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Maria Niedernhuber,1,2,* Joaquim Streicher,1,3,* Bigna Leggenhager,2,4 Tristan A Bekinschtein1,3 1Cambridge Consciousness and Cognition Lab, Department of Psychology, University of Cambridge, Cambridge, UK; 2Department of Psychology, University of Zurich, Zurich, Switzerland; 3Human Experience Dynamics Ltd, London, UK; 4Department of Psychology, University of Konstanz, Konstanz, Germany*These authors contributed equally to this workCorrespondence: Tristan A Bekinschtein, Department of Psychology, University of Cambridge, Downing Pl, Cambridge, CB2 3EB, UK, Email tb419@cam.ac.ukIntroduction: Fluctuations of chronic pain levels are determined by a complex interplay of cognitive, emotional and perceptual variables. We introduce a pain tracking platform composed of wearable neurotechnology and a smartphone application to measure and predict chronic pain levels and its interplay with other dimensions of experience.Methods: Our method measures, dynamically and at home, pain strength, phenomenal and neural time series collected with an online tool and low-density EEG. Here we used data from a single participant who performed an attention task at home for a period of 20 days to investigate the role of attention to different bodily systems in chronic pain.Results: We show a relationship between emotions and pain strength while allocating attention to the heartbeat, the breathing, the affected or the unaffected limb. We found that pain was maximal when attending to the affected limb and decreased when the participant focused on his breathing or his heartbeat. These results provide interesting insights regarding the role of attention to interoceptive signals in chronic pain. We found power changes in the delta, theta, alpha and beta (but not in the gamma) band between the four attention conditions. However, there was no reliable association of these changes to pain intensity ratings. Theta power was higher when attention was directed to the unaffected limb compared to the others. Further, the pain ratings, when attending to unaffected limb, were associated with alpha and theta power band changes.Conclusion: Overall, we demonstrate that our neurophysiology and experience tracking platform can capture how body attention allocation alters the dynamics of subjective measures and its neural correlates. This research approach is proof of concept for the development of personalized clinical assessment tools and a testbed for behavioural, subjective and biomarkers characterization.Keywords: pain, consciousness, EEG, power, CRPS

Determining conscious processing in unresponsive patients relies on subjective behavioural assessment. Using data from hand electromyography, the authors studied the occurrence of subthreshold muscle activity in response to verbal command, as an objective indicator of awareness in 10 disorders of consciousness patients. One out of eight vegetative state patients and both minimally conscious patients (n = 2) demonstrated an increased electromyography signal specifically linked to command. These findings suggest electromyography could be used to assess awareness objectively in pathologies of consciousness. [ABSTRACT FROM AUTHOR]

Throughout the day, humans show natural fluctuations in arousal that impact cognitive function. To study the behavioural dynamics of cognitive control during high and low arousal states, healthy participants performed an auditory conflict task during high-intensity physical exercise (N = 39) or drowsiness (N = 33). In line with the pre-registered hypotheses, conflict and conflict adaptation effects were preserved during both altered arousal states. Overall task performance was markedly poorer during low arousal, but not for high arousal. Modelling behavioural dynamics with drift diffusion analysis revealed evidence accumulation and non-decision time decelerated, and decisional boundaries became wider during low arousal, whereas high arousal was unexpectedly associated with a decrease in the interference of task-irrelevant information processing. These findings show how arousal differentially modulates cognitive control at both sides of normal alertness, and further validate drowsiness and physical exercise as key experimental models to disentangle the interaction between physiological fluctuations on cognitive dynamics., (© 2024 The British Psychological Society.)

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., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

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., Competing Interests: Jacobo D. Sitt and Lionel Naccache are scientific co-founders of NeuroMeters (have scientific advisory activity but no executive or management activity)., (© The Author(s) 2024. Published by Oxford University Press.)

Mental health issues are markedly increased in individuals with autism, making it the number one research priority by stakeholders. There is a crucial need to use personalized approaches to understand the underpinnings of mental illness in autism and consequently, to address individual needs. Based on the risk factors identified in typical mental research, we propose the following themes central to mental health issues in autism: sleep difficulties and stress. Indeed, the prevalence of manifold circadian disruptions and sleep difficulties in autism, alongside stress related to sensory overload, forms an integral part of autistic symptomatology. This proof-of-concept study protocol outlines an innovative, individualised approach towards investigating the interrelationships between stress indices, sleep and circadian activation patterns, and sensory sensitivity in autism. Embracing an individualized methodology, we aim to collect 14 days of data per participant from 20 individuals with autism diagnoses and 20 without. Participants' sleep will be monitored using wearable EEG headbands and a sleep diary. Diurnal tracking of heart rate and electrodermal activity through wearables will serve as proxies of stress. Those objective data will be synchronized with subjective experience traces collected throughout the day using the Temporal Experience Tracing (TET) method. TET facilitates the quantification of relevant aspects of individual experience states, such as stress or sensory sensitivities, by providing a continuous multidimensional description of subjective experiences. Capturing the dynamics of subjective experiences phase-locked to neural and physiological proxies both between and within individuals, this approach has the potential to contribute to our understanding of critical issues in autism, including sleep problems, sensory reactivity and stress. The planned strives to provide a pathway towards developing a more nuanced and individualized approach to addressing mental health in autism., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Gernert et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Important efforts have been made to describe the neural and cognitive features of healthy and clinical populations. However, the neural and cognitive features of socially vulnerable individuals remain largely unexplored, despite their proneness to developing neurocognitive disorders. Socially vulnerable individuals can be characterised as socially deprived, having a low socioeconomic status, suffering from chronic social stress, and exhibiting poor social adaptation. While it is known that such individuals are likely to perform worse than their peers on executive function tasks, studies on healthy but socially vulnerable groups are lacking. In the current study, we explore whether neural power and connectivity signatures can characterise executive function performance in healthy but socially vulnerable individuals, shedding light on the impairing effects that chronic stress and social disadvantages have on cognition. We measured resting-state electroencephalography and executive functioning in 38 socially vulnerable participants and 38 matched control participants. Our findings indicate that while neural power was uninformative, lower delta and theta phase synchrony are associated with worse executive function performance in all participants, whereas delta phase synchrony is higher in the socially vulnerable group compared to the control group. Finally, we found that delta phase synchrony and years of schooling are the best predictors for belonging to the socially vulnerable group. Overall, these findings suggest that exposure to chronic stress due to socioeconomic factors and a lack of education are associated with changes in slow-wave neural connectivity and executive functioning., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Introduction: Social adaptation is a multifaceted process that encompasses cognitive, social, and affective factors. Previous research often focused on isolated variables, overlooking their interactions, especially in challenging environments. Our study addresses this by investigating how cognitive (working memory, verbal intelligence, self-regulation), social (affective empathy, family networks, loneliness), and psychological (locus of control, self-esteem, perceived stress) factors interact to influence social adaptation., Methods: We analyzed data from 254 adults (55% female) aged 18 to 46 in economically vulnerable households in Santiago, Chile. We used Latent profile analysis (LPA) and machine learning to uncover distinct patters of socioadaptive features and identify the most discriminating features., Results: LPA showed two distinct psychosocial adaptation profiles: one characterized by effective psychosocial adaptation and another by poor psychosocial adaptation. The adaptive profile featured individuals with strong emotional, cognitive, and behavioral self-regulation, an internal locus of control, high self-esteem, lower stress levels, reduced affective empathy, robust family support, and decreased loneliness. Conversely, the poorly adapted profile exhibited the opposite traits. Machine learning pinpointed six key differentiating factors in various adaptation pathways within the same vulnerable context: high self-esteem, cognitive and behavioral self-regulation, low stress levels, higher education, and increased social support., Discussion: This research carries significant policy implications, highlighting the need to reinforce protective factors and psychological resources, such as self-esteem, self-regulation, and education, to foster effective adaptation in adversity. Additionally, we identified critical risk factors impacting social adaptation in vulnerable populations, advancing our understanding of this intricate phenomenon., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer KS declared a past co-authorship with the author AI to the handling editor., (Copyright © 2024 Carriedo, Rodríguez-Villagra, Moguilner, Morales-Sepulveda, Huepe-Artigas, Soto, Franco-O’Byrne, Ibáñez, Bekinschtein and Huepe.)

