Neural correlates of consciousness: progress and problems

Neuroimaging biomarkers for the diagnosis and prognosis of patients with disorders of consciousness

The progress in neuroimaging and electrophysiological techniques has shown substantial promise in improving the clinical assessment of disorders of consciousness (DOC). Through the examination of both stimulus-induced and spontaneous brain activity, numerous comprehensive investigations have explored variations in brain activity patterns among patients with DOC, yielding valuable insights for clinical diagnosis and prognostic purposes. Nonetheless, reaching a consensus on precise neuroimaging biomarkers for patients with DOC remains a challenge. Therefore, in this review, we begin by summarizing the empirical evidence related to neuroimaging biomarkers for DOC using various paradigms, including active, passive, and resting-state approaches, by employing task-based fMRI, resting-state fMRI (rs-fMRI), electroencephalography (EEG), and positron emission tomography (PET) techniques. Subsequently, we conducted a review of studies examining the neural correlates of consciousness in patients with DOC, with the findings holding potential value for the clinical application of DOC. Notably, previous research indicates that neuroimaging techniques have the potential to unveil covert awareness that conventional behavioral assessments might overlook. Furthermore, when integrated with various task paradigms or analytical approaches, this combination has the potential to significantly enhance the accuracy of both diagnosis and prognosis in DOC patients. Nonetheless, the stability of these neural biomarkers still needs additional validation, and future directions may entail integrating diagnostic and prognostic methods with big data and deep learning approaches.

Interoceptive signals shape the earliest markers and neural pathway to awareness at the visual threshold

Variations in interoceptive signals from the baroreceptors (BRs) across the cardiac and respiratory cycle can modulate cortical excitability and so affect awareness. It remains debated at what stages of processing they affect awareness-related event-related potentials (ERPs) in different sensory modalities. We investigated the influence of the cardiac (systole/diastole) and the respiratory (inhalation/exhalation) phase on awareness-related ERPs. Subjects discriminated visual threshold stimuli while their electroencephalogram, electrocardiogram, and respiration were simultaneously recorded. We compared ERPs and their intracranial generators for stimuli classified correctly with and without awareness as a function of the cardiac and respiratory phase. Cyclic variations of interoceptive signals from the BRs modulated both the earliest electrophysiological markers and the trajectory of brain activity when subjects became aware of the stimuli: an early sensory component (P1) was the earliest marker of awareness for low (diastole/inhalation) and a perceptual component (visual awareness negativity) for high (systole/exhalation) BR activity, indicating that BR signals interfere with the sensory processing of the visual input. Likewise, activity spread from the primary visceral cortex (posterior insula) to posterior parietal cortices during high and from associative interoceptive centers (anterior insula) to the prefrontal cortex during low BR activity. Consciousness is thereby resolved in cognitive/associative regions when BR is low and in perceptual centers when it is high. Our results suggest that cyclic fluctuations of BR signaling affect both the earliest markers of awareness and the brain processes underlying conscious awareness.

Covert Consciousness in the ICU

OBJECTIVES

For critically ill patients with acute severe brain injuries, consciousness may reemerge before behavioral responsiveness. The phenomenon of covert consciousness (i.e., cognitive motor dissociation) may be detected by advanced neurotechnologies such as task-based functional MRI (fMRI) and electroencephalography (EEG) in patients who appear unresponsive on the bedside behavioral examination. In this narrative review, we summarize the state-of-the-science in ICU detection of covert consciousness. Further, we consider the prognostic and therapeutic implications of diagnosing covert consciousness in the ICU, as well as its potential to inform discussions about continuation of life-sustaining therapy for patients with severe brain injuries.

DATA SOURCES

We reviewed salient medical literature regarding covert consciousness.

STUDY SELECTION

We included clinical studies investigating the diagnostic performance characteristics and prognostic utility of advanced neurotechnologies such as task-based fMRI and EEG. We focus on clinical guidelines, professional society scientific statements, and neuroethical analyses pertaining to the implementation of advanced neurotechnologies in the ICU to detect covert consciousness.

DATA EXTRACTION AND DATA SYNTHESIS

We extracted study results, guideline recommendations, and society scientific statement recommendations regarding the diagnostic, prognostic, and therapeutic relevance of covert consciousness to the clinical care of ICU patients with severe brain injuries.

CONCLUSIONS

Emerging evidence indicates that covert consciousness is present in approximately 15-20% of ICU patients who appear unresponsive on behavioral examination. Covert consciousness may be detected in patients with traumatic and nontraumatic brain injuries, including patients whose behavioral examination suggests a comatose state. The presence of covert consciousness in the ICU may predict the pace and extent of long-term functional recovery. Professional society guidelines now recommend assessment of covert consciousness using task-based fMRI and EEG. However, the clinical criteria for patient selection for such investigations are uncertain and global access to advanced neurotechnologies is limited.

Beyond primary visual cortex: The leading role of lateral occipital complex in early conscious visual processing

The study of the neural substrates that serve conscious vision is one of the unsolved questions of cognitive neuroscience. So far, consciousness literature has endeavoured to disentangle which brain areas and in what order are involved in giving rise to visual awareness, but the problem of consciousness still remains unsolved. Availing of two different but complementary sources of data (i.e., Fast Optical Imaging and EEG), we sought to unravel the neural dynamics responsible for the emergence of a conscious visual experience. Our results revealed that conscious vision is characterized by a significant increase of activation in extra-striate visual areas, specifically in the Lateral Occipital Complex (LOC), and that, more interestingly, such activity occurred in the temporal window of the ERP component commonly thought to represent the electrophysiological signature of visual awareness, i.e., the Visual Awareness Negativity (VAN). Furthermore, Granger causality analysis, performed to further investigate the flow of activity occurring in the investigated areas, unveiled that neural processes relating to conscious perception mainly originated in LOC and subsequently spread towards visual and motor areas. In general, the results of the present study seem to advocate for an early contribution of LOC in conscious vision, thus suggesting that it could represent a reliable neural correlate of visual awareness. Conversely, striate visual areas, showing awareness-related activity only in later stages of stimulus processing, could be part of the cascade of neural events following awareness emergence.

Intracranial neural representation of phenomenal and access consciousness in the human brain

After more than 30 years of extensive investigation, impressive progress has been made in identifying the neural correlates of consciousness (NCC). However, the functional role of spatiotemporally distinct consciousness-related neural activity in conscious perception is debated. An influential framework proposed that consciousness-related neural activities could be dissociated into two distinct processes: phenomenal and access consciousness. However, though hotly debated, its authenticity has not been examined in a single paradigm with more informative intracranial recordings. In the present study, we employed a visual awareness task and recorded the local field potential (LFP) of patients with electrodes implanted in cortical and subcortical regions. Overall, we found that the latency of visual awareness-related activity exhibited a bimodal distribution, and the recording sites with short and long latencies were largely separated in location, except in the lateral prefrontal cortex (lPFC). The mixture of short and long latencies in the lPFC indicates that it plays a critical role in linking phenomenal and access consciousness. However, the division between the two is not as simple as the central sulcus, as proposed previously. Moreover, in 4 patients with electrodes implanted in the bilateral prefrontal cortex, early awareness-related activity was confined to the contralateral side, while late awareness-related activity appeared on both sides. Finally, Granger causality analysis showed that awareness-related information flowed from the early sites to the late sites. These results provide the first LFP evidence of neural correlates of phenomenal and access consciousness, which sheds light on the spatiotemporal dynamics of NCC in the human brain.

