Electroencephalography theta/beta ratio covaries with mind wandering and functional connectivity in the executive control network

Dana van Son, Mischa de Rover, Frances M De Blasio, Willem van der Does, Robert J Barry, Peter Putman, Dana van Son, Mischa de Rover, Frances M De Blasio, Willem van der Does, Robert J Barry, Peter Putman

Abstract

The ratio between frontal resting-state electroencephalography (EEG) theta and beta frequency power (theta/beta ratio, TBR) is negatively related to cognitive control. It is unknown which psychological processes during resting state account for this. Increased theta and reduced beta power are observed during mind wandering (MW), and MW is related to decreased connectivity in the executive control network (ECN) and increased connectivity in the default mode network (DMN). The goal of this study was to test if MW-related fluctuations in TBR covary with such functional variation in ECN and DMN connectivity and if this functional variation is related to resting-state TBR. Data were analyzed for 26 participants who performed a 40-min breath-counting task and reported the occurrence of MW episodes while EEG was measured and again during magnetic resonance imaging. Frontal TBR was higher during MW than controlled thought and this was marginally related to resting-state TBR. DMN connectivity was higher and ECN connectivity was lower during MW. Greater ECN connectivity during focus than MW was correlated to lower TBR during focus than MW. These results provide the first evidence of the neural correlates of TBR and its functional dynamics and further establish TBR's usefulness for the study of executive control, in normal and potentially abnormal psychology.

Keywords: EEG; controlled thought; default mode network; executive control; mind wandering.

Conflict of interest statement

The authors declare no competing interests.

© 2019 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

Figures

Figure 1
Figure 1
ERSP spectral plot of the frontal average (across F3, Fz, and F4 sites) at 1‐Hz frequency resolution and 62.5 ms time resolution. Rectangular frames highlight the epochs of primary interest corresponding to the two “real time” 2‐TR epochs that fall within the predefined periods for MW and focused attention (the upper high‐frequency frames are for beta and the lower are for theta).
Figure 2
Figure 2
Slopes of normalized functional connectivity over time for the executive control network (ECN) and the default mode network (DMN). Rectangular frames highlight the epochs of interest. After correction for the HRF delay, the button press occurs at 6 seconds. The y‐axis shows the demeaned beta values resulting from the first stage of the dual regression, representing functional connectivity.
Figure 3
Figure 3
Scatterplot of the significant relation between the MW‐related changes in frontal EEG theta/beta ratio (TBR; x‐axis) and the corresponding changes in ECN functional connectivity (y‐axis); r(23) = −0.58, P = 0.002. Spearman's ranked order correlation (insensitive to outliers) was also significant; Spearman's r(23) = −0.54, P = 0.006. The plot shows log‐transformed data.