Sleep is crucial for many vital functions and has been extensively studied. By contrast, the sleep-onset period (SOP), often portrayed as a mere prelude to sleep, has been largely overlooked and remains poorly characterized. Recent findings, however, have reignited interest in this transitional period and have shed light on its neural mechanisms, cognitive dynamics, and clinical implications. This review synthesizes the existing knowledge about the SOP in humans. We first examine the current definition of the SOP and its limits, and consider the dynamic and complex electrophysiological changes that accompany the descent to sleep. We then describe the interplay between internal and external processing during the wake-to-sleep transition. Finally, we discuss the putative cognitive benefits of the SOP and identify novel directions to better diagnose sleep-onset disorders., Competing Interests: Declaration of interests T.A.B. is a cofounder of Human Experience Dynamics Ltd. The other authors declare no conflicts of interest., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Despite a surge of studies on the effects of COVID-19 on our well-being, we know little about how the pandemic is reflected in people's spontaneous thoughts and experiences, such as mind-wandering (or daydreaming) during wakefulness and dreaming during sleep. We investigated whether and how COVID-19-related general concern, anxiety, and daily worry are associated with the daily fluctuation of the affective quality of mind-wandering and dreaming, and to what extent these associations can be explained by poor sleep quality. We used ecological momentary assessment by asking participants to rate the affect they experienced during mind-wandering and dreaming in daily logs over a 2-week period. Our preregistered analyses based on 1,755 dream logs from 172 individuals and 1,496 mind-wandering logs from 152 individuals showed that, on days when people reported higher levels of negative affect and lower levels of positive affect during mind-wandering, they experienced more worry. Only daily sleep quality was associated with affect experienced during dreaming at the within-person level: on nights with poorer sleep quality people reported experiencing more negative and less positive affect in dreams and were more likely to experience nightmares. However, at the between-person level, individuals who experienced more daily COVID-19 worry during the study period also reported experiencing more negative affect during mind-wandering and during dreaming. As such, the continuity between daily and nightly experiences seems to rely more on stable trait-like individual differences in affective processing. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

From the perspective of predictive coding, normal aging is accompanied by decreased weighting of sensory inputs and increased reliance on predictions, resulting in the attenuation of prediction errors in older age. Recent electroencephalography (EEG) research further revealed that the age-related shift from sensorium to predictions is hierarchy-selective, as older brains show little reduction in lower-level but significant suppression in higher-level prediction errors. Moreover, the disrupted propagation of prediction errors from the lower-level to the higher-level seems to be linked to deficient maintenance of information in working memory. However, it is unclear whether the hierarchical predictive processing continues to decline with advancing age as working memory. Here, we longitudinally followed a sample of 78 participants from three age groups (including seniors, adults, and adolescents) over three years' time. Seniors exhibited largely preserved local processing [consisting of comparable mismatch negativity (MMN), delayed P3a, and comparable reorienting negativity (RON)] but significantly compromised global processing (consisting of suppressed frontocentral negativity and suppressed P3b) in the auditory local-global paradigm. These electrophysiological responses did not change with the passing of time, unlike working memory which deteriorated with advancing age. Correlation analysis further showed that these electrophysiological responses signaling prediction errors are indicative of concurrent working memory. Moreover, there was a correlation between earlier predictive processing and later working memory but not between earlier working memory and later predictive processing. The temporal asymmetry suggested that the hierarchy-selective attenuation of prediction errors is likely a precursor of working memory decline., (Copyright © 2023 Dien et al.)

To ensure survival in a dynamic environment, the human neocortex monitors input streams from different sensory organs for important sensory events. Which principles govern whether different senses share common or modality-specific brain networks for sensory target detection? We examined whether complex targets evoke sustained supramodal activity while simple targets rely on modality-specific networks with short-lived supramodal contributions. In a series of hierarchical multisensory target detection studies ( n = 77, of either sex) using EEG, we applied a temporal cross-decoding approach to dissociate supramodal and modality-specific cortical dynamics elicited by rule-based global and feature-based local sensory deviations within and between the visual, somatosensory, and auditory modality. Our data show that each sense implements a cortical hierarchy orchestrating supramodal target detection responses, which operate at local and global timescales in successive processing stages. Across different sensory modalities, simple feature-based sensory deviations presented in temporal vicinity to a monotonous input stream triggered a mismatch negativity-like local signal which decayed quickly and early, whereas complex rule-based targets tracked across time evoked a P3b-like global neural response which generalized across a late time window. Converging results from temporal cross-modality decoding analyses across different datasets, we reveal that global neural responses are sustained in a supramodal higher-order network, whereas local neural responses canonically thought to rely on modality-specific regions evolve into short-lived supramodal activity. Together, our findings demonstrate that cortical organization largely follows a gradient in which short-lived modality-specific as well as supramodal processes dominate local responses, whereas higher-order processes encode temporally extended abstract supramodal information fed forward from modality-specific cortices. SIGNIFICANCE STATEMENT Each sense supports a cortical hierarchy of processes tracking deviant sensory events at multiple timescales. Conflicting evidence produced a lively debate around which of these processes are supramodal. Here, we manipulated the temporal complexity of auditory, tactile, and visual targets to determine whether cortical local and global ERP responses to sensory targets share cortical dynamics between the senses. Using temporal cross-decoding, we found that temporally complex targets elicit a supramodal sustained response. Conversely, local responses to temporally confined targets typically considered modality-specific rely on early short-lived supramodal activation. Our finding provides evidence for a supramodal gradient supporting sensory target detection in the cortex, with implications for multiple fields in which these responses are studied (e.g., predictive coding, consciousness, and attention)., (Copyright © 2022 the authors.)

