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Resting-state BOLD oscillation frequency predicts vigilance task performance at both normal and high environmental temperatures

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Abstract

Hyperthermia may impair vigilance functions and lead to slower reaction times (RTs) in the psychomotor vigilance task (PVT) and possibly disturbing cerebral hemodynamic rhythms. To test these hypotheses, we acquired the resting-state BOLD and cerebral blood flow (CBF) data, as well as PVTRTs from 15 participants in two simulated environmental thermal conditions (50 °C/25 °C). We adopted a data-driven method, frequency component analysis, to quantify the mean frequency of the BOLD series of each voxel. Across-subject correlation analysis was employed to detect the brain areas whose BOLD oscillation frequency was correlated with the RTs. Significant changes of BOLD frequency and CBF within these areas were compared between hyperthermia and normothermia conditions. Spatial correlations between BOLD frequency and CBF were calculated within different brain areas for each subject under both thermal conditions. Results showed that, under both thermal conditions, the RTs correlated with the BOLD frequency positively in the default mode network (DMN) and negatively in the sensorimotor network (SMN). The increase of BOLD frequency in the thalamus and ventral medial prefrontal cortex was correlated with the increase of RTs in hyperthermia compared with normothermia. Hyperthermia decreased BOLD frequency and CBF in the SMN, while it increased CBF in the thalamus and posterior cingulate. In both thermal conditions, the spatial distribution of CBF negatively correlated with the spatial distribution of BOLD oscillation frequency in most cortical areas, especially in cingulate cortices, precuneus, and primary visual cortex. These results suggest that hyperthermia might deteriorate task performance by interfering with the resting-state CBF, and with BOLD rhythms. The overlapping of the thermoregulatory and vigilance functions in the SMN and DMN might underlie the neural mechanisms of the cognitive-behavioral impairments induced by hyperthermia.

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Abbreviations

FCA:

Frequency component analysis

EMD:

Empirical mode decomposition

IMF:

Intrinsic mode decomposition

BOLD-fMRI:

Blood-oxygen-level-dependent functional magnetic resonance imaging

CBF:

Cerebral blood flow

PVT:

Psychomotor vigilance task

RT:

Reaction time

DMN:

Default mode network

SMN:

Sensorimotor network

References

  • Baria AT, Mansour A, Huang L, Baliki MN, Cecchi GA, Mesulam MM, Apkarian AV (2013) Linking human brain local activity fluctuations to structural and functional network architectures. Neuroimage 73:144–155

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Birn RM, Diamond JB, Smith MA, Bandettini PA (2006) Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI. Neuroimage 31(4):1536–1548

    Article  PubMed  Google Scholar 

  • Brothers RM, Wingo JE, Hubing KA, Crandall CG (2009) The effects of reduced end-tidal carbon dioxide tension on cerebral blood flow during heat stress. J Physiol 587(Pt 15):3921–3927

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Buzsáki G, Geisler C, Henze DA, Wang XJ (2004) Interneuron Diversity series: circuit complexity and axon wiring economy of cortical interneurons. Trends Neurosci 27(4):186

    Article  PubMed  Google Scholar 

  • Chang C, Glover GH (2009) Relationship between respiration, end-tidal CO2, and BOLD signals in resting-state fMRI. Neuroimage 47(4):1381–1393

    Article  PubMed  PubMed Central  Google Scholar 

  • Chang C, Liu Z, Chen MC, Liu X, Duyn JH (2013) EEG correlates of time-varying BOLD functional connectivity. NeuroImage 72:227–236

    Article  PubMed  PubMed Central  Google Scholar 

  • Cordes D, Haughton VM, Arfanakis K, Carew JD, Turski PA, Moritz CH, Quigley MA, Meyerand ME (2001) Frequencies contributing to functional connectivity in the cerebral cortex in “resting-state” data. AJNR Am J Neuroradiol 22(7):1326–1333

