Evaluation of nuisance removal for functional MRI of rodent brain

被引:27
作者
Chuang, Kai-Hsiang [1 ,2 ]
Lee, Hsu-Lei [1 ,2 ]
Li, Zengmin [1 ]
Chang, Wei-Tang [3 ]
Nasrallah, Fatima A. [1 ]
Yeow, Ling Yun [4 ]
Kaur, Kavita [4 ]
机构
[1] Univ Queensland, Queensland Brain Inst, Brisbane, Qld 4072, Australia
[2] Univ Queensland, Ctr Adv Imaging, Brisbane, Qld 4072, Australia
[3] Univ N Carolina, Chapel Hill, NC 27515 USA
[4] Agcy Sci Technol & Res, Singapore Bioimaging Consortium, Singapore, Singapore
关键词
Resting state network; Functional MRI; Functional connectivity; Brain connectome; Artifact; Nuisance; Rodent; RESTING-STATE FMRI; RAT-BRAIN; CONNECTIVITY NETWORKS; MOTION CORRECTION; GLOBAL SIGNAL; MOUSE-BRAIN; BOLD; RELIABILITY; ANESTHESIA; IMPACT;
D O I
10.1016/j.neuroimage.2018.12.048
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Functional MRI (fMRI) has become an important translational tool for studying brain activity and connectivity in animal models and humans. For accurate and reliable measurement of functional connectivity, nuisance removal strategies developed for human brain, such as regressing motion parameters, cerebrospinal fluid (CSF)/white matter-derived signals and the global signal, have been applied to rodent. However, due to the very different anatomy, with the majority of the rodent brain being gray matter, and experimental conditions, in which animals are anesthetized and head-fixed, these methods may not be suitable for rodent fMRI. In this study, we assessed various nuisance regression methods and the effects of motion correction on a large dataset of both task and resting fMRI of anesthetized rat brain. Sensitivity and specificity were assessed in the somatosensory pathway under forepaw stimulation and resting state. Reproducibility at various sample sizes was simulated by randomly subsampling the dataset. To overcome the difficulty in extracting nuisance from the brain, a method using principal components estimated from tissues outside the brain was evaluated. Our results showed that neither detrend, motion correction, motion regression nor CSF signal regression could improve specificity despite increasing temporal signal-to-noise ratios. Although global signal regression increased the specificity of task activation and functional connectivity, the sensitivity and connectivity strength was drastically reduced, likely due to its strong correlation with the cortical signal. Motion parameters also correlated with task activation and the global signal, indicating that motion correction detected intensity variations in the brain. The nuisance estimated from tissues outside the brain produced a moderate improvement in specificity. In conclusion, nuisance removal suitable for human fMRI may not be optimal for rodents. While further development is needed, estimating nuisance from tissues outside the brain may be an alternative.
引用
收藏
页码:694 / 709
页数:16
相关论文
共 75 条
[1]   A component based noise correction method (CompCor) for BOLD and perfusion based fMRI [J].
Behzadi, Yashar ;
Restom, Khaled ;
Liau, Joy ;
Liu, Thomas T. .
NEUROIMAGE, 2007, 37 (01) :90-101
[2]   Dynamic resting state fMRI analysis in mice reveals a set of Quasi-Periodic Patterns and illustrates their relationship with the global signal [J].
Belloy, Micha El E. ;
Naeyaert, Maarten ;
Abbas, Anzar ;
Shah, Disha ;
Vanreusel, Verdi ;
Van Audekerke, Johan ;
Keilholz, Shella D. ;
Keliris, Georgios A. ;
Van der Linden, Annemie ;
Verhoye, Marleen .
NEUROIMAGE, 2018, 180 :463-484
[3]   The Organization of Mouse and Human Cortico-Hippocampal Networks Estimated by Intrinsic Functional Connectivity [J].
Bergmann, Eyal ;
Zur, Gil ;
Bershadsky, Guy ;
Kahn, Itamar .
CEREBRAL CORTEX, 2016, 26 (12) :4497-4512
[4]   Gradual emergence of spontaneous correlated brain activity during fading of general anesthesia in rats: Evidences from fMRI and local field potentials [J].
Bettinardi, Ruggero G. ;
Tort-Colet, Nuria ;
Ruiz-Mejias, Marcel ;
Sanchez-Vives, Maria V. ;
Deco, Gustavo .
NEUROIMAGE, 2015, 114 :185-198
[5]   Methods for cleaning the BOLD fMRI signal [J].
Caballero-Gaudes, Cesar ;
Reynolds, Richard C. .
NEUROIMAGE, 2017, 154 :128-149
[6]   In vivo visuotopic brain mapping with manganese-enhanced MRI and resting-state functional connectivity MRI [J].
Chan, Kevin C. ;
Fan, Shu-Juan ;
Chan, Russell W. ;
Cheng, Joe S. ;
Zhou, Iris Y. ;
Wu, Ed X. .
NEUROIMAGE, 2014, 90 :235-245
[7]   Connectomic imaging reveals Huntington-related pathological and pharmaceutical effects in a mouse model [J].
Chang, Wei-Tang ;
Puspitasari, Fiftarina ;
Garcia-Miralles, Marta ;
Yeow, Ling Yun ;
Tay, Hui-Chien ;
Koh, Katrianne Bethia ;
Tan, Liang Juin ;
Pouladi, Mahmoud A. ;
Chuang, Kai-Hsiang .
NMR IN BIOMEDICINE, 2018, 31 (12)
[8]   Robust Automatic Rodent Brain Extraction Using 3-D Pulse-Coupled Neural Networks (PCNN) [J].
Chou, Nigel ;
Wu, Jiarong ;
Bingren, Jordan Bai ;
Qiu, Anqi ;
Chuang, Kai-Hsiang .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2011, 20 (09) :2554-2564
[9]   Functional networks and network perturbations in rodents [J].
Chuang, Kai-Hsiang ;
Nasrallah, Fatima A. .
NEUROIMAGE, 2017, 163 :419-436
[10]   IMPACT: Image-based physiological artifacts estimation and correction technique for functional MRI [J].
Chuang, KH ;
Chen, JH .
MAGNETIC RESONANCE IN MEDICINE, 2001, 46 (02) :344-353