Functional Connectivity Mapping in the Animal Model: Principles and Applications of Resting-State fMRI

"Resting-state" fMRI has substantially contributed to the understanding of human and non-human functional brain organization by the analysis of correlated patterns in spontaneous activity within dedicated brain systems. Spontaneous neural activity is indirectly measured from the blood oxyg...

Full description

Saved in:
Bibliographic Details
Published inFrontiers in neurology Vol. 8; p. 200
Main Authors Gorges, Martin, Roselli, Francesco, Müller, Hans-Peter, Ludolph, Albert C, Rasche, Volker, Kassubek, Jan
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 10.05.2017
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:"Resting-state" fMRI has substantially contributed to the understanding of human and non-human functional brain organization by the analysis of correlated patterns in spontaneous activity within dedicated brain systems. Spontaneous neural activity is indirectly measured from the blood oxygenation level-dependent signal as acquired by echo planar imaging, when subjects quietly "resting" in the scanner. Animal models including disease or knockout models allow a broad spectrum of experimental manipulations not applicable in humans. The non-invasive fMRI approach provides a promising tool for cross-species comparative investigations. This review focuses on the principles of "resting-state" functional connectivity analysis and its applications to living animals. The translational aspect from animal models toward clinical applications in humans is emphasized. We introduce the fMRI-based investigation of the non-human brain's hemodynamics, the methodological issues in the data postprocessing, and the functional data interpretation from different abstraction levels. The longer term goal of integrating fMRI connectivity data with structural connectomes obtained with tracing and optical imaging approaches is presented and will allow the interrogation of fMRI data in terms of directional flow of information and may identify the structural underpinnings of observed functional connectivity patterns.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-3
content type line 23
ObjectType-Review-1
Specialty section: This article was submitted to Applied Neuroimaging, a section of the journal Frontiers in Neurology
Edited by: Itamar Ronen, Leiden University, Netherlands
Reviewed by: Andres Ortiz, University of Málaga, Spain; Konstantinos Kalafatakis, University of Bristol, UK
ISSN:1664-2295
1664-2295
DOI:10.3389/fneur.2017.00200