Decreased Delta/Beta ratio index as the sleep state-independent electrophysiological signature of sleep state misperception in Insomnia disorder: A focus on the sleep onset and the whole night

PURPOSE

Sleep State Misperception (SSM) is described as the tendency of Insomnia Disorder (ID) patients to overestimate Sleep Latency (SL) and underestimate Total Sleep Time (TST). Literature exploring topographical components in ID with SSM is scarce and does not allow us to fully understand the potential mechanisms underlying this phenomenon. This study aims to evaluate the existence of sleep EEG topography alterations in ID patients associated with SSM compared to Healthy Controls (HC), focusing on two distinct periods: the Sleep Onset (SO) and the whole night.

METHODS

Twenty ID patients (mean age: 43.5 ± 12.7; 7 M/13F) and 18 HCs (mean age: 41.6 ± 11.9; 8 M/10F) underwent a night of Polysomnography (PSG) and completed sleep diaries the following morning upon awakening. Two SSM indices, referring to the misperception of SL (SLm) and TST (TSTm), were calculated by comparing objective and subjective sleep indices extracted by PSG and sleep diary. According to these indices, the entire sample was split into 4 sub-groups: ID +SLm vs HC -SLm; ID +TSTm vs HC -TSTm.

RESULTS

Considering the SO, the two-way mixed-design ANOVA showed a significant main effect of Groups pointing to a decreased delta/beta ratio in the whole scalp topography. Moreover, we found a significant interaction effect for the sigma and beta bands. Post Hoc tests showed higher sigma and beta power in anterior and temporo-parietal sites during the SO period in IDs +SLm compared to HC -SLm. Considering the whole night, the unpaired t-test revealed in IDs +TSTm significantly lower delta power during NREM, and lower delta/beta ratio index during NREM and REM sleep compared to HCs -TSTm. Finally, we found diffuse significant negative correlations between SSM indices and the delta/beta ratio during SO, NREM, and REM sleep.

CONCLUSION

The main finding of the present study suggests that higher SL overestimation and TST underestimation are both phenomena related to diffuse cortical hyperarousal interpreted as a sleep state-independent electrophysiological correlate of the SSM, both during the SO and the whole night.

A functional contextual, observer-centric, quantum mechanical, and neuro-symbolic approach to solving the alignment problem of artificial general intelligence: safe AI through intersecting computational psychological neuroscience and LLM architecture for emergent theory of mind

There have been impressive advancements in the field of natural language processing (NLP) in recent years, largely driven by innovations in the development of transformer-based large language models (LLM) that utilize "attention." This approach employs masked self-attention to establish (via similarly) different positions of tokens (words) within an inputted sequence of tokens to compute the most appropriate response based on its training corpus. However, there is speculation as to whether this approach alone can be scaled up to develop emergent artificial general intelligence (AGI), and whether it can address the alignment of AGI values with human values (called the alignment problem). Some researchers exploring the alignment problem highlight three aspects that AGI (or AI) requires to help resolve this problem: (1) an interpretable values specification; (2) a utility function; and (3) a dynamic contextual account of behavior. Here, a neurosymbolic model is proposed to help resolve these issues of human value alignment in AI, which expands on the transformer-based model for NLP to incorporate symbolic reasoning that may allow AGI to incorporate perspective-taking reasoning (i.e., resolving the need for a dynamic contextual account of behavior through deictics) as defined by a multilevel evolutionary and neurobiological framework into a functional contextual post-Skinnerian model of human language called "Neurobiological and Natural Selection Relational Frame Theory" (N-Frame). It is argued that this approach may also help establish a comprehensible value scheme, a utility function by expanding the expected utility equation of behavioral economics to consider functional contextualism, and even an observer (or witness) centric model for consciousness. Evolution theory, subjective quantum mechanics, and neuroscience are further aimed to help explain consciousness, and possible implementation within an LLM through correspondence to an interface as suggested by N-Frame. This argument is supported by the computational level of hypergraphs, relational density clusters, a conscious quantum level defined by QBism, and real-world applied level (human user feedback). It is argued that this approach could enable AI to achieve consciousness and develop deictic perspective-taking abilities, thereby attaining human-level self-awareness, empathy, and compassion toward others. Importantly, this consciousness hypothesis can be directly tested with a significance of approximately 5-sigma significance (with a 1 in 3.5 million probability that any identified AI-conscious observations in the form of a collapsed wave form are due to chance factors) through double-slit intent-type experimentation and visualization procedures for derived perspective-taking relational frames. Ultimately, this could provide a solution to the alignment problem and contribute to the emergence of a theory of mind (ToM) within AI.

Examining the lateralization of electrophysiological correlates of auditory awareness

The neurological basis for perceptual awareness remains unclear, and theories disagree as to whether sensory cortices per se generate awareness. Critically, neural activity in the sensory cortices is only a neural correlate of consciousness (NCC) if it closely matches the contents of perceptual awareness. Research in vision and touch suggest that contralateral activity in sensory cortices is an NCC. Similarly, research in hearing with two sound sources (left and right) presented over headphones also suggests that a candidate NCC called the auditory awareness negativity (AAN) matches perceived location of sound. The current study used 13 different sound sources presented over loudspeakers for natural localization cues and measured event-related potentials to a threshold stimulus in a sound localization task. Preregistered Bayesian mixed models provided moderate evidence against an overall AAN and very strong evidence against its lateralization. Because of issues regarding data quantity and quality, exploratory analyses with aggregated data from multiple loudspeakers were conducted. Results provided moderate evidence for an overall AAN and strong evidence against its lateralization. Nonetheless, the interpretations of these results remain inconclusive. Therefore, future research should reduce the number of conditions and/or test over several sessions to procure a sufficient amount of data. Taken at face value, the results may suggest issues with AAN as an NCC of auditory awareness, as it does not laterally map onto experiences in a free-field auditory environment, in contrast to the NCCs of vision and touch.

Bridging flexible goal-directed cognition and consciousness: The Goal-Aligning Representation Internal Manipulation theory

Goal-directed manipulation of internal representations is a key element of human flexible behaviour, while consciousness is commonly associated with higher-order cognition and human flexibility. Current perspectives have only partially linked these processes, thus preventing a clear understanding of how they jointly generate flexible cognition and behaviour. Moreover, these limitations prevent an effective exploitation of this knowledge for technological scopes. We propose a new theoretical perspective that extends our 'three-component theory of flexible cognition' toward higher-order cognition and consciousness, based on the systematic integration of key concepts from Cognitive Neuroscience and AI/Robotics. The theory proposes that the function of conscious processes is to support the alignment of representations with multi-level goals. This higher alignment leads to more flexible and effective behaviours. We analyse here our previous model of goal-directed flexible cognition (validated with more than 20 human populations) as a starting GARIM-inspired model. By bridging the main theories of consciousness and goal-directed behaviour, the theory has relevant implications for scientific and technological fields. In particular, it contributes to developing new experimental tasks and interpreting clinical evidence. Finally, it indicates directions for improving machine learning and robotics systems and for informing real-world applications (e.g., in digital-twin healthcare and roboethics).

