Neural signature of the conscious processing of auditory regularities

Propofol-mediated loss of consciousness disrupts predictive routing and local field phase modulation of neural activity

Predictive coding is a fundamental function of the cortex. The predictive routing model proposes a neurophysiological implementation for predictive coding. Predictions are fed back from the deep-layer cortex via alpha/beta (8 to 30 Hz) oscillations. They inhibit the gamma (40 to 100 Hz) and spiking that feed sensory inputs forward. Unpredicted inputs arrive in circuits unprepared by alpha/beta, resulting in enhanced gamma and spiking. To test the predictive routing model and its role in consciousness, we collected data from intracranial recordings of macaque monkeys during passive presentation of auditory oddballs before and after propofol-mediated loss of consciousness (LOC). In line with the predictive routing model, alpha/beta oscillations in the awake state served to inhibit the processing of predictable stimuli. Propofol-mediated LOC eliminated alpha/beta modulation by a predictable stimulus in the sensory cortex and alpha/beta coherence between sensory and frontal areas. As a result, oddball stimuli evoked enhanced gamma power, late period (>200 ms from stimulus onset) spiking, and superficial layer sinks in the sensory cortex. LOC also resulted in diminished decodability of pattern-level prediction error signals in the higher-order cortex. Therefore, the auditory cortex was in a disinhibited state during propofol-mediated LOC. However, despite these enhanced feedforward responses in the auditory cortex, there was a loss of differential spiking to oddballs in the higher-order cortex. This may be a consequence of a loss of within-area and interareal spike-field coupling in the alpha/beta and gamma frequency bands. These results provide strong constraints for current theories of consciousness.

Pain anticipation is a new behavioural sign of minimally conscious state

Probing cognition and consciousness in the absence of functional communication remains an extremely challenging task. In this perspective, we imagined a basic clinical procedure to explore pain anticipation at bedside. In a series of 61 patients with a disorder of consciousness, we tested the existence of a nociceptive anticipation response by pairing a somaesthetic stimulation with a noxious stimulation. We then explored how nociceptive anticipation response correlated with (i) clinical status inferred from Coma Recovery Scale-Revised scoring, (ii) with an EEG signature of stimulus anticipation-the contingent negative variation-and (iii) how nociceptive anticipation response could predict consciousness outcome at 6 months. Proportion of nociceptive anticipation response differed significantly according to the state of consciousness: nociceptive anticipation response was present in 5 of 5 emerging from minimally conscious state patients (100%), in 10 of 11 minimally conscious state plus patients (91%), but only in 8 of 17 minimally conscious state minus patients (47%), and only in 1 of 24 vegetative state/unresponsive wakefulness syndrome patients (4%) (χ 2  P < 0.0001). Nociceptive anticipation response correlated with the presence of a contingent negative variation, suggesting that patients with nociceptive anticipation response were more prone to actively expect and anticipate auditory stimuli (Fisher's exact test P = 0.05). However, nociceptive anticipation response presence did not predict consciousness recovery. Nociceptive anticipation response appears as a new additional behavioural sign that can be used to differentiate minimally conscious state from vegetative state/unresponsive wakefulness syndrome patients. As most behavioural signs of minimally conscious state, the nociceptive anticipation response seems to reveal the existence of a cortically mediated state that does not necessarily reflect residual conscious processing.

Language experience shapes predictive coding of rhythmic sound sequences

Perceptual systems heavily rely on prior knowledge and predictions to make sense of the environment. Predictions can originate from multiple sources of information, including contextual short-term priors, based on isolated temporal situations, and context-independent long-term priors, arising from extended exposure to statistical regularities. While the effects of short-term predictions on auditory perception have been well-documented, how long-term predictions shape early auditory processing is poorly understood. To address this, we recorded magnetoencephalography data from native speakers of two languages with different word orders (Spanish: functor-initial vs Basque: functor-final) listening to simple sequences of binary sounds alternating in duration with occasional omissions. We hypothesized that, together with contextual transition probabilities, the auditory system uses the characteristic prosodic cues (duration) associated with the native language's word order as an internal model to generate long-term predictions about incoming non-linguistic sounds. Consistent with our hypothesis, we found that the amplitude of the mismatch negativity elicited by sound omissions varied orthogonally depending on the speaker's linguistic background and was most pronounced in the left auditory cortex. Importantly, listening to binary sounds alternating in pitch instead of duration did not yield group differences, confirming that the above results were driven by the hypothesized long-term 'duration' prior. These findings show that experience with a given language can shape a fundamental aspect of human perception - the neural processing of rhythmic sounds - and provides direct evidence for a long-term predictive coding system in the auditory cortex that uses auditory schemes learned over a lifetime to process incoming sound sequences.

Does Cognitive Load Affect Measures of Consciousness?

BACKGROUND

Developing and testing methods for reliably measuring the state of consciousness of individuals is important for both basic research and clinical purposes. In recent years, several promising measures of consciousness, grounded in theoretical developments, have been proposed. However, the degrees to which these measures are affected by changes in brain activity that are not related to changes in the degree of consciousness has not been well tested. In this study, we examined whether several of these measures are modulated by the loading of cognitive resources.

METHODS

We recorded electroencephalography (EEG) from 12 participants in two conditions: (1) while passively attending to sensory stimuli related to the measures and (2) during increased cognitive load consisting of a demanding working memory task. We investigated whether a set of proposed objective EEG-based measures of consciousness differed between the passive and the cognitively demanding conditions.

RESULTS

The P300b event-related potential (sensitive to conscious awareness of deviance from an expected pattern in auditory stimuli) was significantly affected by concurrent performance on a working memory task, whereas various measures based on signal diversity of spontaneous and perturbed EEG were not.

CONCLUSION

Because signal diversity-based measures of spontaneous or perturbed EEG are not sensitive to the degree of cognitive load, we suggest that these measures may be used in clinical situations where attention, sensory processing, or command following might be impaired.

Surprising sounds influence risky decision making

Adaptive behavior depends on appropriate responses to environmental uncertainty. Incidental sensory events might simply be distracting and increase errors, but alternatively can lead to stereotyped responses despite their irrelevance. To evaluate these possibilities, we test whether task-irrelevant sensory prediction errors influence risky decision making in humans across seven experiments (total n = 1600). Rare auditory sequences preceding option presentation systematically increase risk taking and decrease choice perseveration (i.e., increased tendency to switch away from previously chosen options). The risk-taking and perseveration effects are dissociable by manipulating auditory statistics: when rare sequences end on standard tones, including when rare sequences consist only of standard tones, participants are less likely to perseverate after rare sequences but not more likely to take risks. Computational modeling reveals that these effects cannot be explained by increased decision noise but can be explained by value-independent risky bias and perseveration parameters, decision biases previously linked to dopamine. Control experiments demonstrate that both surprise effects can be eliminated when tone sequences are presented in a balanced or fully predictable manner, and that surprise effects cannot be explained by erroneous beliefs. These findings suggest that incidental sounds may influence many of the decisions we make in daily life.

