Breakdown in cortical effective connectivity during midazolam-induced loss of consciousness. Proc Natl Acad Sci U S A. 2010;107:2681-2686. [PMID: 20133802 DOI: 10.1073/pnas.0913008107]

Transient brain activity dynamics discriminate levels of consciousness during anesthesia

The awake mammalian brain is functionally organized in terms of large-scale distributed networks that are constantly interacting. Loss of consciousness might disrupt this temporal organization leaving patients unresponsive. We hypothesize that characterizing brain activity in terms of transient events may provide a signature of consciousness. For this, we analyze temporal dynamics of spatiotemporally overlapping functional networks obtained from fMRI transient activity across different anesthetics and levels of anesthesia. We first show a striking homology in spatial organization of networks between monkeys and humans, indicating cross-species similarities in resting-state fMRI structure. We then track how network organization shifts under different anesthesia conditions in macaque monkeys. While the spatial aspect of the networks is preserved, their temporal dynamics are highly affected by anesthesia. Networks express for longer durations and co-activate in an anesthetic-specific configuration. Additionally, hierarchical brain organization is disrupted with a consciousness-level-signature role of the default mode network. In conclusion, large-scale brain network temporal dynamics capture differences in anesthetic-specific consciousness-level, paving the way towards a clinical translation of these cortical signature.

A measure centrality index for systematic empirical comparison of consciousness theories

Consciousness science is marred by disparate constructs and methodologies, making it challenging to systematically compare theories. This foundational crisis casts doubts on the scientific character of the field itself. Addressing it, we propose a framework for systematically comparing consciousness theories by introducing a novel inter-theory classification interface, the Measure Centrality Index (MCI). Recognizing its gradient distribution, the MCI assesses the degree of importance a specific empirical measure has for a given consciousness theory. We apply the MCI to probe how the empirical measures of the Global Neuronal Workspace Theory (GNW), Integrated Information Theory (IIT), and Temporospatial Theory of Consciousness (TTC) would fare within the context of the other two. We demonstrate that direct comparison of IIT, GNW, and TTC is meaningful and valid for some measures like Lempel-Ziv Complexity (LZC), Autocorrelation Window (ACW), and possibly Mutual Information (MI). In contrast, it is problematic for others like the anatomical and physiological neural correlates of consciousness (NCC) due to their MCI-based differential weightings within the structure of the theories. In sum, we introduce and provide proof-of-principle of a novel systematic method for direct inter-theory empirical comparisons, thereby addressing isolated evolution of theories and confirmatory bias issues in the state-of-the-art neuroscience of consciousness.

Thalamic contributions to the state and contents of consciousness

Consciousness can be conceptualized as varying along at least two dimensions: the global state of consciousness and the content of conscious experience. Here, we highlight the cellular and systems-level contributions of the thalamus to conscious state and then argue for thalamic contributions to conscious content, including the integrated, segregated, and continuous nature of our experience. We underscore vital, yet distinct roles for core- and matrix-type thalamic neurons. Through reciprocal interactions with deep-layer cortical neurons, matrix neurons support wakefulness and determine perceptual thresholds, whereas the cortical interactions of core neurons maintain content and enable perceptual constancy. We further propose that conscious integration, segregation, and continuity depend on the convergent nature of corticothalamic projections enabling dimensionality reduction, a thalamic reticular nucleus-mediated divisive normalization-like process, and sustained coherent activity in thalamocortical loops, respectively. Overall, we conclude that the thalamus plays a central topological role in brain structures controlling conscious experience.

Anesthesia and the neurobiology of consciousness

In the 19th century, the discovery of general anesthesia revolutionized medical care. In the 21st century, anesthetics have become indispensable tools to study consciousness. Here, I review key aspects of the relationship between anesthesia and the neurobiology of consciousness, including interfaces of sleep and anesthetic mechanisms, anesthesia and primary sensory processing, the effects of anesthetics on large-scale functional brain networks, and mechanisms of arousal from anesthesia. I discuss the implications of the data derived from the anesthetized state for the science of consciousness and then conclude with outstanding questions, reflections, and future directions.

Consciousness and sleep

Sleep is a universal, essential biological process. It is also an invaluable window on consciousness. It tells us that consciousness can be lost but also that it can be regained, in all its richness, when we are disconnected from the environment and unable to reflect. By considering the neurophysiological differences between dreaming and dreamless sleep, we can learn about the substrate of consciousness and understand why it vanishes. We also learn that the ongoing state of the substrate of consciousness determines the way each experience feels regardless of how it is triggered-endogenously or exogenously. Dreaming consciousness is also a window on sleep and its functions. Dreams tell us that the sleeping brain is remarkably lively, recombining intrinsic activation patterns from a vast repertoire, freed from the requirements of ongoing behavior and cognitive control.

Breakdown of effective information flow in disorders of consciousness: Insights from TMS-EEG

BACKGROUND

The complexity of the neurophysiological mechanisms underlying human consciousness is widely acknowledged, with information processing and flow originating in cortex conceived as a core mechanism of consciousness emergence. Combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is considered as a promising technique to understand the effective information flow associated with consciousness.

OBJECTIVES

To investigate information flow with TMS-EEG and its relationship to different consciousness states.

METHODS

We applied an effective information flow analysis by combining time-varying multivariate adaptive autoregressive model and adaptive directed transfer function on TMS-EEG data of frontal, motor and parietal cortex in patients with disorder of consciousness (DOC), including 14 vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients, 21 minimally conscious state (MCS) patients, and 22 healthy subjects.

RESULTS

TMS in DOC patients, particularly VS/UWS, induced a significantly weaker effective information flow compared to healthy subjects. The bidirectional directed information flow was lost in DOC patients with TMS of frontal, motor and parietal cortex. The interactive ROI rate of the information flow network induced by TMS of frontal and parietal cortex was significantly lower in VS/UWS than in MCS. The interactive ROI rate correlated with DOC clinical scales.

CONCLUSIONS

TMS-EEG revealed a physiologically relevant correlation between TMS-induced information flow and levels of consciousness. This suggests that breakdown of effective cortical information flow serves as a viable marker of human consciousness.

SIGNIFICANCE

Findings offer a unique perspective on the relevance of information flow in DOC, thus providing a novel way of understanding the physiological basis of human consciousness.

Re-awakening the brain: Forcing transitions in disorders of consciousness by external in silico perturbation

A fundamental challenge in neuroscience is accurately defining brain states and predicting how and where to perturb the brain to force a transition. Here, we investigated resting-state fMRI data of patients suffering from disorders of consciousness (DoC) after coma (minimally conscious and unresponsive wakefulness states) and healthy controls. We applied model-free and model-based approaches to help elucidate the underlying brain mechanisms of patients with DoC. The model-free approach allowed us to characterize brain states in DoC and healthy controls as a probabilistic metastable substate (PMS) space. The PMS of each group was defined by a repertoire of unique patterns (i.e., metastable substates) with different probabilities of occurrence. In the model-based approach, we adjusted the PMS of each DoC group to a causal whole-brain model. This allowed us to explore optimal strategies for promoting transitions by applying off-line in silico probing. Furthermore, this approach enabled us to evaluate the impact of local perturbations in terms of their global effects and sensitivity to stimulation, which is a model-based biomarker providing a deeper understanding of the mechanisms underlying DoC. Our results show that transitions were obtained in a synchronous protocol, in which the somatomotor network, thalamus, precuneus and insula were the most sensitive areas to perturbation. This motivates further work to continue understanding brain function and treatments of disorders of consciousness.

