Skip to main content
SpringerLink
Log in

One dataset, many conclusions: BOLD variability’s complicated relationships with age and motion artifacts

  • SI: Developing Brain
  • Published:
Brain Imaging and Behavior Aims and scope Submit manuscript

Abstract

In recent years, the variability of the blood-oxygen level dependent (BOLD) signal has received attention as an informative measure in its own right. At the same time, there has been growing concern regarding the impact of motion in fMRI, particularly in the domain of resting state studies. Here, we demonstrate that, not only does motion (among other confounds) exert an influence on the results of a BOLD variability analysis of task-related fMRI data—but, that the exact method used to deal with this influence has at least as large an effect as the motion itself. This sensitivity to relatively minor methodological changes is particularly concerning as studies begin to take on a more applied bent, and the risk of mischaracterizing the relationship between BOLD variability and various individual difference variables (for instance, disease progression) acquires real-world relevance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Aanerud, J., Borghammer, P., Chakravarty, M.M., Vang, K., Rodell, A.B., Jónsdottir, K.Y., Møller, A., Ashkanian, M. , Vafaee, M.S. , Iversen, P., et al. (2012). Brain energy metabolism and blood flow differences in healthy aging. Journal of Cerebral Blood Flow & Metabolism, 32(7), 1177–1187.

    Article  CAS  Google Scholar 

  • Cabeza, R., Grady, C.L., Nyberg, L., McIntosh, A.R., Tulving, E., Kapur, S., Jennings, J.M., Houle, S., Craik, F.I. (1997). Age-related differences in neural activity during memory encoding and retrieval: a positron emission tomography study. The Journal of Neuroscience, 17(1), 391–400.

    CAS  PubMed  Google Scholar 

  • Cabeza, R., Anderson, N.D., Locantore, J.K., McIntosh, A.R. (2002). Aging gracefully: compensatory brain activity in high-performing older adults. Neuroimage, 17(3), 1394–1402.

    Article  PubMed  Google Scholar 

  • Carp, J. (2012). The secret lives of experiments: methods reporting in the fmri literature. Neuroimage, 63(1), 289–300.

    Article  PubMed  Google Scholar 

  • Cohen, A.L., Fair, D.A., Dosenbach, N.U., Miezin, F.M., Dierker, D., Van Essen, D.C., Schlaggar, B.L., Petersen, S.E. (2008). Defining functional areas in individual human brains using resting functional connectivity mri. Neuroimage, 41(1), 45–57.

    Article  PubMed Central  PubMed  Google Scholar 

  • Fisher, R.A. (1924). The distribution of the partial correlation coefficient. Metron, 3, 329–332.

    Google Scholar 

  • Folstein, M.F., Folstein, S.E., McHugh, P.R. (1975). Mini-mental state: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189– 198.

    Article  CAS  PubMed  Google Scholar 

  • Garrett, D.D., Kovacevic, N., McIntosh, A.R., Grady, C.L. (2010). Blood oxygen level-dependent signal variability is more than just noise. The Journal of Neuroscience, 30(14), 4914–4921.

    Article  CAS  PubMed  Google Scholar 

  • Garrett, D.D., Kovacevic, N., McIntosh, A.R., Grady, C.L. (2011). The importance of being variable. The Journal of Neuroscience, 31(12), 4496–4503.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Garrett, D.D., Kovacevic, N., McIntosh, A.R., Grady, C.L. (2012). The modulation of bold variability between cognitive states varies by age and processing speed. Cerebral Cortex, 684–693.

  • Garrett, D.D., Samanez-Larkin, G.R., MacDonald, S.W., Lindenberger, U., McIntosh, A.R., Grady, C.L. (2013). Moment-to-moment brain signal variability: a next frontier in human brain mapping Neuroscience & Biobehavioral Reviews, 37(4), 610– 624.

    Article  Google Scholar 

  • He, B.J. (2011). Scale-free properties of the functional magnetic resonance imaging signal during rest and task. The Journal of neuroscience, 31(39), 13,786–13,795.

    Article  CAS  Google Scholar 

  • Kannurpatti, S.S., Motes, M.A., Rypma, B., Biswal, B.B. (2011). Increasing measurement accuracy of age-related bold signal change: Minimizing vascular contributions by resting-state-fluctuation-of-amplitude scaling. Human Brain Mapping, 32(7), 1125–1140.

    Article  PubMed Central  PubMed  Google Scholar 

  • Klein, A., Andersson, J., Ardekani, B.A., Ashburner, J., Avants, B., Chiang, M.C., Christensen, G.E., Collins, D.L., Gee, J., Hellier, P., Song, J.H., Jerkinson, M., Lepage, C., Rueckert, D., Thompson, P., Vercauteren, T., Woods, R.P., Mann, J.J., Ramin, V.P. (2009). Evaluation of 14 nonlinear deformation algorithms applied to human brain mri registration. Neuroimage, 46(3), 786–802.

    Article  PubMed Central  PubMed  Google Scholar 

  • Knopman, D.S., Jack Jr, C.R., Wiste, H.J., Lundt, E.S., Weigand, S.D., Vemuri, P., Lowe, V.J., Kantarci, K., Gunter, J.L., Senjem, M.L., et al (2014). 18F-fluorodeoxyglucose positron emission tomography, aging, and apolipoprotein e genotype in cognitively normal persons. Neurobiology of Aging, 35, 2096–2106.

    Article  CAS  PubMed  Google Scholar 

  • Leo, A., Bernardi, G., Handjaras, G., Bonino, D., Ricciardi, E., Pietrini, P. (2012). Increased bold variability in the parietal cortex and enhanced parieto-occipital connectivity during tactile perception in congenitally blind individuals. Neural plasticity, 2012.

