Cardio-audio synchronization elicits neural and cardiac surprise responses in human wakefulness and sleep.

The human brain can encode auditory regularities with fixed sound-to-sound intervals and with sound onsets locked to cardiac inputs. Here, we investigated auditory and cardio-audio regularity encoding during sleep, when bodily and environmental stimulus processing may be altered. Using electroencephalography and electrocardiography in healthy volunteers (N = 26) during wakefulness and sleep, we measured the response to unexpected sound omissions within three regularity conditions: synchronous, where sound and heartbeat are temporally coupled, isochronous, with fixed sound-to-sound intervals, and a control condition without regularity. Cardio-audio regularity encoding manifested as a heartbeat deceleration upon omissions across vigilance states. The synchronous and isochronous sequences induced a modulation of the omission-evoked neural response in wakefulness and N2 sleep, the former accompanied by background oscillatory activity reorganization. The violation of cardio-audio and auditory regularity elicits cardiac and neural responses across vigilance states, laying the ground for similar investigations in altered consciousness states such as coma and anaesthesia.

The effect of sedation and time after cardiac arrest on coma outcome prognostication based on EEG power spectra.

Early prognostication of long-term outcome of comatose patients after cardiac arrest remains challenging. Electroencephalography-based power spectra after cardiac arrest have been shown to help with the identification of patients with favourable outcome during the first day of coma. Here, we aim at comparing the power spectra prognostic value during the first and second day after coma onset following cardiac arrest and to investigate the impact of sedation on prognostication. In this cohort observational study, we included comatose patients (N = 91) after cardiac arrest for whom resting-state electroencephalography was collected on the first and second day after cardiac arrest in four Swiss hospitals. We evaluated whether the average power spectra values at 4.6-15.2 Hz were predictive of patients' outcome based on the best cerebral performance category score at 3 months, with scores ranging from 1 to 5 and dichotomized as favourable (1-2) and unfavourable (3-5). We assessed the effect of sedation and its interaction with the electroencephalography-based power spectra on patient outcome prediction through a generalized linear mixed model. Power spectra values provided 100% positive predictive value (95% confidence intervals: 0.81-1.00) on the first day of coma, with correctly predicted 18 out of 45 favourable outcome patients. On the second day, power spectra values were not predictive of patients' outcome (positive predictive value: 0.46, 95% confidence intervals: 0.19-0.75). On the first day, we did not find evidence of any significant contribution of sedative infusion rates to the patient outcome prediction (P > 0.05). Comatose patients' outcome prediction based on electroencephalographic power spectra is higher on the first compared with the second day after cardiac arrest. Sedation does not appear to impact patient outcome prediction.

Single-subject electroencephalography measurement of interhemispheric transfer time for the in-vivo estimation of axonal morphology.

Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject-specific IHTTs are computed in a data-driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject-specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between-session variability was comparable to between-subject variability. The mean radius of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 1.09 µm across subjects. The change in axonal g-ratio with axonal radius ranged from 0.62 to 0.81 µm-α . The single-subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single-subject axonal morphology estimates.

Auditory stimulation and deep learning predict awakening from coma after cardiac arrest.