Distributional learning drives statistical deafening

Humans and other animals use information about how likely it is for something to happen. The absolute and relative probability of an event influences a remarkable breadth of behaviors, from foraging for food to comprehending linguistic constructions -- even when these probabilities are learned implicitly. It is less clear how, and under what circumstances, statistical learning of simple probabilities might drive changes in perception and cognition. Here, across a series of 29 experiments, we probe listeners' sensitivity to task-irrelevant changes in the probability distribution of tones' acoustic frequency across tone-in-noise detection and tone duration decisions. We observe that the task-irrelevant frequency distribution influences the ability to detect a sound and the speed with which perceptual decisions are made. The shape of the probability distribution, its range, and a tone's relative position within that range impact observed patterns of suppression and enhancement of tone detection and decision making. Perceptual decisions are also modulated by a newly discovered perceptual bias, with lower frequencies in the distribution more often and more rapidly perceived as longer, and higher frequencies as shorter. Perception is sensitive to rapid distribution changes, but distributional learning from previous probability distributions also carries over. In fact, massed exposure to a single point along the dimension results in a sustained 'statistical deafening' along a range of subsequently encountered frequencies. This seemingly maladaptive loss of sensitivity - occurring entirely in the absence of feedback or reward - points to a gain mechanism that suppresses sensitivity to regions along a perceptual dimension that are less likely to be encountered.

Effective Connectivity Network of Aberrant Prediction Error Processing in Auditory Phantom Perception

Introduction: Prediction error (PE) is key to perception in the predictive coding framework. However, previous studies indicated the varied neural activities evoked by PE in tinnitus patients. Here, we aimed to reconcile the conflict by (1) a more nuanced view of PE, which could be driven by changing stimulus (stimulus-driven PE [sPE]) and violation of current context (context-driven PE [cPE]) and (2) investigating the aberrant connectivity networks that are engaged in the processing of the two types of PEs in tinnitus patients. Methods: Ten tinnitus patients with normal hearing and healthy controls were recruited, and a local-global auditory oddball paradigm was applied to measure the electroencephalographic difference between the two groups during sPE and cPE conditions. Results: Overall, the sPE condition engaged bottom-up and top-down connections, whereas the cPE condition engaged mostly top-down connections. The tinnitus group showed decreased sensitivity to the sPE and increased sensitivity to the cPE condition. Particularly, the auditory cortex and posterior cingulate cortex were the hubs for processing cPE in the control and tinnitus groups, respectively, showing the orientation to an internal state in tinnitus. Furthermore, tinnitus patients showed stronger connectivity to the parahippocampus and pregenual anterior cingulate cortex for the establishment of the prediction during the cPE condition. Conclusion: These results begin to dissect the role of changes in stimulus characteristics versus changes in the context of processing the same stimulus in mechanisms of tinnitus generation.

Chronic pain - A maladaptive compensation to unbalanced hierarchical predictive processing

The ability to perceive pain presents an interesting evolutionary advantage to adapt to an ever-changing environment. However, in the case of chronic pain (CP), pain perception hinders the capacity of the system to adapt to changing sensory environments. Similar to other chronic perceptual disorders, CP is also proposed to be a maladaptive compensation to aberrant sensory predictive processing. The local-global oddball paradigm relies on learning hierarchical rules and processing environmental irregularities at a local and global level. Prediction errors (PE) between actual and predicted input typically trigger an update of the forward model to limit the probability of encountering future PEs. It has been hypothesised that CP hinders forward model updating, reflected in increased local deviance and decreased global deviance. In the present study, we used the local-global paradigm to examine how CP influences hierarchical learning relative to healthy controls. As hypothesised, we observed that deviance in the stimulus characteristics evoked heightened local deviance and decreased global deviance of the stimulus-driven PE. This is also accompanied by respective changes in theta phase locking that is correlated with the subjective pain perception. Changes in the global deviant in the stimulus-driven-PE could also be explained by dampened attention-related responses. Changing the context of the auditory stimulus did not however show a difference in the context-driven PE. These findings suggest that CP is accompanied by maladaptive forward model updating where the constant presence of pain perception disrupts local deviance in non-nociceptive domains. Furthermore, we hypothesise that the auditory-processing based biomarker identified here could be a marker of domain-general dysfunction that could be confirmed by future research.

Crossmodal hierarchical predictive coding for audiovisual sequences in the human brain

Predictive coding theory suggests the brain anticipates sensory information using prior knowledge. While this theory has been extensively researched within individual sensory modalities, evidence for predictive processing across sensory modalities is limited. Here, we examine how crossmodal knowledge is represented and learned in the brain, by identifying the hierarchical networks underlying crossmodal predictions when information of one sensory modality leads to a prediction in another modality. We record electroencephalogram (EEG) during a crossmodal audiovisual local-global oddball paradigm, in which the predictability of transitions between tones and images are manipulated at both the stimulus and sequence levels. To dissect the complex predictive signals in our EEG data, we employed a model-fitting approach to untangle neural interactions across modalities and hierarchies. The model-fitting result demonstrates that audiovisual integration occurs at both the levels of individual stimulus interactions and multi-stimulus sequences. Furthermore, we identify the spatio-spectro-temporal signatures of prediction-error signals across hierarchies and modalities, and reveal that auditory and visual prediction errors are rapidly redirected to the central-parietal electrodes during learning through alpha-band interactions. Our study suggests a crossmodal predictive coding mechanism where unimodal predictions are processed by distributed brain networks to form crossmodal knowledge.

Habituation of Central and Electrodermal Responses to an Auditory Two-Stimulus Oddball Paradigm

The orienting reaction (OR) towards a new stimulus is subject to habituation, i.e., progressively attenuates with stimulus repetition. The skin conductance responses (SCRs) are known to represent a reliable measure of OR at the peripheral level. Yet, it is still a matter of debate which of the P3 subcomponents is the most likely to represent the central counterpart of the OR. The aim of the present work was to study habituation, recovery, and dishabituation phenomena intrinsic to a two-stimulus auditory oddball paradigm, one of the most-used paradigms both in research and clinic, by simultaneously recording SCRs and P3 in twenty healthy volunteers. Our findings show that the target stimulus was capable of triggering a more marked OR, as indexed by both SCRs and P3, compared to the standard stimulus, that could be due to its affective saliency and relevance for task completion; the application of temporal principal components analysis (PCA) to the P3 complex allowed us to identify several subcomponents including both early and late P3a (eP3a; lP3a), P3b, novelty P3 (nP3), and both a positive and a negative Slow Wave (+SW; -SW). Particularly, lP3a and P3b subcomponents showed a similar behavior to that observed for SCRs , suggesting them as central counterparts of OR. Finally, the P3 evoked by the first standard stimulus after the target showed a significant dishabituation phenomenon which could represent a sign of the local stimulus change. However, it did not reach a sufficient level to trigger an SCR/OR since it did not represent a salient event in the context of the task.

