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Considerations for resting state functional MRI and functional connectivity studies in rodents.

Pan WJ, Billings JC, Grooms JK, Shakil S, Keilholz SD - Front Neurosci (2015)

Bottom Line: However, impediments exist to the optimal application of rs-fMRI in small animals, some similar to those encountered in humans and some quite different.In this review we identify the most prominent of these barriers, discuss differences between rs-fMRI in rodents and in humans, highlight best practices for animal studies, and review selected applications of rs-fMRI in rodents.Our goal is to facilitate the integration of human and animal work to the benefit of both fields.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Georgia Institute of Technology, Emory University Atlanta, GA, USA.

ABSTRACT
Resting state functional MRI (rs-fMRI) and functional connectivity mapping have become widely used tools in the human neuroimaging community and their use is rapidly spreading into the realm of rodent research as well. One of the many attractive features of rs-fMRI is that it is readily translatable from humans to animals and back again. Changes in functional connectivity observed in human studies can be followed by more invasive animal experiments to determine the neurophysiological basis for the alterations, while exploratory work in animal models can identify possible biomarkers for further investigation in human studies. These types of interwoven human and animal experiments have a potentially large impact on neuroscience and clinical practice. However, impediments exist to the optimal application of rs-fMRI in small animals, some similar to those encountered in humans and some quite different. In this review we identify the most prominent of these barriers, discuss differences between rs-fMRI in rodents and in humans, highlight best practices for animal studies, and review selected applications of rs-fMRI in rodents. Our goal is to facilitate the integration of human and animal work to the benefit of both fields.

No MeSH data available.


Related in: MedlinePlus

Distribution of power for low frequency fluctuations, respiratory noise, and cardiac noise from a single coronal slice in a rat imaged with a TR of 100 ms. The low frequency fluctuations exhibit high power across the entire cortex. Respiratory effects localize near the midline, the ventricles, and the surface of the brain. Cardiac effects are primarily seen along the surface of the brain and at the base of the brain. The power spectral density plot below shows the low frequency range (< 0.2 Hz), the respiratory peak at ~1 Hz, and the cardiac peak at ~4.7 Hz. Adapted from Williams et al. MRI (2010).
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Figure 2: Distribution of power for low frequency fluctuations, respiratory noise, and cardiac noise from a single coronal slice in a rat imaged with a TR of 100 ms. The low frequency fluctuations exhibit high power across the entire cortex. Respiratory effects localize near the midline, the ventricles, and the surface of the brain. Cardiac effects are primarily seen along the surface of the brain and at the base of the brain. The power spectral density plot below shows the low frequency range (< 0.2 Hz), the respiratory peak at ~1 Hz, and the cardiac peak at ~4.7 Hz. Adapted from Williams et al. MRI (2010).

Mentions: As a first step toward obtaining stable physiological conditions and ensuring reproducible experimental conditions, experimental groups of animals should be consistent in strain, gender, age, weight, housing condition, food and lighting cycle, and so on (Hildebrandt et al., 2008). Furthermore, physiological parameters should be monitored and controlled (to the extent possible) during an experiment. These physiological parameters include anesthetic dose, body temperature, blood oxygenation level, and respiratory and cardiac rates. Fluctuations in body temperature can contribute to drifts in the BOLD signal baseline, even when the temperature changes are within physiological ranges (Vanhoutte et al., 2006). Respiratory and cardiac cycles are known to contribute to the rs-fMRI signal and can introduce unwanted correlations (Wise et al., 2004; Birn et al., 2006; Shmueli et al., 2007) (Figure 2). Ideally, these contributions can be removed in post-processing if the cardiac and respiratory cycles are recorded and time-locked to rs-fMRI acquisition (Hu et al., 1995; Glover et al., 2000). For the respiratory cycle, the most common recording device is a pressure-sensitive balloon placed under the animal's chest and abdomen. For the cardiac cycle, electrocardiography is a logical choice but often proves unreliable in practice due to interference from the gradients during image acquisition. An alternative is a pulse oximeter, usually applied to one of the animal's hind limbs. This device does not record the entire cardiac cycle, but does give a time course of the heart rate and blood oxygenation level. For studies that involve comparing different groups of animals, showing that the heart rate and blood oxygenation levels are comparable across groups and stable over the course of the experiment greatly increases confidence that any effects on functional connectivity are not due to these basic physiological processes.