Presleep exposure to short-wavelength light suppresses melatonin and decreases sleepiness with activating effects extending to sleep. This has mainly been attributed to melanopic effects, but mechanistic insights are missing. Thus, we investigated whether two light conditions only differing in the melanopic effects (123 vs. 59 lx melanopic EDI) differentially affect sleep besides melatonin. Additionally, we studied whether the light differentially modulates sensory processing during wakefulness and sleep. Twenty-nine healthy volunteers (18-30 years, 15 women) were exposed to two metameric light conditions (high- vs. low-melanopic, ≈60 photopic lx) for 1 h ending 50 min prior to habitual bed time. This was followed by an 8-h sleep opportunity with polysomnography. Objective sleep measurements were complemented by self-report. Salivary melatonin, subjective sleepiness, and behavioral vigilance were sampled at regular intervals. Sensory processing was evaluated during light exposure and sleep on the basis of neural responses related to violations of expectations in an oddball paradigm. We observed suppression of melatonin by ≈14% in the high- compared to the low-melanopic condition. However, conditions did not differentially affect sleep, sleep quality, sleepiness, or vigilance. A neural mismatch response was evident during all sleep stages, but not differentially modulated by light. Suppression of melatonin by light targeting the melanopic system does not automatically translate to acutely altered levels of vigilance or sleepiness or to changes in sleep, sleep quality, or basic sensory processing. Given contradicting earlier findings and the retinal anatomy, this may suggest that an interaction between melanopsin and cone-rod signals needs to be considered. Clinical Trial Registry: German Clinical Trials Register, DRKS00023602, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00023602., (© Sleep Research Society 2022. Published by Oxford University Press on behalf of the Sleep Research Society.)

Down's syndrome is associated with pathological ageing and a propensity for early-onset Alzheimer's disease. The early symptoms of dementia in people with Down's syndrome may reflect frontal lobe vulnerability to amyloid deposition. Auditory predictive processes rely on the bilateral auditory cortices with the recruitment of frontal cortices and appear to be impaired in pathologies characterized by compromised frontal lobe. Hence, auditory predictive processes were investigated to assess Down's syndrome pathology and its relationship with pathological ageing. An auditory electroencephalography (EEG) global-local paradigm was presented to the participants, in which oddball stimuli could either violate local or higher level global rules. We characterised predictive processes in individuals with Down's syndrome and their relationship with pathological ageing, with a focus on the EEG event-related potential called Mismatch Negativity (MMN) and the P300. In Down's syndrome, we also evaluated the EEG components as predictor of cognitive decline 1 year later. We found that predictive processes of detection of auditory violations are overall preserved in Down's syndrome but also that the amplitude of the MMN to local deviancies decreases with age. However, the 1-year follow-up of Down's syndrome found that none of the ERPs measures predicted subsequent cognitive decline. The present study provides a novel characterization of electrophysiological markers of local and global predictive processes in Down's syndrome., (© 2022 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

There is increasing evidence that the level of consciousness can be captured by neural informational complexity: for instance, complexity, as measured by the Lempel Ziv (LZ) compression algorithm, decreases during anaesthesia and non-rapid eye movement (NREM) sleep in humans and rats, when compared with LZ in awake and REM sleep. In contrast, LZ is higher in humans under the effect of psychedelics, including subanaesthetic doses of ketamine. However, it is both unclear how this result would be modulated by varying ketamine doses, and whether it would extend to other species. Here, we studied LZ with and without auditory stimulation during wakefulness and different sleep stages in five cats implanted with intracranial electrodes, as well as under subanaesthetic doses of ketamine (5, 10, and 15 mg/kg i.m.). In line with previous results, LZ was lowest in NREM sleep, but similar in REM and wakefulness. Furthermore, we found an inverted U-shaped curve following different levels of ketamine doses in a subset of electrodes, primarily in prefrontal cortex. However, it is worth noting that the variability in the ketamine dose-response curve across cats and cortices was larger than that in the sleep-stage data, highlighting the differential local dynamics created by two different ways of modulating conscious state. These results replicate previous findings, both in humans and other species, demonstrating that neural complexity is highly sensitive to capture state changes between wake and sleep stages while adding a local cortical description. Finally, this study describes the differential effects of ketamine doses, replicating a rise in complexity for low doses, and further fall as doses approach anaesthetic levels in a differential manner depending on the cortex., (© 2022 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

While religious beliefs are typically studied using questionnaires, there are no standardized tools available for cognitive psychology and neuroscience studies of religious cognition. Here we present the first such tool-the Cambridge Psycholinguistic Inventory of Christian Beliefs (CPICB)-which consists of audio-recorded items of religious beliefs as well as items of three control conditions: moral beliefs, abstract scientific knowledge and empirical everyday life knowledge. The CPICB is designed in such a way that the ultimate meaning of each sentence is revealed only by its final critical word, which enables the precise measurement of reaction times and/or latencies of neurophysiological responses. Each statement comes in a pair of Agree/Disagree versions of critical words, which allows for experimental contrasting between belief and disbelief conditions. Psycholinguistic and psychoacoustic matching between Agree/Disagree versions of sentences, as well as across different categories of the CPICB items (Religious, Moral, Scientific, Everyday), enables rigorous control of low-level psycholinguistic and psychoacoustic features while testing higher-level beliefs. In the exploratory Study 1 (N = 20), we developed and tested a preliminary version of the CPICB that had 480 items. After selecting 400 items that yielded the most consistent responses, we carried out a confirmatory test-retest Study 2 (N = 40). Preregistered data analyses confirmed excellent construct validity, internal consistency and test-retest reliability of the CPICB religious belief statements. We conclude that the CPICB is suitable for studying Christian beliefs in an experimental setting involving behavioural and neuroimaging paradigms, and provide Open Access to the inventory items, fostering further development of the experimental research of religiosity., (© 2021. The Author(s).)

