluster analyses were also performed. Our results showed that the two correlation matrices were visually similar but had many differences related to different cognitive functions. Differences were especially apparent in the anterior default mode network (DMN), while the visual resting-state network (RSN) showed no differences between groups. Differences in connectivity patterns in the anterior DMN should be studied more extensively to fully understand its role in the differentiation of healthy aging and an MCI diagnosis. |