Metacognition as a window into subjective affective experience

When patients seek professional help for mental disorders, they often do so because of troubling subjective affective experiences. While these subjective states are at the center of the patient's symptomatology, scientific tools for studying them and their cognitive antecedents are limited. Here, we explore the use of concepts and analytic tools from the science of consciousness, a field of research that has faced similar challenges in having to develop robust empirical methods for addressing a phenomenon that has been considered difficult to pin down experimentally. One important strand is the operationalization of some relevant processes in terms of metacognition and confidence ratings, which can be rigorously studied in both humans and animals. By assessing subjective experience with similar approaches, we hope to develop new scientific approaches for studying affective processes and promoting psychological resilience in the face of debilitating emotional experiences.

An interhemispheric frontoparietal network supports hypnotic states

Understanding the neural substrate of altered conscious states is an important cultural, scientific, and clinical endeavour. Although hypnosis causes strong shifts in conscious perception and cognition, it remains largely unclear how hypnosis affects information processing in cortical networks. Here we manipulated the depth of hypnotic states to study information processing between cortical regions involved in attention and awareness. We used high-density Electroencephalography (EEG) to record resting-state cortical activity from 30 hypnosis experts during two hypnotic states with different depth. Each participant entered a light and a deep hypnotic state as well as two well-matched control states. Bridging top-down and lateralisation models of hypnosis, we found that interhemispheric frontoparietal connectivity distinguished hypnosis and control conditions, while no difference was found between the two hypnotic states. Using a graph-theoretic measure, we revealed that the amount of information passing through individual nodes (measured via betweenness centrality) is reduced during hypnosis relative to control states. Finally, we found that theta power was enhanced during hypnosis. Our result contributes to the current discussion around a role for theta power in bringing about hypnotic states, as well as other altered conscious states. Overall, our findings support the notion that altered top-down control in frontoparietal regions facilitates hypnosis by integrating information between cortical hemispheres.

Simultaneous invasive and non-invasive recordings in humans: A novel Rosetta stone for deciphering brain activity

Simultaneous noninvasive and invasive electrophysiological recordings provide a unique opportunity to achieve a comprehensive understanding of human brain activity, much like a Rosetta stone for human neuroscience. In this review we focus on the increasingly-used powerful combination of intracranial electroencephalography (iEEG) with scalp electroencephalography (EEG) or magnetoencephalography (MEG). We first provide practical insight on how to achieve these technically challenging recordings. We then provide examples from clinical research on how simultaneous recordings are advancing our understanding of epilepsy. This is followed by the illustration of how human neuroscience and methodological advances could benefit from these simultaneous recordings. We conclude with a call for open data sharing and collaboration, while ensuring neuroethical approaches and argue that only with a true collaborative approach the promises of simultaneous recordings will be fulfilled.

Disorders of Consciousness

This article reviews the definition, assessment, neuroimaging, treatment, and rehabilitation for disorders of consciousness after an acquired brain injury. It also explores special considerations and new neuromodulation treatment options.

Macroscale brain states support the control of semantic cognition

A crucial aim in neuroscience is to understand how the human brain adapts to varying cognitive demands. This study investigates network reconfiguration during controlled semantic retrieval in differing contexts. We analyze brain responses to two semantic tasks of varying difficulty - global association and feature matching judgments - which are contrasted with non-semantic tasks on the cortical surface and within a whole-brain state space. Demanding semantic association tasks elicit activation in anterior prefrontal and temporal regions, while challenging semantic feature matching and non-semantic tasks predominantly activate posterior regions. Task difficulty also modulates activation along different dimensions of functional organization, suggesting different mechanisms of cognitive control. More demanding semantic association judgments engage cognitive control and default mode networks together, while feature matching and non-semantic tasks are skewed towards cognitive control networks. These findings highlight the brain's dynamic ability to tailor its networks to support diverse neurocognitive states, enriching our understanding of controlled cognition.

Breathwork-induced psychedelic experiences modulate neural dynamics

Breathwork is an understudied school of practices involving intentional respiratory modulation to induce an altered state of consciousness (ASC). We simultaneously investigate the phenomenological and neural dynamics of breathwork by combining Temporal Experience Tracing, a quantitative methodology that preserves the temporal dynamics of subjective experience, with low-density portable EEG devices. Fourteen novice participants completed a course of up to 28 breathwork sessions-of 20, 40, or 60 min-in 28 days, yielding a neurophenomenological dataset of 301 breathwork sessions. Using hypothesis-driven and data-driven approaches, we found that "psychedelic-like" subjective experiences were associated with increased neural Lempel-Ziv complexity during breathwork. Exploratory analyses showed that the aperiodic exponent of the power spectral density-but not oscillatory alpha power-yielded similar neurophenomenological associations. Non-linear neural features, like complexity and the aperiodic exponent, neurally map both a multidimensional data-driven composite of positive experiences, and hypothesis-driven aspects of psychedelic-like experience states such as high bliss.

EEG signature of near-death-like experiences during syncope-induced periods of unresponsiveness

During fainting, disconnected consciousness may emerge in the form of dream-like experiences. Characterized by extra-ordinary and mystical features, these subjective experiences have been associated to near-death-like experiences (NDEs-like). We here aim to assess brain activity during syncope-induced disconnected consciousness by means of high-density EEG monitoring. Transient loss of consciousness and unresponsiveness were induced in 27 healthy volunteers through hyperventilation, orthostasis, and Valsalva maneuvers. Upon awakening, subjects were asked to report memories, if any. The Greyson NDE scale was used to evaluate the potential phenomenological content experienced during the syncope-induced periods of unresponsiveness. EEG source reconstruction assessed cortical activations during fainting, which were regressed out with subjective reports collected upon recovery of normal consciousness. We also conducted functional connectivity, graph-theoretic and complexity analyses. High quality high-density EEG data were obtained in 22 volunteers during syncope and unresponsiveness (lasting 22±8 s). NDE-like features (Greyson NDE scale total score ≥7/32) were apparent for eight volunteers and characterized by higher activity in delta, theta and beta2 bands in temporal and frontal regions. The richness of the NDE-like content was associated with delta, theta and beta2 bands cortical current densities, in temporal, parietal and frontal lobes, including insula, right temporoparietal junction, and cingulate cortex. Our analyses also revealed a higher complexity and that networks related to delta, theta, and beta2 bands were characterized by a higher overall connectivity paralleled by a higher segregation (i.e., local efficiency) and a higher integration (i.e., global efficiency) for the NDE-like group compared to the non-NDE-like group. Fainting-induced NDE-like episodes seem to be sustained by surges of neural activity representing promising markers of disconnected consciousness.

Insights into conscious cognitive information processing

For over a century, the neuro- and pathophysiological, behavioral, and cognitive correlates of consciousness have been an active field of theoretical considerations and empirical research in a wide range of modern disciplines. Conscious cognitive processing of information cannot be observed directly, but might be inferred from step-like discontinuities in learning performance or sudden insight-based improvements in problem solving behavior. It is assumed that a sudden step of knowledge associated with insight requires a creative reorganization of mental representations of task- or problem-relevant information and the restructuration of the task, respectively problem to overcome an cognitive dead-end or impasse. Discontinuities in learning performance or problem solving after an insight event can be used as time-tags to capture the time window in which conscious cognitive information processing must have taken place. According to the platform theory of conscious cognitive information processing, the reorganization and restructuration processes, require the maintenance of task- or problem-relevant information in working memory for the operation of executive functions on these mental representations. Electrophysiological evidence suggests that the reorganization and restructuration processes in working memory, that precede insight-based problem solutions are accompanied by an increase in the power of gamma oscillations in cortical areas including the prefrontal cortex. Empirical evidence and theoretical assumptions argue for an involvement of gap junction channels and connexin hemichannels in cortical gamma-oscillations and working memory processes. Discontinuities in learning or problem solving performance might be used as time-tags to investigate the implication of gap junction channels and hemichannels in conscious cognitive processing.

Eight challenges in developing theory of intelligence

A good theory of mathematical beauty is more practical than any current observation, as new predictions about physical reality can be self-consistently verified. This belief applies to the current status of understanding deep neural networks including large language models and even the biological intelligence. Toy models provide a metaphor of physical reality, allowing mathematically formulating the reality (i.e., the so-called theory), which can be updated as more conjectures are justified or refuted. One does not need to present all details in a model, but rather, more abstract models are constructed, as complex systems such as the brains or deep networks have many sloppy dimensions but much less stiff dimensions that strongly impact macroscopic observables. This type of bottom-up mechanistic modeling is still promising in the modern era of understanding the natural or artificial intelligence. Here, we shed light on eight challenges in developing theory of intelligence following this theoretical paradigm. Theses challenges are representation learning, generalization, adversarial robustness, continual learning, causal learning, internal model of the brain, next-token prediction, and the mechanics of subjective experience.

The influence of feature-based attention and response requirements on ERP correlates of auditory awareness

In search for the neural correlates of consciousness (NCCs), it is important to isolate the true NCCs from their prerequisites, consequences, and co-occurring processes. To date, little is known about how attention affects the event-related potential (ERP) correlates of auditory awareness and there is contradictory evidence on whether one of them, the late positivity (LP), is affected by response requirements. By implementing a GO-NOGO design with target and nontarget stimuli, we controlled for feature-based attention and response requirements in the same experiment, while participants rated their awareness using a perceptual awareness scale. The results showed a prolonged auditory awareness negativity (AAN) for aware trials, which was influenced neither by attention nor by response requirement. The LP was affected by both attention and response requirements. Consistent with the levels of processing hypothesis, the LP was related to consciousness as a correlate of the processing of higher-level stimulus features, likely requiring access to a "global workspace." Our findings further suggest that AAN is a proper ERP correlate of auditory consciousness and thus a true NCC in the auditory modality.

Preparatory activity of anterior insula predicts conflict errors: integrating convolutional neural networks and neural mass models

Preparatory brain activity is a cornerstone of proactive cognitive control, a top-down process optimizing attention, perception, and inhibition, fostering cognitive flexibility and adaptive attention control in the human brain. In this study, we proposed a neuroimaging-informed convolutional neural network model to predict cognitive control performance from the baseline pre-stimulus preparatory electrophysiological activity of core cognitive control regions. Particularly, combined with perturbation-based occlusion sensitivity analysis, we pinpointed regions with the most predictive preparatory activity for proactive cognitive control. We found that preparatory arrhythmic broadband neural dynamics in the right anterior insula, right precentral gyrus, and the right opercular part of inferior frontal gyrus (posterior ventrolateral prefrontal cortex), are highly predictive of prospective cognitive control performance.  The pre-stimulus preparatory activity in these regions corresponds to readiness for conflict detection, inhibitory control, and overall elaborate attentional processing. We integrated the convolutional neural network with biologically inspired Jansen-Rit neural mass model to investigate neurostimulation effects on cognitive control. High-frequency stimulation (130 Hz) of the left anterior insula provides significant cognitive enhancement, especially in reducing conflict errors, despite the right anterior insula's higher predictive value for prospective cognitive control performance. Thus, effective neurostimulation targets may differ from regions showing biomarker activity. Finally, we validated our theoretical finding by evaluating intrinsic neuromodulation through neurofeedback-guided volitional control in an independent dataset. We found that left anterior insula was intrinsically modulated in real-time by volitional control of emotional valence, but not arousal. Our findings further highlight central role of anterior insula in orchestrating proactive cognitive control processes, positioning it at the top of hierarchy for cognitive control.

Content-state dimensions characterize different types of neuronal markers of consciousness

Identifying the neuronal markers of consciousness is key to supporting the different scientific theories of consciousness. Neuronal markers of consciousness can be defined to reflect either the brain signatures underlying specific conscious content or those supporting different states of consciousness, two aspects traditionally studied separately. In this paper, we introduce a framework to characterize markers according to their dynamics in both the "state" and "content" dimensions. The 2D space is defined by the marker's capacity to distinguish the conscious states from non-conscious states (on the x-axis) and the content (e.g. perceived versus unperceived or different levels of cognitive processing on the y-axis). According to the sign of the x- and y-axis, markers are separated into four quadrants in terms of how they distinguish the state and content dimensions. We implement the framework using three types of electroencephalography markers: markers of connectivity, markers of complexity, and spectral summaries. The neuronal markers of state are represented by the level of consciousness in (i) healthy participants during a nap and (ii) patients with disorders of consciousness. On the other hand, the neuronal markers of content are represented by (i) the conscious content in healthy participants' perception task using a visual awareness paradigm and (ii) conscious processing of hierarchical regularities using an auditory local-global paradigm. In both cases, we see separate clusters of markers with correlated and anticorrelated dynamics, shedding light on the complex relationship between the state and content of consciousness and emphasizing the importance of considering them simultaneously. This work presents an innovative framework for studying consciousness by examining neuronal markers in a 2D space, providing a valuable resource for future research, with potential applications using diverse experimental paradigms, neural recording techniques, and modeling investigations.

Development of emergent processes and threshold of consciousness with levels of processing

Introduction

The transition of experience from unconscious to conscious, the emergent process, is a crucial topic in consciousness studies. Three frameworks exist to explain the process: (1) consciousness arises in an all-or-none manner; (2) consciousness arises gradually; (3) consciousness arises either all at once or gradually, depending on the level of stimulus processing (low- vs. high-level). However, the development of emergent processes of consciousness remains unclear. This study examines the development of emergent processes of consciousness based on the level of stimulus processing framework.

Methods

Ninety-nine children (5-12 year-olds) and adults participated in two online discrimination tasks. These tasks involved color discrimination as lower-level processing and number magnitude discrimination as higher-level processing, as well as backward masking with stimulus onset asynchronies (SOAs) varying from 16.7 to 266.7 ms. We measured objective discrimination accuracy and used a 4-scale Perceptual Awareness Scale (PAS) to assess subjective awareness. We fit the data to a four-parameter nonlinear function to estimate the center of the slope (threshold) and the range of the slope (gradualness, the measure of emergent process of consciousness) of the model.

Results

The results showed the threshold of objective discrimination was significantly higher in 5-6 year-olds than in 7-12 year-olds, but not of subjective awareness. The emergent process of objective discrimination in the number task was more gradual than in the color task.

Discussion

The findings suggest that the thresholds of subjective awareness in 5-6 year-olds and objective discrimination in 7-9 year-olds are similar to those in adults. Moreover, the emergent processes of subjective awareness and objective discrimination in 5-6 year-olds are also similar to those in adults. Our results support the level of processing hypothesis but suggest that its effects may differ across developmental stages.

Lateral frontoparietal effective connectivity differentiates and predicts state of consciousness in a cohort of patients with traumatic disorders of consciousness

Neuroimaging studies have suggested an important role for the default mode network (DMN) in disorders of consciousness (DoC). However, the extent to which DMN connectivity can discriminate DoC states-unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS)-is less evident. Particularly, it is unclear whether effective DMN connectivity, as measured indirectly with dynamic causal modelling (DCM) of resting EEG can disentangle UWS from healthy controls and from patients considered conscious (MCS+). Crucially, this extends to UWS patients with potentially "covert" awareness (minimally conscious star, MCS*) indexed by voluntary brain activity in conjunction with partially preserved frontoparietal metabolism as measured with positron emission tomography (PET+ diagnosis; in contrast to PET- diagnosis with complete frontoparietal hypometabolism). Here, we address this gap by using DCM of EEG data acquired from patients with traumatic brain injury in 11 UWS (6 PET- and 5 PET+) and in 12 MCS+ (11 PET+ and 1 PET-), alongside with 11 healthy controls. We provide evidence for a key difference in left frontoparietal connectivity when contrasting UWS PET- with MCS+ patients and healthy controls. Next, in a leave-one-subject-out cross-validation, we tested the classification performance of the DCM models demonstrating that connectivity between medial prefrontal and left parietal sources reliably discriminates UWS PET- from MCS+ patients and controls. Finally, we illustrate that these models generalize to an unseen dataset: models trained to discriminate UWS PET- from MCS+ and controls, classify MCS* patients as conscious subjects with high posterior probability (pp > .92). These results identify specific alterations in the DMN after severe brain injury and highlight the clinical utility of EEG-based effective connectivity for identifying patients with potential covert awareness.

Beyond task response-Pre-stimulus activity modulates contents of consciousness

The current discussion on the neural correlates of the contents of consciousness (NCCc) focuses mainly on the post-stimulus period of task-related activity. This neglects the substantial impact of the spontaneous or ongoing activity of the brain as manifest in pre-stimulus activity. Does the interaction of pre- and post-stimulus activity shape the contents of consciousness? Addressing this gap in our knowledge, we review and converge two recent lines of findings, that is, pre-stimulus alpha power and pre- and post-stimulus alpha trial-to-trial variability (TTV). The data show that pre-stimulus alpha power modulates post-stimulus activity including specifically the subjective features of conscious contents like confidence and vividness. At the same time, alpha pre-stimulus variability shapes post-stimulus TTV reduction including the associated contents of consciousness. We propose that non-additive rather than merely additive interaction of the internal pre-stimulus activity with the external stimulus in the alpha band is key for contents to become conscious. This is mediated by mechanisms on different levels including neurophysiological, neurocomputational, neurodynamic, neuropsychological and neurophenomenal levels. Overall, considering the interplay of pre-stimulus intrinsic and post-stimulus extrinsic activity across wider timescales, not just evoked responses in the post-stimulus period, is critical for identifying neural correlates of consciousness. This is well in line with both processing and especially the Temporo-spatial theory of consciousness (TTC).

The experimental study of consciousness: Is psychology travelling back to the future?

It was with the promise of rendering an experimental approach to consciousness that psychology started its trajectory as an independent science more than 150 years ago. Here, we will posit that the neurosciences were instrumental in leading psychology to resume the study of consciousness by projecting an empirical agenda for the future. First, we will start by showing how scientists were able to venture into the consciousness of supposedly unconscious patients, opening the door for the identification of important neural correlates of distinct consciousness states. Then, we will describe how different technological advances and elegant experimental paradigms helped in establishing important neuronal correlates of global consciousness (i.e., being conscious at all), perceptual consciousness (i.e., being conscious of something), and self-consciousness (i.e., being conscious of itself). Finally, we will illustrate how the study of complex consciousness experiences may contribute to the clarification of the mechanisms associated with global consciousness, the relationship between perceptual and self-consciousness, and the interface among distinct self-consciousness domains. In closing, we will elaborate on the road ahead of us for re-establishing psychology as a science of consciousness.

Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.

The Persistent Paradox of Rapid Eye Movement Sleep (REMS): Brain Waves and Dreaming

The original conceptualization of REM sleep as paradoxical sleep was based on its EEG resembling wakefulness and its association with dreaming. Over time, the concept of paradox was expanded to include various associations with REM sleep, such as dream exclusivity, high recall, and pathophysiology. However, none of these associations are unique to REM sleep; they can also occur in other sleep states. Today, after more than fifty years of focused research, two aspects of REMS clearly retain paradoxical exclusivity. Despite the persistent contention that the EEG of human REMS consists of wake-like, low-voltage, non-synchronous electrical discharges, REMS is based on and defined by the intracranial electrical presence of 5-8 Hz. theta, which has always been the marker of REMS in other animals. The wake-like EEG used to define REMS on human polysomnography is secondary to a generalized absence of electrophysiological waveforms because the strong waves of intracranial theta do not propagate to scalp electrodes placed outside the skull. It is a persistent paradox that the theta frequency is restricted to a cyclical intracranial dynamic that does not extend beyond the lining of the brain. REMS has a persistent association with narratively long and salient dream reports. However, the extension of this finding to equate REMS with dreaming led to a foundational error in neuroscientific logic. Major theories and clinical approaches were built upon this belief despite clear evidence that dreaming is reported throughout sleep in definingly different physiologic and phenomenological forms. Few studies have addressed the differences between the dreams reported from the different stages of sleep so that today, the most paradoxical aspect of REMS dreaming may be how little the state has actually been studied. An assessment of the differences in dreaming between sleep stages could provide valuable insights into how dreaming relates to the underlying brain activity and physiological processes occurring during each stage. The brain waves and dreams of REMS persist as being paradoxically unique and different from waking and the other states of sleep consciousness.

Behavioral and cortical arousal from sleep, muscimol-induced coma, and anesthesia by direct optogenetic stimulation of cortical neurons

The cerebral cortex is widely considered part of the neural substrate of consciousness, but direct causal evidence is missing. Here, we tested in mice whether optogenetic activation of cortical neurons in posterior parietal cortex (PtA) or medial prefrontal cortex (mPFC) is sufficient for arousal from three behavioral states characterized by progressively deeper unresponsiveness: sleep, a coma-like state induced by muscimol injection in the midbrain, and deep sevoflurane-dexmedetomidine anesthesia. We find that cortical stimulation always awakens the mice from both NREM sleep and REM sleep, with PtA requiring weaker/shorter light pulses than mPFC. Moreover, in most cases light pulses produce both cortical activation (decrease in low frequencies) and behavioral arousal (recovery of the righting reflex) from brainstem coma, as well as cortical activation from anesthesia. These findings provide evidence that direct activation of cortical neurons is sufficient for behavioral and/or cortical arousal from sleep, brainstem coma, and anesthesia.

Bypassing input to V1 in visual awareness: A TMS-EROS investigation

Early visual cortex (V1-V3) is believed to be critical for normal visual awareness by providing the necessary feedforward input. However, it remains unclear whether visual awareness can occur without further involvement of early visual cortex, such as re-entrant feedback. It has been challenging to determine the importance of feedback activity to these areas because of the difficulties in dissociating this activity from the initial feedforward activity. Here, we applied single-pulse transcranial magnetic stimulation (TMS) over the left posterior parietal cortex to elicit phosphenes in the absence of direct visual input to early visual cortex. Immediate neural activity after the TMS pulse was assessed using the event-related optical signal (EROS), which can measure activity under the TMS coil without artifacts. Our results show that: 1) The activity in posterior parietal cortex 50 ms after TMS was related to phosphene awareness, and 2) Activity related to awareness was observed in a small portion of V1 140 ms after TMS, but in contrast (3) Activity in V2 was a more robust correlate of awareness. Together, these results are consistent with interactive models proposing that sustained and recurrent loops of activity between cortical areas are necessary for visual awareness to emerge. In addition, we observed phosphene-related activations of the anteromedial cuneus and lateral occipital cortex, suggesting a functional network subserving awareness comprising these regions, the parietal cortex and early visual cortex.

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.

Consciousness and the Dying Brain

The near-death experience has been reported since antiquity and is often characterized by the perception of light, interactions with other entities, and life recall. Near-death experiences can occur in a variety of situations, but they have been studied systematically after in-hospital cardiac arrest, with an incidence of 10 to 20%. Long attributed to metaphysical or supernatural causes, there have been recent advances in understanding the neurophysiologic basis of this unique category of conscious experience. This article reviews the epidemiology and neurobiology of near-death experiences, with a focus on clinical and laboratory evidence for a surge of neurophysiologic gamma oscillations and cortical connectivity after cardiac and respiratory arrest.

Early Electrophysiological Correlates of Perceptual Consciousness Are Affected by Both Exogenous and Endogenous Attention

It has been proposed that visual awareness negativity (VAN), which is an early ERP component, constitutes a neural correlate of visual consciousness that is independent of perceptual and cognitive mechanisms. In the present study, we investigated whether VAN is indeed a specific marker of phenomenal awareness or rather reflects the involvement of attention. To this end, we reanalyzed data collected in a previously published EEG experiment in which awareness of visual stimuli and two aspects that define attentional involvement, namely, the inherent saliency and task relevance of a stimulus, were manipulated orthogonally. During the experimental procedure, participants (n = 41) were presented with images of faces that were backward-masked or unmasked, fearful or neutral, and defined as task-relevant targets or task-irrelevant distractors. Single-trial ERP analysis revealed that VAN was highly dependent on attentional manipulations in the early time window (140-200 msec), up to the point that the effect of awareness was not observed for attentionally irrelevant stimuli (i.e., neutral faces presented as distractors). In the late time window (200-350 msec), VAN was present in all attentional conditions, but its amplitude was significantly higher in response to fearful faces and task-relevant face images than in response to neutral ones and task-irrelevant ones, respectively. In conclusion, we demonstrate that the amplitude of VAN is highly dependent on both exogenous (stimulus saliency) and endogenous attention (task requirements). Our results challenge the view that VAN constitutes an attention-independent correlate of phenomenal awareness.

The Brain's Topographical Organization Shapes Dynamic Interaction Patterns That Support Flexible Behavior Based on Rules and Long-Term Knowledge

Adaptive behavior relies both on specific rules that vary across situations and stable long-term knowledge gained from experience. The frontoparietal control network (FPCN) is implicated in the brain's ability to balance these different influences on action. Here, we investigate how the topographical organization of the cortex supports behavioral flexibility within the FPCN. Functional properties of this network might reflect its juxtaposition between the dorsal attention network (DAN) and the default mode network (DMN), two large-scale systems implicated in top-down attention and memory-guided cognition, respectively. Our study tests whether subnetworks of FPCN are topographically proximal to the DAN and the DMN, respectively, and how these topographical differences relate to functional differences: the proximity of each subnetwork is anticipated to play a pivotal role in generating distinct cognitive modes relevant to working memory and long-term memory. We show that FPCN subsystems share multiple anatomical and functional similarities with their neighboring systems (DAN and DMN) and that this topographical architecture supports distinct interaction patterns that give rise to different patterns of functional behavior. The FPCN acts as a unified system when long-term knowledge supports behavior but becomes segregated into discrete subsystems with different patterns of interaction when long-term memory is less relevant. In this way, our study suggests that the topographical organization of the FPCN and the connections it forms with distant regions of cortex are important influences on how this system supports flexible behavior.

Task-based EEG and fMRI paradigms in a multimodal clinical diagnostic framework for disorders of consciousness

Disorders of consciousness (DoC) are generally diagnosed by clinical assessment, which is a predominantly motor-driven process and accounts for up to 40 % of non-communication being misdiagnosed as unresponsive wakefulness syndrome (UWS) (previously known as prolonged/persistent vegetative state). Given the consequences of misdiagnosis, a more reliable and objective multimodal protocol to diagnosing DoC is needed, but has not been produced due to concerns regarding their interpretation and reliability. Of the techniques commonly used to detect consciousness in DoC, task-based paradigms (active paradigms) produce the most unequivocal result when findings are positive. It is well-established that command following (CF) reliably reflects preserved consciousness. Task-based electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can detect motor-independent CF and reveal preserved covert consciousness in up to 14 % of UWS patients. Accordingly, to improve the diagnostic accuracy of DoC, we propose a practical multimodal clinical decision framework centered on task-based EEG and fMRI, and complemented by measures like transcranial magnetic stimulation (TMS-EEG).

Taking consciousness for real: Increasing the ecological validity of the study of conscious vs. unconscious processes

The study of consciousness has developed well-controlled, rigorous methods for manipulating and measuring consciousness. Yet, in the process, experimental paradigms grew farther away from everyday conscious and unconscious processes, which raises the concern of ecological validity. In this review, we suggest that the field can benefit from adopting a more ecological approach, akin to other fields of cognitive science. There, this approach challenged some existing hypotheses, yielded stronger effects, and enabled new research questions. We argue that such a move is critical for studying consciousness, where experimental paradigms tend to be artificial and small effect sizes are relatively prevalent. We identify three paths for doing so-changing the stimuli and experimental settings, changing the measures, and changing the research questions themselves-and review works that have already started implementing such approaches. While acknowledging the inherent challenges, we call for increasing ecological validity in consciousness studies.

