mind blanking; resting state; experience sampling; mental content; functional connectivity
Abstract :
[en] Mind blanking (MB) is a waking state during which we do not report any mental content. The phenomenology of MB challenges the view of a constantly thinking mind. Here, we comprehensively characterize the MB’s neurobehavioral profile with the aim to delineate its role during ongoing mentation. Using functional MRI experience sampling, we show that the reportability of MB is less frequent, faster, and with lower transitional dynamics than other mental states, pointing to its role as a transient mental relay. Regarding its neural underpinnings, we observed higher global signal amplitude during MB reports, indicating a distinct physiological state. Using the time-varying functional connectome, we show that MB reports can be classified with high accuracy, suggesting that MB has a unique neural composition. Indeed, a pattern of global positive-phase coherence shows the highest similarity to the connectivity patterns associated with MB reports. We interpret this pattern’s rigid signal architecture as hindering content reportability due to the brain’s inability to differentiate signals in an informative way. Collectively, we show that MB has a unique neurobehavioral profile, indicating that nonreportable mental events can happen during wakefulness. Our results add to the characterization of spontaneous mentation and pave the way for more mechanistic investigations of MB’s phenomenology.
Disciplines :
Neurosciences & behavior
Author, co-author :
Mortaheb, Sepehr ; Université de Liège - ULiège > GIGA Consciousness - Physiology of Cognition
Van Calster, Laurens ; Université de Liège - ULiège > Département de Psychologie > Département de Psychologie
Majerus, Steve ; Université de Liège - ULiège > Département de Psychologie > Département de Psychologie
Van De Ville, Dimitri
Demertzi, Athina ; Université de Liège - ULiège > GIGA Consciousness - Physiology of Cognition
Language :
English
Title :
Mind blanking is a distinct mental state linked to a recurrent brain profile of globally positive connectivity during ongoing mentation
Publication date :
04 October 2022
Journal title :
Proceedings of the National Academy of Sciences of the United States of America
ISSN :
0027-8424
eISSN :
1091-6490
Publisher :
National Academy of Sciences, Washington, United States - District of Columbia
Volume :
119
Issue :
41
Pages :
e2200511119
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique COST - European Cooperation in Science and Technology
Funding text :
This work was supported by the Belgian Fund for Scientific Research (FNRS). S. Mortaheb is a research fellow, A. Demertzi is a research associate, and S. Majerus is a research director at the FNRS. We also thank Dr. Matthieu Koroma, Dr. Camilo Miguel Signorelli, and Mr. Larry D. Fort for proofreading and editing the manuscript. This article is based upon work from COST Action CA18106, supported by COST (European Cooperation in Science and Technology).
Preprocessed functional data at the level of ROI time series can be freely downloaded from: https://osf.io/ 3vqb6/download. The raw data are also freely available in BIDS format from: https://openneuro.org/datasets/ds004134/versions/1.0.0. All the preprocessing and analysis codes are freely available on GitLab: https://gitlab.uliege.be/S.Mortaheb/mind_blanking.
J. Smallwood et al., The neural correlates of ongoing conscious thought. iScience 24, 102132 (2021).
K. Christoff, Z. C. Irving, K. C. R. Fox, R. N. Spreng, J. R. Andrews-Hanna, Mind-wandering as spontaneous thought: A dynamic framework. Nat. Rev. Neurosci. 17, 718–731 (2016).
L. Van Calster, A. D’Argembeau, E. Salmon, F. Peters, S. Majerus, Fluctuations of attentional networks and default mode network during the resting state reflect variations in cognitive states: Evidence from a novel resting-state experience sampling method. J. Cogn. Neurosci. 29, 95–113 (2017).
T. Karapanagiotidis, B. C. Bernhardt, E. Jefferies, J. Smallwood, Tracking thoughts: Exploring the neural architecture of mental time travel during mind-wandering. Neuroimage 147, 272–281 (2017).
A. Turnbull et al., Left dorsolateral prefrontal cortex supports context-dependent prioritisation of off-task thought. Nat. Commun. 10, 3816 (2019).
A. F. Ward, D. M. Wegner, Mind-blanking: When the mind goes away. Front. Psychol. 4, 650 (2013).
T. Kawagoe, K. Onoda, S. Yamaguchi, The neural correlates of “mind blanking”: When the mind goes away. Hum. Brain Mapp. 40, 4934–4940 (2019).
T. Andrillon et al., Does the mind wander when the brain takes a break? Local sleep in wakefulness, attentional lapses and mind-wandering. Front. Neurosci. 13, 949 (2019).