References

    1. Lubar, J.F. 1991. Discourse on the development of EEG diagnostics and biofeedback for attention‐deficit/hyperactivity disorders. Biofeedback Self Regul. 16: 201–225.
    1. Arns, M. , Conners C.K. & Kraemer H.C.. 2013. A decade of EEG theta/beta ratio research in ADHD: a meta‐analysis. J. Atten. Disord. 17: 374–383.
    1. Barry, R.J. , Clarke A.R. & Johnstone S.J.. 2003. A review of electrophysiology in attention‐deficit/hyperactivity disorder: I. Qualitative and quantitative electroencephalography. Clin. Neurophysiol. 114: 171–183.
    1. Barry, R.J. , Clarke A.R., Johnstone S.J., et al 2009. Electroencephalogram θ/β ratio and arousal in attention‐deficit/hyperactivity disorder: evidence of independent processes. Biol. Psychiatry 66: 398–401.
    1. Clarke, A.R . et al 2007. Coherence in children with attention‐deficit/hyperactivity disorder and excess beta activity in their EEG. Clin. Neurophysiol. 118: 1472–1479.
    1. Loo, S.K. , Teale P.D. & Reite M.L.. 1999. EEG correlates of methylphenidate response among children with ADHD: a preliminary report. Biol. Psychiatry 45: 1657–1660.
    1. Loo, S.K. , Lenartowicz A. & Makeig S.. 2016. Research review: use of EEG biomarkers in child psychiatry research—current state and future directions. J. Child Psychol. Psychiatry 57: 4–17.
    1. Arnsten, A.F.T. 2006. Stimulants: therapeutic actions in ADHD. Neuropsychopharmacology 31: 2376–2383.
    1. Bush, G. 2011. Frontal, and parietal cortical dysfunction in attention‐deficit/hyperactivity disorder. Biol. Psychiatry 69: 1160–1167.
    1. Putman, P. , van Peer J., Maimari I. & van der Werff S.. 2010. EEG theta/beta ratio in relation to fear‐modulated response‐inhibition, attentional control, and affective traits. Biol. Psychol. 83: 73–78.
    1. Tortella‐Feliu, M. et al 2014. Spontaneous EEG activity and spontaneous emotion regulation. Int. J. Psychophysiol. 94: 365–372.
    1. Putman, P. , Verkuil B., Arias‐Garcia E., et al 2014. EEG theta/beta ratio as a potential biomarker for attentional control and resilience against deleterious effects of stress on attention. Cogn. Affect. Behav. Neurosci. 14: 782–791.
    1. Angelidis, A. , van der Does W., Schakel L. & Putman P.. 2016. Frontal EEG theta/beta ratio as an electrophysiological marker for attentional control and its test‐retest reliability. Biol. Psychol. 121(Pt A): 49–52.
    1. van Son, D. , Putman P., Angelidis A., et al 2018. Early and late dot‐probe attentional bias to mild and high threat pictures: relations with EEG theta/beta ratio, self‐reported trait attentional control, and trait anxiety. Psychophysiology 55: e13274.
    1. Angelidis, A. , Hagenaars M., van Son D., et al 2018. Do not look away! Spontaneous frontal EEG theta/beta ratio as a marker for cognitive control over attention to mild and high threat. Biol. Psychol. 135: 8–17.
    1. van Son, D . et al 2018. Acute effects of caffeine on threat‐selective attention: moderation by anxiety and EEG theta/beta ratio. Biol. Psychol. 136: 100–110.
    1. Keune, P.M. et al 2017. Exploring resting‐state EEG brain oscillatory activity in relation to cognitive functioning in multiple sclerosis. Clin. Neurophysiol. 128: 1746–1754.
    1. Schutter, D.J.L.G. & Van Honk J.. 2005. Electrophysiological ratio markers for the balance between reward and punishment. Brain Res. Cogn. Brain Res. 24: 685–690.
    1. Massar, S. , Rossi V., Schutter D.J.L.G. & Kenemans J.L.. 2012. Baseline EEG theta/beta ratio and punishment sensitivity as biomarkers for feedback‐related negativity (FRN) and risk‐taking. Clin. Neurophysiol. 123: 1958–1965.
    1. Massar, S. , Kenemans J.L. & Schutter D.J.L.G.. 2014. Resting‐state EEG theta activity and risk learning: sensitivity to reward or punishment? Int. J. Psychophysiol. 91: 172–177.