Considerations for resting state functional MRI and functional connectivity studies in rodents.

Pan WJ, Billings JC, Grooms JK, Shakil S, Keilholz SD - Front Neurosci (2015)

Distribution of power for low frequency fluctuations, respiratory noise, and cardiac noise from a single coronal slice in a rat imaged with a TR of 100 ms. The low frequency fluctuations exhibit high power across the entire cortex. Respiratory effects localize near the midline, the ventricles, and the surface of the brain. Cardiac effects are primarily seen along the surface of the brain and at the base of the brain. The power spectral density plot below shows the low frequency range (< 0.2 Hz), the respiratory peak at ~1 Hz, and the cardiac peak at ~4.7 Hz. Adapted from Williams et al. MRI (2010).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4525377&req=5

Figure 2: Distribution of power for low frequency fluctuations, respiratory noise, and cardiac noise from a single coronal slice in a rat imaged with a TR of 100 ms. The low frequency fluctuations exhibit high power across the entire cortex. Respiratory effects localize near the midline, the ventricles, and the surface of the brain. Cardiac effects are primarily seen along the surface of the brain and at the base of the brain. The power spectral density plot below shows the low frequency range (< 0.2 Hz), the respiratory peak at ~1 Hz, and the cardiac peak at ~4.7 Hz. Adapted from Williams et al. MRI (2010).
Mentions: As a first step toward obtaining stable physiological conditions and ensuring reproducible experimental conditions, experimental groups of animals should be consistent in strain, gender, age, weight, housing condition, food and lighting cycle, and so on (Hildebrandt et al., 2008). Furthermore, physiological parameters should be monitored and controlled (to the extent possible) during an experiment. These physiological parameters include anesthetic dose, body temperature, blood oxygenation level, and respiratory and cardiac rates. Fluctuations in body temperature can contribute to drifts in the BOLD signal baseline, even when the temperature changes are within physiological ranges (Vanhoutte et al., 2006). Respiratory and cardiac cycles are known to contribute to the rs-fMRI signal and can introduce unwanted correlations (Wise et al., 2004; Birn et al., 2006; Shmueli et al., 2007) (Figure 2). Ideally, these contributions can be removed in post-processing if the cardiac and respiratory cycles are recorded and time-locked to rs-fMRI acquisition (Hu et al., 1995; Glover et al., 2000). For the respiratory cycle, the most common recording device is a pressure-sensitive balloon placed under the animal's chest and abdomen. For the cardiac cycle, electrocardiography is a logical choice but often proves unreliable in practice due to interference from the gradients during image acquisition. An alternative is a pulse oximeter, usually applied to one of the animal's hind limbs. This device does not record the entire cardiac cycle, but does give a time course of the heart rate and blood oxygenation level. For studies that involve comparing different groups of animals, showing that the heart rate and blood oxygenation levels are comparable across groups and stable over the course of the experiment greatly increases confidence that any effects on functional connectivity are not due to these basic physiological processes.

Bottom Line: However, impediments exist to the optimal application of rs-fMRI in small animals, some similar to those encountered in humans and some quite different.In this review we identify the most prominent of these barriers, discuss differences between rs-fMRI in rodents and in humans, highlight best practices for animal studies, and review selected applications of rs-fMRI in rodents.Our goal is to facilitate the integration of human and animal work to the benefit of both fields.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Georgia Institute of Technology, Emory University Atlanta, GA, USA.

ABSTRACT
Resting state functional MRI (rs-fMRI) and functional connectivity mapping have become widely used tools in the human neuroimaging community and their use is rapidly spreading into the realm of rodent research as well. One of the many attractive features of rs-fMRI is that it is readily translatable from humans to animals and back again. Changes in functional connectivity observed in human studies can be followed by more invasive animal experiments to determine the neurophysiological basis for the alterations, while exploratory work in animal models can identify possible biomarkers for further investigation in human studies. These types of interwoven human and animal experiments have a potentially large impact on neuroscience and clinical practice. However, impediments exist to the optimal application of rs-fMRI in small animals, some similar to those encountered in humans and some quite different. In this review we identify the most prominent of these barriers, discuss differences between rs-fMRI in rodents and in humans, highlight best practices for animal studies, and review selected applications of rs-fMRI in rodents. Our goal is to facilitate the integration of human and animal work to the benefit of both fields.

No MeSH data available.


Related in: MedlinePlus