T. Andrillon, A. Burns, T. Mackay, J. Windt, N. Tsuchiya, Predicting lapses of attention with sleep-like slow waves. Nat. Commun. 12, 3657 (2021).
J. W. Schooler, E. D. Reichle, D. V. Halpern, “Zoning out while reading” in Thinking and Seeing: Visual Metacognition in Adults and Children, D. T. Levin, Ed. (MIT Press, 2004), pp. 203–226.
T. Kawagoe, K. Onoda, S. Yamaguchi, Different pre-scanning instructions induce distinct psychological and resting brain states during functional magnetic resonance imaging. Eur. J. Neurosci. 47, 77–82 (2018).
U. Winter et al., Content-free awareness: EEG-fcMRI correlates of consciousness as Such in an expert meditator. Front. Psychol. 10, 3064 (2020).
J. Li et al., Global signal regression strengthens association between resting-state functional connectivity and behavior. Neuroimage 196, 126–141 (2019).
K. Murphy, M. D. Fox, Towards a consensus regarding global signal regression for resting state functional connectivity MRI. Neuroimage 154, 169–173 (2017).
M. L. Sch€olvinck, A. Maier, F. Q. Ye, J. H. Duyn, D. A. Leopold, Neural basis of global resting-state fMRI activity. Proc. Natl. Acad. Sci. U.S.A. 107, 10238–10243 (2010).
A. Demertzi, et al., Human consciousness is supported by dynamic complex patterns of brain signal coordination. Sci. Adv. 5, eaat7603 (2019).
N. Leonardi et al., Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest. Neuroimage 83, 937–950 (2013).
J. S. Anderson et al., Network anticorrelations, global regression, and phase-shifted soft tissue correction. Hum. Brain Mapp. 32, 919–934 (2011).
K. Murphy, R. M. Birn, D. A. Handwerker, T. B. Jones, P. A. Bandettini, The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced? Neuroimage 44, 893–905 (2009).
H. Xu et al., Impact of global signal regression on characterizing dynamic functional connectivity and brain states. Neuroimage 173, 127–145 (2018).
D. Stawarczyk, A. D’Argembeau, Conjoint influence of mind-wandering and sleepiness on task performance. J. Exp. Psychol. Hum. Percept. Perform. 42, 1587–1600 (2016).
D. Stawarczyk, C. François, J. Wertz, A. D’Argembeau, Drowsiness or mind-wandering? Fluctuations in ocular parameters during attentional lapses. Biol. Psychol. 156, 107950 (2020).
N. Unsworth, M. K. Robison, Pupillary correlates of lapses of sustained attention. Cogn. Affect. Behav. Neurosci. 16, 601–615 (2016).
M. A. Pitts, L. A. Lutsyshyna, S. A. Hillyard, The relationship between attention and consciousness: An expanded taxonomy and implications for ‘no-report’ paradigms. Philos. Trans. R. Soc. Lond. B Biol. Sci. 373, 20170348 (2018).
C. Van den Driessche et al., Attentional lapses in attention-deficit/hyperactivity disorder: Blank rather than wandering thoughts. Psychol. Sci. 28, 1375–1386 (2017).
A. Fornito, B. J. Harrison, A. Zalesky, J. S. Simons, Competitive and cooperative dynamics of large-scale brain functional networks supporting recollection. Proc. Natl. Acad. Sci. U.S.A. 109, 12788–12793 (2012).
F. N. Watts, A. K. MacLeod, L. Morris, Associations between phenomenal and objective aspects of concentration problems in depressed patients. Br. J. Psychol. 79, 241–250 (1988).
M. Fukunaga et al., Large-amplitude, spatially correlated fluctuations in BOLD fMRI signals during extended rest and early sleep stages. Magn. Reson. Imaging 24, 979–992 (2006).
G. Nilsonne et al., Intrinsic brain connectivity after partial sleep deprivation in young and older adults: Results from the Stockholm Sleepy Brain study. Sci. Rep. 7, 9422 (2017).
C. W. Wong, V. Olafsson, O. Tal, T. T. Liu, The amplitude of the resting-state fMRI global signal is related to EEG vigilance measures. Neuroimage 83, 983–990 (2013).
X. Liu et al., Arousal transitions in sleep, wakefulness, and anesthesia are characterized by an orderly sequence of cortical events. Neuroimage 116, 222–231 (2015).
X. Liu et al., Subcortical evidence for a contribution of arousal to fMRI studies of brain activity. Nat. Commun. 9, 395 (2018).
P. Barttfeld et al., Signature of consciousness in the dynamics of resting-state brain activity. Proc. Natl. Acad. Sci. U.S.A. 112, 887–892 (2015).
