Spontaneous Changes in Functional Connectivity of Independent Components of fMRI Signal in Healthy Volunteers at Rest and in Subjects with Mild Depression


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Resumo

Depression is associated with changes in the pattern of interaction of cerebral networks, which can reflect both existing symptoms and compensatory processes. The study is based on analysis of resting state fMRI data from 15 patients with mild depression and 19 conventionally healthy individuals. From fMRI signal recorded at rest for 4 min, the independent components were reconstructed. The intergroup differences and dynamics of functional connectivity from the first to the second recording were analyzed. Initially, depressive patients demonstrated weaker connectivity between cerebellar declive network (CN) and left central executive network (CEN) and also sensorimotor network (SMN); left CEN and primary visual network (PVN). During the second recording, the patients demonstrated more intensive reciprocal connection of the dorsal domain of default mode network (DMN) and auditory network (AN). In healthy subjects, positive correlations of the dorsal DMN and left CEN, right CEN and CN, and negative correlation of dorsal DMN and visuospatial network weakened from the first to second record. In the depression group, the interaction of AN with PVN, the right CEN with the anterior salience network and with ventral DMN weakened. At the same time, the connectivity between SMN and CN were strengthened. The results can be interpreted as spontaneous normalization of brain activity, but no direct evidence for their relation to the improvement of depression symptoms was found.

Sobre autores

D. Bezmaternykh

Research Institute of Molecular Biology and Biophysics; Novosibirsk National Research State University

Email: mikhail-melnikov@mail.ru
Rússia, Novosibirsk; Novosibirsk

M. Mel’nikov

Research Institute of Molecular Biology and Biophysics; Novosibirsk National Research State University

Autor responsável pela correspondência
Email: mikhail-melnikov@mail.ru
Rússia, Novosibirsk; Novosibirsk

E. Petrovskii

International Tomography Center, Siberian Division of the Russian Academy of Sciences

Email: mikhail-melnikov@mail.ru
Rússia, Novosibirsk

L. Kozlova

Research Institute of Molecular Biology and Biophysics; Novosibirsk National Research State University

Email: mikhail-melnikov@mail.ru
Rússia, Novosibirsk; Novosibirsk

M. Shtark

Research Institute of Molecular Biology and Biophysics; Novosibirsk National Research State University

Email: mikhail-melnikov@mail.ru
Rússia, Novosibirsk; Novosibirsk

A. Savelov

International Tomography Center, Siberian Division of the Russian Academy of Sciences

Email: mikhail-melnikov@mail.ru
Rússia, Novosibirsk

O. Shubina

Research Institute of Molecular Biology and Biophysics

Email: mikhail-melnikov@mail.ru
Rússia, Novosibirsk

K. Natarova

International Institute of Psychology and Psychotherapy

Email: mikhail-melnikov@mail.ru
Rússia, Novosibirsk


Declaração de direitos autorais © Springer Science+Business Media, LLC, part of Springer Nature, 2018

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