The Complex Pattern Mismatch Negativity as a Potential Indicator of Psychosis Across all Phases of Illness: A Meta-Analysis

Over the past decade, there has been extensive research on the mismatch negativity (MMN) and its promise as a biomarker of illness in people with schizophrenia (SZ). Nevertheless, when attempting to assess the early stages of illness progression, the utility of MMN has been inconsistent. Recently, researchers have been investigating a more advanced MMN paradigm (the complex MMN [cMMN]) which is believed to index higher-order cognitive processing and has been suggested to be a more effective indicator of the early phases of SZ. The cMMN is defined as a paradigm that relies on alterations within a pre-established pattern of stimuli. In this meta-analysis, we investigated cMMN deficits in individuals with SZ, including an analysis involving those in the first 5 years of illness. Our search also included individuals with bipolar disorder who experience psychosis; however, no related papers were found and thus, no findings are reported. Our findings indicate a small/moderate effect (d = 0.47), suggesting that individuals with SZ exhibit reduced cMMN amplitudes compared to individuals without SZ. Interestingly, this effect seems to be more pronounced in individuals within the first 5 years of their illness (d = 0.58), suggesting that cMMN might be a more sensitive biomarker in the early phases of SZ compared to traditional paradigms.

The developmental cognitive mechanism of learning algebraic rules from the dual-process theory perspective

Rule learning is an important ability that enables human beings to adapt to nature and develop civilizations. There have been many discussions on the mechanism and characteristics of algebraic rule learning, but there are still controversies due to the lack of theoretical guidance. Based on the dual-process theory, this study discussed the following arguments for algebraic rule learning across human and animal studies: whether algebraic rule learning is simply Type 1 processing, whether algebraic rule learning is a domain-general ability, whether algebraic rule learning is shared by humans and animals, and whether an algebraic rule is learned consciously. Moreover, we propose that algebraic rule learning is possibly a cognitive process that combines both Type 1 and Type 2 processing. Further exploration is required to establish the essence and neural basis of algebraic rule learning.

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.

Multimodal assessment improves neuroprognosis performance in clinically unresponsive critical-care patients with brain injury

Accurately predicting functional outcomes for unresponsive patients with acute brain injury is a medical, scientific and ethical challenge. This prospective study assesses how a multimodal approach combining various numbers of behavioral, neuroimaging and electrophysiological markers affects the performance of outcome predictions. We analyzed data from 349 patients admitted to a tertiary neurointensive care unit between 2009 and 2021, categorizing prognoses as good, uncertain or poor, and compared these predictions with observed outcomes using the Glasgow Outcome Scale-Extended (GOS-E, levels ranging from 1 to 8, with higher levels indicating better outcomes). After excluding cases with life-sustaining therapy withdrawal to mitigate the self-fulfilling prophecy bias, our findings reveal that a good prognosis, compared with a poor or uncertain one, is associated with better one-year functional outcomes (common odds ratio (95% CI) for higher GOS-E: OR = 14.57 (5.70-40.32), P < 0.001; and 2.9 (1.56-5.45), P < 0.001, respectively). Moreover, increasing the number of assessment modalities decreased uncertainty (OR = 0.35 (0.21-0.59), P < 0.001) and improved prognostic accuracy (OR = 2.72 (1.18-6.47), P = 0.011). Our results underscore the value of multimodal assessment in refining neuroprognostic precision, thereby offering a robust foundation for clinical decision-making processes for acutely brain-injured patients. ClinicalTrials.gov registration: NCT04534777 .

Functional and structural brain connectivity in disorders of consciousness

Brain connectivity, allowing information to be shared between distinct cortical areas and thus to be processed in an integrated way, has long been considered critical for consciousness. However, the relationship between functional intercortical interactions and the structural connections thought to underlie them is poorly understood. In the present work, we explore both functional (with an EEG-based metric: the median weighted symbolic mutual information in the theta band) and structural (with a brain MRI-based metric: fractional anisotropy) connectivities in a cohort of 78 patients with disorders of consciousness. Both metrics could distinguish patients in a vegetative state from patients in minimally conscious state. Crucially, we discovered a significant positive correlation between functional and structural connectivities. Furthermore, we showed that this structure-function relationship is more specifically observed when considering structural connectivity within the intra- and inter-hemispheric long-distance cortico-cortical bundles involved in the Global Neuronal Workspace (GNW) theory of consciousness, thus supporting predictions of this model. Altogether, these results support the interest of multimodal assessments of brain connectivity in refining the diagnostic evaluation of patients with disorders of consciousness.

Mismatch Negativity and P300 in the Diagnosis and Prognostic Assessment of Coma and Other Disorders of Consciousness

BACKGROUND

The objective of this study was to investigate the value of mismatch negativity (MMN) and P300 event-related potentials for discriminating the consciousness state and predicting improvement of consciousness at 6 months in patients with coma and other disorders of consciousness (DOC).

METHODS

We performed MMN and P300 on 42 patients with DOC with a mean onset time of 40.21 ± 19.43 days. These patients with DOC were categorized into coma, unresponsive wakefulness syndrome (UWS), minimal consciousness minus (MCS-), and minimal consciousness plus (MCS +) groups according to neurobehavioral assessment and the Coma Recovery Scale-Revised score. The primary outcome was the improvement of consciousness at 6 months in patients with DOC. We assessed the efficacy of MMN and P300 in quantitatively predicting the prognosis at 6 months and the capability of MMN and P300 parameters to differentiate between DOC.

RESULTS

At least one significant difference in either MMN or P300 parameters was displayed among the DOC groups, but not between the MCS- and MCS+ groups (significance level: 0.05). Both MMN and P300 amplitudes showed desirable predictive accuracy at 6 months, with areas under the curve (AUCs) of 0.859 and 0.856, respectively. The optimal thresholds for MMN and P300 amplitudes were 2.044 and 1.095 μV. However, the combined MMN-P300 amplitude showed better 6-month predictive accuracy (AUC 0.934, 95% confidence interval 0.860-1.000), with a sensitivity of 85% and a specificity of 90.9%.

