“…diverse anesthetic agents reversibly perturb functional brain networks in a way that cripples the information transfer on which normal consciousness seems to depend.”

Image: A. Johnson, Vivo Visuals.

Image: A. Johnson, Vivo Visuals.

UNDERSTANDING the mechanism of anesthetic-induced unconsciousness remains important for anesthesiology. A precise answer to the longstanding question of how these drugs work would fortify the scientific underpinnings of the field and create new opportunities for improved clinical care through novel anesthetic designs or improved brain monitoring. On the one hand, there is something common to all of the drugs in our armamentarium—they render our patients unconscious or, at least, oblivious to interventional insults. On the other hand, these drugs are structurally, pharmacologically, and neurobiologically diverse. There does not appear to be a trivial explanation at the level of molecular or even neural targets, but could there be some mechanistic Rosetta stone that translates the variety of anesthetic actions to the common language of unconsciousness? The study of dexmedetomidine by Hashmi et al.1  provides further evidence that impaired information transfer in inefficient brain networks might be of central importance.

The investigators reanalyzed functional magnetic resonance imaging data from a previous study of dexmedetomidine-induced unconsciousness2  in which 15 healthy volunteers received a 1-μg/kg loading dose of the drug followed by an infusion at 0.7 μg · kg-1 · h-1. During the experimental protocol, resting-state neuroimaging data were acquired; the designation of resting state denotes that the volunteer was in a relaxed, eyes-closed condition during which the brain was not actively engaged in a cognitive task. After data were acquired during various levels of arousal, they were computationally “sliced and diced” into 131 brain regions, a process known as parcellation. Using these parcels as nodes, a network was reconstructed and analyzed for differences between the states of consciousness (baseline, recovery) and dexmedetomidine-induced unconsciousness.

Modern network science rests on the mathematical technique of graph theory, which extracts common features of distinct networks (e.g., internet, brain, and airport system) in a way that enables standard analysis. Graphs are made up of nodes (i.e., the points on the graph) and links (i.e., the connections between the points). Once defined, the various properties of the nodes and links (table 1) can be mathematically analyzed and visually represented. Although this analysis is clearly technical, we can nonetheless appreciate the principles of network science from experiences in our daily lives. One of the most intuitive examples of a complex network is that of an airport system.

Table 1.

Glossary of Common Network Terms

Glossary of Common Network Terms
Glossary of Common Network Terms

The cities on the map in figure 1 represent the nodes of an airline network, and the lines of travel between those cities represent the links. It is immediately clear that not all nodes are alike: there are sparsely connected airports that are regional nodes and densely connected airports that are hub nodes. Hubs are critically important for networks and tend to be larger nodes that are highly connected and that facilitate efficient pathways. Most of us have had the experience of realizing the importance of network hubs when a major airport is disabled due to a snowstorm. Although a snowstorm in a regional airport might affect local travelers, inclement weather in a hub airport can result in widespread and crippling inefficiency.

Fig. 1.

Airports (nodes) and routes (links) as a complex network.

Fig. 1.

Airports (nodes) and routes (links) as a complex network.

Hashmi et al.1  found that dexmedetomidine-induced unconsciousness was characterized by various neural snow-storms in brain networks, with a preferential effect on highly connected hub nodes. The disruption of hubs was accompanied by reduced network efficiency, which likely leaves bits of information stranded in different brain regions in the same way that travelers are stranded in various cities when bad weather disables a major airport. Disruption of hub organization and other elements of functional network architecture—with negative consequences for network efficiency—has been shown to occur during propofol- and isoflurane-induced unconsciousness.3–8  Furthermore, applying computational “lesions” to hub nodes in human brain network models9  recapitulates the changes in information-theoretic measures empirically observed during propofol-, sevoflurane-, and ketamine-induced unconsciousness in humans.10,11  This suggests the possibility that, despite molecular and neurobiologic differences, diverse anesthetic agents reversibly perturb functional brain networks in a way that cripples the information transfer on which normal consciousness seems to depend.

There are two important points to note. First, the preferential target of hub structures in the brain is intriguing given the various lines of evidence suggesting that the primary sensory cortex and sensory thalamocortical networks appear relatively preserved despite anesthetic-induced unconsciousness.12  Of course, turning up the dial will ultimately suppress all brain functions but, at doses consistent with unresponsiveness, information transfer to the primary sensory cortex seems to be resilient to anesthetic exposure.13  This might beg the question, if information is being transferred to sensory cortex, how can a patient be unconscious? The current study, and others like it, provides an answer: the higher-order hubs that facilitate network efficiency and information transfer are disabled. Returning to our airline analogy, if I wanted to fly from rural Michigan to Paris, a snowstorm in the Detroit hub airport would likely prevent the trip, even if my regional airport was minimally affected (although local efficiency was also found to be impaired in this study). Second, although it is tempting to interpret the study of Hashmi et al.1  in the context of the Integrated Information Theory,14  we must exercise restraint for several reasons: (1) we do not need to invoke Integrated Information Theory to assert the importance of synthesizing neural information for the generation of consciousness—this can be argued based on conventional neuroscientific principles alone; (2) showing impaired integration during general anesthesia supports some claims of Integrated Information Theory of consciousness, but leaves other and less obvious predictions (e.g., consciousness has an identity relationship with integrated information; consciousness is a closed system; nonbiologic systems can have some degree of consciousness) unaddressed; and (3) demonstrating anesthetic disruption of functional hub architecture, information transfer, and efficiency is also consistent with a variety of other theories of consciousness, including (for example) global neuronal workspace, higher-order representationalism, and recurrent processing.15  To distinguish among these options, new paradigms and protocols will need to be designed. Furthermore, it will be critical to move beyond mere surrogates of information processing or transfer—which are known to have assumptions and be vulnerable to inaccuracy16 —to the measure of cognitive information itself.

