Abstract
Although often used as a nuisance in resting-state functional magnetic resonance imaging (rsfMRI), the global brain signal in humans and anesthetized animals has important neural basis. However, our knowledge of the global signal in awake rodents is sparse. To bridge this gap, we systematically analyzed rsfMRI data acquired with a conventional single-echo (SE) echo planar imaging (EPI) sequence in awake rats. The spatial pattern of rsfMRI frames during peaks of the global signal exhibited prominent co-activations in the thalamo-cortical and hippocampo-cortical networks, as well as in the basal forebrain, hinting that these neural networks might contribute to the global brain signal in awake rodents. To validate this concept, we acquired rsfMRI data using a multi-echo (ME) EPI sequence and removed non-neural components in the rsfMRI signal. Consistent co-activation patterns were obtained in extensively de-noised ME-rsfMRI data, corroborating the finding from SE-rsfMRI data. Furthermore, during rsfMRI experiments, we simultaneously recorded neural spiking activities in the hippocampus using GCaMP-based fiber photometry. The hippocampal calcium activity exhibited significant correspondence with the global rsfMRI signal. These data collectively suggest that the global rsfMRI signal contains significant neural components that involve coordinated activities in the thalamo-cortical and hippocampo-cortical networks. These results provide important insight into the neural substrate of the global brain signal in awake rodents.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Aguirre GK, Zarahn E, D’Esposito M (1997) Empirical analyses of BOLD fMRI statistics. II. Spatially smoothed data collected under null-hypothesis and experimental conditions. Neuroimage 5(3):199–212
Bergmann E, Zur G, Bershadsky G, Kahn I (2016) The organization of mouse and human cortico-hippocampal networks estimated by intrinsic functional connectivity. Cereb Cortex 26(12):4497–4512. https://doi.org/10.1093/cercor/bhw327
Birn RM, Smith MA, Jones TB, Bandettini PA (2008) The respiration response function: the temporal dynamics of fMRI signal fluctuations related to changes in respiration. Neuroimage 40(2):644–654. https://doi.org/10.1016/j.neuroimage.2007.11.059
Biswal B, Yetkin FZ, Haughton VM, Hyde JS (1995) Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 34(4):537–541
Biswal BB, Mennes M, Zuo XN, Gohel S, Kelly C, Smith SM, Beckmann CF, Adelstein JS, Buckner RL, Colcombe S, Dogonowski AM, Ernst M, Fair D, Hampson M, Hoptman MJ, Hyde JS, Kiviniemi VJ, Kotter R, Li SJ, Lin CP, Lowe MJ, Mackay C, Madden DJ, Madsen KH, Margulies DS, Mayberg HS, McMahon K, Monk CS, Mostofsky SH, Nagel BJ, Pekar JJ, Peltier SJ, Petersen SE, Riedl V, Rombouts SA, Rypma B, Schlaggar BL, Schmidt S, Seidler RD, Siegle GJ, Sorg C, Teng GJ, Veijola J, Villringer A, Walter M, Wang L, Weng XC, Whitfield-Gabrieli S, Williamson P, Windischberger C, Zang YF, Zhang HY, Castellanos FX, Milham MP (2010) Toward discovery science of human brain function. Proc Natl Acad Sci USA 107(10):4734–4739. https://doi.org/10.1073/pnas.0911855107
Calhoun VD, Adali T, Pearlson GD, Pekar JJ (2001) A method for making group inferences from functional MRI data using independent component analysis. Hum Brain Mapp 14(3):140–151