  • Liu, C.Y., Krishnan, A.P., Yan, L., Smith, R.X., Kilroy, E., Alger, J.R., Ringman, J.M., Wang, D.J. (2013). Complexity and synchronicity of resting state blood oxygenation level-dependent (bold) functional mri in normal aging and cognitive decline. Journal of Magnetic Resonance Imaging, 38(1), 36–45.

    Article  PubMed Central  PubMed  Google Scholar 

  • Marchal, G., Rioux, P., Petit-Taboué, M.C., Sette, G., Travere, J.M., Le Poec, C., Courtheoux, P., Derlon, J.M., Baron, J.C. (1992). Regional cerebral oxygen consumption, blood flow, and blood volume in healthy human aging. Archives of neurology, 49(10), 1013–1020.

    Article  CAS  PubMed  Google Scholar 

  • Mohr, P.N., & Nagel, I.E. (2010). Variability in brain activity as an individual difference measure in neuroscience The Journal of Neuroscience, 30(23), 7755–7757.

    Article  CAS  PubMed  Google Scholar 

  • Patel, A.X., Kundu, P., Rubinov, M., Jones, P.S., Vértes, P.E., Ersche, K.D., Suckling, J., Bullmore, E.T. (2014). A wavelet method for modeling and despiking motion artifacts from resting-state fmri time series. NeuroImage, 95, 287–304.

    Article  PubMed Central  PubMed  Google Scholar 

  • Power, J.D., Barnes, K.A., Snyder, A.Z., Schlaggar, B.L., Petersen, S.E. (2012). Spurious but systematic correlations in functional connectivity mri networks arise from subject motion. Neuroimage, 59(3), 2142–2154.

    Article  PubMed Central  PubMed  Google Scholar 

  • Power, J.D., Mitra, A., Laumann, T.O., Snyder, A.Z., Schlaggar, B.L., Petersen, S.E. (2014). Methods to detect, characterize, and remove motion artifact in resting state fmri. Neuroimage, 84, 320–341.

    Article  PubMed  Google Scholar 

  • Samanez-Larkin, G.R., Kuhnen, C.M., Yoo, D.J., Knutson, B. (2010). Variability in nucleus accumbens activity mediates age-related suboptimal financial risk taking. The Journal of Neuroscience, 30(4), 1426–1434.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Satterthwaite, T.D., Wolf, D.H., Loughead, J., Ruparel, K., Elliott, M.A., Hakonarson, H., Gur, R.C., Gur, R.E. (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.

    Article  PubMed Central  PubMed  Google Scholar 

  • Satterthwaite, T.D., Elliott, M.A., Gerraty, R.T., Ruparel, K., Loughead, J., Calkins, M.E., Eickhoff, S.B., Hakonarson, H., Gur, R.C., Gur, R.E., et al (2013). An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data. Neuroimage, 64, 240–256.

    Article  PubMed  Google Scholar 

  • Shen, Q., Ren, H., Duong, T.Q. (2008). Cbf, bold, cbv, and cmro2 fmri signal temporal dynamics at 500-msec resolution. Journal of Magnetic Resonance Imaging, 27(3), 599–606.

    Article  PubMed Central  PubMed  Google Scholar 

  • Van Dijk, K.R., Sabuncu, M.R., Buckner, R.L. (2012). The influence of head motion on intrinsic functional connectivity mri. Neuroimage, 59(1), 431–438.

    Article  PubMed Central  PubMed  Google Scholar 

  • Wutte, M.G., Smith, M.T., Flanagin, V.L., Wolbers, T. (2011). Physiological signal variability in hmt+ reflects performance on a direction discrimination task. Frontiers in Psychology, 2.

  • Yan, C.G., Cheung, B., Kelly, C., Colcombe, S., Craddock, R.C., Martino, A.D., Li, Q., Zuo, X.N., Castellanos, F.X., Milham, M.P. (2013). A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics. NeuroImage, 76(0), 183–201.

    Article  PubMed Central  PubMed  Google Scholar 

  • Zang, Y.F., He, Y., Zhu, C.Z., Cao, Q.J., Sui, M.Q., Liang, M., Tian, L.X., Jiang, T.Z., Wang, Y.F. (2007). Altered baseline brain activity in children with adhd revealed by resting-state functional mri. Brain and Development, 29(2), 83–91.

    Article  PubMed  Google Scholar 

  • Zou, Q.H., Zhu, C.Z., Yang, Y., Zuo, X.N., Long, X.Y., Cao, Q.J., Wang, Y.F., Zang, Y.F. (2008). An improved approach to detection of amplitude of low-frequency fluctuation (alff) for resting-state fmri: fractional alff. Journal of Neuroscience Methods, 172(1), 137–141.

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by the Institute for Collaborative Biotechnologies through contract no. W911NF-09-D-0001 from the U.S. Army Research Office.

Conflict of interest

Benjamin O. Turner, Brian Lopez, Tyler Santander, and Michael B. Miller declare that they have no conflicts of interest.

Informed Consent

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, and the applicable revisions at the time of the investigation. Informed consent was obtained from all patients for being included in the study.

Author information

Authors and Affiliations

  1. Department of Psychological and Brain Sciences, University of California Santa Barbara, Santa Barbara, CA, USA

    Benjamin O. Turner, Brian Lopez, Tyler Santander & Michael B. Miller

Authors
  1. Benjamin O. Turner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Brian Lopez
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tyler Santander
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Michael B. Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Benjamin O. Turner.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Turner, B.O., Lopez, B., Santander, T. et al. One dataset, many conclusions: BOLD variability’s complicated relationships with age and motion artifacts. Brain Imaging and Behavior 9, 115–127 (2015). https://doi.org/10.1007/s11682-014-9351-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11682-014-9351-7

Keywords

Search

Navigation