The ability to make decisions based on external information, prior knowledge, and evidence is a crucial aspect of cognition and may determine the success and survival of an organism. Despite extensive work on decision-making mechanisms/models, understanding the effects of alertness on neural and cognitive processes remain limited. Here we use EEG and behavioral modeling to characterize cognitive and neural dynamics of perceptual decision-making in awake/low alertness periods in humans (14 male, 18 female) and characterize the compensatory mechanisms as alertness decreases. Well-rested human participants, changing between full-wakefulness and low alertness, performed an auditory tone-localization task, and its behavioral dynamics were quantified with psychophysics, signal detection theory, and drift-diffusion modeling, revealing slower reaction times, inattention to the left side of space, and a lower rate of evidence accumulation in periods of low alertness. Unconstrained multivariate pattern analysis (decoding) showed a ∼280 ms delayed onset driven by low alertness of the neural signatures differentiating between left and right decision, with a spatial reconfiguration from centroparietal to lateral frontal regions 150-360 ms. To understand the neural compensatory mechanisms with decreasing alertness, we connected the evidence-accumulation behavioral parameter to the neural activity, showing in the early periods (125-325 ms) a shift in the associated patterns from right parietal regions in awake, to right frontoparietal during low alertness. This change in the neurobehavioral dynamics for central accumulation-related cognitive processes defines a clear reconfiguration of the brain networks' regions and dynamics needed for the implementation of decision-making, revealing mechanisms of resilience of cognition when challenged by decreased alertness. SIGNIFICANCE STATEMENT Most living organisms make multiple daily decisions, and these require a degree of evidence from both the environment and the internal milieu. Such decisions are usually studied under sequential sampling models and involve making a behavioral choice based on sensory encoding, central accumulation, and motor implementation processes. Since there is little research on how decreasing alertness affects such cognitive processes, this study has looked at the cognitive and neural dynamics of perceptual decision-making in people while fully awake and in drowsy periods. Using computational modeling of behavior and neural dynamics on human participants performing an auditory tone-localization task, we reveal how low alertness modulates evidence accumulation-related processes and its corresponding compensatory neural signatures., (Copyright © 2022 the authors.)

Humans are uniquely capable of adapting to highly changing environments by updating relevant information and adjusting ongoing behaviour accordingly. Here we show how this ability -termed cognitive flexibility- is differentially modulated by high and low arousal fluctuations. We implemented a probabilistic reversal learning paradigm in healthy participants as they transitioned towards sleep or physical extenuation. The results revealed, in line with our pre-registered hypotheses, that low arousal leads to diminished behavioural performance through increased decision volatility, while performance decline under high arousal was attributed to increased perseverative behaviour. These findings provide evidence for distinct patterns of maladaptive decision-making on each side of the arousal inverted u-shaped curve, differentially affecting participants' ability to generate stable evidence-based strategies, and introduces wake-sleep and physical exercise transitions as complementary experimental models for investigating neural and cognitive dynamics., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The overt or covert ability to follow commands in patients with disorders of consciousness is considered a sign of awareness and has recently been defined as cortically mediated behaviour. Despite its clinical relevance, the brain signatures of the perceptual processing supporting command following have been elusive. This multimodal study investigates the temporal spectral pattern of electrical brain activity to identify features that differentiated healthy controls from patients both able and unable to follow commands. We combined evidence from behavioural assessment, functional neuroimaging during mental imagery and high-density electroencephalography collected during auditory prediction, from 21 patients and 10 controls. We used a penalised regression model to identify command following using features from electroencephalography. We identified seven well-defined spatiotemporal signatures in the delta, theta and alpha bands that together contribute to identify DoC subjects with and without the ability to follow command, and further distinguished these groups of patients from controls. A fine-grained analysis of these seven signatures enabled us to determine that increased delta modulation at the frontal sensors was the main feature in command following patients. In contrast, higher frequency theta and alpha modulations differentiated controls from both groups of patients. Our findings highlight a key role of spatiotemporally specific delta modulation in supporting cortically mediated behaviour including the ability to follow command. However, patients able to follow commands nevertheless have marked differences in brain activity in comparison with healthy volunteers., (© 2021. The Author(s).)

Body perceptual disturbances are an increasingly acknowledged set of symptoms and possible clinical markers of complex regional pain syndrome (CRPS), but the neurophysiological and neurocognitive changes that underlie them are still far from being clear. We adopted a multivariate and neurodynamical approach to the analysis of EEG modulations evoked by touch to highlight differences between patients and healthy controls, between affected and unaffected side of the body, and between "passive" (i.e., no task demands and equiprobable digit stimulation) and "active" tactile processing (i.e., where a digit discrimination task was administered and spatial probability manipulated). When correct identifications are considered, an early reduction in cortical decodability (28-56 ms) distinguishes CRPS patients from healthy volunteers. However, when error trials are included in the classifier's training, there is an unexpected increased decodability in the CRPS group compared with healthy volunteers (280-320 ms). These group differences in neural processing seemed to be driven by the affected rather than the unaffected side. We corroborated these findings with several exploratory analyses of neural representation dynamics and behavioural modelling, highlighting the need for single participant analyses. Although several limitations impacted the robustness and generalizability of these comparisons, the proposed analytical approach yielded promising insights (as well as possible biomarkers based on neural dynamics) into the relatively unexplored alterations of tactile decision-making and attentional control mechanisms in chronic CRPS., (© 2021 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Mental imagery is the process through which we retrieve and recombine information from our memory to elicit the subjective impression of "seeing with the mind's eye". In the social domain, we imagine other individuals while recalling our encounters with them or modelling alternative social interactions in future. Many studies using imaging and neurophysiological techniques have shown several similarities in brain activity between visual imagery and visual perception, and have identified frontoparietal, occipital and temporal neural components of visual imagery. However, the neural connectivity between these regions during visual imagery of socially relevant stimuli has not been studied. Here we used electroencephalography to investigate neural connectivity and its dynamics between frontal, parietal, occipital and temporal electrodes during visual imagery of faces. We found that voluntary visual imagery of faces is associated with long-range phase synchronisation in the gamma frequency range between frontoparietal electrode pairs and between occipitoparietal electrode pairs. In contrast, no effect of imagery was observed in the connectivity between occipitotemporal electrode pairs. Gamma range synchronisation between occipitoparietal electrode pairs predicted subjective ratings of the contour definition of imagined faces. Furthermore, we found that visual imagery of faces is associated with an increase of short-range frontal synchronisation in the theta frequency range, which temporally preceded the long-range increase in the gamma synchronisation. We speculate that the local frontal synchrony in the theta frequency range might be associated with an effortful top-down mnemonic reactivation of faces. In contrast, the long-range connectivity in the gamma frequency range along the fronto-parieto-occipital axis might be related to the endogenous binding and subjective clarity of facial visual features.