Chan RW, Leong ATL, Ho LC, Gao PP, Wong EC, Dong CM, Wang X, He J, Chan YS, Lim LW, Wu EX (2017) Low-frequency hippocampal-cortical activity drives brain-wide resting-state functional MRI connectivity. Proc Natl Acad Sci USA 114(33):E6972–E6981. https://doi.org/10.1073/pnas.1703309114
Chang C, Cunningham JP, Glover GH (2009) Influence of heart rate on the BOLD signal: the cardiac response function. Neuroimage 44(3):857–869. https://doi.org/10.1016/j.neuroimage.2008.09.029
Chang C, Leopold DA, Scholvinck ML, Mandelkow H, Picchioni D, Liu X, Ye FQ, Turchi JN, Duyn JH (2016a) Tracking brain arousal fluctuations with fMRI. Proc Natl Acad Sci USA 113(16):4518–4523. https://doi.org/10.1073/pnas.1520613113
Chang PC, Procissi D, Bao Q, Centeno MV, Baria A, Apkarian AV (2016b) Novel method for functional brain imaging in awake minimally restrained rats. J Neurophysiol 116(1):61–80. https://doi.org/10.1152/jn.01078.2015
Ciric R, Rosen AFG, Erus G, Cieslak M, Adebimpe A, Cook PA, Bassett DS, Davatzikos C, Wolf DH, Satterthwaite TD (2018) Mitigating head motion artifact in functional connectivity MRI. Nat Protoc 13(12):2801–2826. https://doi.org/10.1038/s41596-018-0065-y
Colenbier N, Van de Steen F, Uddin LQ, Poldrack RA, Calhoun V, Marinazzo D (2019) Disambiguating the role of blood flow and global signal with Partial Information Decomposition. Front Neurosci. https://doi.org/10.3389/conf.fnins.2019.96.00045
Dopfel D, Zhang N (2018) Mapping stress networks using functional magnetic resonance imaging in awake animals. Neurobiol Stress 9:251–263. https://doi.org/10.1016/j.ynstr.2018.06.002
Dopfel D, Perez PD, Verbitsky A, Bravo-Rivera H, Ma Y, Quirk GJ, Zhang N (2019) Individual variability in behavior and functional networks predicts vulnerability using an animal model of PTSD. Nat Commun 10(1):2372. https://doi.org/10.1038/s41467-019-09926-z
Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci USA 102(27):9673–9678
Gao YR, Ma Y, Zhang Q, Winder AT, Liang Z, Antinori L, Drew PJ, Zhang N (2016) Time to wake up: studying neurovascular coupling and brain-wide circuit function in the un-anesthetized animal. Neuroimage. https://doi.org/10.1016/j.neuroimage.2016.11.069
Gutierrez-Barragan D, Basson MA, Panzeri S, Gozzi A (2019) Infraslow state fluctuations govern spontaneous fMRI network dynamics. Curr Biol. https://doi.org/10.1016/j.cub.2019.06.017
Hamilton C, Ma Y, Zhang N (2017) Global reduction of information exchange during anesthetic-induced unconsciousness. Brain Struct Funct 222(7):3205–3216. https://doi.org/10.1007/s00429-017-1396-0
Kalthoff D, Seehafer JU, Po C, Wiedermann D, Hoehn M (2011) Functional connectivity in the rat at 11.7T: Impact of physiological noise in resting state fMRI. Neuroimage 54(4):2828–2839. https://doi.org/10.1016/j.neuroimage.2010.10.053
Kim CK, Yang SJ, Pichamoorthy N, Young NP, Kauvar I, Jennings JH, Lerner TN, Berndt A, Lee SY, Ramakrishnan C, Davidson TJ, Inoue M, Bito H, Deisseroth K (2016) Simultaneous fast measurement of circuit dynamics at multiple sites across the mammalian brain. Nat Methods 13(4):325–328. https://doi.org/10.1038/nmeth.3770
Kundu P, Inati SJ, Evans JW, Luh WM, Bandettini PA (2012) Differentiating BOLD and non-BOLD signals in fMRI time series using multi-echo EPI. Neuroimage 60(3):1759–1770. https://doi.org/10.1016/j.neuroimage.2011.12.028