CONCLUSIONS

MMN and P300 may help discriminate among coma, UWS, and MCS, but not between patients with MCS- and patients with MCS+ . The MMN amplitude, P300 amplitude, and especially combined MMN-P300 amplitude at 6 months may be interesting predictors of consciousness improvement at 6 months in patients with DOC.

TRIAL REGISTRATION

Chinese Clinical Trial Registry identifier ChiCTR2400083798.

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.

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.

Erroneous predictive coding across brain hierarchies in a non-human primate model of autism spectrum disorder

In autism spectrum disorder (ASD), atypical sensory experiences are often associated with irregularities in predictive coding, which proposes that the brain creates hierarchical sensory models via a bidirectional process of predictions and prediction errors. However, it remains unclear how these irregularities manifest across different functional hierarchies in the brain. To address this, we study a marmoset model of ASD induced by valproic acid (VPA) treatment. We record high-density electrocorticography (ECoG) during an auditory task with two layers of temporal control, and applied a quantitative model to quantify the integrity of predictive coding across two distinct hierarchies. Our results demonstrate a persistent pattern of sensory hypersensitivity and unstable predictions across two brain hierarchies in VPA-treated animals, and reveal the associated spatio-spectro-temporal neural signatures. Despite the regular occurrence of imprecise predictions in VPA-treated animals, we observe diverse configurations of underestimation or overestimation of sensory regularities within the hierarchies. Our results demonstrate the coexistence of the two primary Bayesian accounts of ASD: overly-precise sensory observations and weak prior beliefs, and offer a potential multi-layered biomarker for ASD, which could enhance our understanding of its diverse symptoms.

Carrier-frequency specific omission-related neural activity in ordered sound sequences is independent of omission-predictability

Regularities in our surroundings lead to predictions about upcoming events. Previous research has shown that omitted sounds during otherwise regular tone sequences elicit frequency-specific neural activity related to the upcoming but omitted tone. We tested whether this neural response is depending on the unpredictability of the omission. Therefore, we recorded magnetencephalography (MEG) data while participants listened to ordered or random tone sequences with omissions occurring either ordered or randomly. Using multivariate pattern analysis shows that the frequency-specific neural pattern during omission within ordered tone sequences occurs independent of the regularity of the omissions. These results suggest that the auditory predictions based on sensory experiences are not immediately updated by violations of those expectations.

Perceptual Awareness in Human Infants: What is the Evidence?

Perceptual awareness in infants during the first year of life is understudied, despite the philosophical, scientific, and clinical importance of understanding how and when consciousness emerges during human brain development. Although parents are undoubtedly convinced that their infant is conscious, the lack of adequate experimental paradigms to address this question in preverbal infants has been a hindrance to research on this topic. However, recent behavioral and brain imaging studies have shown that infants are engaged in complex learning from an early age and that their brains are more structured than traditionally thought. I will present a rapid overview of these results, which might provide indirect evidence of early perceptual awareness and then describe how a more systematic approach to this question could stand within the framework of global workspace theory, which identifies specific signatures of conscious perception in adults. Relying on these brain signatures as a benchmark for conscious perception, we can deduce that it exists in the second half of the first year, whereas the evidence before the age of 5 months is less solid, mainly because of the paucity of studies. The question of conscious perception before term remains open, with the possibility of short periods of conscious perception, which would facilitate early learning. Advances in brain imaging and growing interest in this subject should enable us to gain a better understanding of this important issue in the years to come.

Global Field Time-Frequency Representation-Based Discriminative Similarity Analysis of Passive Auditory ERPs for Diagnosis of Disorders of Consciousness

Behavioural diagnosis of patients with disorders of consciousness (DOC) is challenging and prone to inaccuracies. Consequently, there have been increased efforts to develop bedside assessment based on EEG and event-related potentials (ERPs) that are more sensitive to the neural factors supporting conscious awareness. However, individual detection of residual consciousness using these techniques is less established. Here, we hypothesize that the cross-state similarity (defined as the similarity between healthy and impaired conscious states) of passive brain responses to auditory stimuli can index the level of awareness in individual DOC patients. To this end, we introduce the global field time-frequency representation-based discriminative similarity analysis (GFTFR-DSA). This method quantifies the average cross-state similarity index between an individual patient and our constructed healthy templates using the GFTFR as an EEG feature. We demonstrate that the proposed GFTFR feature exhibits superior within-group consistency in 34 healthy controls over traditional EEG features such as temporal waveforms. Second, we observed the GFTFR-based similarity index was significantly higher in patients with a minimally conscious state (MCS, 40 patients) than those with unresponsive wakefulness syndrome (UWS, 54 patients), supporting our hypothesis. Finally, applying a linear support vector machine classifier for individual MCS/UWS classification, the model achieved a balanced accuracy and F1 score of 0.77. Overall, our findings indicate that combining discriminative and interpretable markers, along with automatic machine learning algorithms, is effective for the differential diagnosis in patients with DOC. Importantly, this approach can, in principle, be transferred into any ERP of interest to better inform DOC diagnoses.

Attentional ERPs in consumers of smoked and insufflated cocaine associated with neuropsychological performance

BACKGROUND

Cocaine consumption is associated with reduced attentional event-related potentials (ERPs), namely P3a and P3b, indicating bottom-up and top-down deficits respectively. At cognitive level, these impairments are larger for faster routes of administration (e.g., smoked cocaine [SC]) than slower routes (e.g., insufflated cocaine [IC]). Here we assess these ERPs considering the route of cocaine administration. We hypothesized that SC dependent (SCD) would exhibit reduced amplitude of the P3a, while both SCD and IC dependent (ICD) would show reduced amplitude of the P3b.

METHODS

We examined 25 SCD, 22 ICD matched by poly-consumption profiles, and 25 controls matched by demographic variables. We combined EEG data from the Global-Local task with behavioral data from attentional cognitive tasks.

RESULTS

At the behavioral level, SCD exhibited attentional deficits in both bottom-up and top-down processes, while ICD only showed a tendency for top-down deficits. The amplitude of P3a and P3b was lower in Users groups. We observed subtle route-based differences, with larger differences in the P3a for SCD and in the P3b for ICD. Neurophysiological and behavioral data converged, with the P3a associated to bottom-up performance and P3b to top-down.

CONCLUSIONS

Different routes of administration lead to distinct attentional neurocognitive profiles. Specifically, SCD showed greater attentional impairment, mainly at bottom-up/P3a, while ICD showed a trend of top-down/P3b deficits. These findings emphasize the crucial role of considering the route of administration in both clinical and research settings and support the use of attentional ERPs as valid measures for assessing attentional deficits in substance Dependence.

