Dynamic reorganization of intrinsic functional networks in the mouse brain

Autor: Michaela Buerge, Christopher R. Pryce, Thomas A. W. Bolton, Markus Rudin, Erich Seifritz, Maria Giulia Preti, Dimitri Van De Ville, Joanes Grandjean
Přispěvatelé: University of Zurich, Rudin, Markus
Jazyk: angličtina
Rok vydání: 2017
Předmět:
2805 Cognitive Neuroscience
Male
0301 basic medicine
Mouse
Cognitive Neuroscience
10050 Institute of Pharmacology and Toxicology
610 Medicine & health
ddc:616.0757
Functional networks
Correlation
03 medical and health sciences
Functional connectivity
0302 clinical medicine
Neural Pathways
Image Processing
Computer-Assisted
medicine
Animals
Social Behavior
Dynamic functional states
Social stress
Brain Mapping
Isoflurane
medicine.diagnostic_test
fMRI
Brain
Dictionary learning
Network dynamics
Magnetic Resonance Imaging
Mice
Inbred C57BL
030104 developmental biology
Neurology
10054 Clinic for Psychiatry
Psychotherapy
and Psychosomatics
2808 Neurology
Anesthetics
Inhalation
Female
Functional magnetic resonance imaging
Psychology
Neuroscience
Stress
Psychological
030217 neurology & neurosurgery
Information integration
Zdroj: NeuroImage, Vol. 152 (2017) pp. 497-508
BASE-Bielefeld Academic Search Engine
ISSN: 1053-8119
Popis: Functional connectivity (FC) derived from resting-state functional magnetic resonance imaging (rs-fMRI) allows for the integrative study of neuronal processes at a macroscopic level. The majority of studies to date have assumed stationary interactions between brain regions, without considering the dynamic aspects of network organization. Only recently has the latter received increased attention, predominantly in human studies. Applying dynamic FC (dFC) analysis to mice is attractive given the relative simplicity of the mouse brain and the possibility to explore mechanisms underlying network dynamics using pharmacological, environmental or genetic interventions. Therefore, we have evaluated the feasibility and research potential of mouse dFC using the interventions of social stress or anesthesia duration as two case-study examples. By combining a sliding-window correlation approach with dictionary learning, several dynamic functional states (dFS) with a complex organization were identified, exhibiting highly dynamic inter- and intra-modular interactions. Each dFS displayed a high degree of reproducibility upon changes in analytical parameters and across datasets. They fluctuated at different degrees as a function of anesthetic depth, and were sensitive indicators of pathology as shown for the chronic psychosocial stress mouse model of depression. Dynamic functional states are proposed to make a major contribution to information integration and processing in the healthy and diseased brain.
Databáze: OpenAIRE
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