Skip to main content
SpringerLink
Log in

The Effect of Exogenous and Endogenous Parameters on Group Resting-State Effective Connectivity and BOLD Signal

  • Protocol
  • First Online:
Computational Neuroscience

Part of the book series: Neuromethods ((NM,volume 199))

  • 430 Accesses

Abstract

fMRI has gained popularity in research and clinical settings. The majority of work relies on group comparisons to identify the resting-state network structure, connectivity, and differences between diverse populations. However, the reliability of fMRI has been doubted together with an increasing number of publications on individual differences and other factors affecting the resting-state fMRI. The current publication addresses the factors that are often overlooked or not accounted for when selecting the “healthy control group” as a baseline for comparison. Our results indicate that additional biological factors, such as blood pressure, level of hemoglobin, waist circumference, time of image acquisition, as well as age and sex introduce variability in the group data. It is therefore likely to conclude that this variability on a group level might in turn affect the differences or changes observed between populations.

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

Access this chapter

Log in via an institution
Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Adolphs R (2015) The unsolved problems of neuroscience. Trends Cogn Sci 19:173–175

    Article  PubMed  PubMed Central  Google Scholar 

  2. Wang M-Y, Yuan Z (2021) EEG decoding of dynamic facial expressions of emotion: evidence from SSVEP and causal cortical network dynamics. Neuroscience 459:50–58

    Article  CAS  PubMed  Google Scholar 

  3. Biasiucci A, Franceschiello B, Murray MM (2019) Electroencephalography. Curr Biol 29:R80–R85

    Article  CAS  PubMed  Google Scholar 

  4. da Silva FL (2013) EEG and MEG: relevance to neuroscience. Neuron 80:1112–1128

    Article  Google Scholar 

  5. Vaisvilaite L, Hushagen V, Grønli J, Specht K (2021) Time-of-day effects in resting-state functional magnetic resonance imaging: changes in effective connectivity and blood oxygenation level dependent signal. Brain Connect 12:515. https://doi.org/10.1089/brain.2021.0129

    Article  PubMed  Google Scholar 

  6. Kazimierczak K, Craven AR, Ersland L et al (2021) Combined fMRI region- and network-analysis reveal new insights of top-down modulation of bottom-up processes in auditory laterality. Front Behav Neurosci 15:802319

    Article  PubMed  Google Scholar 

  7. Laeng B, Flaaten CB, Walle KM et al (2021) “Mickey Mousing” in the brain: motion-sound synesthesia and the subcortical substrate of audio-visual integration. Front Hum Neurosci 15:605166

    Article  PubMed  PubMed Central  Google Scholar 

  8. Poldrack RA, Farah MJ (2015) Progress and challenges in probing the human brain. Nature 526:371–379

    Article  CAS  PubMed  Google Scholar 

  9. Ogawa S, Tank DW, Menon R et al (1992) Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci U S A 89:5951–5955

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Kwong KK, Belliveau JW, Chesler DA et al (1992) Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci U S A 89:5675–5679

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Clark VP (2012) A history of randomized task designs in fMRI. NeuroImage 62:1190–1194

    Article  PubMed  Google Scholar 

  12. Liu TT (2012) The development of event-related fMRI designs. NeuroImage 62:1157–1162

    Article  PubMed  Google Scholar 

  13. 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 34:537–541

    Article  CAS  PubMed  Google Scholar 

  14. Sharda M, Silani G, Specht K et al (2019) Music therapy for children with autism: investigating social behaviour through music. Lancet Child Adolesc Health 3:759–761

    Article  PubMed  Google Scholar 

  15. Smith SM, Fox PT, Miller KL et al (2009) Correspondence of the brain’s functional architecture during activation and rest. Proc Natl Acad Sci U S A 106:13040–13045

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Fox MD, Raichle ME (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 8:700–711

    Article  CAS  PubMed  Google Scholar 

  17. Damoiseaux JS, Rombouts SARB, Barkhof F et al (2006) Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci U S A 103:13848–13853

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Raichle ME (2015) The brain’s default mode network. Annu Rev Neurosci 38:433–447

