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DMN in Consciousness


The advent of the resting state functional MRI (R-fMRI) has provided a powerful method of studying functional changes in the Default Mode Network (DMN) with varying levels of consciousness, one of the proposed functions of the DMN. R-fMRI connectivity analyses of regions of the DMN across different states of consciousness reveal a connection between the functional connectivity within certain DMN regions and the degree of consciousness in the patient, indicating that the DMN may be central in creating states of consciousness. Studies supporting this relation have studied patients with consciousness that has been altered naturally (by sleep), via sedation, or due to brain damage.

1 DMN in States of Sedation


R-fMRI sedation studies in humans and monkeys indicate that quantitative, but not qualitative, connectivity measures within DMN regions correlate with the level of consciousness. Temporal coherence of blood oxygen level-dependent (BOLD) signal oscillations in a brain region are taken as evidence of the activity of the studied region, where the presence of BOLD signals in the DMN in resting but not task-dependent states helped implicate the network. The fact that BOLD signal oscillations across the human DMN are also present in both rest and conscious sedation with midazolam indicate that the qualitative presence of the BOLD oscillations also does not to correlate with the level of consciousness1. These results echo the findings of previous studies on the DMN in monkeys sedated with isoflurane, where it was similarly found that BOLD oscillations were present across states of consciousness2. These results indicate that the DMN is capable of supporting aspects of our being that are consistent across different levels of consciousness.
On the other hand, when regions of the DMN are examined separately, there emerge differences from rest to conscious sedation. Both region-of-interest (ROI)-based analysis of fMRI acquired during conscious sedation and through use of independent component analysis (ICA)3 show that the primary sensory and sensory-motor networks of the DMN have higher functional connectivity during conscious sedation than during wakeful rest. Thus, while a qualitative estimate of the presence or absence of DMN activity does not appear to correspond to the presence or absence of consciousness, quantitative measures of reduced connectivity within the DMN may reliably correlate with the level of consciousness.

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frontal-posterior.png
Fig. 1. Connectivity of the main components of the DMN during wake and deep sleep, as determined from temporal correlation analysis of average time courses within each region of interest (ROI). The size of the disks represents within-region connectivity, whereas thickness of lines represents between- region connectivity. During deep sleep, the posterior areas (bilateral IPC and PCC) strengthen their connectivity, whereas the connections between frontal and posterior regions are lost. MF = medial prefrontal/ anterior cingulate cortex; IPl= left inferior parietal/angular gyrus; IPr = right inferior parietal/angular gyrus; PC = posterior cingulate/precuneus. Figure and caption adapted from Horovitz et al. 2009
2 DMN in The Sleep Cycle

R-fMRI studies in humans reveal a correlation between the sleep-induced reduction of consciousness and changes in functional correlation between DMN network components. These DMN changes are seen only in deep, but not light, sleep4. Though the transition from rest to light sleep is associated with significant changes in several cortical areas (most notably the visual cortex (ref to other wiki)) light sleep shows conserved correlations among the brain regions of the DMN, as measured by BOLD fMRI fluctuations5. This suggests that that activity in the DMN does not require the level of consciousness seen in wakefulness or rest.
In deep sleep, however, the DMN's activity is different from that of rest or light sleep. The most notably reduced correlation within the DMN is that between its frontal and posterior areas6 (Fig.1). Given that the frontal cortex is known to be a main contributor to such executive processes as logical reasoning7, its changing correlation with the posterior DMN and other brain networks may be related to the illogic and nonsense contained within dreams, which are generally only noted by the dreamer until the wakefulness-associated correlations of the frontal cortex return. Notably, despite changes in correlation, activity levels in the individual network components of the DMN are preserved, “suggesting that it is not activity per se but rather the coherent activation of all parts within the net work that leads to a conscious experience”8.


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3 In Brain-damaged Persons


precuneus.png
Fig. 3. Sagittal MRI slice with the precuneus shown in red. Connectivity in the precuneus was found to be most significantly correlated with the level of consciousness in brain-damaged patients. Image from http://en.wikipedia.org/wiki/Precuneus#cite_ref-Cavanna_2-0

Yet another patient group to show that DMN connectivity reflects the level of the patient's consciousness is that of non-communicative brain-damaged patients9 (Fig. 2). In these studies, though several areas of the DMN were implicated as relating to consciousness, the greatest predictor of consciousness was found to be the connectivity of the PCC/precuneus (Fig. 3), where connectivity is significantly lesser in unconscious patients compared with minimally conscious patients10. The strength of this correlation was found to be strong enough to differentiate minimally conscious (vegetative) from unconscious

(comatose) patients; a result with powerful clinical implications (selfwiki link). The precuneus is a medial part of the superior parietal lobule, and has consistently been linked to consciousness; its activity is disrupted in altered states of consciousness beyond that of brain damage (for ex. In epilepsy), and the precuneus has the brain's highest rates of cerebral glucose metabolism during wakefulness but the lowest rates of cerebral glucose metabolism during anesthesia11. Additionally, the precuneus is one of the brain areas that is most deactivated during deep sleep and rapid eye movement (REM) sleep12.




Picture_1.1png.jpg
Fig.2 Default network connectivity correlates with the level of consciousness, ranging from healthy controls, minimally conscious, vegetative, to comatose patients. Mean Z-scores and the 90% confidence interval for default network connectivity in PCC/precuneus, temporo-parietal junction, medial prefrontal cortex and parahippocampal gyrus across patient populations. Figure and caption adapted from A. Vanhaudenhuyse et al. (2010).



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4 Clinical Significance of the Consciousness and DMN Connectivity Correlate


Differentiating between minimally conscious (vegetative) and unconscious (coma) patients presents a clinical challenge, both groups of patients being non-communicative, and given the current lack of an objective measure consciousness. Currently, the consciousness of non-communicative patients is estimated following scales assessing the patient's response to behavioural tests and the presentation of certain clinical signs. Many such scales have been developed for the quantification of assessed consciousness, the most commonly used being the Glasgow Coma Scale. Though useful in many clinical situations, these scales have proved disconcertingly unreliable in differentiating minimally conscious from unconscious patients, where rates of misdiagnosis having been reported up to 40%. For instance, a 1993 U.S report found that 37% of patients admitted more than 1 month post-injury and diagnosed with coma or persistent vegetative state13 and 43% of patients admitted to a profound brain injury unit at least 6 months following their brain damage14 had some level of awareness despite their consciousness-precluding diagnosis.

To be able to supply the ethically and medically optimal treatments, a reliable differentiation between that minimally conscious and unconscious patients is critical. The resting state fMRI may prove to be a useful tool in this process; the fact that connectivity within areas of the DMN may be quantitatively related (self ref) to the level of consciousness suggest a new, more objective way of assessing consciousness. The fact that resting state fMRIs are much easier to administer than a standard fMRI is hoped to prove the tool practical on top of reliable.

Importantly, the reports on the misdiagnosis of non-communicative patients show that there is also a large potential for improvement within the current diagnostic system; in the patients included in the reports on the rates of misdiagnosis, a correct diagnosis using existing paradigms was possible - otherwise the diagnosis could not have been corrected.

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References

  1. Greicius MD, Kiviniemi V, Tervonen O, Vainionpää V, Alahuhta S, Reiss AL, Menon V. Hum Brain Mapp. Persistent default-mode network connectivity during light sedation. Human Brain Mapping 29(7):839-47 (2008).
  2. Vincent JL, Patel GH, Fox MD, Snyder AZ, Baker JT, Van Essen DC, Zempel JM, Snyder LH, Corbetta M, Raichle ME. Intrinsic functional architecture in the anaesthetized monkey brain. Nature 447:83–86 (2007).
  3. Kiviniemi V, Haanpaa H, Kantola JH, Jauhiainen J, Vainionpaa V, Alahuhta S, Tervonen O. Midazolam sedation increases fluctuation and synchrony of the resting brain BOLD signal. Magn Reson Imaging 23:531–537 (2005).
  4. Horovitz SG, Braunc AR, Carrd WS, Picchionie D, Balkine TJ, Fukunagab M, et al Decoupling of the brain’s default mode network during deep sleep. PNAS;106:11376-81 (2009).
  5. Horovitz SG, Fukunaga M, de Zwart JA, van Gelderen P, Fulton SC, Balkin TJ, et al. Low frequency BOLD fluctuations during resting wakefulness and light sleep: a simultaneous EEG-fMRI study. Human Brain Mapping ;29:671-82 (2008).
  6. J. M. Fuster. Synopsis of function and dysfunction of the frontal lobe. Acta Psychiatrica Scandinavica. 99, Issue Supplement s395,: 51–57 (1999).
  7. A. Vanhaudenhuyse et al. Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients” Brain: 133; 161–171 (2010).
  8. Vogt BA, Laureys S. Posterior cingulate, precuneal and retrosplenial cortices: cytology and components of the neural network correlates of consciousness. Progress in brain research; 150: 205–17 (2005).
  9. Cavanna A, Trimble M. The precuneus: a review of its functional anatomy and behavioural correlates. Brain; 129(Pt 3): 564–83 (2006).
  10. Childs, N.L., Mercer, W.N. and Childs, H.W. Accuracy of diagnosis of persistent vegetative state. Neurology, 43: 1465–1467 (1993).
  11. Andrews, K. International Working Party on the Management of the Vegetative State: summary report. Brain Inj;10: 797–806 (1996).








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