Transcranial magnetic stimulation (TMS) has been widely used in human cognitive neuroscience to examine the causal role of distinct cortical areas in perceptual, cognitive and motor functions. However, it is widely acknowledged that the effects of focal cortical stimulation can vary substantially between participants and even from trial to trial within individuals. Recent work from resting state functional magnetic resonance imaging (fMRI) studies has suggested that spontaneous fluctuations in alertness over a testing session can modulate the neural dynamics of cortical processing, even when participants remain awake and responsive to the task at hand. Here we investigated the extent to which spontaneous fluctuations in alertness during wake-to-sleep transition can account for the variability in neurophysiological responses to TMS. We combined single-pulse TMS with neural recording via electroencephalography (EEG) to quantify changes in motor and cortical reactivity with fluctuating levels of alertness defined objectively on the basis of ongoing brain activity. We observed rapid, non-linear changes in TMS-evoked responses with decreasing levels of alertness, even while participants remained responsive in the behavioural task. Specifically, we found that the amplitude of motor evoked potentials peaked during periods of EEG flattening, whereas TMS-evoked potentials increased and remained stable during EEG flattening and the subsequent occurrence of theta ripples that indicate the onset of NREM stage 1 sleep. Our findings suggest a rapid and complex reorganization of active neural networks in response to spontaneous fluctuations of alertness over relatively short periods of behavioural testing during wake-to-sleep transition., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2020. Published by Elsevier Inc.)

In construing meaning, the brain recruits multimodal (conceptual) systems and embodied (modality-specific) mechanisms. Yet, no consensus exists on how crucial the latter are for the inception of semantic distinctions. To address this issue, we combined electroencephalographic (EEG) and intracranial EEG (iEEG) to examine when nouns denoting facial body parts (FBPs) and nonFBPs are discriminated in face-processing and multimodal networks. First, FBP words increased N170 amplitude (a hallmark of early facial processing). Second, they triggered fast (~100 ms) activity boosts within the face-processing network, alongside later (~275 ms) effects in multimodal circuits. Third, iEEG recordings from face-processing hubs allowed decoding ~80% of items before 200 ms, while classification based on multimodal-network activity only surpassed ~70% after 250 ms. Finally, EEG and iEEG connectivity between both networks proved greater in early (0-200 ms) than later (200-400 ms) windows. Collectively, our findings indicate that, at least for some lexico-semantic categories, meaning is construed through fast reenactments of modality-specific experience., (© The Author(s) 2020. Published by Oxford University Press.)

Humans' remarkable capacity to flexibly adapt their behavior based on rapid situational changes is termed cognitive control. Intuitively, cognitive control is thought to be affected by the state of alertness; for example, when drowsy, we feel less capable of adequately implementing effortful cognitive tasks. Although scientific investigations have focused on the effects of sleep deprivation and circadian time, little is known about how natural daily fluctuations in alertness in the regular awake state affect cognitive control. Here we combined a conflict task in the auditory domain with EEG neurodynamics to test how neural and behavioral markers of conflict processing are affected by fluctuations in alertness. Using a novel computational method, we segregated alert and drowsy trials from two testing sessions and observed that, although participants (both sexes) were generally sluggish, the typical conflict effect reflected in slower responses to conflicting information compared with nonconflicting information, as well as the moderating effect of previous conflict (conflict adaptation), were still intact. However, the typical neural markers of cognitive control-local midfrontal theta-band power changes-that participants show during full alertness were no longer noticeable when alertness decreased. Instead, when drowsy, we found an increase in long-range information sharing (connectivity) between brain regions in the same frequency band. These results show the resilience of the human cognitive control system when affected by internal fluctuations of alertness and suggest that there are neural compensatory mechanisms at play in response to physiological pressure during diminished alertness. SIGNIFICANCE STATEMENT The normal variability in alertness we experience in daily tasks is rarely taken into account in cognitive neuroscience. Here we studied neurobehavioral dynamics of cognitive control with decreasing alertness. We used the classic Simon task where participants hear the word "left" or "right" in the right or left ear, eliciting slower responses when the word and the side are incongruent-the conflict effect. Participants performed the task both while fully awake and while getting drowsy, allowing for the characterization of alertness modulating cognitive control. The changes in the neural signatures of conflict from local theta oscillations to a long-distance distributed theta network suggest a reconfiguration of the underlying neural processes subserving cognitive control when affected by alertness fluctuations., (Copyright © 2020 the authors.)

At any given moment, we experience a perceptual scene as a single whole and yet we may distinguish a variety of objects within it. This phenomenon instantiates two properties of conscious perception: integration and differentiation. Integration is the property of experiencing a collection of objects as a unitary percept and differentiation is the property of experiencing these objects as distinct from each other. Here, we evaluated the neural information dynamics underlying integration and differentiation of perceptual contents during bistable perception. Participants listened to a sequence of tones (auditory bistable stimuli) experienced either as a single stream (perceptual integration) or as two parallel streams (perceptual differentiation) of sounds. We computed neurophysiological indices of information integration and information differentiation with electroencephalographic and intracranial recordings. When perceptual alternations were endogenously driven, the integrated percept was associated with an increase in neural information integration and a decrease in neural differentiation across frontoparietal regions, whereas the opposite pattern was observed for the differentiated percept. However, when perception was exogenously driven by a change in the sound stream (no bistability), neural oscillatory power distinguished between percepts but information measures did not. We demonstrate that perceptual integration and differentiation can be mapped to theoretically motivated neural information signatures, suggesting a direct relationship between phenomenology and neurophysiology., (© The Author(s) 2020. Published by Oxford University Press.)

After severe brain injury, it can be difficult to determine the state of consciousness of a patient, to determine whether the patient is unresponsive or perhaps minimally conscious 1 , and to predict whether they will recover. These diagnoses and prognoses are crucial, as they determine therapeutic strategies such as pain management, and can underlie end-of-life decisions 2,3 . Nevertheless, there is an error rate of up to 40% in determining the state of consciousness in patients with brain injuries 4,5 . Olfaction relies on brain structures that are involved in the basic mechanisms of arousal 6 , and we therefore hypothesized that it may serve as a biomarker for consciousness 7 . Here we use a non-verbal non-task-dependent measure known as the sniff response 8-11 to determine consciousness in patients with brain injuries. By measuring odorant-dependent sniffing, we gain a sensitive measure of olfactory function 10-15 . We measured the sniff response repeatedly over time in patients with severe brain injuries and found that sniff responses significantly discriminated between unresponsive and minimally conscious states at the group level. Notably, at the single-patient level, if an unresponsive patient had a sniff response, this assured future regaining of consciousness. In addition, olfactory sniff responses were associated with long-term survival rates. These results highlight the importance of olfaction in human brain function, and provide an accessible tool that signals consciousness and recovery in patients with brain injuries.