    Article  CAS  PubMed  Google Scholar 

  19. Raichle ME, MacLeod AM, Snyder AZ et al (2001) A default mode of brain function. Proc Natl Acad Sci U S A 98:676–682

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Uddin LQ (2015) Salience processing and insular cortical function and dysfunction. Nat Rev Neurosci 16:55–61

    Article  CAS  PubMed  Google Scholar 

  21. Seeley WW, Menon V, Schatzberg AF et al (2007) Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci 27:2349–2356

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Noble S, Scheinost D, Constable RT (2019) A decade of test-retest reliability of functional connectivity: a systematic review and meta-analysis. NeuroImage 203:116157

    Article  PubMed  Google Scholar 

  23. Bennett CM, Miller MB (2010) How reliable are the results from functional magnetic resonance imaging? Ann N Y Acad Sci 1191:133–155

    Article  PubMed  Google Scholar 

  24. Botvinik-Nezer R, Holzmeister F, Camerer CF et al (2020) Variability in the analysis of a single neuroimaging dataset by many teams. Nature 582:84–88

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Rosen BR, Savoy RL (2012) fMRI at 20: has it changed the world? NeuroImage 62:1316–1324

    Article  PubMed  Google Scholar 

  26. Specht K (2019) Current challenges in translational and clinical fMRI and future directions. Front Psych 10:924

    Article  Google Scholar 

  27. Tian F, Wang J, Xu C et al (2018) Corrigendum: focusing on the differences of resting-state brain networks, using a data-driven approach to explore the functional neuroimaging characteristics of extraversion trait. Front Neurosci 12:380

    Article  PubMed  PubMed Central  Google Scholar 

  28. Dubois J, Galdi P, Han Y et al (2018) Resting-state functional brain connectivity best predicts the personality dimension of openness to experience. Personal Neurosci 1:E6

    Article  PubMed  PubMed Central  Google Scholar 

  29. Hjelmervik H, Hausmann M, Osnes B et al (2014) Resting states are resting traits--an FMRI study of sex differences and menstrual cycle effects in resting state cognitive control networks. PLoS One 9:e103492

    Article  PubMed  PubMed Central  Google Scholar 

  30. Sie J-H, Chen Y-H, Shiau Y-H, Chu W-C (2019) Gender- and age-specific differences in resting-state functional connectivity of the central autonomic network in adulthood. Front Hum Neurosci 13:369

    Article  PubMed  PubMed Central  Google Scholar 

  31. Baird A (2019) Sex in the brain: how seizures, strokes, dementia, tumors, and trauma can change your sex life. Columbia University Press, New York Chichester

    Google Scholar 

  32. Tooley UA, Mackey AP, Ciric R et al (2021) Erratum to: associations between neighborhood SES and functional brain network development. Cereb Cortex 31:2307

    Article  PubMed  Google Scholar 

  33. Bellucci G, Hahn T, Deshpande G, Krueger F (2019) Functional connectivity of specific resting-state networks predicts trust and reciprocity in the trust game. Cogn Affect Behav Neurosci 19:165–176

    Article  PubMed  Google Scholar 

  34. Cole DM, Smith SM, Beckmann CF (2010) Advances and pitfalls in the analysis and interpretation of resting-state FMRI data. Front Syst Neurosci 4:8

    PubMed  PubMed Central  Google Scholar 

  35. Dubois J, Adolphs R (2016) Building a science of individual differences from fMRI. Trends Cogn Sci 20:425–443

    Article  PubMed  PubMed Central  Google Scholar 

  36. Sjuls GS, Specht K (2021) Why blood pressure and body mass should be controlled for in resting-state functional magnetic resonance imaging studies. bioRxiv. https://doi.org/10.1101/2021.06.02.446721

  37. Wen Z, Hammoud MZ, Scott JC et al (2021) Impact of exogenous estradiol on task-based and resting-state neural signature during and after fear extinction in healthy women. Neuropsychopharmacology 46:2278–2287

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Zeidman P, Jafarian A, Corbin N et al (2019) A guide to group effective connectivity analysis, part 1: first level analysis with DCM for fMRI. NeuroImage 200:174–190