In summary, the study by Hashmi et al.1  demonstrates that a sedative-hypnotic drug with a distinct molecular target and distinct neurobiology can—like propofol and halogenated ethers—disrupt functional hub structure and impair efficiency at multiple scales in large-scale brain networks. This work supports the prediction of graph-theoretical analysis as an approach that “promises to provide a framework for mechanistic studies”17  of anesthesia and, more importantly, sheds further light on a Rosetta stone that reveals how the different molecular languages of diverse anesthetics can all be translated to the common expression of oblivion.

Competing Interests

The author is not supported by, nor maintains any financial interest in, any commercial activity that may be associated with the topic of this article.

References

1.
Hashmi
JA
,
Loggia
ML
,
Khan
S
,
Gao
L
,
Kim
J
,
Napadow
V
,
Brown
EN
,
Akeju
O
:
Dexmedetomidine disrupts the local and global efficiency of large-scale brain networks.
Anesthesiology
2017
;
126
:
419
30
.
2.
Akeju
O
,
Loggia
ML
,
Catana
C
,
Pavone
KJ
,
Vazquez
R
,
Rhee
J
,
Contreras Ramirez
V
,
Chonde
DB
,
Izquierdo-Garcia
D
,
Arabasz
G
,
Hsu
S
,
Habeeb
K
,
Hooker
JM
,
Napadow
V
,
Brown
EN
,
Purdon
PL
:
Disruption of thalamic functional connectivity is a neural correlate of dexmedetomidine-induced unconsciousness.
Elife
2014
;
3
:
e04499
3.
Lee
U
,
Oh
G
,
Kim
S
,
Noh
G
,
Choi
B
,
Mashour
GA
:
Brain networks maintain a scale-free organization across consciousness, anesthesia, and recovery: Evidence for adaptive reconfiguration.
Anesthesiology
2010
;
113
:
1081
91
.
4.
Lee
U
,
Müller
M
,
Noh
GJ
,
Choi
B
,
Mashour
GA
:
Dissociable network properties of anesthetic state transitions.
Anesthesiology
2011
;
114
:
872
81
.
5.
Schröter
MS
,
Spoormaker
VI
,
Schorer
A
,
Wohlschläger
A
,
Czisch
M
,
Kochs
EF
,
Zimmer
C
,
Hemmer
B
,
Schneider
G
,
Jordan
D
,
Ilg
R
:
Spatiotemporal reconfiguration of large-scale brain functional networks during propofol-induced loss of consciousness.
J Neurosci
2012
;
32
:
12832
40
.
6.
Liang
Z
,
King
J
,
Zhang
N
:
Intrinsic organization of the anesthetized brain.
J Neurosci
2012
;
32
:
10183
91
.
7.
Lee
H
,
Mashour
GA
,
Noh
GJ
,
Kim
S
,
Lee
U
:
Reconfiguration of network hub structure after propofol-induced unconsciousness.
Anesthesiology
2013
;
119
:
1347
59
.
8.
Chennu
S
,
O’Connor
S
,
Adapa
R
,
Menon
DK
,
Bekinschtein
TA
:
Brain Connectivity dissociates responsiveness from drug exposure during propofol-induced transitions of consciousness.
PLoS Comput Biol
2016
;
12
:
e1004669
9.
Moon
JY
,
Lee
U
,
Blain-Moraes
S
,
Mashour
GA
:
General relationship of global topology, local dynamics, and directionality in large-scale brain networks.
PLoS Comput Biol
2015
;
11
:
e1004225
10.
Ku
SW
,
Lee
U
,
Noh
GJ
,
Jun
IG
,
Mashour
GA
:
Preferential inhibition of frontal-to-parietal feedback connectivity is a neurophysiologic correlate of general anesthesia in surgical patients.
PLoS One
2011
;
6
:
e25155
11.
Lee
U
,
Ku
S
,
Noh
G
,
Baek
S
,
Choi
B
,
Mashour
GA
:
Disruption of frontal-parietal communication by ketamine, propofol, and sevoflurane.
Anesthesiology
2013
;
118
:
1264
75
.
12.
Mashour
GA
:
Top-down mechanisms of anesthetic-induced unconsciousness.
Front Syst Neurosci
2014
;
8
:
115
13.
Schroeder
KE
,
Irwin
ZT
,
Gaidica
M
,
Bentley
JN
,
Patil
PG
,
Mashour
GA
,
Chestek
CA
:
Disruption of corticocortical information transfer during ketamine anesthesia in the primate brain.
Neuroimage
2016
;
134
:
459
65
.
14.
Tononi
G
,
Boly
M
,
Massimini
M
,
Koch
C
:
Integrated information theory: From consciousness to its physical substrate.
Nat Rev Neurosci
2016
;
17
:
450
61
.
15.
Mehta
N
,
Mashour
GA
:
General and specific consciousness: A first-order representationalist approach.
Front Psychol
2013
;
4
:
407
16.
James
RG
,
Barnett
N
,
Crutchfield
JP
:
Information flows? A critique of transfer entropies.
Phys Rev Lett
2016
;
116
:
238701
17.
Pryor
KO
,
Sleigh
J
:
The seven bridges of Königsberg.
Anesthesiology
2011
;
114
:
739
40
.