Kundu P, Brenowitz ND, Voon V, Worbe Y, Vertes PE, Inati SJ, Saad ZS, Bandettini PA, Bullmore ET (2013) Integrated strategy for improving functional connectivity mapping using multiecho fMRI. Proc Natl Acad Sci USA 110(40):16187–16192. https://doi.org/10.1073/pnas.1301725110
Kundu P, Santin MD, Bandettini PA, Bullmore ET, Petiet A (2014) Differentiating BOLD and non-BOLD signals in fMRI time series from anesthetized rats using multi-echo EPI at 11.7 T. Neuroimage 102(Pt 2):861–874. https://doi.org/10.1016/j.neuroimage.2014.07.025
Leong AT, Chan RW, Gao PP, Chan YS, Tsia KK, Yung WH, Wu EX (2016) Long-range projections coordinate distributed brain-wide neural activity with a specific spatiotemporal profile. Proc Natl Acad Sci USA 113(51):E8306–E8315. https://doi.org/10.1073/pnas.1616361113
Liang Z, King J, Zhang N (2011) Uncovering intrinsic connectional architecture of functional networks in awake rat brain. J Neurosci 31(10):3776–3783
Liang Z, King J, Zhang N (2012a) Anticorrelated resting-state functional connectivity in awake rat brain. Neuroimage 59(2):1190–1199. https://doi.org/10.1016/j.neuroimage.2011.08.009
Liang Z, King J, Zhang N (2012b) Intrinsic organization of the anesthetized brain. J Neurosci 32(30):10183–10191. https://doi.org/10.1523/JNEUROSCI.1020-12.2012
Liang Z, Li T, King J, Zhang N (2013) Mapping thalamocortical networks in rat brain using resting-state functional connectivity. Neuroimage 83:237–244. https://doi.org/10.1016/j.neuroimage.2013.06.029
Liang Z, King J, Zhang N (2014) Neuroplasticity to a single-episode traumatic stress revealed by resting-state fMRI in awake rats. Neuroimage 103:485–491. https://doi.org/10.1016/j.neuroimage.2014.08.050
Liang Z, Liu X, Zhang N (2015a) Dynamic resting state functional connectivity in awake and anesthetized rodents. Neuroimage 104:89–99. https://doi.org/10.1016/j.neuroimage.2014.10.013
Liang Z, Watson GD, Alloway KD, Lee G, Neuberger T, Zhang N (2015b) Mapping the functional network of medial prefrontal cortex by combining optogenetics and fMRI in awake rats. Neuroimage 117:114–123. https://doi.org/10.1016/j.neuroimage.2015.05.036
Liang Z, Ma Y, Watson GDR, Zhang N (2017) Simultaneous GCaMP6-based fiber photometry and fMRI in rats. J Neurosci Methods 289:31–38. https://doi.org/10.1016/j.jneumeth.2017.07.002
Liu TT (2016) Noise contributions to the fMRI signal: an overview. Neuroimage 143:141–151. https://doi.org/10.1016/j.neuroimage.2016.09.008
Liu Y, Zhang N (2019) Propagations of spontaneous brain activity in awake rats. Neuroimage 202:116176. https://doi.org/10.1016/j.neuroimage.2019.116176
Liu TT, Nalci A, Falahpour M (2017) The global signal in fMRI: nuisance or information? Neuroimage 150:213–229. https://doi.org/10.1016/j.neuroimage.2017.02.036
Liu X, de Zwart JA, Scholvinck ML, Chang C, Ye FQ, Leopold DA, Duyn JH (2018) Subcortical evidence for a contribution of arousal to fMRI studies of brain activity. Nat Commun 9(1):395. https://doi.org/10.1038/s41467-017-02815-3
Logothetis NK, Eschenko O, Murayama Y, Augath M, Steudel T, Evrard HC, Besserve M, Oeltermann A (2012) Hippocampal-cortical interaction during periods of subcortical silence. Nature 491(7425):547–553. https://doi.org/10.1038/nature11618
Ma Z, Zhang N (2018) Temporal transitions of spontaneous brain activity. eLife 2018:7. https://doi.org/10.7554/elife.33562
Ma Y, Shaik MA, Kozberg MG, Kim SH, Portes JP, Timerman D, Hillman EM (2016) Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons. Proc Natl Acad Sci USA 113(52):E8463–E8471. https://doi.org/10.1073/pnas.1525369113
Ma Y, Hamilton C, Zhang N (2017) Dynamic connectivity patterns in conscious and unconscious brain. Brain connectivity 7(1):1–12. https://doi.org/10.1089/brain.2016.0464
Ma Z, Perez P, Ma Z, Liu Y, Hamilton C, Liang Z, Zhang N (2018) Functional atlas of the awake rat brain: a neuroimaging study of rat brain specialization and integration. Neuroimage 170:95–112. https://doi.org/10.1016/j.neuroimage.2016.07.007
Matsui T, Murakami T, Ohki K (2016) Transient neuronal coactivations embedded in globally propagating waves underlie resting-state functional connectivity. Proc Natl Acad Sci USA 113(23):6556–6561. https://doi.org/10.1073/pnas.1521299113
Murphy K, Birn RM, Handwerker DA, Jones TB, Bandettini PA (2009) The impact of global signal regression on resting state correlations: are anti-correlated networks introduced? Neuroimage 44(3):893–905
Nalci A, Rao BD, Liu TT (2017) Global signal regression acts as a temporal downweighting process in resting-state fMRI. Neuroimage 152:602–618. https://doi.org/10.1016/j.neuroimage.2017.01.015
Perez PD, Ma Z, Hamilton C, Sanchez C, Mork A, Pehrson AL, Bundgaard C, Zhang N (2018) Acute effects of vortioxetine and duloxetine on resting-state functional connectivity in the awake rat. Neuropharmacology 128:379–387. https://doi.org/10.1016/j.neuropharm.2017.10.038
Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE (2012) Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59(3):2142–2154. https://doi.org/10.1016/j.neuroimage.2011.10.018
Power JD, Schlaggar BL, Petersen SE (2015) Recent progress and outstanding issues in motion correction in resting state fMRI. Neuroimage 105:536–551. https://doi.org/10.1016/j.neuroimage.2014.10.044
Rack-Gomer AL, Liu TT (2012) Caffeine increases the temporal variability of resting-state BOLD connectivity in the motor cortex. Neuroimage 59(3):2994–3002. https://doi.org/10.1016/j.neuroimage.2011.10.001
Raichle ME (2006) Neuroscience. The brain’s dark energy. Science 314(5803):1249–1250. https://doi.org/10.1126/science.1134405
Raichle ME (2010) The brain’s dark energy. Sci Am 302(3):44–49
Ramirez-Villegas JF, Logothetis NK, Besserve M (2015) Diversity of sharp-wave-ripple LFP signatures reveals differentiated brain-wide dynamical events. Proc Natl Acad Sci USA 112(46):E6379–E6387. https://doi.org/10.1073/pnas.1518257112
Rivera B, Miller S, Brown E, Price R (2005) A novel method for endotracheal intubation of mice and rats used in imaging studies. Contemp Top Lab Anim Sci 44(2):52–55
Satterthwaite TD, Wolf DH, Loughead J, Ruparel K, Elliott MA, Hakonarson H, Gur RC, Gur RE (2012) Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. Neuroimage 60(1):623–632. https://doi.org/10.1016/j.neuroimage.2011.12.063
Scholvinck ML, Maier A, Ye FQ, Duyn JH, Leopold DA (2010) Neural basis of global resting-state fMRI activity. Proc Natl Acad Sci USA 107(22):10238–10243
Smith SM, Fox PT, Miller KL, Glahn DC, Fox PM, Mackay CE, Filippini N, Watkins KE, Toro R, Laird AR, Beckmann CF (2009) Correspondence of the brain’s functional architecture during activation and rest. Proc Natl Acad Sci USA 106(31):13040–13045. https://doi.org/10.1073/pnas.0905267106
Smith JB, Liang Z, Watson GDR, Alloway KD, Zhang N (2017) Interhemispheric resting-state functional connectivity of the claustrum in the awake and anesthetized states. Brain Struct Funct 222(5):2041–2058. https://doi.org/10.1007/s00429-016-1323-9
Turchi J, Chang C, Ye FQ, Russ BE, Yu DK, Cortes CR, Monosov IE, Duyn JH, Leopold DA (2018) The basal forebrain regulates global resting-state fMRI fluctuations. Neuron 97(4):940–952 e944. https://doi.org/10.1016/j.neuron.2018.01.032
Van Dijk KR, Sabuncu MR, Buckner RL (2012) The influence of head motion on intrinsic functional connectivity MRI. Neuroimage 59(1):431–438. https://doi.org/10.1016/j.neuroimage.2011.07.044
Wen H, Liu Z (2016) Broadband electrophysiological dynamics contribute to global resting-state fMRI signal. J Neurosci 36(22):6030–6040. https://doi.org/10.1523/JNEUROSCI.0187-16.2016
Wong CW, Olafsson V, Tal O, Liu TT (2012) Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI. Neuroimage 63(1):356–364. https://doi.org/10.1016/j.neuroimage.2012.06.035
Wong CW, Olafsson V, Tal O, Liu TT (2013) The amplitude of the resting-state fMRI global signal is related to EEG vigilance measures. Neuroimage 83:983–990. https://doi.org/10.1016/j.neuroimage.2013.07.057
Yang GJ, Murray JD, Repovs G, Cole MW, Savic A, Glasser MF, Pittenger C, Krystal JH, Wang XJ, Pearlson GD, Glahn DC, Anticevic A (2014) Altered global brain signal in schizophrenia. Proc Natl Acad Sci USA 111(20):7438–7443. https://doi.org/10.1073/pnas.1405289111
Yang GJ, Murray JD, Glasser M, Pearlson GD, Krystal JH, Schleifer C, Repovs G, Anticevic A (2017) Altered global signal topography in schizophrenia. Cereb Cortex 27(11):5156–5169. https://doi.org/10.1093/cercor/bhw297
Yoshida K, Mimura Y, Ishihara R, Nishida H, Komaki Y, Minakuchi T, Tsurugizawa T, Mimura M, Okano H, Tanaka KF, Takata N (2016) Physiological effects of a habituation procedure for functional MRI in awake mice using a cryogenic radiofrequency probe. J Neurosci Methods 274:38–48. https://doi.org/10.1016/j.jneumeth.2016.09.013
Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC, Gerig G (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 31(3):1116–1128. https://doi.org/10.1016/j.neuroimage.2006.01.015
Zhang D, Raichle ME (2010) Disease and the brain’s dark energy. Nat Rev Neurol 6(1):15–28. https://doi.org/10.1038/nrneurol.2009.198
Zhang N, Rane P, Huang W, Liang Z, Kennedy D, Frazier JA, King J (2010) Mapping resting-state brain networks in conscious animals. J Neurosci Methods 189(2):186–196. https://doi.org/10.1016/j.jneumeth.2010.04.001S0165-0270(10)00186-X
Funding
The present study was supported by National Institute of Neurological Disorders and Stroke (R01NS085200, PI: Nanyin Zhang, PhD) and National Institute of Mental Health (R01MH098003 and RF1MH114224, PI: Nanyin Zhang, PhD).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The author(s) declare that they have no conflict of interest.
Research involving human participants and/or animals
The research involved animals. All procedures were conducted in accordance with approved protocols from the Institutional Animal Care and Use Committee (IACUC) of the Pennsylvania State University.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ma, Y., Ma, Z., Liang, Z. et al. Global brain signal in awake rats. Brain Struct Funct 225, 227–240 (2020). https://doi.org/10.1007/s00429-019-01996-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00429-019-01996-5