Assessing the integrity of neural functions in coma after cardiac arrest remains an open challenge. Prognostication of coma outcome relies mainly on visual expert scoring of physiological signals, which is prone to subjectivity and leaves a considerable number of patients in a 'grey zone', with uncertain prognosis. Quantitative analysis of EEG responses to auditory stimuli can provide a window into neural functions in coma and information about patients' chances of awakening. However, responses to standardized auditory stimulation are far from being used in a clinical routine due to heterogeneous and cumbersome protocols. Here, we hypothesize that convolutional neural networks can assist in extracting interpretable patterns of EEG responses to auditory stimuli during the first day of coma that are predictive of patients' chances of awakening and survival at 3 months. We used convolutional neural networks (CNNs) to model single-trial EEG responses to auditory stimuli in the first day of coma, under standardized sedation and targeted temperature management, in a multicentre and multiprotocol patient cohort and predict outcome at 3 months. The use of CNNs resulted in a positive predictive power for predicting awakening of 0.83 ± 0.04 and 0.81 ± 0.06 and an area under the curve in predicting outcome of 0.69 ± 0.05 and 0.70 ± 0.05, for patients undergoing therapeutic hypothermia and normothermia, respectively. These results also persisted in a subset of patients that were in a clinical 'grey zone'. The network's confidence in predicting outcome was based on interpretable features: it strongly correlated to the neural synchrony and complexity of EEG responses and was modulated by independent clinical evaluations, such as the EEG reactivity, background burst-suppression or motor responses. Our results highlight the strong potential of interpretable deep learning algorithms in combination with auditory stimulation to improve prognostication of coma outcome.

In vivo Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data.

Purpose: We present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired in vivo in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity. Theory: The proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on (1) the distribution of axonal radius [P(r)] and (2) the g-ratio of the individual axons that compose this tract [g(r)]. P(r) is assumed to follow a Gamma distribution with mode and scale parameters, M and θ, and g(r) is described by a power law with parameters α and ß. Methods: MRI and EEG data were recorded from 14 healthy volunteers. MRI data were collected with a 3T scanner. MRI-measured g-ratio maps were computed and sampled along the visual transcallosal tract. EEG data were recorded using a 128-lead system with a visual Poffenberg paradigm. The interhemispheric transfer time and axonal conduction velocity were computed from the EEG current density at the group level. Using the MRI and EEG measures and the proposed model, we estimated morphological properties of axons in the visual transcallosal tract. Results: The estimated interhemispheric transfer time was 11.72 ± 2.87 ms, leading to an average conduction velocity across subjects of 13.22 ± 1.18 m/s. Out of the 4 free parameters of the proposed model, we estimated θ - the width of the right tail of the axonal radius distribution - and ß - the scaling factor of the axonal g-ratio, a measure of fiber myelination. Across subjects, the parameter θ was 0.40 ± 0.07 µm and the parameter ß was 0.67 ± 0.02 µm-α. Conclusion: The estimates of axonal radius and myelination are consistent with histological findings, illustrating the feasibility of this approach. The proposed method allows the measurement of the distribution of axonal radius and myelination within a white matter tract, opening new avenues for the combined study of brain structure and function, and for in vivo histological studies of the human brain.

Heart rate complexity: An early prognostic marker of patient outcome after cardiac arrest.

OBJECTIVE: Early prognostication in comatose patients after cardiac arrest (CA) is difficult but essential to inform relatives and optimize treatment. Here we investigate the predictive value of heart-rate variability captured by multiscale entropy (MSE) for long-term outcomes in comatose patients during the first 24 hours after CA. METHODS: In this retrospective analysis of prospective multi-centric cohort, we analyzed MSE of the heart rate in 79 comatose patients after CA while undergoing targeted temperature management and sedation during the first day of coma. From the MSE, two complexity indices were derived by summing values over short and long time scales (CIs and CIl). We splitted the data in training and test datasets for analysing the predictive value for patient outcomes (defined as best cerebral performance category within 3 months) of CIs and CIl. RESULTS: Across the whole dataset, CIl provided the best sensitivity, specificity, and accuracy (88%, 75%, and 82%, respectively). Positive and negative predictive power were 81% and 84%. CONCLUSIONS: Characterizing the complexity of the ECG in patients after CA provides an accurate prediction of both favorable and unfavorable outcomes. SIGNIFICANCE: The analysis of heartrate variability by means of MSE provides accurate outcome prediction on the first day of coma.

Neural signatures of visuo-motor integration during human-robot interactions.

