- Email: [email protected]
Low-frequency blood oxygen level-dependent fluctuations in the brain white matter: more than just noise
Science Bulletin xxx (2017) xxx–xxx
Contents lists available at ScienceDirect
Science Bulletin journal homepage: www.elsevier.com/locate/scib
Short Communication
Low-frequency blood oxygen level-dependent fluctuations in the brain white matter: more than just noise Gong-Jun Ji a,d,e,1, Wei Liao b,1, Fang-Fang Chen a, Lei Zhang a,d,e, Kai Wang c,a,d,e,⇑ a
Laboratory of Cognitive Neuropsychology, Department of Medical Psychology, Anhui Medical University, Hefei 230000, China Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China c Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230000, China d Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei 230000, China e Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China b
a r t i c l e
i n f o
Article history: Received 23 February 2017 Received in revised form 28 February 2017 Accepted 28 February 2017 Available online xxxx
a b s t r a c t Ó 2017 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved.
The spontaneous activity of the blood oxygen level-dependent (BOLD) signal has been demonstrated as a promising way for understanding how the brain intrinsically organized. However, most of these studies focused solely on the spontaneous activity in gray matter (GM) and not on white matter (WM). This is likely because low-frequency BOLD fluctuations (LFBFs) in GM are related to postsynaptic potential, while the physiological significance of fluctuations in WM is largely unknown [1]. Recently, there are increasing evidences implicating the neurobiological significance of LFBFs in WM [2–4]. Here, we further investigated this issue from the perspective of energy consumption. The analytical and data processing strategy were shown in the Supplementary data online. Firstly, we hypothesized that power of LFBFs [5] could be modulated by physiological states, and predicted that relative to the resting state, visual stimulation would increase the energy requirement in the optic radiation (OR). The pathway for the transmission of visual information is well-established: visual information from bilateral visual fields travels via the optic tract, terminating in the lateral geniculate nucleus of the thalamus before projecting to the bilateral visual cortex through the OR. Accordingly, we found that bilateral thalami and visual cortices were activated during visual stimulation (Fig. S2, Table S1 online). We produced a population-based (n = 22) probability map of bilateral ORs as regions-of-interest (ROIs) (Fig. 1a), and the following state-based analysis indicated that the LFBFs power of both left (t = 3.52, P = 0.001) and right (t = 1.73,
⇑ Corresponding author at: Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China. E-mail address: [email protected] (K. Wang). 1 G.J.J. and W.L. contributed equally to this work.
P = 0.048) ORs was higher in the task state than in the resting state (Fig. 1b). These findings were further conformed by a voxel-wise analysis which showed that the power of LFBFs specifically increased in OR but not other WM areas (Fig. S3, S4 online). Secondly, we hypothesized that the variation of power across WM voxels can be partly explained by their structural features, and predicted a positive correlation between LFBFs and fractional anisotropy (FA) or volume in WM. The within-state analysis indicated that the power of LFBFs is not homogeneous across WM regions. We speculate that the high energy consumption in the thalamofrontal pathway (frontal WM and capsula interna, Fig. S5 online) is associated with an arousal system that automatically and continuously monitors the surroundings [6]. Correlation analysis (n = 21) indicated that the variation in the power of LFBFs across WM voxels is related to WM density (r = 0.60, P < 0.001) and FA (r = 0.32, P < 0.001) features (Fig. 1c). When focusing on the left OR, correlation strengths were 0.83 (P < 10 3) for power– density and 0.44 (P = 0.07) for power–FA (Fig. 1d). For the right OR, power–density correlation was significant (r = 0.50, P = 0.04) while that of power–FA was non-significant (r = 0.19, P = 0.47) (Fig. 1e). In WM, axons provide a pathway for information transmission, the velocity of which is increased by the myelin sheath produced by oligodendrocytes. FA reflects both the degree of myelination and axonal density [7]. Its correlation with WM power suggests that LFBFs in WM are related to microstructural properties. Besides oligodendrocytes, microglia and astrocytes are also present in WM. The latter supply nutrients and oxygen to neurons and maintain brain homeostasis [8]. More importantly, astrocytes couple neuronal architecture to mapping signals that are critical in noninvasive brain imaging [9]. The higher correlation of power–volume relative to power–FA is likely due to the fact that
http://dx.doi.org/10.1016/j.scib.2017.03.021 2095-9273/Ó 2017 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved.