An integrative view of the role of prefrontal cortex in consciousness

The involvement of the prefrontal cortex (PFC) in consciousness is an ongoing focus of intense investigation. An important question is whether representations of conscious contents and experiences in the PFC are confounded by post-perceptual processes related to cognitive functions. Here, I review recent findings suggesting that neuronal representations of consciously perceived contents-in the absence of post-perceptual processes-can indeed be observed in the PFC. Slower ongoing fluctuations in the electrophysiological state of the PFC seem to control the stability and updates of these prefrontal representations of conscious awareness. In addition to conscious perception, the PFC has been shown to play a critical role in controlling the levels of consciousness as observed during anesthesia, while prefrontal lesions can result in severe loss of perceptual awareness. Together, the convergence of these processes in the PFC suggests its integrative role in consciousness and highlights the complex nature of consciousness itself.

An integrative, multiscale view on neural theories of consciousness

How is conscious experience related to material brain processes? A variety of theories aiming to answer this age-old question have emerged from the recent surge in consciousness research, and some are now hotly debated. Although most researchers have so far focused on the development and validation of their preferred theory in relative isolation, this article, written by a group of scientists representing different theories, takes an alternative approach. Noting that various theories often try to explain different aspects or mechanistic levels of consciousness, we argue that the theories do not necessarily contradict each other. Instead, several of them may converge on fundamental neuronal mechanisms and be partly compatible and complementary, so that multiple theories can simultaneously contribute to our understanding. Here, we consider unifying, integration-oriented approaches that have so far been largely neglected, seeking to combine valuable elements from various theories.

Artificial intelligence, human cognition, and conscious supremacy

The computational significance of consciousness is an important and potentially more tractable research theme than the hard problem of consciousness, as one could look at the correlation of consciousness and computational capacities through, e.g., algorithmic or complexity analyses. In the literature, consciousness is defined as what it is like to be an agent (i.e., a human or a bat), with phenomenal properties, such as qualia, intentionality, and self-awareness. The absence of these properties would be termed "unconscious." The recent success of large language models (LLMs), such as ChatGPT, has raised new questions about the computational significance of human conscious processing. Although instances from biological systems would typically suggest a robust correlation between intelligence and consciousness, certain states of consciousness seem to exist without manifest existence of intelligence. On the other hand, AI systems seem to exhibit intelligence without consciousness. These instances seem to suggest possible dissociations between consciousness and intelligence in natural and artificial systems. Here, I review some salient ideas about the computational significance of human conscious processes and identify several cognitive domains potentially unique to consciousness, such as flexible attention modulation, robust handling of new contexts, choice and decision making, cognition reflecting a wide spectrum of sensory information in an integrated manner, and finally embodied cognition, which might involve unconscious processes as well. Compared to such cognitive tasks, characterized by flexible and ad hoc judgments and choices, adequately acquired knowledge and skills are typically processed unconsciously in humans, consistent with the view that computation exhibited by LLMs, which are pretrained on a large dataset, could in principle be processed without consciousness, although conversations in humans are typically done consciously, with awareness of auditory qualia as well as the semantics of what are being said. I discuss the theoretically and practically important issue of separating computations, which need to be conducted consciously from those which could be done unconsciously, in areas, such as perception, language, and driving. I propose conscious supremacy as a concept analogous to quantum supremacy, which would help identify computations possibly unique to consciousness in biologically practical time and resource limits. I explore possible mechanisms supporting the hypothetical conscious supremacy. Finally, I discuss the relevance of issues covered here for AI alignment, where computations of AI and humans need to be aligned.

Shared EEG correlates between non-REM parasomnia experiences and dreams

Sleepwalking and related parasomnias result from incomplete awakenings out of non-rapid eye movement sleep. Behavioral episodes can occur without consciousness or recollection, or in relation to dream-like experiences. To understand what accounts for these differences in consciousness and recall, here we recorded parasomnia episodes with high-density electroencephalography (EEG) and interviewed participants immediately afterward about their experiences. Compared to reports of no experience (19%), reports of conscious experience (56%) were preceded by high-amplitude EEG slow waves in anterior cortical regions and activation of posterior cortical regions, similar to previously described EEG correlates of dreaming. Recall of the content of the experience (56%), compared to no recall (25%), was associated with higher EEG activation in the right medial temporal region before movement onset. Our work suggests that the EEG correlates of parasomnia experiences are similar to those reported for dreams and may thus reflect core physiological processes involved in sleep consciousness.

Electrophysiological correlates of sustained conscious perception

Previous research on the neural correlates of consciousness (NCC) in visual perception revealed an early event-related potential (ERP), the visual awareness negativity (VAN), to be associated with stimulus awareness. However, due to the use of brief stimulus presentations in previous studies, it remains unclear whether awareness-related negativities represent a transient onset-related response or correspond to the duration of a conscious percept. Studies are required that allow prolonged stimulus presentation under aware and unaware conditions. The present ERP study aimed to tackle this challenge by using a novel stimulation design. Male and female human participants (n = 62) performed a visual task while task-irrelevant line stimuli were presented in the background for either 500 or 1000 ms. The line stimuli sometimes contained a face, which needed so-called visual one-shot learning to be seen. Half of the participants were informed about the presence of the face, resulting in faces being perceived by the informed but not by the uninformed participants. Comparing ERPs between the informed and uninformed group revealed an enhanced negativity over occipitotemporal electrodes that persisted for the entire duration of stimulus presentation. Our results suggest that sustained visual awareness negativities (SVAN) are associated with the duration of stimulus presentation.

Multimodal MRI reveals brainstem connections that sustain wakefulness in human consciousness

Consciousness is composed of arousal (i.e., wakefulness) and awareness. Substantial progress has been made in mapping the cortical networks that underlie awareness in the human brain, but knowledge about the subcortical networks that sustain arousal in humans is incomplete. Here, we aimed to map the connectivity of a proposed subcortical arousal network that sustains wakefulness in the human brain, analogous to the cortical default mode network (DMN) that has been shown to contribute to awareness. We integrated data from ex vivo diffusion magnetic resonance imaging (MRI) of three human brains, obtained at autopsy from neurologically normal individuals, with immunohistochemical staining of subcortical brain sections. We identified nodes of the proposed default ascending arousal network (dAAN) in the brainstem, hypothalamus, thalamus, and basal forebrain. Deterministic and probabilistic tractography analyses of the ex vivo diffusion MRI data revealed projection, association, and commissural pathways linking dAAN nodes with one another and with DMN nodes. Complementary analyses of in vivo 7-tesla resting-state functional MRI data from the Human Connectome Project identified the dopaminergic ventral tegmental area in the midbrain as a widely connected hub node at the nexus of the subcortical arousal and cortical awareness networks. Our network-based autopsy methods and connectivity data provide a putative neuroanatomic architecture for the integration of arousal and awareness in human consciousness.

State-related Electroencephalography Microstate Complexity during Propofol- and Esketamine-induced Unconsciousness

BACKGROUND

Identifying the state-related "neural correlates of consciousness" for anesthetics-induced unconsciousness is challenging. Spatiotemporal complexity is a promising tool for investigating consciousness. The authors hypothesized that spatiotemporal complexity may serve as a state-related but not drug-related electroencephalography (EEG) indicator during an unconscious state induced by different anesthetic drugs (e.g., propofol and esketamine).