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.

Investigating sensitivity to multi-domain prediction errors in chronic auditory phantom perception

The perception of a continuous phantom in a sensory domain in the absence of an external stimulus is explained as a maladaptive compensation of aberrant predictive coding, a proposed unified theory of brain functioning. If this were true, these changes would occur not only in the domain of the phantom percept but in other sensory domains as well. We confirm this hypothesis by using tinnitus (continuous phantom sound) as a model and probe the predictive coding mechanism using the established local-global oddball paradigm in both the auditory and visual domains. We observe that tinnitus patients are sensitive to changes in predictive coding not only in the auditory but also in the visual domain. We report changes in well-established components of event-related EEG such as the mismatch negativity. Furthermore, deviations in stimulus characteristics were correlated with the subjective tinnitus distress. These results provide an empirical confirmation that aberrant perceptions are a symptom of a higher-order systemic disorder transcending the domain of the percept.

Distributed representations of prediction error signals across the cortical hierarchy are synergistic

A relevant question concerning inter-areal communication in the cortex is whether these interactions are synergistic. Synergy refers to the complementary effect of multiple brain signals conveying more information than the sum of each isolated signal. Redundancy, on the other hand, refers to the common information shared between brain signals. Here, we dissociated cortical interactions encoding complementary information (synergy) from those sharing common information (redundancy) during prediction error (PE) processing. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics encoded synergistic and redundant information about PE processing. The information conveyed by ERPs and BB signals was synergistic even at lower stages of the hierarchy in the auditory cortex and between auditory and frontal regions. Using a brain-constrained neural network, we simulated the synergy and redundancy observed in the experimental results and demonstrated that the emergence of synergy between auditory and frontal regions requires the presence of strong, long-distance, feedback, and feedforward connections. These results indicate that distributed representations of PE signals across the cortical hierarchy can be highly synergistic.

Dissecting Mismatch Negativity: Early and Late Subcomponents for Detecting Deviants in Local and Global Sequence Regularities

Mismatch negativity (MMN) is commonly recognized as a neural signal of prediction error evoked by deviants from the expected patterns of sensory input. Studies show that MMN diminishes when sequence patterns become more predictable over a longer timescale. This implies that MMN is composed of multiple subcomponents, each responding to different levels of temporal regularities. To probe the hypothesized subcomponents in MMN, we record human electroencephalography during an auditory local-global oddball paradigm where the tone-to-tone transition probability (local regularity) and the overall sequence probability (global regularity) are manipulated to control temporal predictabilities at two hierarchical levels. We find that the size of MMN is correlated with both probabilities and the spatiotemporal structure of MMN can be decomposed into two distinct subcomponents. Both subcomponents appear as negative waveforms, with one peaking early in the central-frontal area and the other late in a more frontal area. With a quantitative predictive coding model, we map the early and late subcomponents to the prediction errors that are tied to local and global regularities, respectively. Our study highlights the hierarchical complexity of MMN and offers an experimental and analytical platform for developing a multitiered neural marker applicable in clinical settings.

Tests for consciousness in humans and beyond

Which systems/organisms are conscious? New tests for consciousness ('C-tests') are urgently needed. There is persisting uncertainty about when consciousness arises in human development, when it is lost due to neurological disorders and brain injury, and how it is distributed in nonhuman species. This need is amplified by recent and rapid developments in artificial intelligence (AI), neural organoids, and xenobot technology. Although a number of C-tests have been proposed in recent years, most are of limited use, and currently we have no C-tests for many of the populations for which they are most critical. Here, we identify challenges facing any attempt to develop C-tests, propose a multidimensional classification of such tests, and identify strategies that might be used to validate them.

Overlearned sequence and perceived time: possible involvement of attention

Overlearned sequences, characterized by specific ordinal ranks for each element, elicit strong predictions when presented in their natural order. The present study aimed to test the role of predictions on the perceived duration in a stimulus series that followed an overlearned sequence. Participants judged the duration of the target digit in a sequence that followed a regular or random order, while the overall context in which these sequences were presented was varied in two blocks. The results suggest that, with the possible involvement of attention, the target element that followed the regular order was perceived to be relatively accurate. The violation of an overlearned sequence leads to an underestimation of duration, particularly when the participants are aware of the violation. Further, the perceived duration of the target element in an overlearned sequence does not modulate as a function of the global context. These findings contribute to our understanding of the differential effect of various predictive processes on perceived time.

Spontaneously emerging internal models of visual sequences combine abstract and event-specific information in the prefrontal cortex

When exposed to sensory sequences, do macaque monkeys spontaneously form abstract internal models that generalize to novel experiences? Here, we show that neuronal populations in macaque ventrolateral prefrontal cortex jointly encode visual sequences by separate codes for the specific pictures presented and for their abstract sequential structure. We recorded prefrontal neurons while macaque monkeys passively viewed visual sequences and sequence mismatches in the local-global paradigm. Even without any overt task or response requirements, prefrontal populations spontaneously form representations of sequence structure, serial order, and image identity within distinct but superimposed neuronal subspaces. Representations of sequence structure rapidly update following single exposure to a mismatch sequence, while distinct populations represent mismatches for sequences of different complexity. Finally, those representations generalize across sequences following the same repetition structure but comprising different images. These results suggest that prefrontal populations spontaneously encode rich internal models of visual sequences reflecting both content-specific and abstract information.

Neural correlates of novelty detection in the primary auditory cortex of behaving monkeys

The neural mechanisms underlying novelty detection are not well understood, especially in relation to behavior. Here, we present single-unit responses from the primary auditory cortex (A1) from two monkeys trained to detect deviant tones amid repetitive ones. Results show that monkeys can detect deviant sounds, and there is a strong correlation between late neuronal responses (250-350 ms after deviant onset) and the monkeys' perceptual decisions. The magnitude and timing of both neuronal and behavioral responses are increased by larger frequency differences between the deviant and standard tones and by increasing the number of standard tones preceding the deviant. This suggests that A1 neurons encode novelty detection in behaving monkeys, influenced by stimulus relevance and expectations. This study provides evidence supporting aspects of predictive coding in the sensory cortex.