Please cite this article in press as: Ji G-J et al. Low-frequency blood oxygen level-dependent fluctuations in the brain white matter: more than just noise. Sci Bull (2017), http://dx.doi.org/10.1016/j.scib.2017.03.021
2
G.-J. Ji et al. / Science Bulletin xxx (2017) xxx–xxx
Fig. 1. (Color online) The feature of LFBFs power in WM. Bilateral ORs were tracked in individual diffusion space, normalized to MNI space, and overlapped to produce a population-based probabilistic map across subjects (a). The paired t test indicated that the power of bilateral ORs was higher in the task than resting state (b). Brain images show the spatial pattern of group-averaged power, density, and FA. Line graphs show correlation between modalities in the whole WM (c) and in the left (d) and right (e) ORs.
the former is a macrostructural property that takes axons/glia into greater consideration, whereas the latter is a microstructural feature that reflects only axons and myelin sheath. Taken together, these results imply a structural basis for LFBFs in WM. Recently, functional connectivity and diffusion tractography have become two of the most powerful investigative tools in neuroimage. However, the inherent gap between dynamic functional and static structural measures makes their direct integration difficult. While functional diffusion tensor imaging has been proposed to detect brain activation [10], our findings highlight the neurobiological relevance of LFBFs in WM. It suggests that LFBFs can be used to estimate the dynamic functioning of fiber tracts, providing a powerful way to investigate how information is transferred and integrated between functionally specialized cortices. Meanwhile, a functional investigation of WM would also provide insight into disorders associated with WM abnormalities [1]. Conflict of interest The authors declare that they have no conflict of interest. Acknowledgments This work was supported by the National Natural Science Foundation of China (81401400 to G.J.J., 81471653 to W.L., 31571149, 91432301 and 91232717 to K.W.), the Doctoral Foundation of Anhui Medical University (XJ201532 to G.J.J.), Youth Top-notch Talent Support Program of Anhui Medical University (to G.J.J.), the China Postdoctoral Science Foundation (2013M532229 to W. L.), National Basic Research Program of China
(2015CB856405, 2012CB720704, and 2011CB707805 to K.W.), and Anhui Collaborative Innovation Center of Neuropsychiatric Disorder and Mental Health. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.scib.2017.03.021. References [1] Gawryluk JR, Mazerolle EL, D’Arcy RC. Does functional mri detect activation in white matter? A review of emerging evidence, issues, and future directions. Front Neurosci 2014;8:239. [2] van Osch MJ, Teeuwisse WM, van Walderveen MA, et al. Can arterial spin labeling detect white matter perfusion signal? Magn Reson Med 2009;62:165–73. [3] Aslan S, Huang H, Uh J, et al. White matter cerebral blood flow is inversely correlated with structural and functional connectivity in the human brain. NeuroImage 2011;56:1145–53. [4] Ding Z, Newton AT, Xu R, et al. Spatio-temporal correlation tensors reveal functional structure in human brain. PLoS ONE 2013;8:e82107. [5] Zang YF, He Y, Zhu CZ, et al. Altered baseline brain activity in children with adhd revealed by resting-state functional mri. Brain Dev 2007;29:83–91. [6] Henderson JM. ‘‘Connectomic surgery”: diffusion tensor imaging (dti) tractography as a targeting modality for surgical modulation of neural networks. Front Integr Neurosci 2012;6:15. [7] Johansen-Berg H, Behrens TEJ. Diffusion MRI from quantitative measurement to in-vivo neuroanatomy. second ed. London, UK; Waltham, MA: Elsevier/ Academic Press; 2014. [8] Allaman I, Belanger M, Magistretti PJ. Astrocyte-neuron metabolic relationships: for better and for worse. Trends Neurosci 2011;34:76–87. [9] Schummers J, Yu H, Sur M. Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex. Science 2008;320:1638–43. [10] Le Bihan D, Urayama S, Aso T, et al. Direct and fast detection of neuronal activation in the human brain with diffusion mri. Proc Natl Acad Sci USA 2006;103:8263–8.