    1. Schutter, D.J.L.G. & Van Honk J.. 2004. Decoupling of midfrontal delta‐beta oscillations after testosterone administration. Int. J. Psychophysiol. 53: 71–73.
    1. Sari, B.A. , Koster E.H.W., Pourtois G. & Derakshan N.. 2016. Training working memory to improve attentional control in anxiety: a proof‐of‐principle study using behavioral and electrophysiological measures. Biol. Psychol. 121(Pt B): 203–212.
    1. Ottaviani, C. et al 2015. Cognitive, behavioral, and autonomic correlates of mind wandering and perseverative cognition in major depression. Front. Neurosci. 8: 433.
    1. McVay, J.C. & Kane M.J.. 2009. Conducting the train of thought: working memory capacity, goal neglect, and mind wandering in an executive‐control task. J. Exp. Psychol. Learn. Mem. Cogn. 35: 196–204.
    1. Unsworth, N. & McMillan B.D.. 2014. Similarities and differences between mind‐wandering and external distraction: a latent variable analysis of lapses of attention and their relation to cognitive abilities. Acta Psychol. (Amst.) 150: 14–25.
    1. Baumeister, R.F. & Masicampo E.J.. 2010. Conscious thought is for facilitating social and cultural interactions: how mental simulations serve the animal‐culture interface. Psychol. Rev. 117: 945–971.
    1. Baumeister, R. , Masicampo E.J. & Vohs K.. 2011. Do conscious thoughts cause behavior? Annu. Rev. Psychol. 62: 331–361.
    1. Baird, B . et al 2012. Inspired by distraction: mind wandering facilitates creative incubation. Psychol. Sci. 23: 1117–1122.
    1. Ruby, F.J.M. , Smallwood J., Engen H. & Singer T.. 2013. How self‐generated thought shapes mood—the relation between mind‐wandering and mood depends on the socio‐temporal content of thoughts. PLoS One 8: e77554.
    1. Smallwood, J. & Schooler J.W.. 2006. The restless mind. Psychol. Bull. 132: 946–958.
    1. Smallwood, J. , Nind L. & O'Connor R.C.. 2009. When is your head at? An exploration of the factors associated with the temporal focus of the wandering mind. Conscious. Cogn. 18: 118–125.
    1. Stawarczyk, D. , Majerus S., Maquet P. & D'Argembeau A.. 2011. Neural correlates of ongoing conscious experience: both task‐unrelatedness and stimulus‐independence are related to default network activity. PLoS One 6: e16997.
    1. Braboszcz, C. & Delorme A.. 2011. Lost in thoughts: neural markers of low alertness during mind wandering. Neuroimage 54: 3040–3047.
    1. van Son, D. et al 2019. Frontal EEG theta/beta ratio during mind wandering episodes. Biol. Psychol. 140: 19–27.
    1. Hasenkamp, W. , Wilson‐Mendenhall C.D., Duncan E. & Barsalou L.W.. 2012. Mind wandering and attention during focused meditation: a fine‐grained temporal analysis of fluctuating cognitive states. Neuroimage 59: 750–760.
    1. Ward, A.M . et al 2014. The parahippocampal gyrus links the default‐mode cortical network with the medial temporal lobe memory system. Hum. Brain Mapp. 35: 1061–1073.
    1. Greicius, M.D. , Krasnow B., Reiss A.L. & Menon V.. 2003. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc. Natl. Acad. Sci. USA 100: 253–258.
    1. Karapanagiotidis, T. , Bernhardt B.C., Jefferies E. & Smallwood J.. 2017. Tracking thoughts: exploring the neural architecture of mental time travel during mind‐wandering. Neuroimage 147: 272–281.
    1. Smallwood, J. , Beach E., Schooler J.W. & Handy T.C.. 2008. Going AWOL in the brain: mind wandering reduces cortical analysis of external events. J. Cogn. Neurosci. 20: 458–469.
    1. Christoff, K. , Ream J.M., Geddes L.P.T. & Gabrieli J.D.E.. 2003. Evaluating self‐generated information: anterior prefrontal contributions to human cognition. Behav. Neurosci. 117: 1161–1168.
    1. Delaveau, P . et al 2017. Default mode and task‐positive networks connectivity during the N‐Back task in remitted depressed patients with or without emotional residual symptoms. Hum. Brain Mapp. 38: 3491–3501.
