[en] Human consciousness is considered a result of the synchronous “humming” of multiple dynamic networks. We performed a dynamic functional connectivity analysis using resting state functional magnetic resonance imaging (rsfMRI) in 14 patients before and during a propofol infusion to characterize the sedation-induced alterations in consciousness. A sliding 36-second window was used to derive 59 time points of whole brain integrated local connectivity measurements. Significant changes in the connectivity strength (Z Corr) at various time points were used to measure the connectivity fluctuations during awake and sedated states. Compared with the awake state, sedation was associated with reduced cortical connectivity fluctuations in several areas connected to the default mode network and around the perirolandic cortex with a significantly decreased correlation of connectivity between their anatomical homologues. In addition, sedation was associated with increased connectivity fluctuations in the frequency range of 0.027 to 0.063 Hz in several deep nuclear regions, including the cerebellum, thalamus, basal ganglia and insula. These findings advance our understanding of sedation-induced altered consciousness by visualizing the altered dynamics in several cortical and subcortical regions and support the concept of defining consciousness as a dynamic and integrated network.
Disciplines :
Neurosciences & behavior
Author, co-author :
Bharath, Rose Dawn; National Institute of Mental Health and Neurosciences
Panda, Rajanikant ; Université de Liège - ULiège > GIGA Consciousness - Coma Science Group
Saini, Jitender; National Institute of Mental Health and Neurosciences
Sriganesh, Kamath; National Institute of Mental Health and Neurosciences
Rao, G. S. Umamaheswara; National Institute of Mental Health and Neurosciences
Language :
English
Title :
Dynamic local connectivity uncovers altered brain synchrony during propofol sedation
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.
Bibliography
Martuzzi, R. et al. A whole-brain voxel based measure of intrinsic connectivity contrast reveals local changes in tissue connectivity with anesthetic without a priori assumptions on thresholds or regions of interest. Neuroimage 58, 1044-1050 (2011).
Stamatakis, E. A., Adapa, R. M., Absalom, A. R. & Menon, D. K. Changes in resting neural connectivity during propofol sedation. PLoS One 5, (2010).
Kiviniemi, V. J. et al. Midazolam sedation increases fluctuation and synchrony of the resting brain BOLD signal. Magn. Reson. Imaging 23, 531-537 (2005).
Martuzzi, R., Ramani, R., Qiu, M., Rajeevan, N. & Constable, R. T. Functional connectivity and alterations in baseline brain state in humans. Neuroimage 49, 823-834 (2010).
Deshpande, G., Kerssens, C., Sebel, P. S. & Hu, X. Altered local coherence in the default mode network due to sevoflurane anesthesia. Brain Res. 1318, 110-121 (2010).
Peltier, S. J. et al. Functional connectivity changes with concentration of sevoflurane anesthesia. Neuroreport 16, 285-288 (2005).
Greicius, M. D. et al. Persistent default-mode network connectivity during light sedation. Hum. Brain Mapp. 29, 839-847 (2008).
Schrouff, J. et al. Brain functional integration decreases during propofol-induced loss of consciousness. Neuroimage 57, 198-205 (2011).
Kamath, S., Bagepally, R., Bhavani Shankar, B., Saini, J. & Rao, G. S. U. R. Effect of Propofol Anesthesia on Resting State Brain Functional Connectivity in Indian Population with Chronic Back Pain. Neurol. India 65, 286-292 (2017).
Liu, X. et al. Propofol attenuates low-frequency fluctuations of resting-state fMRI BOLD signal in the anterior frontal cortex upon loss of consciousness. Neuroimage 174, 295-301 (2016).
Monti, M. M. et al. Dynamic change of global and local information processing in propofol-induced loss and recovery of consciousness. PLoS Comput. Biol., doi:10.1371/journal.pcbi.1003271 (2013).
Deco, G., Jirsa, V. K. & McIntosh, A. R. Resting brains never rest: Computational insights into potential cognitive architectures. Trends in Neurosciences 36, 268-274 (2013).