METHODS

The authors recorded EEG from patients with unconsciousness induced by propofol (n = 10) and esketamine (n = 10). Both conventional microstate parameters and microstate complexity were analyzed. Spatiotemporal complexity was constructed by microstate sequences and complexity measures. Two different EEG microstate complexities were proposed to quantify the randomness (type I) and complexity (type II) of the EEG microstate series during the time course of the general anesthesia.

RESULTS

The coverage and occurrence of microstate E (prefrontal pattern) and the duration of microstate B (right frontal pattern) could distinguish the states of preinduction wakefulness, unconsciousness, and recovery under both anesthetics. Type I EEG microstate complexity based on mean information gain significantly increased from awake to unconsciousness state (propofol: from mean ± SD, 1.562 ± 0.059 to 1.672 ± 0.023, P < 0.001; esketamine: 1.599 ± 0.051 to 1.687 ± 0.013, P < 0.001), and significantly decreased from unconsciousness to recovery state (propofol: 1.672 ± 0.023 to 1.537 ± 0.058, P < 0.001; esketamine: 1.687 ± 0.013 to 1.608 ± 0.028, P < 0.001) under both anesthetics. In contrast, type II EEG microstate fluctuation complexity significantly decreased in the unconscious state under both drugs (propofol: from 2.291 ± 0.771 to 0.782 ± 0.163, P < 0.001; esketamine: from 1.645 ± 0.417 to 0.647 ± 0.252, P < 0.001), and then increased in the recovery state (propofol: 0.782 ± 0.163 to 2.446 ± 0.723, P < 0.001; esketamine: 0.647 ± 0.252 to 1.459 ± 0.264, P < 0.001).

CONCLUSIONS

Both type I and type II EEG microstate complexities are drug independent. Thus, the EEG microstate complexity measures that the authors proposed are promising tools for building state-related neural correlates of consciousness to quantify anesthetic-induced unconsciousness.

EDITOR’S PERSPECTIVE

Cell consciousness: a dissenting opinion : The cellular basis of consciousness theory lacks empirical evidence for its claims that all cells have consciousness

The proponents of CBC claim that all living organisms down to prokaryotes have consciousness. However, their arguments lack empirical evidence or are refuted by established facts.

Conscious perception of fear in faces: Insights from high-density EEG and perceptual awareness scale with threshold stimuli

Contrary to the extensive research on processing subliminal and/or unattended emotional facial expressions, only a minority of studies have investigated the neural correlates of consciousness (NCCs) of emotions conveyed by faces. In the present high-density electroencephalography (EEG) study, we first employed a staircase procedure to identify each participant's perceptual threshold of the emotion expressed by the face and then compared the EEG signals elicited in trials where the participants were aware with the activity elicited in trials where participants were unaware of the emotions expressed by these, otherwise identical, faces. Drawing on existing knowledge of the neural mechanisms of face processing and NCCs, we hypothesized that activity in frontal electrodes would be modulated in relation to participants' awareness of facial emotional content. More specifically, we hypothesized that the NCC of fear seen on someone else's face could be detected as a modulation of a later and more anterior (i.e., at frontal sites) event-related potential (ERP) than the face-sensitive N170. By adopting a data-driven approach and cluster-based statistics to the analysis of EEG signals, the results were clear-cut in showing that visual awareness of fear was associated with the modulation of a frontal ERP component in a 150-300 msec interval. These insights are dissected and contextualized in relation to prevailing theories of visual consciousness and their proposed NCC benchmarks.

The Loss of Spatiality and Temporality in Twilight Consciousness: The Emergence of Exogenous Psychosis Induced by Novel Psychoactive Substances

BACKGROUND

The state of twilight consciousness is marked by a focused narrowing of awareness, maintaining vigilance and attention while simultaneously experiencing perceptual shifts in the surrounding environment. It is crucial to recognize that this twilight state represents not just a contraction but also an expansion of conscious experience.

SUMMARY

Substances of abuse, particularly new psychoactive substances, play a significant role in inducing this twilight state. They achieve this by deconstructing essential components of consciousness, such as the perception of time and space.

KEY MESSAGE

This paper aimed to explore the phenomenon of the twilight state of consciousness and shed light on how new psychoactive substances can alter the perception of time and space during this twilight phase, potentially triggering exogenous psychosis. This comprehensive inquiry employs a phenomenological approach to the study of consciousness, recognizing it as the primary tool for ascribing significance to this intricate yet often overlooked aspect of psychopathology.

The hidden structure of consciousness

According to Loorits, if we want consciousness to be explained in terms of natural sciences, we should be able to analyze its seemingly non-structural aspects, like qualia, in structural terms. However, the studies conducted over the last three decades do not seem to be able to bridge the explanatory gap between physical phenomena and phenomenal experience. One possible way to bridge the explanatory gap is to seek the structure of consciousness within consciousness itself, through a phenomenal analysis of the qualitative aspects of experience. First, this analysis leads us to identify the explanandum concerning the simplest forms of experience not in qualia but in the unitary set of qualities found in early vision. Second, it leads us to hypothesize that consciousness is also made up of non-apparent parts, and that there exists a hidden structure of consciousness. This structure, corresponding to a simple early visual experience, is constituted by a Hierarchy of Spatial Belongings nested within each other. Each individual Spatial Belonging is formed by a primary content and a primary space. The primary content can be traced in the perceptibility of the contents we can distinguish in the phenomenal field. The primary space is responsible for the perceptibility of the content and is not perceptible in itself. However, the phenomenon I refer to as subtraction of visibility allows us to characterize it as phenomenally negative. The hierarchical relationships between Spatial Belongings can ensure the qualitative nature of components of perceptual organization, such as object, background, and detail. The hidden structure of consciousness presents aspects that are decidedly counterintuitive compared to our idea of phenomenal experience. However, on the one hand, the Hierarchy of Spatial Belongings can explain the qualities of early vision and their appearance as a unitary whole, while on the other hand, it might be more easily explicable in terms of brain organization. In other words, the hidden structure of consciousness can be considered a bridge structure which, placing itself at an intermediate level between experience and physical properties, can contribute to bridging the explanatory gap.

A mechanistic alternative to minimal sufficiency as the guiding principle for NCC research

A central project for the neuroscience of consciousness is to reveal the neural basis of consciousness. For the past 20-odd years, this project has been conceptualized in terms of minimal sufficiency. Recently, a number of authors have suggested that the project is better conceived in mechanistic terms as the search for difference-makers. In this paper, I (i) motivate this mechanistic alternative to minimal sufficiency, (ii) develop it further by clarifying debates about the prospects of leveraging mutual manipulability to distinguish constitutive difference-makers from those that are merely causal, and (iii) explore the implications this has for recent debates concerning the status of the prefrontal cortex. I argue that adopting a mechanistic approach to the neuroscience of consciousness suggests that the prefrontal cortex is part of the neural mechanisms underlying consciousness even if it is not strictly speaking a necessary part.