    1. Seeley, W.W. et al 2007. Dissociable intrinsic connectivity networks for salience processing and executive control. J. Neurosci. 27: 2349–2356.
    1. Mazoyer, B . et al 2001. Cortical networks for working memory and executive functions sustain the conscious resting state in man. Brain Res. Bull. 54: 287–298.
    1. Corbetta, M. & Shulman G.L.. 2002. Control of goal‐directed and stimulus‐driven attention in the brain. Nat. Rev. Neurosci. 3: 201–215.
    1. Corbetta, M. , Patel G. & Shulman G.L.. 2008. The reorienting system of the human brain: from environment to theory of mind. Neuron 58: 306–324.
    1. Spielberger, C.D. , Gorsuch R.L. & Lushene R.E.. 1970. STAI manual for the state‐trait anxiety inventory. Self‐Evaluation Questionnaire. Palo Alto, CA: Consulting Psychologists Press.
    1. Derryberry, D. & Reed M.A.. 2002. Anxiety‐related attentional biases and their regulation by attentional control. J. Abnorm. Psychol. 111: 225–236.
    1. Gratton, G. , Coles M.G.H. & Donchin E.. 1983. A new method for off‐line removal of ocular artifact. Electroencephalogr. Clin. Neurophysiol. 55: 468–484.
    1. Delorme, A. & Makeig S.. 2004. EEGLAB: an open source toolbox for analysis of single‐trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134: 9–21.
    1. Beckmann, C. , Mackay C., Filippini N. & Smith S.. 2009. Group comparison of resting‐state FMRI data using multi‐subject ICA and dual regression. Neuroimage 47(Suppl. 1). 10.1016/S1053-8119(09)71511-3
    1. Smith, S.M . et al 2009. Correspondence of the brain's functional architecture during activation and rest. Proc. Natl. Acad. Sci. USA 106: 13040–13045.
    1. Nešlehová, J. 2007. On rank correlation measures for non‐continuous random variables. J. Multivar. Anal. 98: 544–567.
    1. Daniel, R.S. 1967. Alpha and theta EEG in vigilance. Percept. Mot. Skills 25: 697–703.
    1. Belyavin, A. & Wright N.A.. 1987. Changes in electrical activity of the brain with vigilance. Electroencephalogr. Clin. Neurophysiol. 66: 137–144.
    1. Brown, P. 2007. Abnormal oscillatory synchronisation in the motor system leads to impaired movement. Curr. Opin. Neurobiol. 17: 656–664.
    1. Engel, A.K. & Fries P.. 2010. Beta‐band oscillations‐signalling the status quo? Curr. Opin. Neurobiol. 20: 156–165.
    1. Baker, S.N. 2007. Oscillatory interactions between sensorimotor cortex and the periphery. Curr. Opin. Neurobiol. 17: 649–655.
    1. Jenkinson, N. & Brown P.. 2011. New insights into the relationship between dopamine, beta oscillations and motor function. Trends Neurosci. 34: 611–618.
    1. Jensen, O. & Lisman J.E.. 2005. Hippocampal sequence‐encoding driven by a cortical multi‐item working memory buffer. Trends Neurosci. 28: 67–72.
    1. Rosanova, M. et al 2009. Natural frequencies of human corticothalamic circuits. J. Neurosci. 29: 7679–7685.
    1. Vázquez Marrufo, M. , Vaquero E., Cardoso M.J. & Gómez C.M.. 2001. Temporal evolution of α and β bands during visual spatial attention. Cogn. Brain Res. 12: 315–320.
    1. Wróbel, A. 2000. Beta activity: a carrier for visual attention. Acta Neurobiol. Exp. (Wars) 60: 247–260.
    1. Valentino, D.A. , Arruda J.E. & Gold S.M.. 1993. Comparison of QEEG and response accuracy in good vs poorer performers during a vigilance task. Int. J. Psychophysiol. 15: 123–133.
    1. Mason, M.F . et al 2007. Wandering minds: the default network and stimulus‐independent thought. Science 315: 393–395.
    1. Smallwood, J. 2013. Distinguishing how from why the mind wanders: a process‐occurrence framework for self‐generated mental activity. Psychol. Bull. 139: 519–535.
    1. Klimesch, W. , Sauseng P. & Hanslmayr S.. 2007. EEG alpha oscillations: the inhibition‐timing hypothesis. Brain Res. Rev. 53: 63–88.