Deco, G., Jirsa, V. K. & McIntosh, A. R. Emerging concepts for the dynamical organization of resting-state activity in the brain. Nat. Rev. Neurosci. 12, 43-56 (2011).
Deco, G., Jirsa, V. K. & McIntosh, A. R. Resting brains never rest: Computational insights into potential cognitive architectures. Trends in Neurosciences 36, 268-274 (2013).
Barttfeld, P. et al. Signature of consciousness in the dynamics of resting-state brain activity. Proc. Natl. Acad. Sci. 112, 201418031 (2014).
Alkire, M. T., Hudetz, A. G. & Tononi, G. Consciusness and Anesthesia. Science (80-.). 7, 876-880 (2008).
Zalesky, A., Fornito, A., Cocchi, L., Gollo, L. L. & Breakspear, M. Time-resolved resting-state brain networks. Proc. Natl. Acad. Sci. USA 111, 10341-6 (2014).
Deng, L., Sun, J., Cheng, L. & Tong, S. Characterizing dynamic local functional connectivity in the human brain. Sci. Rep., doi:10.1038/srep26976 (2016).
Allen, E. A. et al. Tracking whole-brain connectivity dynamics in the resting state. Cereb. Cortex 24, 663-676 (2014).
Hutchison, R. M., Womelsdorf, T., Gati, J. S., Everling, S. & Menon, R. S. Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques. Hum. Brain Mapp., doi:10.1002/hbm.22058 (2013).
Hutchison, R. M. et al. Dynamic functional connectivity: Promise, issues, and interpretations. Neuroimage 80, 360-378 (2013).
Liang, Z., Liu, X. & Zhang, N. Dynamic resting state functional connectivity in awake and anesthetized rodents. Neuroimage. doi:10.1016/j.neuroimage.2014.10.013 (2015).
Keilholz, S. D., Magnuson, M. E., Pan, W.-J., Willis, M. & Thompson, G. J. Dynamic properties of functional connectivity in the rodent. Brain Connect., doi:10.1089/brain.2012.0115 (2013).
Liao, W. et al. Dynamical intrinsic functional architecture of the brain during absence seizures. Brain Struct. Funct., doi:10.1007/ s00429-013-0619-2 (2014).
Jones, D. T. et al. Non-stationarity in the 'resting brain's' modular architecture. PLoS One, doi:10.1371/journal.pone.0039731 (2012).
Sakoǧlu, Ü. et al. A method for evaluating dynamic functional network connectivity and task-modulation: Application to schizophrenia. Magn. Reson. Mater. Physics, Biol. Med., doi:10.1007/s10334-010-0197-8 (2010).
Chen, J. E., Chang, C., Greicius, M. D. & Glover, G. H. Introducing co-activation pattern metrics to quantify spontaneous brain network dynamics. Neuroimage, doi:10.1016/j.neuroimage.2015.01.057 (2015).
Hudetz, A. G., Liu, X. & Pillay, S. Dynamic Repertoire of Intrinsic Brain States Is Reduced in Propofol-Induced Unconsciousness. Brain Connect., doi:10.1089/brain.2014.0230 (2015).
Amico, E. et al. Posterior cingulate cortex-related co-activation patterns: A resting state fMRI study in propofol-induced loss of consciousness. PLoS One, doi:10.1371/journal.pone.0100012 (2014).
Kaiser, R. H. et al. Dynamic Resting-State Functional Connectivity in Major Depression. Neuropsychopharmacology 1-9, doi:10.1038/npp.2015.352 (2015).
Wu, C. W. et al. Frequency specificity of functional connectivity in brain networks. Neuroimage 42, 1047-1055 (2008).
Goelman, G. et al. Frequency-phase analysis of resting-state functional MRI. Sci. Rep. 7 (2017).
Martuzzi, R. et al. A whole-brain voxel based measure of intrinsic connectivity contrast reveals local changes in tissue connectivity with anesthetic without a priori assumptions on thresholds or regions of interest. Neuroimage 58, 1044-1050 (2011).
Monti, M. M. et al. Dynamic change of global and local information processing in propofol-induced loss and recovery of consciousness. PLoS Comput Biol, doi:10.1371/journal.pcbi.1003271 (2013).