Visuo-motor integration shapes our daily experience and underpins the sense of feeling in control over our actions. The last decade has seen a surge in robotically and virtually mediated interactions, whereby bodily actions ultimately result in an artificial movement. But despite the growing number of applications, the neurophysiological correlates of visuo-motor processing during human-machine interactions under dynamic conditions remain scarce. Here we address this issue by employing a bimanual robotic interface able to track voluntary hands movement, rendered in real-time into the motion of two virtual hands. We experimentally manipulated the visual feedback in the virtual reality with spatial and temporal conflicts and investigated their impact on (1) visuo-motor integration and (2) the subjective experience of being the author of one's action (i.e., sense of agency). Using somatosensory evoked responses measured with electroencephalography, we investigated neural differences occurring when the integration between motor commands and visual feedback is disrupted. Our results show that the right posterior parietal cortex encodes for differences between congruent and spatially-incongruent interactions. The experimental manipulations also induced a decrease in the sense of agency over the robotically-mediated actions. These findings offer solid neurophysiological grounds that can be used in the future to monitor integration mechanisms during movements and ultimately enhance subjective experience during human-machine interactions.

Individual EEG profiling of attention deficits in left spatial neglect: A pilot study.

Electrophysiological group studies in brain-damaged patients can be run to capture the EEG correlates of specific cognitive impairments. Nonetheless, this procedure is not adequate to characterize the inter-individual variability present in major neuropsychological syndromes. We tested the possibility of getting a reliable individual EEG characterization of deficits of endogenous orienting of spatial attention in right-brain damaged (RBD) patients with left spatial neglect (N+). We used a single-trial topographical analysis (STTA; [39] of individual scalp EEG topographies recorded during leftward and rightward orienting of attention with central cues in RBD patients with and without (N-) neglect and in healthy controls (HC). We found that the STTA successfully decoded EEG signals related to leftward and rightward orienting in five out of the six N+, five out of the six N- patients and in all the six HC. In agreement with findings from conventional average-group studies, successful classifications of EEG signals in N+ were observed during the 400-800 ms period post-cue-onset, which reflects preserved voluntary engagement of attention resources (ADAN component). These results suggest the possibility of acquiring reliable individual EEG profiles of neglect patients.

Disentangling the percepts of illusory movement and sensory stimulation during tendon vibration in the EEG.

Mechanical vibration of muscle tendons in specific frequencies - termed functional proprioceptive stimulation (FPS) - has the ability to induce the illusion of a movement which is congruent with a lengthening of the vibrated tendon and muscle. The majority of previous reports of the brain correlates of this illusion are based on functional neuroimaging. Contrary to the electroencephalogram (EEG) however, such technologies are not suitable for bedside or ambulant use. While a handful of studies have shown EEG changes during FPS, it remains underinvestigated whether these changes were due to the perceived illusion or the perceived vibration. Here, we aimed at disentangling the neural correlates of the illusory movement from those produced by the vibration sensation by comparing the neural responses to two vibration types, one that did and one that did not elicit an illusion. We recruited 40 naïve participants, 20 for the EEG experiment and 20 for a supporting behavioral study, who received functional tendon co-vibration on the biceps and triceps tendon at their left elbow, pseudo-randomly switching between the illusion and non-illusion trials. Time-frequency decomposition uncovered a strong and lasting event-related desynchronization (ERD) in the mu and beta band in both conditions, suggesting a strong somatosensory response to the vibration. Additionally, the analysis of the evoked potentials revealed a significant difference between the two experimental conditions from 310 to 990ms post stimulus onset. Training classifiers on the frequency-based and voltage-based correlates of illusion perception yielded above chance accuracies for 17 and 13 out of the 20 subjects respectively. Our findings show that FPS-induced illusions produce EEG correlates that are distinct from a vibration-based control and which can be classified reliably in a large number of participants. These results encourage pursuing EEG-based detection of kinesthetic illusions as a tool for clinical use, e.g., to uncover aspects of cognitive perception in unresponsive patients.

Brain functional connectivity during the first day of coma reflects long-term outcome.