F. Aedo-Jury, M. Schwalm, L. Hamzehpour, A. Stroh, Brain states govern the spatio-temporal dynamics of resting-state functional connectivity. eLife 9, 1–23 (2020).
M. El-Baba et al., Functional connectivity dynamics slow with descent from wakefulness to sleep. PLoS One 14, e0224669 (2019).
V. V. Vyazovskiy et al., Local sleep in awake rats. Nature 472, 443–447 (2011).
M. C. D. Bridi et al., Daily oscillation of the excitation–inhibition balance in visual cortical circuits. Neuron 105, 621–629.e4 (2020).
S. Dehaene, J. P. Changeux, L. Naccache, J. Sackur, C. Sergent, Conscious, preconscious, and subliminal processing: A testable taxonomy. Trends Cogn. Sci. 10, 204–211 (2006).
C. Sergent, S. Dehaene, Neural processes underlying conscious perception: Experimental findings and a global neuronal workspace framework. J. Physiol. Paris 98, 374–384 (2004).
S. Dehaene, C. Sergent, J. P. Changeux, A neuronal network model linking subjective reports and objective physiological data during conscious perception. Proc. Natl. Acad. Sci. U.S.A. 100, 8520–8525 (2003).
G. Tononi, Consciousness as integrated information: A provisional manifesto. Biol. Bull. 215, 216–242 (2008).
H. Blumenfeld, Impaired consciousness in epilepsy. Lancet Neurol. 11, 814–826 (2012).
J. R. Searle, Consciousness. Annu. Rev. Neurosci. 23, 557–578 (2000).
R. E. Nisbett, T. D. Wilson, Telling more than we can know: Verbal reports on mental processes. Psychol. Rev. 84, 231–259 (1977).
Y. Weinstein, H. J. De Lima, T. van der Zee, Are you mind-wandering, or is your mind on task? The effect of probe framing on mind-wandering reports. Psychon. Bull. Rev. 25, 754–760 (2018).
B. Thirion et al., Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses. Neuroimage 35, 105–120 (2007).
C. J. Anderson, J. Verkuilen, T. R. Johnson, Applied Generalized Linear Mixed Models: Continuous and Discrete Data (Springer, 2010).
K. Gorgolewski et al., Nipype: A flexible, lightweight and extensible neuroimaging data processing framework in python. Front. Neuroinform. 5, 13 (2011).
W. D. Penny, K. J. Friston, J. T. Ashburner, S. J. Kiebel, T. E. Nichols, Statistical Parametric Mapping: The Analysis of Functional Brain Images (Elsevier, 2011).
M. Jenkinson, C. F. Beckmann, T. E. J. Behrens, M. W. Woolrich, S. M. Smith, FSL. Neuroimage 62, 782–790 (2012).
R. W. Cox, AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29, 162–173 (1996).
S. M. Smith, Fast robust automated brain extraction. Hum. Brain Mapp. 17, 143–155 (2002).
J. D. Power et al., Methods to detect, characterize, and remove motion artifact in resting state fMRI. Neuroimage 84, 320–341 (2014).
A. Schaefer et al., Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI. Cereb. Cortex 28, 3095–3114 (2018).
J. D. Power, M. Plitt, T. O. Laumann, A. Martin, Sources and implications of whole-brain fMRI signals in humans. Neuroimage 146, 609–625 (2017).
C. Chang, G. H. Glover, Time-frequency dynamics of resting-state brain connectivity measured with fMRI. Neuroimage 50, 81–98 (2010).
D. C. Zhu, T. Tarumi, M. A. Khan, R. Zhang, Vascular coupling in resting-state fMRI: Evidence from multiple modalities. J. Cereb. Blood Flow Metab. 35, 1910–1920 (2015).
N. Colenbier et al., Disambiguating the role of blood flow and global signal with partial information decomposition. Neuroimage 213, 116699 (2020).
H. J. Aizenstein et al., The BOLD hemodynamic response in healthy aging. J. Cogn. Neurosci. 16, 786–793 (2004).
M. Sormaz et al., Default mode network can support the level of detail in experience during active task states. Proc. Natl. Acad. Sci. U.S.A. 115, 9318–9323 (2018).
S. Mortaheb et al., Experience Sampling in Resting State. OpenNeuro. https://openneuro.org/datasets/ds004134/versions/1.0.0. Deposited 27 May 2022.
S. Mortaheb, Mind_Blanking. gitlab. https://gitlab.uliege.be/S.Mortaheb/mind_blanking. Accessed 20 September 2022.