Year: 2011
Type: article
Abstract: Resting state networks (RSNs) have been studied extensively with functional MRI in humans in health and disease to reflect brain function in the un-stimulated state as well as reveal how the brain is altered with disease. Rodent models of disease have been used comprehensively to understand the biology of the disease as well as in the development of new therapies. RSN reported studies in rodents, however, are few, and most studies are performed with anesthetized rodents that might alter networks and differ from their non-anesthetized state. Acquiring RSN data in the awake rodent avoids the issues of anesthesia effects on brain function. Using high field fMRI we determined RSNs in awake rats using an independent component analysis (ICA) approach, however, ICA analysis can produce a large number of components, some with biological relevance (networks). We further have applied a novel method to determine networks that are robust and reproducible among all the components found with ICA. This analysis indicates that 7 networks are robust and reproducible in the rat and their putative role is discussed.
Source: PLoS ONE
Authors: Lino Becerra, Gautam Pendse, Pei-Ching Chang, James Bishop, David Borsook
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,382
Awards: Elekta Neuromag Electronics Upgrade, Imaging Pain and Analgesia: Mentoring in Basic and Applied Research, G2227408383, G393103480, G593577925, Computeserver Structural &Functional Image Analysis, G6110067775, G668207740, G824017836, A Storage Area Network for Structural and Functional Image Analysis, Silicon Graphics Prism Extreme 128P/1TB
OpenAlex ID: W1975312371