Please cite this article in press as: Ji G-J et al. Low-frequency blood oxygen level-dependent fluctuations in the brain white matter: more than just noise. Sci Bull (2017), http://dx.doi.org/10.1016/j.scib.2017.03.021
Contents lists available at ScienceDirect
Science Bulletin journal homepage: www.elsevier.com/locate/scib
Short Communication
Low-frequency blood oxygen level-dependent fluctuations in the brain white matter: more than just noise Gong-Jun Ji a,d,e,1, Wei Liao b,1, Fang-Fang Chen a, Lei Zhang a,d,e, Kai Wang c,a,d,e,⇑ a
Laboratory of Cognitive Neuropsychology, Department of Medical Psychology, Anhui Medical University, Hefei 230000, China Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China c Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230000, China d Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei 230000, China e Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China b
a r t i c l e
i n f o
Article history: Received 23 February 2017 Received in revised form 28 February 2017 Accepted 28 February 2017 Available online xxxx
a b s t r a c t Ó 2017 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved.
The spontaneous activity of the blood oxygen level-dependent (BOLD) signal has been demonstrated as a promising way for understanding how the brain intrinsically organized. However, most of these studies focused solely on the spontaneous activity in gray matter (GM) and not on white matter (WM). This is likely because low-frequency BOLD fluctuations (LFBFs) in GM are related to postsynaptic potential, while the physiological significance of fluctuations in WM is largely unknown [1]. Recently, there are increasing evidences implicating the neurobiological significance of LFBFs in WM [2–4]. Here, we further investigated this issue from the perspective of energy consumption. The analytical and data processing strategy were shown in the Supplementary data online. Firstly, we hypothesized that power of LFBFs [5] could be modulated by physiological states, and predicted that relative to the resting state, visual stimulation would increase the energy requirement in the optic radiation (OR). The pathway for the transmission of visual information is well-established: visual information from bilateral visual fields travels via the optic tract, terminating in the lateral geniculate nucleus of the thalamus before projecting to the bilateral visual cortex through the OR. Accordingly, we found that bilateral thalami and visual cortices were activated during visual stimulation (Fig. S2, Table S1 online). We produced a population-based (n = 22) probability map of bilateral ORs as regions-of-interest (ROIs) (Fig. 1a), and the following state-based analysis indicated that the LFBFs power of both left (t = 3.52, P = 0.001) and right (t = 1.73,
⇑ Corresponding author at: Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China. E-mail address: [email protected] (K. Wang). 1 G.J.J. and W.L. contributed equally to this work.
P = 0.048) ORs was higher in the task state than in the resting state (Fig. 1b). These findings were further conformed by a voxel-wise analysis which showed that the power of LFBFs specifically increased in OR but not other WM areas (Fig. S3, S4 online). Secondly, we hypothesized that the variation of power across WM voxels can be partly explained by their structural features, and predicted a positive correlation between LFBFs and fractional anisotropy (FA) or volume in WM. The within-state analysis indicated that the power of LFBFs is not homogeneous across WM regions. We speculate that the high energy consumption in the thalamofrontal pathway (frontal WM and capsula interna, Fig. S5 online) is associated with an arousal system that automatically and continuously monitors the surroundings [6]. Correlation analysis (n = 21) indicated that the variation in the power of LFBFs across WM voxels is related to WM density (r = 0.60, P < 0.001) and FA (r = 0.32, P < 0.001) features (Fig. 1c). When focusing on the left OR, correlation strengths were 0.83 (P < 10 3) for power– density and 0.44 (P = 0.07) for power–FA (Fig. 1d). For the right OR, power–density correlation was significant (r = 0.50, P = 0.04) while that of power–FA was non-significant (r = 0.19, P = 0.47) (Fig. 1e). In WM, axons provide a pathway for information transmission, the velocity of which is increased by the myelin sheath produced by oligodendrocytes. FA reflects both the degree of myelination and axonal density [7]. Its correlation with WM power suggests that LFBFs in WM are related to microstructural properties. Besides oligodendrocytes, microglia and astrocytes are also present in WM. The latter supply nutrients and oxygen to neurons and maintain brain homeostasis [8]. More importantly, astrocytes couple neuronal architecture to mapping signals that are critical in noninvasive brain imaging [9]. The higher correlation of power–volume relative to power–FA is likely due to the fact that
http://dx.doi.org/10.1016/j.scib.2017.03.021 2095-9273/Ó 2017 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved.
