Optimization of anesthesia protocol for resting-state fMRI in mice based on differential effects of anesthetics on functional connectivity patterns
Introduction
Resting state functional magnetic resonance imaging (rs-fMRI) yields information on the functional connectivity (FC) of spatially distinct regions of the brain and thus insight into its overall organization. The relative ease of data acquisition, the identification of distinct networks within the human brain, and the demonstration that alterations in FC could be associated with neurological disorders has generated widespread interest in rs-fMRI (Greicius et al., 2004, Rombouts et al., 2005). Experimental studies in monkeys (Vincent et al., 2007), rats (Lu et al., 2007, Zhao et al., 2008), and recently also in mice (Guilfoyle et al., 2013, Jonckers et al., 2011, Jonckers et al., 2013, Nasrallah et al., 2014, Sforazzini et al., 2014) allow addressing questions regarding mechanisms underlying the fluctuations that constitute the rs-fMRI signal and offer an experimental approach for studying models of human disease.
While rs-fMRI measurements in sedated or anesthetized humans are of interest for evaluating FC features related to consciousness (Heine et al., 2012) as well as for understanding the effects of anesthetics (Peltier et al., 2005, Schrouff et al., 2011), the use of anesthesia in rodent fMRI studies constitutes a practical need to keep the animal restrained during experiments. Controlled anesthetic conditions offer potential advantages with respect to the use of awake animals as contributions arising from motion, irregular breathing, and heart rhythm as well as from changes of stress-related physiological parameters will affect FC analysis to a level that might not be fully accounted for by post-processing procedures. Correspondingly, imaging of awake animals remains a matter of debate as these might experience non-negligible stress despite time-consuming acclimation training.
On the other hand, anesthesia will inevitably affect the fMRI response. We have previously shown that anesthetics affect the cerebral hemodynamic fMRI responses in a drug-specific manner and that these effects could be largely explained by the known effects of the anesthetics on animal physiology. Furthermore, our results revealed that independent of the anesthetic used, fMRI responses to electrical hind paw stimulation in mice were influenced by stimulus-induced cardiovascular changes. The observed systemic physiological changes indicated an arousal response even when applying innocuous stimuli, which might mask specific fMRI signals associated to the stimulus (Schroeter et al., 2014). Hence, studying the processing of peripheral input in mice using fMRI techniques constitutes a major challenge. In view of these results, analysis of blood oxygenation level-dependent (BOLD) fMRI signal fluctuations during resting state becomes attractive as it should be largely devoid of changes in the arousal state of the mouse during the course of the experiment. Nevertheless, effects of anesthesia on neuronal activity, systemic physiological parameters, and on the cerebral vasculature will influence the measured rs-fMRI signal; thus, understanding these effects is essential for the interpretation of the results.
Recent studies in mice investigating the effects of specific anesthetic regimens on FC data derived from rs-fMRI revealed anesthesia-specific patterns, but lack coherence (Guilfoyle et al., 2013, Jonckers et al., 2011, Jonckers et al., 2013, Nasrallah et al., 2014, Sforazzini et al., 2014). Hence, comparative studies using several anesthetics with differential effects on neural and vascular properties should help identify commonalities as well as anesthesia-specific signatures within FC patterns and might provide insight into mechanisms underlying the FC observed. Furthermore, in order to minimize potential confounds arising from anesthesia, it is important to identify an anesthetic regimen for rs-fMRI studies in small animals that ensures maximum resemblance of FC compared to that observed in awake animals and humans.
In this study, we compared the effects of isoflurane, medetomidine, propofol, urethane, and a combination of medetomidine and isoflurane on spontaneous low-frequency fluctuations of the BOLD fMRI signal in the absence of external stimuli. Using seed-based analysis, frequency power analysis, and the approximate entropy approach to characterize the differences in FC, we propose a categorization of anesthetics based on phenomenological characteristics of the FC patterns. Our comparison identifies a combination of low-dose medetomidine and isoflurane as a suitable anesthesia for rs-fMRI measurements in mice, as the application of this protocol seems to recover both the cortical and subcortical functional topology of FC networks.
Section snippets
Animals, preparation, and anesthesia
The experiments were performed in compliance with Swiss laws on animal protection. Female C57BL/6 mice (Janvier, Le Genest-St Isle, France) between 10 and 15 weeks old, weighing between 20 and 23 g were studied. Animal numbers are indicated in Table 1. All mice were initially anesthetized with isoflurane in a 20% O2/80% air mixture: 3.5% for induction, 2% for endotracheal intubation and during set-up on the animal bed. Throughout the course of the experiment, the animals were connected to a small
Results
GE-EPI images presented minimal susceptibility-related signal dephasing and geometric distortions, which facilitated accurate registration to a template, a prerequisite for proper analysis of rs-fMRI data (Suppl. Fig. S1).
Discussion
Anesthetics affect neural activity, metabolism, cerebrovascular tone, perfusion pressure, and/or cerebral autoregulation and are therefore likely to have an impact on FC patterns derived from rs-fMRI experiments. In fact, we obtained highly reproducible anesthetic-specific FC maps for mice studied under commonly used doses of isoflurane, medetomidine, propofol, and urethane, all administered in conjunction with a neuromuscular blocking agent. Analysis of GSR data for Iso1 and Pro30 revealed
Acknowledgments
This study was supported by the Swiss National Science Foundation (SNF 310030–141202, SNF 310030–126029) and the National Center for Competence in Research “Neural Plasticity & Repair” of the Swiss National Science Foundation.
Conflict of Interest Statement
None of the material contained in this manuscript has been published or presented previously, except in abstract form at international conferences. This paper has not been submitted for publication elsewhere, and it has been reviewed and
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These authors contributed equally to this work.