Anesthetic Suppression of Thalamic High-Frequency Oscillations: Evidence that the Thalamus Is More Than Just a Gateway to Consciousness?

Berger, Miles; García, Paul S.

doi:10.1213/ane.0000000000001207

“…The thalamus is responsible for nearly all input to the cortex—including sensory information (except olfaction), motor inputs from structures like the cerebellum and basal ganglia, inputs from limbic structures such as the hippocampus, and widespread modulatory inputs from structures involved in regulating arousal and the sleep-wake cycle—and is thus integral to proper neurocognitive function. While full thalamic lesions usually cause a near-total loss of consciousness (Castaigne et al, 1981 ; Blumenfeld, 2010 ; Berger and García, 2016 ), more subtle insults can lead to deficits in working memory, attention, and perception that can be detected by cognitive testing (Blumenfeld, 2010 ).…”

Section: Discussionmentioning

confidence: 99%

“…These mechanisms are thought to give rise to large-scale, anesthetic-induced changes to alpha topography, which correlate with anesthetic-induced unconsciousness (Tinker et al, 1977 ; although also see Blain-Moraes et al, 2016 , which suggested that anteriorization occurs at higher doses of anesthetics than are necessary for loss of consciousness). Since thalamocortical interactions are critical for consciousness and cognitive function (Castaigne et al, 1981 ; Blumenfeld, 2010 ; Berger and García, 2016 ), and lower awake alpha power has been shown to be associated with cognitive deficits (reviewed in Rossini et al, 2007 ), we hypothesized that the ability of anesthesia to induce strong frontal alpha oscillations might also be a predictor or correlate of a patient’s preoperative cognitive function.…”

Section: Introductionmentioning

confidence: 99%

Intraoperative Frontal Alpha-Band Power Correlates with Preoperative Neurocognitive Function in Older Adults

Giattino

¹

,

Gardner

²

,

Sbahi

³

et al. 2017

Front. Syst. Neurosci.

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Each year over 16 million older Americans undergo general anesthesia for surgery, and up to 40% develop postoperative delirium and/or cognitive dysfunction (POCD). Delirium and POCD are each associated with decreased quality of life, early retirement, increased 1-year mortality, and long-term cognitive decline. Multiple investigators have thus suggested that anesthesia and surgery place severe stress on the aging brain, and that patients with less ability to withstand this stress will be at increased risk for developing postoperative delirium and POCD. Delirium and POCD risk are increased in patients with lower preoperative cognitive function, yet preoperative cognitive function is not routinely assessed, and no intraoperative physiological predictors have been found that correlate with lower preoperative cognitive function. Since general anesthesia causes alpha-band (8–12 Hz) electroencephalogram (EEG) power to decrease occipitally and increase frontally (known as “anteriorization”), and anesthetic-induced frontal alpha power is reduced in older adults, we hypothesized that lower intraoperative frontal alpha power might correlate with lower preoperative cognitive function. Here, we provide evidence that such a correlation exists, suggesting that lower intraoperative frontal alpha power could be used as a physiological marker to identify older adults with lower preoperative cognitive function. Lower intraoperative frontal alpha power could thus be used to target these at-risk patients for possible therapeutic interventions to help prevent postoperative delirium and POCD, or for increased postoperative monitoring and follow-up. More generally, these results suggest that understanding interindividual differences in how the brain responds to anesthetic drugs can be used as a probe of neurocognitive function (and dysfunction), and might be a useful measure of neurocognitive function in older adults.

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Brain network motifs are markers of loss and recovery of consciousness