    Article  PubMed  Google Scholar 

  39. Friston KJ (2011) Functional and effective connectivity: a review. Brain Connect 1:13–36

    Article  PubMed  Google Scholar 

  40. Nilsson L-G, Bäckman L, Erngrund K et al (1997) The Betula prospective cohort study: memory, health, and aging. Aging Neuropsychol Cognit 4:1–32

    Article  Google Scholar 

  41. Salami A, Wåhlin A, Kaboodvand N et al (2016) Longitudinal evidence for dissociation of anterior and posterior MTL resting-state connectivity in aging: links to perfusion and memory. Cereb Cortex 26:3953–3963

    Article  PubMed  PubMed Central  Google Scholar 

  42. Lanka P, Deshpande G (2019) Combining Prospective Acquisition CorrEction (PACE) with retrospective correction to reduce motion artifacts in resting state fMRI data. Brain Behav 9:e01341

    Article  PubMed  PubMed Central  Google Scholar 

  43. Buxton RB (2013) The physics of functional magnetic resonance imaging (fMRI). Rep Prog Phys 76:096601

    Article  PubMed  PubMed Central  Google Scholar 

  44. Park B-Y, Park H, Morys F et al (2021) Inter-individual body mass variations relate to fractionated functional brain hierarchies. Commun Biol 4:735

    Article  PubMed  PubMed Central  Google Scholar 

  45. Wilmet G, Verlinde R, Vandevoorde J et al (2017) Correlation between Body Mass Index and abdominal circumference in Belgian adults: a cross-sectional study. Rom J Intern Med 55:28–35

    PubMed  Google Scholar 

  46. Ward PGD, Orchard ER, Oldham S et al (2020) Individual differences in haemoglobin concentration influence bold fMRI functional connectivity and its correlation with cognition. NeuroImage 221:117196

    Article  CAS  PubMed  Google Scholar 

  47. Murphy K, Birn RM, Bandettini PA (2013) Resting-state fMRI confounds and cleanup. NeuroImage 80:349–359

    Article  PubMed  Google Scholar 

  48. Tsvetanov KA, Henson RNA, Rowe JB (2021) Separating vascular and neuronal effects of age on fMRI BOLD signals. Philos Trans R Soc Lond Ser B Biol Sci 376:20190631

    Article  Google Scholar 

Download references

Acknowledgments

The study was financed by the Research Council of Norway (Project no. 276044: When Default is not Default: Solutions to the replication crisis and beyond). The data were provided by the Betula prospective cohort study, Umeå University, Sweden. The Betula Project is supported by Knut and Alice Wallenberg Foundation (KAW) and the Swedish Research Council (K2010-61X-21446-01).

Author information

Authors and Affiliations

  1. Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway

    Liucija Vaisvilaite, Meng-Yun Wang & Karsten Specht

  2. Mohn Medical and Imaging Visualization Centre, Haukeland University Hospital, Bergen, Norway

    Liucija Vaisvilaite, Meng-Yun Wang & Karsten Specht

  3. Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden

    Micael Andersson

  4. Department of Integrative Medical Biology, Umeå University, Umeå, Sweden

    Micael Andersson

  5. Department of Education, UiT/The Arctic University of Norway, Tromsø, Norway

    Karsten Specht

Authors
  1. Liucija Vaisvilaite
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Meng-Yun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Micael Andersson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Karsten Specht
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Liucija Vaisvilaite .

Editor information

Editors and Affiliations

  1. Division of Translational Neuroscience, Medical University of Plovdiv, Plovdiv, Bulgaria

    Drozdstoy Stoyanov

  2. University of Lausanne, CHUV, Lausanne, Switzerland

    Bogdan Draganski

  3. Pathophysiology and Transplantation, University of Milan, Milan, Italy

    Paolo Brambilla

  4. Cognitive & Affective Neuroscience Unit, University of Vienna, Vienna, Austria

    Claus Lamm

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Vaisvilaite, L., Wang, MY., Andersson, M., Specht, K. (2023). The Effect of Exogenous and Endogenous Parameters on Group Resting-State Effective Connectivity and BOLD Signal. In: Stoyanov, D., Draganski, B., Brambilla, P., Lamm, C. (eds) Computational Neuroscience. Neuromethods, vol 199. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3230-7_13

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-3230-7_13

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-3229-1

  • Online ISBN: 978-1-0716-3230-7

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation