Skip to main content
SpringerLink
Log in

Differences in brain activity between fast and slow responses on psychomotor vigilance task: an fNIRS study

  • Original Research
  • Published:
Brain Imaging and Behavior Aims and scope Submit manuscript

Abstract

Attention is a basic human function underlying every other cognitive process. It is demonstrated in the functional Magnetic Resonance Imaging literature that frontoparietal networks are involved with attentive performance while default mode networks are involved with inattentive performance. Yet, it is still not clear whether similar results would be found with functional Near-Infrared Spectroscopy. The goal of our study was to investigate differences in hemodynamic activity measured by functional Near-Infrared Spectroscopy between fast and slow responses on a simple sustained attention task both before and after stimulus onset. Thirty healthy adults took part in the study. Our results have shown differences between fast and slow responses only on channels over medial frontal cortex and inferior parietal cortex (p < 0,05). These differences were observed both before and after stimulus presentation. It is discussed that functional Near-Infrared Spectroscopy is a good tool to investigate the frontoparietal network and its relationship with performance in attention tasks; it could be used to further investigate other approaches on attention, such as the dual network model of cognitive control and brain states views based on complex systems analysis; and finally, it could be used to investigate attention in naturalistic settings.

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

Similar content being viewed by others

Data availability

Data and code will be soon public and available at Mendeley Data (Nogueira, 2021).

References

  • Arsintescu, L., Mulligan, J. B., & Flynn-Evans, E. E. (2017). Evaluation of a psychomotor vigilance task for touch screen devices. Human Factors, 59(4), 661–670.

    Article  Google Scholar 

  • Balardin, J. B., Zimeo Morais, G. A., Furucho, R. A., Trambaiolli, L., Vanzella, P., Biazoli, C., Jr., & Sato, J. R. (2017). Imaging brain function with functional near-infrared spectroscopy in unconstrained environments. Frontiers in Human Neuroscience, 11, 258.

    Article  Google Scholar 

  • Bogler, C., Mehnert, J., Steinbrink, J., & Haynes, J.-D. (2014). Decoding vigilance with NIRS. PLoS One, 9(7), e101729.

    Article  Google Scholar 

  • Borragán, G., Guerrero-Mosquera, C., Guillaume, C., Slama, H., & Peigneux, P. (2019). Decreased prefrontal connectivity parallels cognitive fatigue-related performance decline after sleep deprivation. An optical imaging study. Biological Psychology, 144, 115–124.

    Article  Google Scholar 

  • Brockington, G., Balardin, J. B., Zimeo Morais, G. A., Malheiros, A., Lent, R., Moura, L. M., & Sato, J. R. (2018). From the laboratory to the classroom: The potential of functional near-infrared spectroscopy in educational neuroscience. Frontiers in Psychology, 9, 1840.

    Article  Google Scholar 

  • Brown, H., Friston, K., & Bestmann, S. (2011). Active inference, attention, and motor preparation. Frontiers in Psychology, 2, 218.

    PubMed  PubMed Central  Google Scholar 

  • Brunia, C. H. (1993). Waiting in readiness: Gating in attention and motor preparation. Psychophysiology, 30(4), 327–339.

    Article  CAS  Google Scholar 

  • Carlisi, C. O., Norman, L., Murphy, C. M., Christakou, A., Chantiluke, K., Giampietro, V., Simmons, A., Brammer, M., Murphy, D. G., MRC AIMS Consortium, Mataix-Cols, D., & Rubia, K. (2017). Disorder-specific and shared brain abnormalities during vigilance in autism and obsessive-compulsive disorder. Biological Psychiatry. Cognitive Neuroscience and Neuroimaging, 2(8), 644–654.

    Article  Google Scholar 

  • Cope, M., & Delpy, D. T. (1988). System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination. Medical & Biological Engineering & Computing, 26(3), 289–294.

    Article  CAS  Google Scholar 

  • Coste, C. P., Sadaghiani, S., Friston, K. J., & Kleinschmidt, A. (2011). Ongoing brain activity fluctuations directly account for Intertrial and indirectly for Intersubject variability in Stroop task performance. Cerebral Cortex, 21(11), 2612–2619. https://doi.org/10.1093/cercor/bhr050

    Article  PubMed  Google Scholar 

  • Deco, G., Cruzat, J., Cabral, J., Tagliazucchi, E., Laufs, H., Logothetis, N. K., & Kringelbach, M. L. (2019). Awakening: Predicting external stimulation to force transitions between different brain states. Proceedings of the National Academy of Sciences of the United States of America, 116(36), 18088–18097.

    Article  CAS  Google Scholar 

  • Dinges, D. F., & Powell, J. W. (1985). Microcomputer analyses of performance on a portable, simple visual RT task during sustained operations. In Behavior Research Methods, Instruments, & Computers, 17(6), 652–655. https://doi.org/10.3758/bf03200977

    Article  Google Scholar 

  • Dosenbach, N. U. F., Visscher, K. M., Palmer, E. D., Miezin, F. M., Wenger, K. K., Kang, H. C., Burgund, E. D., Grimes, A. L., Schlaggar, B. L., & Petersen, S. E. (2006). A core system for the implementation of task sets. Neuron, 50(5), 799–812.

    Article  CAS  Google Scholar 

  • Dosenbach, N. U. F., Fair, D. A., Miezin, F. M., Cohen, A. L., Wenger, K. K., Dosenbach, R. A. T., Fox, M. D., Snyder, A. Z., Vincent, J. L., Raichle, M. E., Schlaggar, B. L., & Petersen, S. E. (2007). Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences of the United States of America, 104(26), 11073–11078.

    Article  CAS  Google Scholar 

  • Dosenbach, N. U. F., Fair, D. A., Cohen, A. L., Schlaggar, B. L., & Petersen, S. E. (2008). A dual-networks architecture of top-down control. Trends in Cognitive Sciences, 12(3), 99–105.

    Article  Google Scholar 

  • Drummond, S. P. A., Bischoff-Grethe, A., Dinges, D. F., Ayalon, L., Mednick, S. C., & Meloy, M. J. (2005). The neural basis of the psychomotor vigilance task. Sleep, 28(9), 1059–1068.

    PubMed  Google Scholar 

  • Fortenbaugh, F. C., DeGutis, J., & Esterman, M. (2017). Recent theoretical, neural, and clinical advances in sustained attention research. Annals of the New York Academy of Sciences, 1396(1), 70–91.

    Article  Google Scholar 

  • Hall, R. W., Huitt, T. W., Thapa, R., Williams, D. K., Anand, K. J. S., & Garcia-Rill, E. (2008). Long-term deficits of preterm birth: Evidence for arousal and attentional disturbances. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 119(6), 1281–1291.

    Article  Google Scholar 

  • Harrivel, A. R., Weissman, D. H., Noll, D. C., & Peltier, S. J. (2013). Monitoring attentional state with fNIRS. Frontiers in Human Neuroscience, 7, 861.

    Article  Google Scholar 

  • Hinds, O., Thompson, T. W., Ghosh, S., Yoo, J. J., Whitfield-Gabrieli, S., Triantafyllou, C., & Gabrieli, J. D. E. (2013). Roles of default-mode network and supplementary motor area in human vigilance performance: Evidence from real-time fMRI. Journal of Neurophysiology, 109(5), 1250–1258.

    Article  CAS  Google Scholar 

  • Hiroyasu, T., Fukushima, A., & Yokouchi, H. (2012). Differences in blood flow between auditory and visual stimuli in the Psychomotor Vigilance Task and GO/NOGO Task. Conference Proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2012, 1466–1469.

  • Hosomi, F., Yanagi, M., Kawakubo, Y., Tsujii, N., Ozaki, S., & Shirakawa, O. (2019). Capturing spontaneous activity in the medial prefrontal cortex using near-infrared spectroscopy and its application to schizophrenia. Scientific Reports, 9(1), 5283.

    Article  Google Scholar 

  • Hsu, Y.-F. (2005). On measuring the minimum detection time: A simple reaction time study in the time estimation paradigm. The British Journal of Mathematical and Statistical Psychology, 58(Pt 2), 259–284.

    Article  Google Scholar 

  • Huppert, T. J., Diamond, S. G., Franceschini, M. A., & Boas, D. A. (2009). HomER: A review of time-series analysis methods for near-infrared spectroscopy of the brain. Applied Optics, 48(10), D280–D298.

    Article  Google Scholar 

  • Jaipurkar, R., Mahapatra, S. S., Bobdey, S., & Banerji, C. (2019). Work-rest pattern, alertness and performance assessment among naval personnel deployed at sea: A cross sectional study. Armed Forces Medical Journal, India, 75(2), 158–163.

    Article  Google Scholar 

  • Khitrov, M. Y., Laxminarayan, S., Thorsley, D., Ramakrishnan, S., Rajaraman, S., Wesensten, N. J., & Reifman, J. (2014). PC-PVT: A platform for psychomotor vigilance task testing, analysis, and prediction. Behavior Research Methods, 46(1), 140–147.

    Article  Google Scholar 

  • Klem, G. H., Lüders, H. O., Jasper, H. H., & Elger, C. (1999). The ten-twenty electrode system of the international federation. The International Federation of Clinical Neurophysiology. Electroencephalography and Clinical Neurophysiology. Supplement, 52, 3–6.

    CAS  PubMed  Google Scholar 

  • Langner, R., & Eickhoff, S. B. (2013). Sustaining attention to simple tasks: A meta-analytic review of the neural mechanisms of vigilant attention. Psychological Bulletin, 139(4), 870–900. https://doi.org/10.1037/a0030694

    Article  PubMed  Google Scholar 

  • Lawrence, N. S., Ross, T. J., Hoffmann, R., Garavan, H., & Stein, E. A. (2003). Multiple neuronal networks mediate sustained attention. Journal of Cognitive Neuroscience, 15(7), 1028–1038.

    Article  Google Scholar 

  • Len-Carrin, J., & Len-Domnguez, U. (2012). Functional near-infrared spectroscopy (fNIRS): Principles and neuroscientific applications. Neuroimaging - Methods. https://doi.org/10.5772/23146

  • McHill, A. W., & Wright, K. P., Jr. (2019). Cognitive impairments during the transition to working at night and on subsequent night shifts. Journal of Biological Rhythms, 34(4), 432–446.

    Article  Google Scholar 

  • Morais, G. A. Z., Balardin, J. B., & Sato, J. R. (2018). fNIRS Optodes’ location decider (fOLD): A toolbox for probe arrangement guided by brain regions-of-interest. Scientific Reports, 8(1). https://doi.org/10.1038/s41598-018-21716-z.

  • Nordin, L. E., Möller, M. C., Julin, P., Bartfai, A., Hashim, F., & Li, T.-Q. (2016). Post mTBI fatigue is associated with abnormal brain functional connectivity. Scientific Report,s 6(1). https://doi.org/10.1038/srep21183.

  • Nozawa, T., Sugiura, M., Yokoyama, R., Ihara, M., Kotozaki, Y., Miyauchi, C. M., Kanno, A., & Kawashima, R. (2014). Ongoing activity in temporally coherent networks predicts intra-subject fluctuation of response time to sporadic executive control demands. PLoS One, 9(6), e99166.

    Article  Google Scholar 

  • Oken, B. S., Salinsky, M. C., & Elsas, S. M. (2006). Vigilance, alertness, or sustained attention: Physiological basis and measurement. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 117(9), 1885–1901.

    Article  CAS  Google Scholar 

  • Pinti, P., Tachtsidis, I., Hamilton, A., Hirsch, J., Aichelburg, C., Gilbert, S., & Burgess, P. W. (2020). The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience. Annals of the New York Academy of Sciences, 1464(1), 5–29.

    Article  Google Scholar 

  • Ponce-Alvarez, A., Mochol, G., Hermoso-Mendizabal, A., de la Rocha, J., & Deco, G. (n.d.). Cortical state transitions and stimulus response evolve along stiff and sloppy parameter dimensions, respectively. https://doi.org/10.1101/839365.

  • Raichle, M. E., & Snyder, A. Z. (2007). A default mode of brain function: A brief history of an evolving idea. NeuroImage, 37(4), 1083–1090. https://doi.org/10.1016/j.neuroimage.2007.02.041

    Article  PubMed  Google Scholar 

  • de Souza Rodrigues, J., Ribeiro, F. L., Sato, J. R., Mesquita, R. C., & Júnior, C. E. B. (2019). Identifying individuals using fNIRS-based cortical connectomes. Biomedical Optics Express, 10(6), 2889. https://doi.org/10.1364/boe.10.002889

    Article  PubMed  PubMed Central  Google Scholar 

  • Sturm, W., & Willmes, K. (2001). On the functional neuroanatomy of intrinsic and phasic alertness. NeuroImage, 14(1 Pt 2), S76–S84.

    Article  CAS  Google Scholar 

  • Xu Y., Graber H., Barbour R. (2016). nirsLAB user manual. Available online at: https://www.nitrc.org/frs/shownotes.php?release_id=2663

  • Yu, C., & Smith, L. B. (2016). The social origins of sustained attention in one-year-old human infants. Current Biology: CB, 26(9), 1235–1240.

    Article  CAS  Google Scholar 

Download references

Funding

The first author of this publication received funding from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001.

The second author of this publication thanks thanks the São Paulo Research Foundation (FAPESP) for the funding on the project number 2016/24951–2. And the fourth author of this publication thanks the same institution for the funding on the project number 2018/21934–5. AFB is supported by CNPq, grant number 314149/2018-0, and by BRAINN CEPID, FAPESP, Brazil.

Author information

Authors and Affiliations

  1. Center for Mathematics, Computation and Cognition, UFABC – Universidade Federal do ABC -SP, Avenida dos Estados, 5001, Bloco B, Sala 803, São Bernardo do Campo, Brazil

    Mateus G. Nogueira, Mateus Silvestrin, Cândida S. F. Barreto, João Ricardo Sato, Claudinei Biazoli & Abrahão F. Baptista

  2. Institute of Physics, University of Campinas, Campinas, Brazil

    Rickson C. Mesquita

Authors
  1. Mateus G. Nogueira
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mateus Silvestrin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Cândida S. F. Barreto
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. João Ricardo Sato
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rickson C. Mesquita
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Claudinei Biazoli
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Abrahão F. Baptista
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Author contributions included conception and study design (MGN, CEB, JRS, AFB), data collection or acquisition (MGN), statistical analysis (MGN, MS, CSFB), interpretation of results (MGN, CEB, JRS, RCM, AFB), drafting the manuscript work or revising it critically for important intellectual content (MGN, CEB, RCM, AFB) and approval of final version to be published and agreement to be accountable for the integrity and accuracy of all aspects of the work (All authors).

Corresponding author

Correspondence to Abrahão F. Baptista.

Ethics declarations

Ethics approval

The present work was carried out in accordance with the Declaration of Helsinki. It was submitted to the UFABC ethical committee (CAAE: 846099318.0.0000.5594) and has been approved (number: 2.754.496).

Consent to participate

All participants signed a freely given, informed consent to participate term. This term was previously approved by the aforementioned committee.

Consent to publish

This work does not include materials from participants that require consent to publish.

Conflict of interest

We have no conflict of interest to disclose.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

ESM 1

(DOCX 407 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nogueira, M.G., Silvestrin, M., Barreto, C.S.F. et al. Differences in brain activity between fast and slow responses on psychomotor vigilance task: an fNIRS study. Brain Imaging and Behavior 16, 1563–1574 (2022). https://doi.org/10.1007/s11682-021-00611-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11682-021-00611-8

Keywords

Search

Navigation