Duclos

¹

,

Nadin

²

,

Mahdid

³

et al. 2021

Sci Rep

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Motifs are patterns of inter-connections between nodes of a network, and have been investigated as building blocks of directed networks. This study explored the re-organization of 3-node motifs during loss and recovery of consciousness. Nine healthy subjects underwent a 3-h anesthetic protocol while 128-channel electroencephalography (EEG) was recorded. In the alpha (8–13 Hz) band, 5-min epochs of EEG were extracted for: Baseline; Induction; Unconscious; 30-, 10- and 5-min pre-recovery of responsiveness; 30- and 180-min post-recovery of responsiveness. We constructed a functional brain network using the weighted and directed phase lag index, on which we calculated the frequency and topology of 3-node motifs. Three motifs (motifs 1, 2 and 5) were significantly present across participants and epochs, when compared to random networks (p < 0.05). The topology of motifs 1 and 5 changed significantly between responsive and unresponsive epochs (p-values < 0.01; Kendall’s W = 0.664 (motif 1) and 0.529 (motif 5)). Motif 1 was constituted of long-range chain-like connections, while motif 5 was constituted of short-range, loop-like connections. Our results suggest that anesthetic-induced unconsciousness is associated with a topological re-organization of network motifs. As motif topological re-organization may precede (motif 5) or accompany (motif 1) the return of responsiveness, motifs could contribute to the understanding of the neural correlates of consciousness.

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Brain network motifs are markers of loss and recovery of consciousness

Duclos

¹

,

Mahdid

²

,

Nadin

³

et al. 2020

Preprint

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Motifs are patterns of inter-connections between nodes of a network, and have been investigated as building blocks of directed networks. This study explored the re-organization of 3-node motifs during loss and recovery of consciousness. Nine healthy subjects underwent a 3-hour anesthetic protocol while 128-channel electroencephalography (EEG) was recorded. In the alpha (8)(9)(10)(11)(12)(13) band, five-minute epochs of EEG were extracted for: baseline; induction; unconsciousness; 30-, 10-and 5-minutes pre-recovery of consciousness; 30-and 180-minutes post-recovery of consciousness. We constructed a functional brain network using both the weighted and the directed phase lag index, on which we calculated graph theoretical network properties, and the frequency and topography of 3-node motifs. Three motifs (motifs 1, 2 and 5) were significantly present across participants and epochs, when compared to random networks (p<0.05). While graph theoretical properties varied inconsistently across unconscious epochs (p-values<0.05), the topography of motifs 1 and 5 changed significantly between conscious and unconscious states (p<0.01). Our results suggest that anesthetic-induced unconsciousness is associated with a topographic re-organization of network motifs. As motif topographic re-organization may precede (motif 1) or accompany (motif 5) the behavioral return of consciousness, motifs could contribute to the understanding of the neural building blocks of consciousness.representing the spurious connectivity. The wPLI and dPLI values of the original, non-shuffled EEG data were compared to this distribution of surrogate data using a Wilcoxon signed rank test and were set to 0 (wPLI) or 0.5 (dPLI) if they did not achieve statistical significance. Statistical significance was set to p < 0.05. Construction and analysis of brain networksThe functional brain network was constructed using the wPLI of all pairwise combinations of electrode channels. We constructed a binary adjacency matrix Aij using a threshold of 35%: if the wPLIij value of nodes i and j was within the top 35% of all wPLI values, Aij = 1; otherwise, Aij = 0. This threshold was selected because it was previously shown to be the optimum threshold to avoid an isolated node in the EEG network during baseline [47]. From the binary adjacency matrix, we calculated basic graph theoretical network properties, including global efficiency, clustering coefficient, and modularity (Fig. 6). Global efficiency is the inverse of the average shortest path length ( ! ! ! ), where Lw is the average of the shortest path lengths (Lij) between all pairs of nodes in the network [48]. The clustering coefficient, calculated by averaging the clustering coefficients of all individual nodes (Ci), represents the degree to which nodes of a graph tend to cluster together, such that higher values imply networks with highly clustered or regular structures [49]. The modularity of the network represents the strength of division of a network into modules, such that high modularity implies a network w...

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Anesthetic Suppression of Thalamic High-Frequency Oscillations: Evidence that the Thalamus Is More Than Just a Gateway to Consciousness?

Cited by 3 publications

References 28 publications

Intraoperative Frontal Alpha-Band Power Correlates with Preoperative Neurocognitive Function in Older Adults

Intraoperative Frontal Alpha-Band Power Correlates with Preoperative Neurocognitive Function in Older Adults

Brain network motifs are markers of loss and recovery of consciousness

Brain network motifs are markers of loss and recovery of consciousness

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