Please cite this article in press as: Ji G-J et al. Low-frequency blood oxygen level-dependent fluctuations in the brain white matter: more than just noise. Sci Bull (2017), http://dx.doi.org/10.1016/j.scib.2017.03.021
2
G.-J. Ji et al. / Science Bulletin xxx (2017) xxx–xxx
Fig. 1. (Color online) The feature of LFBFs power in WM. Bilateral ORs were tracked in individual diffusion space, normalized to MNI space, and overlapped to produce a population-based probabilistic map across subjects (a). The paired t test indicated that the power of bilateral ORs was higher in the task than resting state (b). Brain images show the spatial pattern of group-averaged power, density, and FA. Line graphs show correlation between modalities in the whole WM (c) and in the left (d) and right (e) ORs.
the former is a macrostructural property that takes axons/glia into greater consideration, whereas the latter is a microstructural feature that reflects only axons and myelin sheath. Taken together, these results imply a structural basis for LFBFs in WM. Recently, functional connectivity and diffusion tractography have become two of the most powerful investigative tools in neuroimage. However, the inherent gap between dynamic functional and static structural measures makes their direct integration difficult. While functional diffusion tensor imaging has been proposed to detect brain activation [10], our findings highlight the neurobiological relevance of LFBFs in WM. It suggests that LFBFs can be used to estimate the dynamic functioning of fiber tracts, providing a powerful way to investigate how information is transferred and integrated between functionally specialized cortices. Meanwhile, a functional investigation of WM would also provide insight into disorders associated with WM abnormalities [1]. Conflict of interest The authors declare that they have no conflict of interest. Acknowledgments This work was supported by the National Natural Science Foundation of China (81401400 to G.J.J., 81471653 to W.L., 31571149, 91432301 and 91232717 to K.W.), the Doctoral Foundation of Anhui Medical University (XJ201532 to G.J.J.), Youth Top-notch Talent Support Program of Anhui Medical University (to G.J.J.), the China Postdoctoral Science Foundation (2013M532229 to W. L.), National Basic Research Program of China
(2015CB856405, 2012CB720704, and 2011CB707805 to K.W.), and Anhui Collaborative Innovation Center of Neuropsychiatric Disorder and Mental Health. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.scib.2017.03.021. References [1] Gawryluk JR, Mazerolle EL, D’Arcy RC. Does functional mri detect activation in white matter? A review of emerging evidence, issues, and future directions. Front Neurosci 2014;8:239. [2] van Osch MJ, Teeuwisse WM, van Walderveen MA, et al. Can arterial spin labeling detect white matter perfusion signal? Magn Reson Med 2009;62:165–73. [3] Aslan S, Huang H, Uh J, et al. White matter cerebral blood flow is inversely correlated with structural and functional connectivity in the human brain. NeuroImage 2011;56:1145–53. [4] Ding Z, Newton AT, Xu R, et al. Spatio-temporal correlation tensors reveal functional structure in human brain. PLoS ONE 2013;8:e82107. [5] Zang YF, He Y, Zhu CZ, et al. Altered baseline brain activity in children with adhd revealed by resting-state functional mri. Brain Dev 2007;29:83–91. [6] Henderson JM. ‘‘Connectomic surgery”: diffusion tensor imaging (dti) tractography as a targeting modality for surgical modulation of neural networks. Front Integr Neurosci 2012;6:15. [7] Johansen-Berg H, Behrens TEJ. Diffusion MRI from quantitative measurement to in-vivo neuroanatomy. second ed. London, UK; Waltham, MA: Elsevier/ Academic Press; 2014. [8] Allaman I, Belanger M, Magistretti PJ. Astrocyte-neuron metabolic relationships: for better and for worse. Trends Neurosci 2011;34:76–87. [9] Schummers J, Yu H, Sur M. Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex. Science 2008;320:1638–43. [10] Le Bihan D, Urayama S, Aso T, et al. Direct and fast detection of neuronal activation in the human brain with diffusion mri. Proc Natl Acad Sci USA 2006;103:8263–8.
Please cite this article in press as: Ji G-J et al. Low-frequency blood oxygen level-dependent fluctuations in the brain white matter: more than just noise. Sci Bull (2017), http://dx.doi.org/10.1016/j.scib.2017.03.021