Neural complexity and the spectral slope characterise auditory processing in wakefulness and sleep

Auditory processing and the complexity of neural activity can both indicate residual consciousness levels and differentiate states of arousal. However, how measures of neural signal complexity manifest in neural activity following environmental stimulation and, more generally, how the electrophysiological characteristics of auditory responses change in states of reduced consciousness remain under-explored. Here, we tested the hypothesis that measures of neural complexity and the spectral slope would discriminate stages of sleep and wakefulness not only in baseline electroencephalography (EEG) activity but also in EEG signals following auditory stimulation. High-density EEG was recorded in 21 participants to determine the spatial relationship between these measures and between EEG recorded pre- and post-auditory stimulation. Results showed that the complexity and the spectral slope in the 2-20 Hz range discriminated between sleep stages and had a high correlation in sleep. In wakefulness, complexity was strongly correlated to the 20-40 Hz spectral slope. Auditory stimulation resulted in reduced complexity in sleep compared to the pre-stimulation EEG activity and modulated the spectral slope in wakefulness. These findings confirm our hypothesis that electrophysiological markers of arousal are sensitive to sleep/wake states in EEG activity during baseline and following auditory stimulation. Our results have direct applications to studies using auditory stimulation to probe neural functions in states of reduced consciousness.

Assessing mismatch negativity (MMN) and P3b within-individual sensitivity - A comparison between the local-global paradigm and two specialized oddball sequences

Mismatch negativity (MMN) and P3b are well known for their clinical utility. There exists no gold standard, however, for acquiring them as EEG markers of consciousness in clinical settings. This may explain why the within-individual sensitivity of MMN/P3b paradigms is often quite poor and why seemingly identical EEG markers can behave differently across Disorders of consciousness (DoC) studies. Here, we compare two traditional paradigms for MMN or P3b assessment with the recently more popular local-global paradigm that promises to assess MMN and P3b orthogonally within one oddball sequence. All three paradigms were administered to healthy participants (N = 15) with concurrent EEG. A clear MMN and local effect were found for 15/15 participants. The P3b and global effect were found for 14/15 and 13/15 participants, respectively. There were no systematic differences between the global effect and P3b. Indeed, P3b amplitude was highly correlated across paradigms. The local effect differed clearly from the MMN, however. It occurred earlier than MMN and was followed by a much more prominent P3a. The peak latencies and amplitudes were also not correlated across paradigms. Caution should therefore be exercised when comparing the local effect and MMN across studies. We conclude that the within-individual MMN sensitivity is adequate for both the local-global and a dedicated MMN paradigm. The within-individual sensitivity of P3b was lower than expected for both the local-global and a dedicated P3b paradigm, which may explain the often-low sensitivity of P3b paradigms in patients with DoC.

Altered hierarchical auditory predictive processing after lesions to the orbitofrontal cortex

Orbitofrontal cortex (OFC) is classically linked to inhibitory control, emotion regulation, and reward processing. Recent perspectives propose that the OFC also generates predictions about perceptual events, actions, and their outcomes. We tested the role of the OFC in detecting violations of prediction at two levels of abstraction (i.e., hierarchical predictive processing) by studying the event-related potentials (ERPs) of patients with focal OFC lesions (n = 12) and healthy controls (n = 14) while they detected deviant sequences of tones in a local-global paradigm. The structural regularities of the tones were controlled at two hierarchical levels by rules defined at a local (i.e., between tones within sequences) and at a global (i.e., between sequences) level. In OFC patients, ERPs elicited by standard tones were unaffected at both local and global levels compared to controls. However, patients showed an attenuated mismatch negativity (MMN) and P3a to local prediction violation, as well as a diminished MMN followed by a delayed P3a to the combined local and global level prediction violation. The subsequent P3b component to conditions involving violations of prediction at the level of global rules was preserved in the OFC group. Comparable effects were absent in patients with lesions restricted to the lateral PFC, which lends a degree of anatomical specificity to the altered predictive processing resulting from OFC lesion. Overall, the altered magnitudes and time courses of MMN/P3a responses after lesions to the OFC indicate that the neural correlates of detection of auditory regularity violation are impacted at two hierarchical levels of rule abstraction.

The empirical status of predictive coding and active inference

Research on predictive processing models has focused largely on two specific algorithmic theories: Predictive Coding for perception and Active Inference for decision-making. While these interconnected theories possess broad explanatory potential, they have only recently begun to receive direct empirical evaluation. Here, we review recent studies of Predictive Coding and Active Inference with a focus on evaluating the degree to which they are empirically supported. For Predictive Coding, we find that existing empirical evidence offers modest support. However, some positive results can also be explained by alternative feedforward (e.g., feature detection-based) models. For Active Inference, most empirical studies have focused on fitting these models to behavior as a means of identifying and explaining individual or group differences. While Active Inference models tend to explain behavioral data reasonably well, there has not been a focus on testing empirical validity of active inference theory per se, which would require formal comparison to other models (e.g., non-Bayesian or model-free reinforcement learning models). This review suggests that, while promising, a number of specific research directions are still necessary to evaluate the empirical adequacy and explanatory power of these algorithms.

Cognitive Motor Dissociation: Gap Analysis and Future Directions

BACKGROUND

Patients with disorders of consciousness who are behaviorally unresponsive may demonstrate volitional brain responses to motor imagery or motor commands detectable on functional magnetic resonance imaging or electroencephalography. This state of cognitive motor dissociation (CMD) may have prognostic significance.

METHODS

The Neurocritical Care Society's Curing Coma Campaign identified an international group of experts who convened in a series of monthly online meetings between September 2021 and April 2023 to examine the science of CMD and identify key knowledge gaps and unmet needs.

RESULTS

The group identified major knowledge gaps in CMD research: (1) lack of information about patient experiences and caregiver accounts of CMD, (2) limited epidemiological data on CMD, (3) uncertainty about underlying mechanisms of CMD, (4) methodological variability that limits testing of CMD as a biomarker for prognostication and treatment trials, (5) educational gaps for health care personnel about the incidence and potential prognostic relevance of CMD, and (6) challenges related to identification of patients with CMD who may be able to communicate using brain-computer interfaces.

CONCLUSIONS

To improve the management of patients with disorders of consciousness, research efforts should address these mechanistic, epidemiological, bioengineering, and educational gaps to enable large-scale implementation of CMD assessment in clinical practice.

A Novel Approach to Screen for Somatosensory Evoked Potentials in Critical Care

BACKGROUND

Somatosensory evoked potentials (SSEPs) help prognostication, particularly in patients with diffuse brain injury. However, use of SSEP is limited in critical care. We propose a novel, low-cost approach allowing acquisition of screening SSEP using widely available intensive care unit (ICU) equipment, specifically a peripheral "train-of-four" stimulator and standard electroencephalograph.

