Physiological effects of a habituation procedure for functional MRI in awake mice using a cryogenic radiofrequency probe

Yoshida, Kouji; Mimura, Yu; Ishihara, Ryosuke; Nishida, Hiroshi; Komaki, Yuji; Minakuchi, Tomohito; Tsurugizawa, Tomokazu; Mimura, Masaru; Okano, Hideyuki; Tanaka, Kenji F.; Takata, Norio

doi:10.1016/j.jneumeth.2016.09.013

Cited by 82 publications

(98 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such amount of data has yet to be achieved in anesthetized mice in which acquisition is predominantly between several minutes and up to 40 minutes per session 38,39 and a substantive repeated-measurement design is not feasible due to the difficulties that arise from repeated ventilation and catheterization and the potential impact of prolonged anesthesia. On the other hand, experimental setup for awake fcMRI 27,[40][41][42] can support such repeated-measurement designs.…”

Section: Discussionmentioning

confidence: 99%

Individual variability in functional connectivity architecture of the mouse brain

Bergmann

Gofman

Kavushansky

et al. 2020

Preprint

View full text Add to dashboard Cite

The functional organization of brain networks can be estimated using fMRI by examining the coherence of spontaneous fluctuations in the fMRI signal, a method known as resting-state functional connectivity MRI. Previous studies in humans reported that such functional networks are dominated by stable group and individual factors, demonstrating that fMRI is suited to measuring subject-specific characteristics, and suggesting the utility of such precision fMRI approach in personalized medicine. However, mechanistic investigations to the sources of individual variability in health and disease are limited in humans and thus require animal models.Here, we used repeated-measurement resting-state fMRI in awake mice to quantify the contribution of individual variation to the functional architecture of the mouse cortex. Comparing the organization of functional networks across the group, we found dominant common organizational principles. The data also revealed stable individual features, which create a unique fingerprint that allow identification of individual mice from the group. Examining the distribution of individual variation across the mouse cortex, we found it is homogeneously distributed in both sensory and association networks. Finally, connectome-based predictive modeling of motor behavior in the rotarod task revealed that individual variation in functional connectivity explained behavioral variability. Collectively, these results show that mouse functional networks are characterized by individual variations suggesting that individual variation characterizes the mammalian cortex in general, and not only the primate cortex. These findings lay the foundation for future mechanistic investigations of individual brain organization and pre-clinical studies of brain disorders in the context of personalized medicine.

show abstract

Section: Discussionmentioning

confidence: 99%

Individual variability in functional connectivity architecture of the mouse brain

Bergmann

Gofman

Kavushansky

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Neuroscience and psychiatric research have been substantially facilitated by open neuroimaging datasets (Poldrack and Gorgolewski, 2017;Thompson et al, 2014;Van Essen et al, 2013 There has been growing interest in studying brain function and organization in awake rodents using rsfMRI, which avoids interference of anesthesia and permits correlation to behavioral data (Bergmann et al, 2016;Brydges et al, 2013;Chang et al, 2016;Liang et al, 2011;Stenroos et al, 2018;Yoshida et al, 2016). One major challenge of awake rodent fMRI is to control motion and stress during data acquisition.…”

Section: Discussionmentioning

confidence: 99%

An open database of resting-state fMRI in awake rats

Liu

Pérez

et al. 2019

Preprint

View full text Add to dashboard Cite

Rodent models are essential to translational research in health and disease.Investigation in rodent brain function and organization at the systems level using restingstate functional magnetic resonance imaging (rsfMRI) has become increasingly popular, owing to its high spatial resolution and whole-brain coverage. Due to this rapid progress, shared rodent rsfMRI databases can be of particular interest and importance to the scientific community, as inspired by human neuroscience and psychiatric research that are substantially facilitated by open human neuroimaging datasets. However, such databases in rats are still lacking. In this paper, we share an open rsfMRI database acquired in 90 rats with a well-established awake imaging paradigm that avoids anesthesia interference. Both raw and preprocessed data are made publically available.Procedures in data preprocessing to remove artefacts induced by the scanner, head motion, non-neural physiological noise are described in details. We also showcase interregional functional connectivity and functional networks calculated from the database.

show abstract

“…Our findings relied on long (38 min), high-quality rs-fMRI measurements of BOLD dynamics across the whole mouse brain, which were compared with a tract-tracing based structural connectome for the first time in this work. The use of awake mice in rs-fMRI protocols is impracticable for long scan times (notwithstanding the use of invasive methods for head fixation 58 ), making light anesthesia the de facto option. 59 As previously demonstrated in rats 60 and monkeys, 61 decreasing (or abolishing) levels of anesthesia are mirrored by an increase in BOLD variability.…”

Section: Discussionmentioning

confidence: 99%

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

Sethi

Zerbi

Wenderoth

et al. 2017

Chaos: An Interdisciplinary Journal of Nonlinear Science

View full text Add to dashboard Cite

Brain dynamics are thought to unfold on a network determined by the pattern of axonal connections linking pairs of neuronal elements; the so-called connectome. Prior work has indicated that structural brain connectivity constrains pairwise correlations of brain dynamics ("functional connectivity"), but it is not known whether inter-regional axonal connectivity is related to the intrinsic dynamics of individual brain areas. Here we investigate this relationship using a weighted, directed mesoscale mouse connectome from the Allen Mouse Brain Connectivity Atlas and resting state functional MRI (rs-fMRI) time-series data measured in 184 brain regions in eighteen anesthetized mice. For each brain region, we measured degree, betweenness, and clustering coefficient from weighted and unweighted, and directed and undirected versions of the connectome. We then characterized the univariate rs-fMRI dynamics in each brain region by computing 6930 time-series properties using the time-series analysis toolbox, hctsa. After correcting for regional volume variations, strong and robust correlations between structural connectivity properties and rs-fMRI dynamics were found only when edge weights were accounted for, and were associated with variations in the autocorrelation properties of the rs-fMRI signal. The strongest relationships were found for weighted in-degree, which was positively correlated to the autocorrelation of fMRI time series at time lag Nervous systems are complex networks with a topology governed by the pattern of axonal connections linking distinct neural elements. Highly connected and topologically central elements are thought to play an important role in meditating the flow of information across different parts of the system. However, it is unclear how the intrinsic dynamics of a given neuronal population relates to the pattern of connections that population shares with other network nodes. In this work, we show that there is a strong and robust correlation between the structural connectivity properties of a brain region and its blood-oxygenation-level-dependent (BOLD) signal dynamics, as measured with resting-state fMRI (rs-fMRI) in the mouse. The strongest relationship is found with the total weight of incoming connections to a brain region, or weighted in-degree, which is associated with longer dynamical timescales of rs-fMRI dynamics. Our findings indicate that structural connection weights convey important information about neural activity, and that the aggregate strength of incoming projections to a brain region is closely related to its BOLD signal dynamics.

show abstract

Physiological effects of a habituation procedure for functional MRI in awake mice using a cryogenic radiofrequency probe

Cited by 82 publications

References 49 publications

Individual variability in functional connectivity architecture of the mouse brain

Individual variability in functional connectivity architecture of the mouse brain

An open database of resting-state fMRI in awake rats

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

Contact Info

Product

Resources

About