    CAS  PubMed  Google Scholar 

  • Craig A, Tran Y, Wijesuriya N, Nguyen H (2012) Regional brain wave activity changes associated with fatigue. Psychophysiology 49(4):574–582

    Article  PubMed  Google Scholar 

  • Dimicco JA, Zaretsky DV (2007) The dorsomedial hypothalamus: a new player in thermoregulation. Am J Physiol Regul Integr Comp Physiol 292(1):R47–R63. doi:10.1152/ajpregu.00498.2006

    Article  CAS  PubMed  Google Scholar 

  • Drummond SP, Bischoff-Grethe A, Dinges DF, Ayalon L, Mednick SC, Meloy MJ (2005) The neural basis of the psychomotor vigilance task. Sleep 28(9):1059–1068

    PubMed  Google Scholar 

  • Engel AK, Fries P, Singer W (2001) Dynamic predictions: oscillations and synchrony in top-down processing. Nat Rev Neurosci 2(10):704–716

    Article  CAS  PubMed  Google Scholar 

  • Gorgoni M, Ferlazzo F, Ferrara M, Moroni F, D’Atri A, Fanelli S, Gizzi TI, Lauri G, Marzano C, Rossini PM, De Gennaro L (2014) Topographic electroencephalogram changes associated with psychomotor vigilance task performance after sleep deprivation. Sleep Med 15(9):1132–1139

    Article  PubMed  Google Scholar 

  • Hoedlmoser K, Griessenberger H, Fellinger R, Freunberger R, Klimesch W, Gruber W, Schabus M (2011) Event-related activity and phase locking during a psychomotor vigilance task over the course of sleep deprivation. J Sleep Res 20(3):377–385

    Article  PubMed  Google Scholar 

  • Huang NE, Shen SS (2005) Hilbert–Huang transform and its applications, vol 5. World Scientific Publishing Company Incorporated

  • Huang NE, Shen Z, Long SR, Wu MC, Shih HH, Zheng Q, Yen NC, Tung CC, Liu HH (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc R Soc Lond Ser A Math Phys Eng Sci 454(1971):903–995

    Article  Google Scholar 

  • Jann K, Gee DG, Kilroy E, Schwab S, Smith RX, Cannon TD, Wang DJ (2015) Functional connectivity in BOLD and CBF data: similarity and reliability of resting brain networks. Neuroimage 106:111–122. doi:10.1016/j.neuroimage.2014.11.028

    Article  PubMed  Google Scholar 

  • Khalili-Mahani N, van Osch MJ, de Rooij M, Beckmann CF, van Buchem MA, Dahan A, van Gerven JM, Rombouts SA (2014) Spatial heterogeneity of the relation between resting-state connectivity and blood flow: an important consideration for pharmacological studies. Hum Brain Mapp 35(3):929–942

    Article  PubMed  Google Scholar 

  • Kim SG, Ogawa S (2012) Biophysical and physiological origins of blood oxygenation level-dependent fMRI signals. J Cereb Blood Flow Metab 32(7):1188–1206. doi:10.1038/jcbfm.2012.23

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lebedev MA, Messinger A, Kralik JD, Wise SP (2004) Representation of attended versus remembered locations in prefrontal cortex. PLoS Biol 2(11):e365

    Article  PubMed  PubMed Central  Google Scholar 

  • Liang X, Zou Q, He Y, Yang Y (2013) Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain. Proc Natl Acad Sci USA 110(5):1929–1934

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lim J, Wu WC, Wang J, Detre JA, Dinges DF, Rao H (2010) Imaging brain fatigue from sustained mental workload: an ASL perfusion study of the time-on-task effect. Neuroimage 49(4):3426–3435

    Article  PubMed  Google Scholar 

  • Lindstedt F, Johansson B, Martinsen S, Kosek E, Fransson P, Ingvar M (2011) Evidence for thalamic involvement in the thermal grill illusion: an FMRI study. PLoS ONE 6(11):e27075

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Marx E, Deutschlander A, Stephan T, Dieterich M, Wiesmann M, Brandt T (2004) Eyes open and eyes closed as rest conditions: impact on brain activation patterns. Neuroimage 21(4):1818–1824