Neural assemblies coordinated by cortical waves are associated with waking and hallucinatory brain states

The relationship between sensory stimuli and perceptions is brain-state dependent: in wakefulness, suprathreshold stimuli evoke perceptions; under anesthesia, perceptions are abolished; and during dreaming and in dissociated states, percepts are internally generated. Here, we exploit this state dependence to identify brain activity associated with internally generated or stimulus-evoked perceptions. In awake mice, visual stimuli phase reset spontaneous cortical waves to elicit 3-6 Hz feedback traveling waves. These stimulus-evoked waves traverse the cortex and entrain visual and parietal neurons. Under anesthesia as well as during ketamine-induced dissociation, visual stimuli do not disrupt spontaneous waves. Uniquely, in the dissociated state, spontaneous waves traverse the cortex caudally and entrain visual and parietal neurons, akin to stimulus-evoked waves in wakefulness. Thus, coordinated neuronal assemblies orchestrated by traveling cortical waves emerge in states in which perception can manifest. The awake state is privileged in that this coordination is reliably elicited by external visual stimuli.

Electroencephalographic features of elderly patients during anesthesia induction with remimazolam: a sub-study of a randomized controlled trial

BACKGROUND

Although remimazolam is used as a general anesthetic in elderly patients due to its hemodynamic stability, the electroencephalogram (EEG) characteristics of remimazolam are not well-known. The purpose of this study was to identify the EEG features of remimazolam-induced unconsciousness in elderly patients and compare them with propofol.

METHODS

Remimazolam (n=26) or propofol (n=26) were randomly administered for anesthesia induction in surgical patients. The hypnotic agent was blinded only to the patients. During the induction of anesthesia, remimazolam was administered at a rate of 6 mg/kg/h, and propofol was administered at a target effect-site concentration of 3.5 μg/ml. The EEG signals from 8 channels (Fp1,Fp2,Fz,F3,F4,Pz,P3,P4, referenced to A2, using the 10-20 system) were acquired during the induction of anesthesia and in the postoperative care unit. Power spectrum analysis was performed, and directed functional connectivity between frontal and parietal regions was evaluated using normalized symbolic transfer entropy. Functional connectivity in unconscious processes induced by remimazolam or propofol was compared with baseline. To compare each power of frequency over time of the two hypnotic agents, a permutation test with t statistic was conducted.

RESULTS

Compared to the baseline in the alpha band, the feedback connectivity decreased by an average of 46% and 43%, respectively, after the loss of consciousness induced by remimazolam and propofol (95% CI for the mean difference:-0.073 to -0.044 for remimazolam, P<0.001,-0.068 to -0.042 for propofol,P<0.001). Asymmetry in the feedback and feedforward connectivity in the alpha band was suppressed after the loss of consciousness induced by remimazolam and propofol. There were no significant differences in the power of each frequency over time between the two hypnotic agents (minimum q-value=0.4235).

CONCLUSIONS

Both regimens showed a greater decrease in feedback connectivity compared to a decrease in feedforward connectivity after loss of consciousness, leading to a disruption of asymmetry between the frontoparietal connectivity.

Breakdown of oscillatory effective networks in disorders of consciousness

INTRODUCTION

Combining transcranial magnetic stimulation with electroencephalography (TMS-EEG), oscillatory reactivity can be measured, allowing us to investigate the interaction between local and distant cortical oscillations. However, the extent to which human consciousness is related to these oscillatory effective networks has yet to be explored.

AIMS

We tend to investigate the link between oscillatory effective networks and brain consciousness, by monitoring the global transmission of TMS-induced oscillations in disorders of consciousness (DOC).

RESULTS

A cohort of DOC patients was included in this study, which included 28 patients with a minimally conscious state (MCS) and 20 patients with vegetative state/unresponsive wakefulness syndrome (VS/UWS). Additionally, 25 healthy controls were enrolled. The oscillatory reactivity to single-pulse TMS of the frontal, sensorimotor and parietal cortex was measured using event-related spectral perturbation of TMS-EEG. The temporal-spatial properties of the oscillatory reactivity were illustrated through life time, decay gradients and accumulative power. In DOC patients, an oscillatory reactivity was observed to be temporally and spatially suppressed. TMS-EEG of DOC patients showed that the oscillations did not travel as far in healthy controls, in terms of both temporal and spatial dimensions. Moreover, cortical theta reactivity was found to be a reliable indicator in distinguishing DOC versus healthy controls when TMS of the parietal region and in distinguishing MCS versus VS/UWS when TMS of the frontal region. Additionally, a positive correlation was observed between the Coma Recovery Scale-Revised scores of the DOC patients and the cortical theta reactivity.

CONCLUSIONS

The findings revealed a breakdown of oscillatory effective networks in DOC patients, which has implications for the use of TMS-EEG in DOC evaluation and offers a neural oscillation viewpoint on the neurological basis of human consciousness.

Two models of mind blanking

Mind blanking is a mental state in which attention does not bring any perceptual input into conscious awareness. As this state is still largely unexplored, we suggest that a comprehensive understanding of mind blanking can be achieved through a multifaceted approach combining self-assessment methods, neuroimaging and neuromodulation. In this article, we explain how electroencephalography and transcranial magnetic stimulation could be combined to help determine whether mind blanking is associated with a lack of mental content or a lack of linguistically or conceptually determinable mental content. We also question whether mind blanking occurs spontaneously or intentionally and whether these two forms are instantiated by the same or different neural correlates.

Prelimbic cortical pyramidal neurons to ventral tegmental area projections promotes arousal from sevoflurane anesthesia

AIMS

General anesthesia has been used in surgical procedures for approximately 180 years, yet the precise mechanism of anesthetic drugs remains elusive. There is significant anatomical connectivity between the ventral tegmental area (VTA) and the prelimbic cortex (PrL). Projections from VTA dopaminergic neurons (VTADA ) to the PrL play a role in the transition from sevoflurane anesthesia to arousal. It is still uncertain whether the prelimbic cortex pyramidal neuron (PrLPyr ) and its projections to VTA (PrLPyr -VTA) are involved in anesthesia-arousal regulation.

METHODS

We employed chemogenetics and optogenetics to selectively manipulate neuronal activity in the PrLPyr -VTA pathway. Electroencephalography spectra and burst-suppression ratios (BSR) were used to assess the depth of anesthesia. Furthermore, the loss or recovery of the righting reflex was monitored to indicate the induction or emergence time of general anesthesia. To elucidate the receptor mechanisms in the PrLPyr -VTA projection's impact on anesthesia and arousal, we microinjected NMDA receptor antagonists (MK-801) or AMPA receptor antagonists (NBQX) into the VTA.

RESULTS

Our findings show that chemogenetic or optogenetic activation of PrLPyr neurons prolonged anesthesia induction and promoted emergence. Additionally, chemogenetic activation of the PrLPyr -VTA neural pathway delayed anesthesia induction and promoted anesthesia emergence. Likewise, optogenetic activation of the PrLPyr -VTA projections extended the induction time and facilitated emergence from sevoflurane anesthesia. Moreover, antagonizing NMDA receptors in the VTA attenuates the delayed anesthesia induction and promotes emergence caused by activating the PrLPyr -VTA projections.

CONCLUSION

This study demonstrates that PrLPyr neurons and their projections to the VTA are involved in facilitating emergence from sevoflurane anesthesia, with the PrLPyr -VTA pathway exerting its effects through the activation of NMDA receptors within the VTA.

Dynamic nonreversibility view of intrinsic brain organization and brain dynamic analysis of repetitive transcranial magnitude stimulation

Intrinsic neural activities are characterized as endless spontaneous fluctuation over multiple time scales. However, how the intrinsic brain organization changes over time under local perturbation remains an open question. By means of statistical physics, we proposed an approach to capture whole-brain dynamics based on estimating time-varying nonreversibility and k-means clustering of dynamic varying nonreversibility patterns. We first used synthetic fMRI to investigate the effects of window parameters on the temporal variability of varying nonreversibility. Second, using real test-retest fMRI data, we examined the reproducibility, reliability, biological, and physiological correlation of the varying nonreversibility substates. Finally, using repetitive transcranial magnetic stimulation-fMRI data, we investigated the modulation effects of repetitive transcranial magnetic stimulation on varying nonreversibility substate dynamics. The results show that: (i) as window length increased, the varying nonreversibility variance decreased, while the sliding step almost did not alter it; (ii) the global high varying nonreversibility states and low varying nonreversibility states were reproducible across multiple datasets and different window lengths; and (iii) there were increased low varying nonreversibility states and decreased high varying nonreversibility states when the left frontal lobe was stimulated, but not the occipital lobe. Taken together, these results provide a thermodynamic equilibrium perspective of intrinsic brain organization and reorganization under local perturbation.

Consciousness and General Anesthesia: Challenges for Measuring the Depth of Anesthesia

The optimal consciousness level required for general anesthesia with surgery is unclear, but in existing practice, anesthetic oblivion, may be incomplete. This article discusses the concept of consciousness, how it is altered by anesthetics, the challenges for assessing consciousness, currently used technologies for assessing anesthesia levels, and future research directions. Wakefulness is marked by a subjective experience of existence (consciousness), perception of input from the body or the environment (connectedness), the ability for volitional responsiveness, and a sense of continuity in time. Anesthetic drugs may selectively impair some of these components without complete extinction of the subjective experience of existence. In agreement with Sanders et al. (2012), the authors propose that a state of disconnected consciousness is the optimal level of anesthesia, as it likely avoids both awareness and the possible dangers of oversedation. However, at present, there are no reliably tested indices that can discriminate between connected consciousness, disconnected consciousness, and complete unconsciousness.

Effect of cognitive load on time spent offline during wakefulness

Humans continuously alternate between online attention to the current environment and offline attention to internally generated thought and imagery. This may be a fundamental feature of the waking brain, but remains poorly understood. Here, we took a data-driven approach to defining online and offline states of wakefulness, using machine learning methods applied to measures of sensory responsiveness, subjective report, electroencephalogram (EEG), and pupil diameter. We tested the effect of cognitive load on the structure and prevalence of online and offline states, hypothesizing that time spent offline would increase as cognitive load of an ongoing task decreased. We also expected that alternation between online and offline states would persist even in the absence of a cognitive task. As in prior studies, we arrived at a three-state model comprised of one online state and two offline states. As predicted, when cognitive load was high, more time was spent online. Also as predicted, the same three states were present even when participants were not performing a task. These observations confirm our method is successful at isolating seconds-long periods of offline time. Varying cognitive load may be a useful way to manipulate time spent in at least one of these offline states in future experimental studies.

Research hotspots and frontiers of neuromodulation techniques in disorders of consciousness: a bibliometric analysis

Background

The characteristics of disorders of consciousness (DOC) are changes in arousal and/or awareness caused by severe brain injuries. To date, the management of DOC patients remains a complex and challenging task, and neuromodulation techniques offer a promising solution. However, a bibliometric analysis focusing on neuromodulation techniques in DOC is currently absent. The aim of this study is to provide a bibliometric visualization analysis to investigate the research hotspots and frontiers in the field of neuromodulation techniques in DOC from 2012 to 2022.

Methods

The publications were collected and retrieved from the Web of Science (WoS) from 2012 to 2022. CiteSpace and Microsoft Excel were utilized perform the first global bibliographic analysis of the literature related to neuromodulation techniques for DOC.

Results

The analysis included a total of 338 publications. From 2012 to 2022, a consistent yet irregular increase in the number of articles published on neuromodulation techniques in DOC was observed. Frontiers in Neurology published the highest number of papers (n = 16). Neurosciences represented the main research hotspot category (n = 170). The most prolific country, institution, and author were the USA (n = 105), the University of Liege (n = 41), and Laureys Steven (n = 38), respectively. An analysis of keywords revealed that UWS/VS, MCS, and TMS constituted the primary research trends and focal points within this domain.

Conclusion

This bibliometric study sheds light on the current progress and emerging trends of neuromodulation techniques in DOC from 2012 to 2022. The focal topics in this domain encompass the precise diagnosis of consciousness levels in patients suffering from DOC and the pursuit of efficacious neuromodulation-based evaluation and treatment protocols for such patients.

Neural effects of TMS trains on the human prefrontal cortex

How does a train of TMS pulses modify neural activity in humans? Despite adoption of repetitive TMS (rTMS) for the treatment of neuropsychiatric disorders, we still do not understand how rTMS changes the human brain. This limited understanding stems in part from a lack of methods for noninvasively measuring the neural effects of a single TMS train-a fundamental building block of treatment-as well as the cumulative effects of consecutive TMS trains. Gaining this understanding would provide foundational knowledge to guide the next generation of treatments. Here, to overcome this limitation, we developed methods to noninvasively measure causal and acute changes in cortical excitability and evaluated this neural response to single and sequential TMS trains. In 16 healthy adults, standard 10 Hz trains were applied to the dorsolateral prefrontal cortex in a randomized, sham-controlled, event-related design and changes were assessed based on the TMS-evoked potential (TEP), a measure of cortical excitability. We hypothesized that single TMS trains would induce changes in the local TEP amplitude and that those changes would accumulate across sequential trains, but primary analyses did not indicate evidence in support of either of these hypotheses. Exploratory analyses demonstrated non-local neural changes in sensor and source space and local neural changes in phase and source space. Together these results suggest that single and sequential TMS trains may not be sufficient to modulate local cortical excitability indexed by typical TEP amplitude metrics but may cause neural changes that can be detected outside the stimulation area or using phase or source space metrics. This work should be contextualized as methods development for the monitoring of transient noninvasive neural changes during rTMS and contributes to a growing understanding of the neural effects of rTMS.

Dissociation of Centrally and Peripherally Induced Transcranial Magnetic Stimulation Effects in Nonhuman Primates

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation method that is rapidly growing in popularity for studying causal brain-behavior relationships. However, its dose-dependent centrally induced neural mechanisms and peripherally induced sensory costimulation effects remain debated. Understanding how TMS stimulation parameters affect brain responses is vital for the rational design of TMS protocols. Studying these mechanisms in humans is challenging because of the limited spatiotemporal resolution of available noninvasive neuroimaging methods. Here, we leverage invasive recordings of local field potentials in a male and a female nonhuman primate (rhesus macaque) to study TMS mesoscale responses. We demonstrate that early TMS-evoked potentials show a sigmoidal dose-response curve with stimulation intensity. We further show that stimulation responses are spatially specific. We use several control conditions to dissociate centrally induced neural responses from auditory and somatosensory coactivation. These results provide crucial evidence regarding TMS neural effects at the brain circuit level. Our findings are highly relevant for interpreting human TMS studies and biomarker developments for TMS target engagement in clinical applications.SIGNIFICANCE STATEMENT Transcranial magnetic stimulation (TMS) is a widely used noninvasive brain stimulation method to stimulate the human brain. To advance its utility for clinical applications, a clear understanding of its underlying physiological mechanisms is crucial. Here, we perform invasive electrophysiological recordings in the nonhuman primate brain during TMS, achieving a spatiotemporal precision not available in human EEG experiments. We find that evoked potentials are dose dependent and spatially specific, and can be separated from peripheral stimulation effects. This means that TMS-evoked responses can indicate a direct physiological stimulation response. Our work has important implications for the interpretation of human TMS-EEG recordings and biomarker development.

The nature of consciousness in anaesthesia

Neuroscientists agree on the value of locating the source of consciousness within the brain. Anaesthesiologists are no exception, and have their own operational definition of consciousness based on phenomenological observations during anaesthesia. The full functional correlates of consciousness are yet to be precisely identified, however rapidly evolving progress in this scientific domain has yielded several theories that attempt to model the generation of consciousness. They have received variable support from experimental observations, including those involving anaesthesia and its ability to reversibly modulate different aspects of consciousness. Aside from the interest in a better understanding of the mechanisms of consciousness, exploring the functional tenets of the phenomenological consciousness states of general anaesthesia has the potential to ultimately improve patient management. It could facilitate the design of specific monitoring devices and approaches, aiming at reliably detecting each of the possible states of consciousness during an anaesthetic procedure, including total absence of mental content (unconsciousness), and internal awareness (sensation of self and internal thoughts) with or without conscious perception of the environment (connected or disconnected consciousness, respectively). Indeed, it must be noted that unresponsiveness is not sufficient to infer absence of connectedness or even absence of consciousness. This narrative review presents the current knowledge in this field from a system-level, underlining the contribution of anaesthesia studies in supporting theories of consciousness, and proposing directions for future research.

Violations of the fluctuation-dissipation theorem reveal distinct nonequilibrium dynamics of brain states

The brain is a nonequilibrium system whose dynamics change in different brain states, such as wakefulness and deep sleep. Thermodynamics provides the tools for revealing these nonequilibrium dynamics. We used violations of the fluctuation-dissipation theorem to describe the hierarchy of nonequilibrium dynamics associated with different brain states. Together with a whole-brain model fitted to empirical human neuroimaging data, and deriving the appropriate analytical expressions, we were able to capture the deviation from equilibrium in different brain states that arises from asymmetric interactions and hierarchical organization.

Differential cortical network engagement during states of un/consciousness in humans

What happens in the human brain when we are unconscious? Despite substantial work, we are still unsure which brain regions are involved and how they are impacted when consciousness is disrupted. Using intracranial recordings and direct electrical stimulation, we mapped global, network, and regional involvement during wake vs. arousable unconsciousness (sleep) vs. non-arousable unconsciousness (propofol-induced general anesthesia). Information integration and complex processing we`re reduced, while variability increased in any type of unconscious state. These changes were more pronounced during anesthesia than sleep and involved different cortical engagement. During sleep, changes were mostly uniformly distributed across the brain, whereas during anesthesia, the prefrontal cortex was the most disrupted, suggesting that the lack of arousability during anesthesia results not from just altered overall physiology but from a disconnection between the prefrontal and other brain areas. These findings provide direct evidence for different neural dynamics during loss of consciousness compared with loss of arousability.

TMS of parietal and occipital cortex locked to spontaneous transient large-scale brain states enhances natural oscillations in EEG

BACKGROUND

Fluctuating neuronal network states influence brain responses to transcranial magnetic stimulation (TMS). Our previous studies revealed that transient spontaneous bihemispheric brain states in the EEG, driven by oscillatory power, information flow and regional domination, modify cortical EEG responses to TMS. However, the impact of ongoing fluctuations of large-scale brain network states on TMS-EEG responses has not been explored.

OBJECTIVES

To determine the effects of large-scale brain network states on TMS-EEG responses.

METHODS

Resting-state EEG and structural MRI from 24 healthy subjects were recorded to infer large-scale brain states. TMS-EEG was acquired with TMS at state-related targets, identified by the spatial distribution of state activation power from resting-state EEG. TMS-induced oscillations were measured by event-related spectral perturbations (ERSPs), and classified with respect to the brain states preceding the TMS pulses. State-locked ERSPs with TMS at specific state-related targets and during state activation were compared with state-unlocked ERSPs.

RESULTS

Intra-individual comparison of ERSPs by threshold free cluster enhancement (TFCE) revealed that posterior and visual state-locked TMS, respectively, increased beta and alpha responses to TMS of parietal and occipital cortex compared to state-unlocked TMS. Also, the peak frequencies of ERSPs were increased with state-locked TMS. In addition, inter-individual correlation analyses revealed that posterior and visual state-locked TMS-induced oscillation power (ERSP clusters identified by TFCE) positively correlated with state-dependent oscillation power preceding TMS.

CONCLUSIONS

Spontaneous transient large-scale brain network states modify TMS-induced natural oscillations in specific brain regions. This significantly extends our knowledge on the critical importance of instantaneous state on explaining the brain's varying responsiveness to external perturbation.

Evaluating the effect of spinal cord stimulation on patient with disorders of consciousness: A TMS-EEG study

OBJECTIVE

The application of spinal cord stimulation (SCS) in the treatment of disorders of consciousness (DOC) has attracted attention, but its effect on brain activity is still unknown. Transcranial magnetic stimulation combined with EEG (TMS-EEG) can measure cortical activity, which can evaluate the effect of SCS on DOC.

METHODS

We record 20 DOC patients' CRS-R values and TMS-EEG data before and after one-session SCS (Pre-SCS and Post-SCS). 20 DOC patients including 10 patients with unresponsive wakefulness syndrome (UWS) and 10 patients with minimally conscious states (MCS). TMS evoked potential (TEP) was used to measure the changes of cortical activity in DOC patients between Pre-SCS and Post-SCS. Firstly, we used the global mean field potential (GMFP) and fast perturbational complexity index (PCIst) to compare the temporal changes of patients' cortical activity. Then, we obtained the frequency feature (natural frequency, NF) based on the TEP time-frequency analysis, and compared the changes of natural frequency between Pre-SCS and Post-SCS. Finally, the study explored the relationship between the patient's baseline CRS-R values and changes of TMS evoked cortical activity in time and frequency domains.

RESULTS

After SCS, MCS and UWS groups almost have no changes of CRS-R values (MCS: 9.9 ± 1.52 at Pre-SCS, 10.2 ± 1.48 at Post-SCS; UWS: 5.6 ± 1.26 at Pre-SCS, 5.7 ± 1.34 at Post-SCS). MCS group showed significant increases of GMFP amplitude (around 100 ms and 300 ms) and PCIst values at Post-SCS (p < 0.05). UWS group had no significant changes (p > 0.05). Besides, SCS induced the significant increases of natural frequency for MCS group(p < 0.05), but not for UWS group. At last, the study found that all patient's baseline CRS-R values were significantly correlated with ΔPCIst (r = 0.67, p < 0.005), and ΔNF (r = 0.72, p < 0.001).

CONCLUSIONS

SCS can modulate cortical activity of DOC patient, including temporal complexity and natural frequency. The changes of cortical activity caused by SCS are related to patients' consciousness level. TMS-EEG can evaluate the effect of SCS on DOC patients.

Is Target-Based Drug Discovery Efficient? Discovery and "Off-Target" Mechanisms of All Drugs

Target-based drug discovery is the dominant paradigm of drug discovery; however, a comprehensive evaluation of its real-world efficiency is lacking. Here, a manual systematic review of about 32000 articles and patents dating back to 150 years ago demonstrates its apparent inefficiency. Analyzing the origins of all approved drugs reveals that, despite several decades of dominance, only 9.4% of small-molecule drugs have been discovered through "target-based" assays. Moreover, the therapeutic effects of even this minimal share cannot be solely attributed and reduced to their purported targets, as they depend on numerous off-target mechanisms unconsciously incorporated by phenotypic observations. The data suggest that reductionist target-based drug discovery may be a cause of the productivity crisis in drug discovery. An evidence-based approach to enhance efficiency seems to be prioritizing, in selecting and optimizing molecules, higher-level phenotypic observations that are closer to the sought-after therapeutic effects using tools like artificial intelligence and machine learning.

Analogous cortical reorganization accompanies entry into states of reduced consciousness during anesthesia and sleep

Theories of consciousness suggest that brain mechanisms underlying transitions into and out of unconsciousness are conserved no matter the context or precipitating conditions. We compared signatures of these mechanisms using intracranial electroencephalography in neurosurgical patients during propofol anesthesia and overnight sleep and found strikingly similar reorganization of human cortical networks. We computed the "effective dimensionality" of the normalized resting state functional connectivity matrix to quantify network complexity. Effective dimensionality decreased during stages of reduced consciousness (anesthesia unresponsiveness, N2 and N3 sleep). These changes were not region-specific, suggesting global network reorganization. When connectivity data were embedded into a low-dimensional space in which proximity represents functional similarity, we observed greater distances between brain regions during stages of reduced consciousness, and individual recording sites became closer to their nearest neighbors. These changes corresponded to decreased differentiation and functional integration and correlated with decreases in effective dimensionality. This network reorganization constitutes a neural signature of states of reduced consciousness that is common to anesthesia and sleep. These results establish a framework for understanding the neural correlates of consciousness and for practical evaluation of loss and recovery of consciousness.

Auditory white noise exposure results in intrinsic cortical excitability changes

Cortical excitability is commonly measured by applying magnetic stimulation in combination with measuring behavioral response. This measure has, however, some shortcomings including spatial limitation to the primary motor cortex and not accounting for intrinsic excitability fluctuations. Here, we use a measure for intrinsic excitability based on phase synchronization previously validated for epilepsy. We apply this measure in 30 healthy participants' magnetoencephalography (MEG) recordings during the exposure of auditory white noise, a stimulus that has been suggested to modify cortical excitability. Using cortical parcellation of the MEG source data, we could find a specific pattern of increased and decreased excitability while participants are exposed to white noise vs. silence. Specifically, excitability during white noise exposure decreases in the frontal lobe and increases in the temporal lobe. This study thus adds to the understanding of cortical excitability changes due to specific environmental stimuli as well as the spatial extent of these effects.

Assessing Consciousness through Neurofeedback and Neuromodulation: Possibilities and Challenges

Neurofeedback is a non-invasive therapeutic approach that has gained traction in recent years, showing promising results for various neurological and psychiatric conditions. It involves real-time monitoring of brain activity, allowing individuals to gain control over their own brainwaves and improve cognitive performance or alleviate symptoms. The use of electroencephalography (EEG), such as brain-computer interface (BCI), transcranial direct current stimulation (tDCS), and transcranial magnetic stimulation (TMS), has been instrumental in developing neurofeedback techniques. However, the application of these tools in patients with disorders of consciousness (DoC) presents unique challenges. In this narrative review, we explore the use of neurofeedback in treating patients with DoC. More specifically, we discuss the advantages and challenges of using tools such as EEG neurofeedback, tDCS, TMS, and BCI for these conditions. Ultimately, we hope to provide the neuroscientific community with a comprehensive overview of neurofeedback and emphasize its potential therapeutic applications in severe cases of impaired consciousness levels.

Reliability and Validity of Transcranial Magnetic Stimulation-Electroencephalography Biomarkers

Noninvasive brain stimulation and neuroimaging have revolutionized human neuroscience with a multitude of applications, including diagnostic subtyping, treatment optimization, and relapse prediction. It is therefore particularly relevant to identify robust and clinically valuable brain biomarkers linking symptoms to their underlying neural mechanisms. Brain biomarkers must be reproducible (i.e., have internal reliability) across similar experiments within a laboratory and be generalizable (i.e., have external reliability) across experimental setups, laboratories, brain regions, and disease states. However, reliability (internal and external) is not alone sufficient; biomarkers also must have validity. Validity describes closeness to a true measure of the underlying neural signal or disease state. We propose that these metrics, reliability and validity, should be evaluated and optimized before any biomarker is used to inform treatment decisions. Here, we discuss these metrics with respect to causal brain connectivity biomarkers from coupling transcranial magnetic stimulation (TMS) with electroencephalography (EEG). We discuss controversies around TMS-EEG stemming from the multiple large off-target components (noise) and relatively weak genuine brain responses (signal), as is unfortunately often the case in noninvasive human neuroscience. We review the current state of TMS-EEG recordings, which consist of a mix of reliable noise and unreliable signal. We describe methods for evaluating TMS-EEG biomarkers, including how to assess internal and external reliability across facilities, cognitive states, brain networks, and disorders and how to validate these biomarkers using invasive neural recordings or treatment response. We provide recommendations to increase reliability and validity, discuss lessons learned, and suggest future directions for the field.

The Current of Consciousness: Neural Correlates and Clinical Aspects

PURPOSE OF REVIEW

In this review, we summarize the current understanding of consciousness including its neuroanatomic basis. We discuss major theories of consciousness, physical exam-based and electroencephalographic metrics used to stratify levels of consciousness, and tools used to shed light on the neural correlates of the conscious experience. Lastly, we review an expanded category of 'disorders of consciousness,' which includes disorders that impact either the level or experience of consciousness.

RECENT FINDINGS

Recent studies have revealed many of the requisite EEG, ERP, and fMRI signals to predict aspects of the conscious experience. Neurological disorders that disrupt the reticular activating system can affect the level of consciousness, whereas cortical disorders from seizures and migraines to strokes and dementia may disrupt phenomenal consciousness. The recently introduced memory theory of consciousness provides a new explanation of phenomenal consciousness that may explain better than prior theories both experimental studies and the neurologist's clinical experience. Although the complete neurobiological basis of consciousness remains a mystery, recent advances have improved our understanding of the physiology underlying level of consciousness and phenomenal consciousness.

The Conscious Nematode: Exploring Hallmarks of Minimal Phenomenal Consciousness in Caenorhabditis Elegans

While subcellular components of cognition and affectivity that involve the interaction between experience, environment, and physiology -such as learning, trauma, or emotion- are being identified, the physical mechanisms of phenomenal consciousness remain more elusive. We are interested in exploring whether ancient, simpler organisms such as nematodes have minimal consciousness. Is there something that feels like to be a worm? Or are worms blind machines? 'Simpler' models allow us to simultaneously extract data from multiple levels such as slow and fast neural dynamics, structural connectivity, molecular dynamics, behavior, decision making, etc., and thus, to test predictions of the current frameworks in dispute. In the present critical review, we summarize the current models of consciousness in order to reassess in light of the new evidence whether Caenorhabditis elegans, a nematode with a nervous system composed of 302 neurons, has minimal consciousness. We also suggest empirical paths to further advance consciousness research using C. elegans.

Cortico-thalamo-cortical interactions modulate electrically evoked EEG responses in mice

Perturbational complexity analysis predicts the presence of consciousness in volunteers and patients by stimulating the brain with brief pulses, recording EEG responses, and computing their spatiotemporal complexity. We examined the underlying neural circuits in mice by directly stimulating cortex while recording with EEG and Neuropixels probes during wakefulness and isoflurane anesthesia. When mice are awake, stimulation of deep cortical layers reliably evokes locally a brief pulse of excitation, followed by a biphasic sequence of 120 ms profound off period and a rebound excitation. A similar pattern, partially attributed to burst spiking, is seen in thalamic nuclei and is associated with a pronounced late component in the evoked EEG. We infer that cortico-thalamo-cortical interactions drive the long-lasting evoked EEG signals elicited by deep cortical stimulation during the awake state. The cortical and thalamic off period and rebound excitation, and the late component in the EEG, are reduced during running and absent during anesthesia.

About the compatibility between the perturbational complexity index and the global neuronal workspace theory of consciousness

This paper investigates the compatibility between the theoretical framework of the global neuronal workspace theory (GNWT) of conscious processing and the perturbational complexity index (PCI). Even if it has been introduced within the framework of a concurrent theory (i.e. Integrated Information Theory), PCI appears, in principle, compatible with the main tenet of GNWT, which is a conscious process that depends on a long-range connection between different cortical regions, more specifically on the amplification, global propagation, and integration of brain signals. Notwithstanding this basic compatibility, a number of limited compatibilities and apparent differences emerge. This paper starts from the description of brain complexity, a notion that is crucial for PCI, to then summary of the main features of PCI and the main tenets of GNWT. Against this background, the text explores the compatibility between PCI and GNWT. It concludes that GNWT and PCI are fundamentally compatible, even though there are some partial disagreements and some points to further examine.

Tonic down-rolling and eccentric down-positioning of eyes under sevoflurane anesthesia without non-depolarizing muscle relaxant and its relationship with depth of anesthesia

Purpose

To analyze the relationship between eccentric downward eye movement/eccentric downward eye-positioning (EDEM/EDEP) encountered in patients undergoing ophthalmic surgeries and its return to a centralized position under general anesthesia (GA) with the depth of anesthesia (DOA).

Methods

Patients undergoing ophthalmic surgeries (6 months-12 years) under sevoflurane anesthesia without non-depolarizing muscle relaxant (NDMR) who witnessed a sudden tonic EDEM/EDEP were both retrospectively (R-group) and prospectively (P-group) enrolled (ambispective study). R-group included data-points after induction (AI) till the time surgery lasted while P-group compiled data both during induction (DI) and AI. DOA in terms of MAC (minimum alveolar concentration) at the time of EDEM/EDEP and centralization of eyeball and their timings were noted and compared for both AI and DI data-points. Also, vertical eccentric eye positions were scored and correlated with MAC.

Results

AI data included 22 (14R+8P) events and their mean MAC of EDEM/EDEP and centralization were 1.60 ± 0.25 and 1.18 ± 0.17 respectively (p = 0.000). DI data included 62 (P) cases and its mean MAC of EDEM/EDEP and centralization was 2.19 ± 0.43 and 1.39 ± 0.26 respectively (p = 0.000). Median (IQR) eye positions during down-positioning in 84 events was -3 (-3.9 to -2.5). It was preceded by an eccentric upward drift of eyes in 10/22 (6R+4P) AI cases. A strong negative correlation was seen between DOA and eccentric eye positions (r = -0.77, p = 0.000).

Conclusions

Tonic down-rolling of eyes is not uncommon in children seen without NDMR with higher depths of sevoflurane anesthesia compared to point of centralization and fluctuations in DOA should be avoided to circumvent inadvertent complications during ocular surgery.

Abnormal functional asymmetry and its behavioural correlates in adults with ADHD: A TMS-EEG study

OBJECTIVES

Abnormal functional brain asymmetry and deficient response inhibition are two core symptoms of attention deficit hyperactivity disorder (ADHD). We investigated whether these symptoms are inter-related and whether they are underlined by altered frontal excitability and by compromised interhemispheric connectivity.

METHODS

We studied these issues in 52 ADHD and 43 non-clinical adults by comparing: (1) stop-signal reaction time (SSRT); (2) frontal asymmetry of the N200 event-related potential component, which is evoked during response inhibition and is lateralised to the right hemisphere; (3) TMS-evoked potential (TEP) in the right frontal hemisphere, which is indicative of local cortical excitability; and (4) frontal right-to-left interhemispheric TMS signal propagation (ISP), which is reversely indicative of interhemispheric connectivity.

RESULTS

Compared to controls, the ADHD group demonstrated elongated SSRT, reduced N200 right-frontal-asymmetry, weaker TEP, and stronger ISP. Moreover, in the ADHD group, N200 right-frontal-asymmetry correlated with SSRT, with TEP, and with symptoms severity. Conversely, no relationship was observed between ISP and N200 right-frontal-asymmetry, and both TEP and ISP were found to be unrelated to SSRT.

CONCLUSIONS

Our results indicate that abnormal frontal asymmetry is related to a key cognitive symptom in ADHD and suggest that it is underlined by reduced right-frontal excitability.

Electroencephalography characteristics of patients with supratentorial glioma in different consciousness states induced by propofol

Gliomas are the most common primary intracranial malignant tumors. Some of these patients exhibit previously clinically undetected neurological deficits after sedation. The absence of neurophysiological evidence for this phenomenon limits the use of time-sensitive monitoring methods. The study aims to compare differences between glioma patients under sedation and those without intracranial lesions by comparing their EEG features. Twenty-one patients without intracranial tumors and 21 with frontal lobe supratentorial gliomas were enrolled. The EEG power spectrum of the glioma group was comparable to that of the control group for both sides of the brain (P>0.05 for all frequencies). Compared with those without intracranial lesions, the weighted phase lag index (wPLI) in the alpha and beta bands on the non-occupied side decreased. Glioma patients had weaker functional connectivity during sedation than patients without intracranial lesions, manifesting as reduced functional connectivity on the non-occupied side.

EEG complexity correlates with residual consciousness level of disorders of consciousness

BACKGROUND AND OBJECTIVE

Electroencephalography (EEG) and neuroimaging measurements have been highly encouraged to be applied in clinics of disorders of consciousness (DOC) to improve consciousness detection. We tested the relationships between neural complexity measured on EEG and residual consciousness levels in DOC patients.

METHODS

Resting-state EEG was recorded from twenty-five patients with DOC. Lempel-Ziv complexity (LZC) and permutation Lempel-Ziv complexity (PLZC) were measured on the EEG, and their relationships were analyzed with the consciousness levels of the patients.

RESULTS

PLZC and LZC values significantly distinguished patients with a minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/UWS), and healthy controls. PLZC was significantly correlated with the Coma Recovery Scale-Revised (CRS-R) scores of DOC patients in the global brain, particularly in electrodes locating in the anterior and posterior brain regions. Patients with higher CRS-R scores showed higher PLZC values. The significant difference in PLZC values between MCS and VS/UWS was mainly located in the bilateral frontal and right hemisphere regions.

CONCLUSION

Neural complexity measured on EEG correlates with residual consciousness levels of DOC patients. PLZC showed higher sensitivity than LZC in the classification of consciousness levels.

Sensory modality defines the relation between EEG Lempel-Ziv diversity and meaningfulness of a stimulus

Diversity of brain activity is a robust neural correlate of global states of consciousness. It has been proposed that diversity measures specifically reflect the temporal variability of conscious experience. Previous studies supported this hypothesis by showing that perception of meaningful visual stimuli causes richer, more-variable experiences than perception of meaningless stimuli, and this is reflected in greater brain signal diversity. To investigate whether this relation is consistent across sensory modalities, to participants we presented three versions of naturalistic visual and auditory stimuli (videos and audiobooks) that varied in the amount of meaning (original, scrambled, and noise), while recording electroencephalographic signals. We report three main findings. First, greater meaningfulness of visual stimuli was related to higher Lempel-Ziv diversity of EEG signals, but the opposite effect was found in the auditory modality. Second, visual perception was related to generally higher EEG diversity than auditory perception. Third, perception of meaningful visual stimuli and auditory stimuli respectively resulted in higher and lower EEG diversity in comparison to the resting state. In conclusion, the signal diversity of continuous brain signals depends on the stimulated sensory modality, therefore it is not a generic index of the variability of conscious experience.

Neuroprotection of Low-Frequency Repetitive Transcranial Magnetic Stimulation after Ischemic Stroke in Rats

OBJECTIVE

Stroke is a leading cause of human death and disability. Effective early treatments with reasonable therapeutic windows remain critically important to improve the outcomes of stroke. Transcranial magnetic stimulation (TMS) is an established noninvasive technique that has been applied clinically and in animal research for multiple brain disorders, but few studies have examined acute neuroprotection against ischemic stroke. The present investigation tested the novel approach of low-frequency repetitive TMS (rTMS) as an acute treatment after ischemic stroke.

METHODS

Adult male rats received focal ischemic surgery through occlusion of the right middle cerebral artery for 60 minutes. The rats received either rTMS or sham treatment with 1.5-, 3-, 4-, or 7-hour delay after the onset of stroke. Low-frequency and low-intensity rTMS was applied to the rat brain for two 30-minute episodes separated by a 1-hour interval.

RESULTS

Three days after stroke, compared to stroke controls, rats receiving rTMS treatment with a 1.5-hour delay showed a 35% reduction of infarct volume. Protective effects were also seen with 3- or 4-hour-delayed treatments by rTMS, shown as reduced infarct volume and cell death. rTMS treatment upregulated the antiapoptotic factor Bcl-2 and downregulated the proapoptotic caspase-3 cleavage, expressions of Bax and matrix metallopeptidase-9. In sensorimotor functional assessments 3 to 21 days after stroke, rats receiving rTMS treatment with a 1.5- or 3-hour delay showed significantly better performance compared to stroke controls.

INTERPRETATION

These results support the inference that low-frequency rTMS may be feasible as a neuroprotective acute treatment after ischemic stroke. ANN NEUROL 2023;93:336-347.

Measure functional network and cortical excitability in post-anoxic patients with unresponsive wakefulness syndrome diagnosed by behavioral scales

Background

Brain assessment shows great values in prognosis, treatment, resource allocation, and decision-making for patients with disorders of consciousness (DOC). However, less research focused on cortical conditions of patients with unresponsive wakefulness syndrome (UWS).

Methods

We recorded resting-state EEG and TMS-EEG from post-anoxic patients with UWS, diagnosed by repeated Coma Recovery Scale-Revised (CRS-R). Measurements of functional connectivity and networks were performed by phase lock value (PLV) and network parameters of graph theory (average path length, clustering coefficient, and small-world). Global cortical reactivity values (GCRV) were used to assess cortical excitability.

Results

The coefficient of variation (CV) presented marked inter-individual variations of PLV (CV = 0.285), network parameters (CV > 0.2), and GCRV (CV = 0.929) within these patients. The patients' PLV and network parameters at theta and alpha bands significantly correlated with their GCRV values. Patients with higher PLV (r = 0.560, 0.406), as well as better preserved network (lower average path length (r = -0.522, -0.483), higher clustering coefficient (r = 0.522, 0.445), and small-world (r = 0.522, 0.445) at theta and alpha bands, presented higher GCRV. The functional connectivity, which is significantly correlated with frontal GCRV, is also mainly located in the frontal region. These correlations were not significant at other frequency bands: Delta, beta, and gamma bands.

Conclusion

These findings suggested that the CRS-R-diagnosed post-anoxic patients with UWS had very different cortical conditions. Functional networks and cortical excitability measured by TMS-EEG could complement behavioral assessment to assess these patients' cortical conditions.

Significance

It provides a deeper understanding of neurophysiological dysfunction in patients with UWS and hints to the clinics that neural-electrophysiological assessment for such patients may be necessary to acquire their brain conditions, which may benefit stratified management for them.

What Is Known about Midazolam? A Bibliometric Approach of the Literature

Midazolam is a drug with actions towards the central nervous system producing sedative and anticonvulsants effects, used for sedation and seizures treatments. A better understanding about its effects in the different scenarios presented in the literature could be helpful to gather information regarding its clinical indications, pharmacological interactions, and adverse events. From this perspective, the aim of this study was to analyze the global research about midazolam mapping, specifically the knowledge of the 100 most-cited papers about this research field. For this, a search was executed on the Web of Science-Core Collection database using bibliometric methodological tools. The search strategy retrieved 34,799 articles. A total of 170 articles were evaluated, with 70 articles being excluded for not meeting the inclusion criteria. The 100 most-cited articles rendered 42,480 citations on WoS-CC, ranging from 253 to 1744. Non-systematic review was the most published study type, mainly from North America, during the period of 1992 to 2002. The most frequent keywords were midazolam and pharmacokinetics. Regarding the authors, Thummel and Kunze were the ones with the greatest number of papers included. Our findings showed the global research trends about midazolam, mainly related to its different effects and uses throughout the time.

Source-based artifact-rejection techniques for TMS-EEG

Neuronal electroencephalography (EEG) signals arise from the cortical postsynaptic currents. Due to the conductive properties of the head, these neuronal sources produce relatively smeared spatial patterns in EEG. We can model these topographies to deduce which signals reflect genuine TMS-evoked cortical activity and which data components are merely noise and artifacts. This review will concentrate on two source-based artifact-rejection techniques developed for TMS-EEG data analysis, signal-space-projection-source-informed reconstruction (SSP-SIR), and the source-estimate-utilizing noise-discarding algorithm (SOUND). The former method was designed for rejecting TMS-evoked muscle artifacts, while the latter was developed to suppress noise signals from EEG and magnetoencephalography (MEG) in general. We shall cover the theoretical background for both methods, but most importantly, we will describe some essential practical perspectives for using these techniques effectively. We demonstrate and explain what approaches produce the most reliable inverse estimates after cleaning the data or how to perform non-biased comparisons between cleaned datasets. All noise-cleaning algorithms compromise the signals of interest to a degree. We elaborate on how the source-based methods allow objective quantification of the overcorrection. Finally, we consider possible future directions. While this article concentrates on TMS-EEG data analysis, many theoretical and practical aspects, presented here, can be readily applied in other EEG/MEG applications. Overall, the source-based cleaning methods provide a valuable set of TMS-EEG preprocessing tools. We can objectively evaluate their performance regarding possible overcorrection. Furthermore, the overcorrection can always be taken into account to compare cleaned datasets reliably. The described methods are based on current electrophysiological and anatomical understanding of the head and the EEG generators; strong assumptions of the statistical properties of the noise and artifact signals, such as independence, are not needed.

Deep brain stimulation improves electroencephalogram functional connectivity of patients with minimally conscious state

AIM

Deep brain stimulation (DBS) is a potential neuromodulatory therapy that enhances recovery from disorders of consciousness, especially minimally conscious state (MCS). This study measured the effects of DBS on the brain and explored the underlying mechanisms of DBS on MCS.

METHODS

Nine patients with MCS were recruited for this study. The neuromodulation effects of 100 Hz DBS were explored via cross-control experiments. Coma Recovery Scale-Revised (CRS-R) and EEG were recorded, and corresponding functional connectivity and network parameters were calculated.

RESULTS

Our results showed that 100 Hz DBS could improve the functional connectivity of the whole, local and local-local brain regions, while no significant change in EEG functional connectivity was observed in sham DBS. The whole brain's network parameters (clustering coefficient, path length, and small world characteristic) were significantly improved. In addition, a significant increase in the CRS-R and functional connectivity of three MCS patients who received 100 Hz DBS for 6 months were observed.

CONCLUSION

This study showed that DBS improved EEG functional connectivity and brain networks, indicating that the long-term use of DBS could improve the level of consciousness of MCS patients.

Strength-dependent perturbation of whole-brain model working in different regimes reveals the role of fluctuations in brain dynamics

Despite decades of research, there is still a lack of understanding of the role and generating mechanisms of the ubiquitous fluctuations and oscillations found in recordings of brain dynamics. Here, we used whole-brain computational models capable of presenting different dynamical regimes to reproduce empirical data's turbulence level. We showed that the model's fluctuations regime fitted to turbulence more faithfully reproduces the empirical functional connectivity compared to oscillatory and noise regimes. By applying global and local strength-dependent perturbations and subsequently measuring the responsiveness of the model, we revealed each regime's computational capacity demonstrating that brain dynamics is shifted towards fluctuations to provide much-needed flexibility. Importantly, fluctuation regime stimulation in a brain region within a given resting state network modulates that network, aligned with previous empirical and computational studies. Furthermore, this framework generates specific, testable empirical predictions for human stimulation studies using strength-dependent rather than constant perturbation. Overall, the whole-brain models fitted to the level of empirical turbulence together with functional connectivity unveil that the fluctuation regime best captures empirical data, and the strength-dependent perturbative framework demonstrates how this regime provides maximal flexibility to the human brain.

Differential Alterations to the Metabolic Connectivity of the Cortical and Subcortical Regions in Rat Brain During Ketamine-Induced Unconsciousness

BACKGROUND

Ketamine anesthesia increased glucose metabolism in most brain regions compared to another intravenous anesthetic propofol. However, whether the changes in cerebral metabolic networks induced by ketamine share the same mechanism with propofol remains to be explored. The purpose of the present study was to identify specific features of metabolic network in rat brains during ketamine-induced subanesthesia state and anesthesia state compared to awake state.

METHODS

We acquired fluorodeoxyglucose positron emission tomography (FDG-PET) images in 20 healthy adult Sprague-Dawley rats that were intravenously administrated saline and ketamine to achieve different conscious states: awake (normal saline), subanesthesia (30 mg kg -1 h -1 ), and anesthesia (160 mg kg -1 h -1 ). Based on the FDG-PET data, the alterations in cerebral glucose metabolism and metabolic topography were investigated by graph-theory analysis.

RESULTS

The baseline metabolism in rat brains was found significantly increased during ketamine-induced subanesthesia and anesthesia. The graph-theory analysis manifested a reduction in metabolism connectivity and network global/local efficiency across cortical regions and an increase across subcortical regions during ketamine-induced anesthesia (nonparametric permutation test: global efficiency between awake and anesthesia, cortex: P = .016, subcortex: P = .015; global efficiency between subanesthesia and anesthesia, subcortex: P = .012).

CONCLUSIONS

Ketamine broadly increased brain metabolism alongside decreased metabolic connectivity and network efficiency of cortex network. Modulation of these cortical metabolic networks may be a candidate mechanism underlying general anesthesia-induced loss of consciousness.

Non-Separability of Physical Systems as a Foundation of Consciousness

A hypothesis is presented that non-separability of degrees of freedom is the fundamental property underlying consciousness in physical systems. The amount of consciousness in a system is determined by the extent of non-separability and the number of degrees of freedom involved. Non-interacting and feedforward systems have zero consciousness, whereas most systems of interacting particles appear to have low non-separability and consciousness. By contrast, brain circuits exhibit high complexity and weak but tightly coordinated interactions, which appear to support high non-separability and therefore high amount of consciousness. The hypothesis applies to both classical and quantum cases, and we highlight the formalism employing the Wigner function (which in the classical limit becomes the Liouville density function) as a potentially fruitful framework for characterizing non-separability and, thus, the amount of consciousness in a system. The hypothesis appears to be consistent with both the Integrated Information Theory and the Orchestrated Objective Reduction Theory and may help reconcile the two. It offers a natural explanation for the physical properties underlying the amount of consciousness and points to methods of estimating the amount of non-separability as promising ways of characterizing the amount of consciousness.

Monitoring the Awake and Anesthetized Unconscious States Using Bispectral Index and Electroencephalographic Connectivity Measures

Objective. Our objective was to compare three electroencephalography (EEG)-based methods with anesthesiologist clinical judgment of the awake and anesthetized unconscious states. Methods. EEG recorded from 25 channels and from four channel bilateral Bispectral index (BIS) electrodes were collected from 20 patients undergoing surgery with general anesthesia. To measure connectivity we applied Directed Transfer Function (DTF) in eight channels of the EEG, and extracted data from BIS over the same time segments. Shannon's entropy was applied to assess the complexity of the EEG signal. Discriminant analysis was used to evaluate the data in relation to clinical judgment. Results. Assessing anesthetic state relative clinical judgment, the bilateral BIS gave the highest accuracy (ACC) (95.4%) and lowest false positive discovery rate (FDR) (0.5%) . Equivalent DTF gave 94.5% for ACC and 2.6% for FDR. Combining all methods gave ACC = 94.9% and FDR = 1%. Generally, entropy scored lower on ACC and higher on FDR than the other methods (ACC 90.87% and FDR 4.6%). BIS showed at least a one minute delay in 18 of the 20 patients. Conclusions. Our results show that BIS and DTF both have a high ACC and low FDR. Because of time delays in BIS values, we recommend combining the two methods.

Are we really unconscious in “unconscious” states? Common assumptions revisited

In the field of consciousness science, there is a tradition to categorize certain states such as slow-wave non-REM sleep and deep general anesthesia as “unconscious”. While this categorization seems reasonable at first glance, careful investigations have revealed that it is not so simple. Given that (1) behavioral signs of (un-)consciousness can be unreliable, (2) subjective reports of (un-)consciousness can be unreliable, and, (3) states presumed to be unconscious are not always devoid of reported experience, there are reasons to reexamine our traditional assumptions about “states of unconsciousness”. While these issues are not novel, and may be partly semantic, they have implications both for scientific progress and clinical practice. We suggest that focusing on approaches that provide a more pragmatic and nuanced characterization of different experimental conditions may promote clarity in the field going forward, and help us build stronger foundations for future studies.

Dynamic alpha-gamma phase-amplitude coupling signatures during sevoflurane-induced loss and recovery of consciousness

Phase-amplitude coupling (PAC) plays an important role in anesthetic-induced unconsciousness. The delta-alpha PAC signature during anesthetic-induced unconsciousness is gradually becoming known; however, the frequency dependence and spatial characteristics of PAC are still unclear. Multi-channel electroencephalography (EEG) was performed during the loss and recovery phases of consciousness in patients undergoing general anesthesia using sevoflurane. First, a spectral analysis was used to investigate the power change of the different frequency bands in the EEG signals. Second, PAC comodulogram analysis was performed to confirm the frequencies of the PAC phase drivers. Finally, to investigate the spatial characteristics of PAC, a novel PAC network was constructed using within- and cross-lead PAC, and a K-means clustering algorithm was used to identify PAC network patterns. Our results show that, in addition to the delta-alpha PAC, unconsciousness induced by sevoflurane was accompanied by spatial non-uniform alpha-gamma PAC in the cortical network, and dynamic PAC patterns between the anterior and posterior brain were observed during the unconscious phase. The dynamic transition of PAC network patterns indicates that brain states under sevoflurane-induced unconsciousness emerge from the regulation of functional integration and segregation instantiated by delta-alpha and alpha-gamma PAC.

Brain Complexities and Anesthesia: Their Meaning and Measurement

A complex system is often associated with emergence of new phenomena from the interactions between the system's components. General anesthesia reduces brain complexity and so inhibits the emergence of consciousness. An understanding of complexity is necessary for the interpretation of brain monitoring algorithms. Complexity indices capture the "difficulty" of understanding brain activity over time and/or space. Complexity-entropy plots reveal the types of complexity indices and their balance of randomness and structure. Lempel-Ziv complexity is a common index of temporal complexity for single-channel electroencephalogram containing both power spectral and nonlinear effects, revealed by phase-randomized surrogate data. Computing spatial complexities involves forming a connectivity matrix and calculating the complexity of connectivity patterns. Spatiotemporal complexity can be estimated in multiple ways including temporal or spatial concatenation, estimation of state switching, or integrated information. This article illustrates the concept and application of various complexities by providing working examples; a website with interactive demonstrations has also been created.