Recent evidence indicates that humans can learn entirely new information during sleep. To elucidate the neural dynamics underlying sleep-learning, we investigated brain activity during auditory-olfactory discriminatory associative learning in human sleep. We found that learning-related delta and sigma neural changes are involved in early acquisition stages, when new associations are being formed. In contrast, learning-related theta activity emerged in later stages of the learning process, after tone-odor associations were already established. These findings suggest that learning new associations during sleep is signaled by a dynamic interplay between slow-waves, sigma, and theta activity., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

As the evidence of predictive processes playing a role in a wide variety of cognitive domains increases, the brain as a predictive machine becomes a central idea in neuroscience. In auditory processing, a considerable amount of progress has been made using variations of the Oddball design, but most of the existing work seems restricted to predictions based on physical features or conditional rules linking successive stimuli. To characterize the predictive capacity of the brain to abstract rules, we present here two experiments that use speech-like stimuli to overcome limitations and avoid common confounds. Pseudowords were presented in isolation, intermixed with infrequent deviants that contained unexpected phoneme sequences. As hypothesized, the occurrence of unexpected sequences of phonemes reliably elicited an early prediction error signal. These prediction error signals do not seemed to be modulated by attentional manipulations due to different task instructions, suggesting that the predictions are deployed even when the task at hand does not volitionally involve error detection. In contrast, the amount of syllables congruent with a standard pseudoword presented before the point of deviance exerted a strong modulation. Prediction error's amplitude doubled when two congruent syllables were presented instead of one, despite keeping local transitional probabilities constant. This suggests that auditory predictions can be built integrating information beyond the immediate past. In sum, the results presented here further contribute to the understanding of the predictive capabilities of the human auditory system when facing complex stimuli and abstract rules., (Copyright © 2019 Vidal et al.)

Background: Inhibitory control, a key modulatory component of cognition guiding strategy and behaviour, can be affected by diverse contingencies. We explore here the effect of expectation of reward over behavioural adjustment in a Stop Signal Task modulated by reward. We hypothesize that cognitive control is modulated by different expectation of the reward., Methods: Participants were allocated to two groups differing in their degree of knowledge in what to expect from rewards. Expected Specific Reward participants (N = 21) were informed of the different monetary feedbacks they would receive after each successful inhibition. Unexpected Reward participants (N = 24) were only told that they would receive monetary reward after correct inhibitory trials, but not the amounts or differences., Results: Our results confirmed previous observations demonstrating a "kick-start effect" where a high reward feedback at the beginning of the task increases response inhibition. The Expected Specific Reward condition seems also to improve inhibitory control -as measured by the stop signal reaction time (SSRT)-, compared to the Unexpected Reward group., Conclusions: Knowledge of reward magnitudes seems to play a role in cognitive control irrespective of feedback magnitude. The manipulation of reward expectation appears to trigger different strategies for cognitive control, inducing a bottom-up effect of external cues, or a top-down effect given by the anticipation of incoming rewards. This is an early exploration to unearth possible higher order modulators - expectation and motivation- of cognitive control. This approach aims to gain insight into diverse psychopathological conditions related to impulsivity and altered reward systems such as Attention Deficit Hyperactive Disorder (ADHD), personality disorders, substance abuse, pathological gambling and cognitive aspects of Parkinson Disease.

Learning and using multiple languages places major demands on our neurocognitive system, which can impact the way the brain processes information. Here we investigated how early bilingualism influences the neural mechanisms of auditory selective attention, and whether this is further affected by the typological similarity between languages. We tested the neural encoding of continuous attended speech in early balanced bilinguals of typologically similar (Dutch-English) and dissimilar languages (Spanish-English) and compared them to results from English monolinguals we reported earlier. In a dichotic listening paradigm, participants attended to a narrative in their native language while ignoring different types of interference in the other ear. The results revealed that bilingualism modulates the neural mechanisms of selective attention even in the absence of consistent behavioural differences between monolinguals and bilinguals. They also suggested that typological similarity between languages helps fine-tune this modulation, reflecting life-long experiences with resolving competition between more or less similar candidates. The effects were consistent over the time-course of the narrative and suggest that learning a second language at an early age triggers neuroplastic adaptation of the attentional processing system.

The individual differences approach focuses on the variation of behavioral and neural signatures across subjects. In this context, we searched for intracranial neural markers of performance in three individuals with distinct behavioral patterns (efficient, borderline, and inefficient) in a dual-valence task assessing facial and lexical emotion recognition. First, we performed a preliminary study to replicate well-established evoked responses in relevant brain regions. Then, we examined time series data and network connectivity, combined with multivariate pattern analyses and machine learning, to explore electrophysiological differences in resting-state versus task-related activity across subjects. Next, using the same methodological approach, we assessed the neural decoding of performance for different dimensions of the task. The classification of time series data mirrored the behavioral gradient across subjects for stimulus type but not for valence. However, network-based measures reflected the subjects' hierarchical profiles for both stimulus types and valence. Therefore, this measure serves as a sensitive marker for capturing distributed processes such as emotional valence discrimination, which relies on an extended set of regions. Network measures combined with classification methods may offer useful insights to study single subjects and understand inter-individual performance variability. Promisingly, this approach could eventually be extrapolated to other neuroscientific techniques.

As we fall sleep, our brain traverses a series of gradual changes at physiological, behavioural and cognitive levels, which are not yet fully understood. The loss of responsiveness is a critical event in the transition from wakefulness to sleep. Here we seek to understand the electrophysiological signatures that reflect the loss of capacity to respond to external stimuli during drowsiness using two complementary methods: spectral connectivity and EEG microstates. Furthermore, we integrate these two methods for the first time by investigating the connectivity patterns captured during individual microstate lifetimes. While participants performed an auditory semantic classification task, we allowed them to become drowsy and unresponsive. As they stopped responding to the stimuli, we report the breakdown of alpha networks and the emergence of theta connectivity. Further, we show that the temporal dynamics of all canonical EEG microstates slow down during unresponsiveness. We identify a specific microstate (D) whose occurrence and duration are prominently increased during this period. Employing machine learning, we show that the temporal properties of microstate D, particularly its prolonged duration, predicts the response likelihood to individual stimuli. Finally, we find a novel relationship between microstates and brain networks as we show that microstate D uniquely indexes significantly stronger theta connectivity during unresponsiveness. Our findings demonstrate that the transition to unconsciousness is not linear, but rather consists of an interplay between transient brain networks reflecting different degrees of sleep depth.