    Article  PubMed  Google Scholar 

  • Mason MF, Norton MI, Van Horn JD, Wegner DM, Grafton ST, Macrae CN (2007) Wandering minds: the default network and stimulus-independent thought. Science 315(5810):393–395

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Miller EK, Cohen JD (2001) An integrative theory of prefrontal cortex function. Annu Rev Neurosci 24:167–202

    Article  CAS  PubMed  Google Scholar 

  • Nagashima K (2006) Central mechanisms for thermoregulation in a hot environment. Ind Health 44(3):359–367

    Article  CAS  PubMed  Google Scholar 

  • Nelson MD, Haykowsky MJ, Stickland MK, Altamirano-Diaz LA, Willie CK, Smith KJ, Petersen SR, Ainslie PN (2011) Reductions in cerebral blood flow during passive heat stress in humans: partitioning the mechanisms. J Physiol 589(Pt 16):4053–4064

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Nunneley SA, Martin CC, Slauson JW, Hearon CM, Nickerson LD, Mason PA (2002) Changes in regional cerebral metabolism during systemic hyperthermia in humans. J Appl Physiol 92(2):846–851

    Article  PubMed  Google Scholar 

  • Prado J, Weissman DH (2011) Heightened interactions between a key default-mode region and a key task-positive region are linked to suboptimal current performance but to enhanced future performance. Neuroimage 56(4):2276–2282

    Article  PubMed  Google Scholar 

  • Qian S, Jiang Q, Liu K, Li B, Li M, Li L, Yang X, Yang Z, Sun G (2014) Effects of short-term environmental hyperthermia on patterns of cerebral blood flow. Physiol Behav 128:99–107

    Article  CAS  PubMed  Google Scholar 

  • Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL (2001) A default mode of brain function. Proc Natl Acad Sci 98(2):676–682

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ramautar JR, Romeijn N, Gomez-Herrero G, Piantoni G, Van Someren EJ (2013) Coupling of infraslow fluctuations in autonomic and central vigilance markers: skin temperature, EEG beta power and ERP P300 latency. Int J Psychophysiol 89(2):158–164

    Article  PubMed  Google Scholar 

  • Raymann RJ, Van Someren EJ (2007) Time-on-task impairment of psychomotor vigilance is affected by mild skin warming and changes with aging and insomnia. Sleep 30(1):96–103

    Article  PubMed  Google Scholar 

  • Retey JV, Adam M, Gottselig JM, Khatami R, Durr R, Achermann P, Landolt HP (2006) Adenosinergic mechanisms contribute to individual differences in sleep deprivation-induced changes in neurobehavioral function and brain rhythmic activity. J Neurosci 26(41):10472–10479

    Article  CAS  PubMed  Google Scholar 

  • Romeijn N, Van Someren EJ (2011) Correlated fluctuations of daytime skin temperature and vigilance. J Biol Rhythms 26(1):68–77

    Article  PubMed  Google Scholar 

  • Ross EZ, Cotter JD, Wilson L, Fan JL, Lucas SJ, Ainslie PN (2012) Cerebrovascular and corticomotor function during progressive passive hyperthermia in humans. J Appl Physiol 112(5):748–758

    Article  CAS  PubMed  Google Scholar 

  • Shmueli K, van Gelderen P, de Zwart JA, Horovitz SG, Fukunaga M, Jansma JM, Duyn JH (2007) Low frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal. Neuroimage 38(2):306

    Article  PubMed  PubMed Central  Google Scholar 

  • Song X, Zhang Y, Liu Y (2014) Frequency specificity of regional homogeneity in the resting-state human brain. PLoS ONE 9(1):e86818. doi:10.1371/journal.pone.0086818

    Article  PubMed  PubMed Central  Google Scholar 

  • Song X, Zhou S, Zhang Y, Liu Y, Zhu H, Gao JH (2015) Frequency-dependent modulation of regional synchrony in the human brain by eyes open and eyes closed resting-states. PLoS ONE 10(11):e0141507. doi:10.1371/journal.pone.0141507

    Article  PubMed  PubMed Central  Google Scholar 

  • Tak S, Wang DJ, Polimeni JR, Yan L, Chen JJ (2014) Dynamic and static contributions of the cerebrovasculature to the resting-state BOLD signal. Neuroimage 84:672–680

    Article  PubMed  Google Scholar 

  • Thompson GJ, Magnuson ME, Merritt MD, Schwarb H, Pan WJ, McKinley A, Tripp LD, Schumacher EH, Keilholz SD (2013) Short-time windows of correlation between large-scale functional brain networks predict vigilance intraindividually and interindividually. Hum Brain Mapp 34(12):3280–3298

    Article  PubMed  Google Scholar 

  • van Buuren M, Gladwin TE, Zandbelt BB, van den Heuvel M, Ramsey NF, Kahn RS, Vink M (2009) Cardiorespiratory effects on default-mode network activity as measured with fMRI. Hum Brain Mapp 30(9):3031–3042

    Article  PubMed  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • Wu CW, Gu H, Lu H, Stein EA, Chen JH, Yang Y (2008) Frequency specificity of functional connectivity in brain networks. Neuroimage 42(3):1047

    Article  PubMed  PubMed Central  Google Scholar 

  • Xie H, Wang Z (2006) Mean frequency derived via Hilbert–Huang transform with application to fatigue EMG signal analysis. Comput Methods Programs Biomed 82(2):114–120. doi:10.1016/j.cmpb.2006.02.009

    Article  PubMed  Google Scholar 

  • Yanaka HT, Saito DN, Uchiyama Y, Sadato N (2010) Neural substrates of phasic alertness: a functional magnetic resonance imaging study. Neurosci Res 68(1):51–58

    Article  PubMed  Google Scholar 

  • Zou Q, Yuan B-K, Gu H, Liu D, Wang DJJ, Gao J-H, Yang Y, Zang Y-F (2015) Detecting static and dynamic differences between eyes-closed and eyes-open resting states using ASL and BOLD fMRI. PLoS ONE 10(3):e0121757. doi:10.1371/journal.pone.0121757

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Science Foundation of China 81430037, 61131003, 31421003, 81671765; Beijing Municipal Science and Technology Commission Z161100000216152, Z171100000117012, Z161100002616006; Beijing Municipal Natural Science Foundation 7172121; China’s National Strategic Basic Research Program (“973”) Grant 2015CB856400; Logistics Research Project of Chinese People's Liberation Army CJN13J004 and Shenzhen Peacock Plan KQTD2015033016104926. We thank the National Center for Protein Sciences at Peking University in Beijing, China, for the assistance with MRI data acquisition and data analyses. We thank Dr. Nelson J. Klahr for the language editing.

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    Authors and Affiliations

    1. Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, 100871, China

      Xiaopeng Song, Shuqin Zhou, Huaiqiu Zhu & Yijun Liu

    2. Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China

      Xiaopeng Song, Shuqin Zhou, Qihong Zou & Jia-Hong Gao

    3. Department of Medical Imaging, Jinan Military General Hospital, Shandong, China

      Shaowen Qian, Kai Liu & Gang Sun

    4. McGovern Institute for Brain Research, Peking University, Beijing, 100871, China

      Jia-Hong Gao

    5. Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China

      Jia-Hong Gao

    6. Shenzhen Institute of Neuroscience, Shenzhen, China

      Jia-Hong Gao

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    Correspondence to Gang Sun or Jia-Hong Gao.

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    Xiaopeng Song and Shaowen Qian have contributed equally to this work.

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    Song, X., Qian, S., Liu, K. et al. Resting-state BOLD oscillation frequency predicts vigilance task performance at both normal and high environmental temperatures. Brain Struct Funct 222, 4065–4077 (2017). https://doi.org/10.1007/s00429-017-1449-4

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