METHODS

The median nerve was stimulated using a train-of-four stimulator, and a standard 21-channel electroencephalograph was recorded to generate the screening SSEP. Generation of the SSEP was supported by visual inspection, univariate event-related potentials statistics, and a multivariate support vector machine (SVM) decoding algorithm. This approach was validated in 15 healthy volunteers and validated against standard SSEPs in 10 ICU patients. The ability of this approach to predict poor neurological outcome, defined as death, vegetative state, or severe disability at 6 months, was tested in an additional set of 39 ICU patients.

RESULTS

In each of the healthy volunteers, both the univariate and the SVM methods reliably detected SSEP responses. In patients, when compared against the standard SSEP method, the univariate event-related potentials method matched in nine of ten patients (sensitivity = 94%, specificity = 100%), and the SVM had 100% sensitivity and specificity when compared with the standard method. For the 49 ICU patients, we performed both the univariate and the SVM methods: a bilateral absence of short latency responses (n = 8) predicted poor neurological outcome with 0% FPR (sensitivity = 21%, specificity = 100%).

CONCLUSIONS

Somatosensory evoked potentials can reliably be recorded using the proposed approach. Given the very good but slightly lower sensitivity of absent SSEPs in the proposed screening approach, confirmation of absent SSEP responses using standard SSEP recordings is advised.

Multiple Concurrent Predictions Inform Prediction Error in the Human Auditory Pathway

The key assumption of the predictive coding framework is that internal representations are used to generate predictions on how the sensory input will look like in the immediate future. These predictions are tested against the actual input by the so-called prediction error units, which encode the residuals of the predictions. What happens to prediction errors, however, if predictions drawn by different stages of the sensory hierarchy contradict each other? To answer this question, we conducted two fMRI experiments while female and male human participants listened to sequences of sounds: pure tones in the first experiment and frequency-modulated sweeps in the second experiment. In both experiments, we used repetition to induce predictions based on stimulus statistics (stats-informed predictions) and abstract rules disclosed in the task instructions to induce an orthogonal set of (task-informed) predictions. We tested three alternative scenarios: neural responses in the auditory sensory pathway encode prediction error with respect to (1) the stats-informed predictions, (2) the task-informed predictions, or (3) a combination of both. Results showed that neural populations in all recorded regions (bilateral inferior colliculus, medial geniculate body, and primary and secondary auditory cortices) encode prediction error with respect to a combination of the two orthogonal sets of predictions. The findings suggest that predictive coding exploits the non-linear architecture of the auditory pathway for the transmission of predictions. Such non-linear transmission of predictions might be crucial for the predictive coding of complex auditory signals like speech.Significance Statement Sensory systems exploit our subjective expectations to make sense of an overwhelming influx of sensory signals. It is still unclear how expectations at each stage of the processing pipeline are used to predict the representations at the other stages. The current view is that this transmission is hierarchical and linear. Here we measured fMRI responses in auditory cortex, sensory thalamus, and midbrain while we induced two sets of mutually inconsistent expectations on the sensory input, each putatively encoded at a different stage. We show that responses at all stages are concurrently shaped by both sets of expectations. The results challenge the hypothesis that expectations are transmitted linearly and provide for a normative explanation of the non-linear physiology of the corticofugal sensory system.

Common Data Elements for Disorders of Consciousness: Recommendations from the Electrophysiology Working Group

BACKGROUND

Electroencephalography (EEG) has long been recognized as an important tool in the investigation of disorders of consciousness (DoC). From inspection of the raw EEG to the implementation of quantitative EEG, and more recently in the use of perturbed EEG, it is paramount to providing accurate diagnostic and prognostic information in the care of patients with DoC. However, a nomenclature for variables that establishes a convention for naming, defining, and structuring data for clinical research variables currently is lacking. As such, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups composed of experts in the field to construct common data elements (CDEs) to provide recommendations for DoC, with the main goal of facilitating data collection and standardization of reporting. This article summarizes the recommendations of the electrophysiology DoC working group.

METHODS

After assessing previously published pertinent CDEs, we developed new CDEs and categorized them into "disease core," "basic," "supplemental," and "exploratory." Key EEG design elements, defined as concepts that pertained to a methodological parameter relevant to the acquisition, processing, or analysis of data, were also included but were not classified as CDEs.

RESULTS

After identifying existing pertinent CDEs and developing novel CDEs for electrophysiology in DoC, variables were organized into a framework based on the two primary categories of resting state EEG and perturbed EEG. Using this categorical framework, two case report forms were generated by the working group.

CONCLUSIONS

Adherence to the recommendations outlined by the electrophysiology working group in the resting state EEG and perturbed EEG case report forms will facilitate data collection and sharing in DoC research on an international level. In turn, this will allow for more informed and reliable comparison of results across studies, facilitating further advancement in the realm of DoC research.

A multimodal cortical network of sensory expectation violation revealed by fMRI

The brain is subjected to multi-modal sensory information in an environment governed by statistical dependencies. Mismatch responses (MMRs), classically recorded with EEG, have provided valuable insights into the brain's processing of regularities and the generation of corresponding sensory predictions. Only few studies allow for comparisons of MMRs across multiple modalities in a simultaneous sensory stream and their corresponding cross-modal context sensitivity remains unknown. Here, we used a tri-modal version of the roving stimulus paradigm in fMRI to elicit MMRs in the auditory, somatosensory and visual modality. Participants (N = 29) were simultaneously presented with sequences of low and high intensity stimuli in each of the three senses while actively observing the tri-modal input stream and occasionally reporting the intensity of the previous stimulus in a prompted modality. The sequences were based on a probabilistic model, defining transition probabilities such that, for each modality, stimuli were more likely to repeat (p = .825) than change (p = .175) and stimulus intensities were equiprobable (p = .5). Moreover, each transition was conditional on the configuration of the other two modalities comprising global (cross-modal) predictive properties of the sequences. We identified a shared mismatch network of modality general inferior frontal and temporo-parietal areas as well as sensory areas, where the connectivity (psychophysiological interaction) between these regions was modulated during mismatch processing. Further, we found deviant responses within the network to be modulated by local stimulus repetition, which suggests highly comparable processing of expectation violation across modalities. Moreover, hierarchically higher regions of the mismatch network in the temporo-parietal area around the intraparietal sulcus were identified to signal cross-modal expectation violation. With the consistency of MMRs across audition, somatosensation and vision, our study provides insights into a shared cortical network of uni- and multi-modal expectation violation in response to sequence regularities.