We examined how attention modulates the neural encoding of continuous speech under different types of interference. In an EEG experiment, participants attended to a narrative in English while ignoring a competing stream in the other ear. Four different types of interference were presented to the unattended ear: a different English narrative, a narrative in a language unknown to the listener (Spanish), a well-matched nonlinguistic acoustic interference (Musical Rain), and no interference. Neural encoding of attended and unattended signals was assessed by calculating cross-correlations between their respective envelopes and the EEG recordings. Findings revealed more robust neural encoding for the attended envelopes compared with the ignored ones. Critically, however, the type of the interfering stream significantly modulated this process, with the fully intelligible distractor (English) causing the strongest encoding of both attended and unattended streams and latest dissociation between them and nonintelligible distractors causing weaker encoding and early dissociation between attended and unattended streams. The results were consistent over the time course of the spoken narrative. These findings suggest that attended and unattended information can be differentiated at different depths of processing analysis, with the locus of selective attention determined by the nature of the competing stream. They provide strong support to flexible accounts of auditory selective attention.

The original article [1] contains an error affecting the actigraphy time-stamps throughout the article, particularly in Table 1.

A major problem in psychology and physiology experiments is drowsiness: around a third of participants show decreased wakefulness despite being instructed to stay alert. In some non-visual experiments participants keep their eyes closed throughout the task, thus promoting the occurrence of such periods of varying alertness. These wakefulness changes contribute to systematic noise in data and measures of interest. To account for this omnipresent problem in data acquisition we defined criteria and code to allow researchers to detect and control for varying alertness in electroencephalography (EEG) experiments under eyes-closed settings. We first revise a visual-scoring method developed for detection and characterization of the sleep-onset process, and adapt the same for detection of alertness levels. Furthermore, we show the major issues preventing the practical use of this method, and overcome these issues by developing an automated method (micro-measures algorithm) based on frequency and sleep graphoelements, which are capable of detecting micro variations in alertness. The validity of the micro-measures algorithm was verified by training and testing using a dataset where participants are known to fall asleep. In addition, we tested generalisability by independent validation on another dataset. The methods developed constitute a unique tool to assess micro variations in levels of alertness and control trial-by-trial retrospectively or prospectively in every experiment performed with EEG in cognitive neuroscience under eyes-closed settings., (Copyright © 2018. Published by Elsevier Inc.)

Selective attention is the process of directing limited capacity resources to behaviourally relevant stimuli while ignoring competing stimuli that are currently irrelevant. Studies in healthy human participants and in individuals with focal brain lesions have suggested that the right parietal cortex is crucial for resolving competition for attention. Following right-hemisphere damage, for example, patients may have difficulty reporting a brief, left-sided stimulus if it occurs with a competitor on the right, even though the same left stimulus is reported normally when it occurs alone. Such "extinction" of contralesional stimuli has been documented for all the major sense modalities, but it remains unclear whether its occurrence reflects involvement of one or more specific subregions of the temporo-parietal cortex. Here we employed repetitive transcranial magnetic stimulation (rTMS) over the right hemisphere to examine the effect of disruption of two candidate regions - the supramarginal gyrus (SMG) and the superior temporal gyrus (STG) - on auditory selective attention. Eighteen neurologically normal, right-handed participants performed an auditory task, in which they had to detect target digits presented within simultaneous dichotic streams of spoken distractor letters in the left and right channels, both before and after 20 min of 1 Hz rTMS over the SMG, STG or a somatosensory control site (S1). Across blocks, participants were asked to report on auditory streams in the left, right, or both channels, which yielded focused and divided attention conditions. Performance was unchanged for the two focused attention conditions, regardless of stimulation site, but was selectively impaired for contralateral left-sided targets in the divided attention condition following stimulation of the right SMG, but not the STG or S1. Our findings suggest a causal role for the right inferior parietal cortex in auditory selective attention., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Interoception, the monitoring of visceral signals, is often presumed to engage attentional mechanisms specifically devoted to inner bodily sensing. In fact, most standardized interoceptive tasks require directing attention to internal signals. However, most studies in the field have failed to compare attentional modulations between internally- and externally-driven processes, thus probing blind to the specificity of the former. Here we address this issue through a multidimensional approach combining behavioral measures, analyses of event-related potentials and functional connectivity via high-density electroencephalography, and intracranial recordings. In Study 1, 50 healthy volunteers performed a heartbeat detection task as we recorded modulations of the heartbeat-evoked potential (HEP) in three conditions: exteroception, basal interoception (also termed interoceptive accuracy), and post-feedback interoception (sometimes called interoceptive learning). In Study 2, to evaluate whether key interoceptive areas (posterior insula, inferior frontal gyrus, amygdala, and somatosensory cortex) were differentially modulated by externally- and internally-driven processes, we analyzed human intracranial recordings with depth electrodes in these regions. This unique technique provides a very fine grained spatio-temporal resolution compared to other techniques, such as EEG or fMRI. We found that both interoceptive conditions in Study 1 yielded greater HEP amplitudes than the exteroceptive one. In addition, connectivity analysis showed that post-feedback interoception, relative to basal interoception, involved enhanced long-distance connections linking frontal and posterior regions. Moreover, results from Study 2 showed a differentiation between oscillations during basal interoception (broadband: 35-110 Hz) and exteroception (1-35 Hz) in the insula, the amygdala, the somatosensory cortex, and the inferior frontal gyrus. In sum, this work provides convergent evidence for the specificity and dynamics of attentional mechanisms involved in interoception.

Recent works evince the critical role of visual short-term memory (STM) binding deficits as a clinical and preclinical marker of Alzheimer's disease (AD). These studies suggest a potential role of posterior brain regions in both the neurocognitive deficits of Alzheimer's patients and STM binding in general. Thereupon, we surmised that stimulation of the posterior parietal cortex (PPC) might be a successful approach to tackle working memory deficits in this condition, especially at early stages. To date, no causal evidence exists of the role of the parietal cortex in STM binding. A unique approach to assess this issue is afforded by single-subject direct intracranial electrical stimulation of specific brain regions during a relevant cognitive task. Electrical stimulation has been used both for clinical purposes and to causally probe brain mechanisms. Previous evidence of electrical currents spreading through white matter along well defined functional circuits indicates that visual working memory mechanisms are subserved by a specific widely distributed network. Here, we stimulated the parietal cortex of a subject with intracranial electrodes as he performed the visual STM task. We compared the ensuing results to those from a non-stimulated condition and to the performance of a matched control group. In brief, direct stimulation of the parietal cortex induced a selective improvement in STM. These results, together with previous studies, provide very preliminary but promising ground to examine behavioral changes upon parietal stimulation in AD. We discuss our results regarding: (a) the usefulness of the task to target prodromal stages of AD; (b) the role of a posterior network in STM binding and in AD; and, ((c) the potential opportunity to improve STM binding through brain stimulation.)

The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2-3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions.

Consciousness impairments have been described as a cornerstone of epilepsy. Generalized seizures are usually characterized by a complete loss of consciousness, whereas focal seizures have more variable degrees of responsiveness. In addition to these impairments that occur during ictal episodes, alterations of consciousness have also been repeatedly observed between seizures (i.e. during interictal periods). In this opinion article, we review evidence supporting the novel hypothesis that epilepsy produces consciousness impairments which remain present interictally. Then, we discuss therapies aimed to reduce seizure frequency, which may modulate consciousness between epileptic seizures. We conclude with a consideration of relevant pathophysiological mechanisms. In particular, the thalamocortical network seems to be involved in both seizure generation and interictal consciousness impairments, which could inaugurate a promising translational agenda for epilepsy studies.

We propose that sensory inputs are processed in terms of optimised predictions and prediction error signals within hierarchical neurocognitive models. The combination of non-invasive brain imaging and generative network models has provided support for hierarchical frontotemporal interactions in oddball tasks, including recent identification of a temporal expectancy signal acting on prefrontal cortex. However, these studies are limited by the need to invert magnetoencephalographic or electroencephalographic sensor signals to localise activity from cortical 'nodes' in the network, or to infer neural responses from indirect measures such as the fMRI BOLD signal. To overcome this limitation, we examined frontotemporal interactions estimated from direct cortical recordings from two human participants with cortical electrode grids (electrocorticography - ECoG). Their frontotemporal network dynamics were compared to those identified by magnetoencephalography (MEG) in forty healthy adults. All participants performed the same auditory oddball task with standard tones interspersed with five deviant tone types. We normalised post-operative electrode locations to standardised anatomic space, to compare across modalities, and inverted the MEG to cortical sources using the estimated lead field from subject-specific head models. A mismatch negativity signal in frontal and temporal cortex was identified in all subjects. Generative models of the electrocorticographic and magnetoencephalographic data were separately compared using the free-energy estimate of the model evidence. Model comparison confirmed the same critical features of hierarchical frontotemporal networks in each patient as in the group-wise MEG analysis. These features included bilateral, feedforward and feedback frontotemporal modulated connectivity, in addition to an asymmetric expectancy driving input on left frontal cortex. The invasive ECoG provides an important step in construct validation of the use of neural generative models of MEG, which in turn enables generalisation to larger populations. Together, they give convergent evidence for the hierarchical interactions in frontotemporal networks for expectation and processing of sensory inputs., (Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.)

Unlabelled: There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called "mismatch response"). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an "omission" response). This situation arguably provides a more direct measure of "top-down" predictions in the absence of confounding "bottom-up" input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG and MEG to an auditory paradigm in which we factorially crossed the presence versus absence of "bottom-up" stimuli with the presence versus absence of "top-down" attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward "prediction" connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction., Significance Statement: Human auditory perception is thought to be realized by a network of neurons that maintain a model of and predict future stimuli. Much of the evidence for this comes from experiments where a stimulus unexpectedly differs from previous ones, which generates a well-known "mismatch response." But what happens when a stimulus is unexpectedly omitted altogether? By measuring the brain's electromagnetic activity, we show that it also generates an "omission response" that is contingent on the presence of attention. We model these responses computationally, revealing that mismatch and omission responses only differ in the location of inputs into the same underlying neuronal network. In both cases, we show that attention selectively strengthens the brain's prediction of the future., (Copyright © 2016 Chennu et al.)

Accurately measuring the neural correlates of consciousness is a grand challenge for neuroscience. Despite theoretical advances, developing reliable brain measures to track the loss of reportable consciousness during sedation is hampered by significant individual variability in susceptibility to anaesthetics. We addressed this challenge using high-density electroencephalography to characterise changes in brain networks during propofol sedation. Assessments of spectral connectivity networks before, during and after sedation were combined with measurements of behavioural responsiveness and drug concentrations in blood. Strikingly, we found that participants who had weaker alpha band networks at baseline were more likely to become unresponsive during sedation, despite registering similar levels of drug in blood. In contrast, phase-amplitude coupling between slow and alpha oscillations correlated with drug concentrations in blood. Our findings highlight novel markers that prognosticate individual differences in susceptibility to propofol and track drug exposure. These advances could inform accurate drug titration and brain state monitoring during anaesthesia.

A decisive element of moral cognition is the detection of harm and its assessment as intentional or unintentional. Moral cognition engages brain networks supporting mentalizing, intentionality, empathic concern and evaluation. These networks rely on the amygdala as a critical hub, likely through frontotemporal connections indexing stimulus salience. We assessed inferences about perceived harm using a paradigm validated through functional magnetic resonance imaging, eye-tracking and electroencephalogram recordings. During the task, we measured local field potentials in three patients with depth electrodes (n = 115) placed in the amygdala and in several frontal, temporal, and parietal locations. Direct electrophysiological recordings demonstrate that intentional harm induces early activity in the amygdala (<200 ms), which--in turn--predicts intention attribution. The amygdala was the only site that systematically discriminated between critical conditions and predicted their classification of events as intentional. Moreover, connectivity analysis showed that intentional harm induced stronger frontotemporal information sharing at early stages. Results support the 'many roads' view of the amygdala and highlight its role in the rapid encoding of intention and salience--critical components of mentalizing and moral evaluation., (© The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Interoception, the perception of our body internal signals, plays a key role in maintaining homeostasis and guiding our behavior. Sometimes, we become aware of our body signals and use them in planning and strategic thinking. Here, we show behavioral and neural dissociations between learning to follow one's own heartbeat and metacognitive awareness of one's performance, in a heartbeat-tapping task performed before and after auditory feedback. The electroencephalography amplitude of the heartbeat-evoked potential in interoceptive learners, that is, participants whose accuracy of tapping to their heartbeat improved after auditory feedback, was higher compared with non-learners. However, an increase in gamma phase synchrony (30-45 Hz) after the heartbeat auditory feedback was present only in those participants showing agreement between objective interoceptive performance and metacognitive awareness. Source localization in a group of participants and direct cortical recordings in a single patient identified a network hub for interoceptive learning in the insular cortex. In summary, interoceptive learning may be mediated by the right insular response to the heartbeat, whereas metacognitive awareness of learning may be mediated by widespread cortical synchronization patterns., (© The Author 2015. Published by Oxford University Press.)