    1. Wolfe, C.D. & Bell M.A.. 2004. Working memory and inhibitory control in early childhood: contributions from physiology, temperament, and language. Dev. Psychobiol. 44: 68–83.
    1. Miyake, A. et al 2000. The unity and diversity of executive functions and their contributions to complex ‘frontal lobe’ tasks: a latent variable analysis. Cogn. Psychol. 41: 49–100.
    1. Knyazev, G.G. 2007. Motivation, emotion, and their inhibitory control mirrored in brain oscillations. Neurosci. Biobehav. Rev. 31: 377–395
    1. Bishop, S.J. 2008. Neural mechanisms underlying selective attention to threat. Ann. N.Y. Acad. Sci. 1129: 141–152.
    1. Schutter, D.J.L.G. & Knyazev G.G.. 2012. Cross‐frequency coupling of brain oscillations in studying motivation and emotion. Motiv. Emot. 36: 46–54.
    1. Arnsten, A.F.T. 2009. Stress signalling pathways that impair prefrontal cortex structure and function. Nat. Rev. Neurosci. 10: 410–422.
    1. Cools, R. & D'Esposito M.. 2011. Inverted‐U‐shaped dopamine actions on human working memory and cognitive control. Biol. Psychiatry 69: e113–e125
    1. Mogg, K. & Bradley B.P.. 1998. A cognitive‐motivational analysis of anxiety. Behav. Res. Ther. 36: 809–848.
    1. Mogg, K. & Bradley B.P.. 2016. Anxiety and attention to threat: cognitive mechanisms and treatment with attention bias modification. Behav. Res. Ther. 87: 76–108.
    1. Hermans, E.J. , Henckens M.J.A.G., Joëls M. & Fernández G.. 2014. Dynamic adaptation of large‐scale brain networks in response to acute stressors. Trends Neurosci. 37: 304–314.
    1. Rood, L. , Roelofs J., Bögels S.M., et al 2009. The influence of emotion‐focused rumination and distraction on depressive symptoms in non‐clinical youth: a meta‐analytic review. Clin. Psychol. Rev. 29: 607–616.
    1. Brosschot, J.F. , Gerin W. & Thayer J.F.. 2006. The perseverative cognition hypothesis: a review of worry, prolonged stress‐related physiological activation, and health. J. Psychosom. Res. 60: 113–124.
    1. Hirsch, C.R. & Mathews A.. 2012. A cognitive model of pathological worry. Behav. Res. Ther. 50: 636–646.
    1. Morillas‐Romero, A. , Tortella‐Feliu M., Bornas X. & Putman P.. 2015. Spontaneous EEG theta/beta ratio and delta–beta coupling in relation to attentional network functioning and self‐reported attentional control. Cogn. Affect. Behav. Neurosci. 15: 598–606.
    1. Clarke, A.R. , Barry R.J., McCarthy R. & Selikowitz M.. 2001. EEG‐defined subtypes of children with attention‐deficit/hyperactivity disorder. Clin. Neurophysiol. 112: 2098–2105.
    1. Wischnewski, M. , Zerr P. & Schutter D.J.L.G.. 2016. Effects of theta transcranial alternating current stimulation over the frontal cortex on reversal learning. Brain Stimul. 9: 705–711.
    1. Jap, B.T. , Lal S., Fischer P. & Bekiaris E.. 2009. Using EEG spectral components to assess algorithms for detecting fatigue. Expert Syst. Appl. 36: 2352–2359.
    1. Lorist, M.M. et al 2009. The influence of mental fatigue and motivation on neural network dynamics; an EEG coherence study. Brain Res. 1270: 95–106.
    1. Yordanova, J. , Rosso O.A. & Kolev V.. 2003. A transient dominance of theta event‐related brain potential component characterizes stimulus processing in an auditory oddball task. Clin. Neurophysiol. 114: 529–540.
    1. Hollins, M. et al 2009. Perceived intensity and unpleasantness of cutaneous and auditory stimuli: an evaluation of the generalized hypervigilance hypothesis. Pain 141: 215–221.
    1. Weymar, M. , Keil A. & Hamm A.O.. 2014. Timing the fearful brain: unspecific hypervigilance and spatial attention in early visual perception. Soc. Cogn. Affect. Neurosci. 9: 723–729.

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