Boveroux, P. et al. Breakdown of within- and between-network resting state functional magnetic resonance imaging connectivity during propofol-induced loss of consciousness 11. Anesthesiology (2010).
Tononi, G. An information integration theory of consciousness. BMC Neurosci. 5, 42 (2004).
Song, X., Zhang, Y. & Liu, Y. Frequency specificity of regional homogeneity in the resting-state human brain. PLoS One, doi:10.1371/ journal.pone.0086818 (2014).
Zuo, X. N. et al. The oscillating brain: Complex and reliable. Neuroimage, doi:10.1016/j.neuroimage.2009.09.037 (2010).
Baria, A. T., Baliki, M. N., Parrish, T. & Apkarian, A. V. Anatomical and functional assemblies of brain BOLD oscillations. J. Neurosci., doi:10.1523/JNEUROSCI.1296-11.2011 (2011).
Baria, A. T. et al. Linking human brain local activity fluctuations to structural and functional network architectures. Neuroimage, doi:10.1016/j.neuroimage.2013.01.072 (2013).
Mesulam, M. M. From sensation to cognition. Brain 121, 1013-1052 (1998).
Velly, L. J. et al. Differential dynamic of action on cortical and subcortical structures of anesthetic agents during induction of anesthesia. J. Am. Soc. Anesthesiol. 107, 202-212 (2007).
Schiff, N. D. Recovery of consciousness after brain injury: a mesocircuit hypothesis. Trends Neurosci. 33, 1-9 (2010).
Leonardi, N. & Ville, D. On spurious and real fluctuations of dynamic functional connectivity during rest. NeuroImage 104, 430-436 (2015).
Cordes, D. et al. Frequencies contributing to functional connectivity in the cerebral cortex in 'resting-state' data. Am. J. Neuroradiol. 22, 1326-1333 (2001).
Beall, E. B. & Lowe, M. J. Isolating physiologic noise sources with independently determined spatial measures. Neuroimage 37, 1286-1300 (2007).
Birn, R. M., Diamond, J. B., Smith, M. A. & Bandettini, P. A. Separating respiratory-variation-related fluctuations from neuronalactivity- related fluctuations in fMRI. Neuroimage 31, 1536-1548 (2006).
Whitfield-Gabrieli, S. & Nieto-Castanon, A. Conn: A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks. Brain Connect. 2, 125-141 (2012).
Behzadi, Y., Restom, K., Liau, J. & Liu, T. T. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage 37, 90-101 (2007).
Deshpande, G., LaConte, S., Peltier, S. & Hu, X. Integrated local correlation: A new measure of local coherence in fMRI data. Hum. Brain Mapp. 30, 13-23 (2009).
Hutchison, R. M. et al. Dynamic functional connectivity: Promise, issues, and interpretations. Neuroimage 80, 360-378 (2013).
Allen, E. A. et al. Tracking whole-brain connectivity dynamics in the resting state. Cereb. Cortex 24, 663-676 (2014).
Similar publications
Sorry the service is unavailable at the moment. Please try again later.
This website uses cookies to improve user experience. Read more
Save & Close
Accept all
Decline all
Show detailsHide details
Cookie declaration
About cookies
Strictly necessary
Performance
Strictly necessary cookies allow core website functionality such as user login and account management. The website cannot be used properly without strictly necessary cookies.
This cookie is used by Cookie-Script.com service to remember visitor cookie consent preferences. It is necessary for Cookie-Script.com cookie banner to work properly.
Performance cookies are used to see how visitors use the website, eg. analytics cookies. Those cookies cannot be used to directly identify a certain visitor.
Used to store the attribution information, the referrer initially used to visit the website
Cookies are small text files that are placed on your computer by websites that you visit. Websites use cookies to help users navigate efficiently and perform certain functions. Cookies that are required for the website to operate properly are allowed to be set without your permission. All other cookies need to be approved before they can be set in the browser.
You can change your consent to cookie usage at any time on our Privacy Policy page.