Consciousness in the cradle: on the emergence of infant experience

Although each of us was once a baby, infant consciousness remains mysterious and there is no received view about when, and in what form, consciousness first emerges. Some theorists defend a 'late-onset' view, suggesting that consciousness requires cognitive capacities which are unlikely to be in place before the child's first birthday at the very earliest. Other theorists defend an 'early-onset' account, suggesting that consciousness is likely to be in place at birth (or shortly after) and may even arise during the third trimester. Progress in this field has been difficult, not just because of the challenges associated with procuring the relevant behavioral and neural data, but also because of uncertainty about how best to study consciousness in the absence of the capacity for verbal report or intentional behavior. This review examines both the empirical and methodological progress in this field, arguing that recent research points in favor of early-onset accounts of the emergence of consciousness.

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.

Twenty-four-hour rhythmicities in disorders of consciousness are associated with a favourable outcome

Fluctuations of consciousness and their rhythmicities have been rarely studied in patients with a disorder of consciousness after acute brain injuries. 24-h assessment of brain (EEG), behaviour (eye-opening), and circadian (clock-controlled hormones secretion from urine) functions was performed in acute brain-injured patients. The distribution, long-term predictability, and rhythmicity (circadian/ultradian) of various EEG features were compared with the initial clinical status, the functional outcome, and the circadian rhythmicities of behaviour and clock-controlled hormones. Here we show that more physiological and favourable patterns of fluctuations are associated with a higher 24 h predictability and sharp up-and-down shape of EEG switches, reminiscent of the Flip-Flop model of sleep. Multimodal rhythmic analysis shows that patients with simultaneous circadian rhythmicity for brain, behaviour, and hormones had a favourable outcome. Finally, both re-emerging EEG fluctuations and homogeneous 24-h cycles for EEG, eye-opening, and hormones appeared as surrogates for preserved functionality in brainstem and basal forebrain, which are key prognostic factors for later improvement. While the recovery of consciousness has previously been related to a high short-term complexity, we suggest in this exploratory study the importance of the high predictability of the 24 h long-term generation of brain rhythms and highlight the importance of circadian body-brain rhythms in awakening.

Brainstem fMRI signaling of surprise across different types of deviant stimuli

Detection of deviant stimuli is crucial to orient and adapt our behavior. Previous work shows that deviant stimuli elicit phasic activation of the locus coeruleus (LC), which releases noradrenaline and controls central arousal. However, it is unclear whether the detection of behaviorally relevant deviant stimuli selectively triggers LC responses or other neuromodulatory systems (dopamine, serotonin, and acetylcholine). We combine human functional MRI (fMRI) recordings optimized for brainstem imaging with pupillometry to perform a mapping of deviant-related responses in subcortical structures. Participants have to detect deviant items in a "local-global" paradigm that distinguishes between deviance based on the stimulus probability and the sequence structure. fMRI responses to deviant stimuli are distributed in many cortical areas. Both types of deviance elicit responses in the pupil, LC, and other neuromodulatory systems. Our results reveal that the detection of task-relevant deviant items recruits the same multiple subcortical systems across computationally different types of deviance.

Pupil dilation response elicited by violations of auditory regularities is a promising but challenging approach to probe consciousness at the bedside

Pupil dilation response (PDR) has been proposed as a physiological marker of conscious access to a stimulus or its attributes, such as novelty. In a previous study on healthy volunteers, we adapted the auditory "local global" paradigm and showed that violations of global regularity elicited a PDR. Notably without instructions, this global effect was present only in participants who could consciously report violations of global regularities. In the present study, we used a similar approach in 24 non-communicating patients affected with a Disorder of Consciousness (DoC) and compared PDR to ERPs regarding diagnostic and prognostic performance. At the group level, global effect could not be detected in DoC patients. At the individual level, the only patient with a PDR global effect was in a MCS and recovered consciousness at 6 months. Contrasting the most regular trials to the most irregular ones improved PDR's diagnostic and prognostic power in DoC patients. Pupillometry is a promising tool but requires several methodological improvements to enhance the signal-to-noise ratio and make it more robust for probing consciousness and cognition in DoC patients.

Inaccessible time to visual awareness during attentional blinks in macaques and humans

Even when we attend to successive visual events, we often cannot notice an event occurring during a certain temporal window. Such an inaccessible time for visual awareness is known as "attentional blink" (AB). Whether AB is a phenomenon unique to humans or exists also in other animals is unclear. Using a dual-task paradigm shared between macaques and humans, we here demonstrate a nonhuman primate model of AB. Although macaques also showed behavioral signatures of AB, their AB effect lasted longer than that of humans. To map the relation between macaque and human ABs, we introduced a time warping analysis. The analysis revealed a formal structure behind the interspecies difference of AB; the temporal window of macaque AB was scaled from that of human AB. The present study opens the door to combining the approaches of neuroscience, psychophysics, and theoretical models to further identify a scale-invariant biological substrate of visual awareness.

Is predictive coding falsifiable?

Predictive-coding has justifiably become a highly influential theory in Neuroscience. However, the possibility of its unfalsifiability has been raised. We argue that if predictive-coding were unfalsifiable, it would be a problem, but there are patterns of behavioural and neuroimaging data that would stand against predictive-coding. Contra (vanilla) predictive patterns are those in which the more expected stimulus generates the largest evoked-response. However, basic formulations of predictive-coding mandate that an expected stimulus should generate little, if any, prediction error and thus little, if any, evoked-response. It has, though, been argued that contra (vanilla) predictive patterns can be obtained if precision is higher for expected stimuli. Certainly, using precision, one can increase the amplitude of an evoked-response, turning a predictive into a contra (vanilla) predictive pattern. We demonstrate that, while this is true, it does not present an absolute barrier to falsification. This is because increasing precision also reduces latency and increases the frequency of the response. These properties can be used to determine whether precision-weighting in predictive-coding justifiably explains a contra (vanilla) predictive pattern, ensuring that predictive-coding is falsifiable.

Behavioral and brain responses to verbal stimuli reveal transient periods of cognitive integration of the external world during sleep

Sleep has long been considered as a state of behavioral disconnection from the environment, without reactivity to external stimuli. Here we questioned this 'sleep disconnection' dogma by directly investigating behavioral responsiveness in 49 napping participants (27 with narcolepsy and 22 healthy volunteers) engaged in a lexical decision task. Participants were instructed to frown or smile depending on the stimulus type. We found accurate behavioral responses, visible via contractions of the corrugator or zygomatic muscles, in most sleep stages in both groups (except slow-wave sleep in healthy volunteers). Across sleep stages, responses occurred more frequently when stimuli were presented during high cognitive states than during low cognitive states, as indexed by prestimulus electroencephalography. Our findings suggest that transient windows of reactivity to external stimuli exist during bona fide sleep, even in healthy individuals. Such windows of reactivity could pave the way for real-time communication with sleepers to probe sleep-related mental and cognitive processes.