OBJECTIVE: In patients with disorders of consciousness (DOC), properties of functional brain networks at rest are informative of the degree of consciousness impairment and of long-term outcome. Here we investigate whether connectivity differences between patients with favorable and unfavorable outcome are already present within 24 h of coma onset. METHODS: We prospectively recorded 63-channel electroencephalography (EEG) at rest during the first day of coma after cardiac arrest. We analyzed 98 adults, of whom 57 survived beyond unresponsive wakefulness. Functional connectivity was estimated by computing the 'debiased weighted phase lag index' over epochs of five seconds duration. We evaluated the network's topological features, including clustering coefficient, path length, modularity and participation coefficient and computed their variance over time. Finally, we estimated the predictive value of these topological features for patients' outcomes by splitting the patient sample in training and test datasets. RESULTS: Group-level analysis revealed lower clustering coefficient, higher modularity and path length variance in patients with favorable compared to those with unfavorable outcomes (p < 0.01). Within all features, the path length variance in the network provided the best positive predictive value (PPV) for favorable outcome and specificity for unfavorable outcome in the test dataset (PPV: 0.83, p < 0.01; specificity: 0.86, p < 0.01) with above-chance negative predictive value and accuracy. Of note, the exclusion of patients with epileptiform activity (20 in total) eliminates all false positive predictions (n = 6) for path length variance. INTERPRETATION: Topological features of functional connectivity differ as a function of long-term outcome in patients on the first day of coma. These differences are not interpretable in terms of consciousness levels as all patients were in a deep unconscious state. The time variance of path length is informative of comatose patients' outcome, as patients with favorable outcome exhibit a richer repertoire of path length than those with unfavorable outcomes.

Peri-personal space encoding in patients with disorders of consciousness and cognitive-motor dissociation.

Behavioral assessments of consciousness based on overt command following cannot differentiate patients with disorders of consciousness (DOC) from those who demonstrate a dissociation between intent/awareness and motor capacity: cognitive motor dissociation (CMD). We argue that delineation of peri-personal space (PPS) - the multisensory-motor space immediately surrounding the body - may differentiate these patients due to its central role in mediating human-environment interactions, and putatively in scaffolding a minimal form of selfhood. In Experiment 1, we determined a normative physiological index of PPS by recording electrophysiological (EEG) responses to tactile, auditory, or audio-tactile stimulation at different distances (5 vs. 75 cm) in healthy volunteers (N = 19). Contrasts between paired (AT) and summed (A + T) responses demonstrated multisensory supra-additivity when AT stimuli were presented near, i.e., within the PPS, and highlighted somatosensory-motor sensors as electrodes of interest. In Experiment 2, we recorded EEG in patients behaviorally diagnosed as DOC or putative CMD (N = 17, 30 sessions). The PPS-measure developed in Experiment 1 was analyzed in relation with both standard clinical diagnosis (i.e., Coma Recovery Scale; CRS-R) and a measure of neural complexity associated with consciousness. Results demonstrated a significant correlation between the PPS measure and neural complexity, but not with the CRS-R, highlighting the added value of the physiological recordings. Further, multisensory processing in PPS was preserved in putative CMD but not in DOC patients. Together, the findings suggest that indexing PPS allows differentiating between groups of patients whom both show overt motor impairments (DOC and CMD) but putatively distinct levels of awareness or motor intent.

Electroencephalography-based power spectra allow coma outcome prediction within 24 h of cardiac arrest.

BACKGROUND: Outcome prediction in comatose patients following cardiac arrest remains challenging. Here, we assess the predictive performance of electroencephalography-based power spectra within 24 h from coma onset. METHODS: We acquired electroencephalography (EEG) from comatose patients (n = 138) on the first day of coma in four hospital sites in Switzerland. Outcome was categorised as favourable or unfavourable based on the best state within three months. Data were split in training and test sets. We evaluated the predictive performance of EEG power spectra for long term outcome and its added value to standard clinical tests. RESULTS: Out of 138 patients, 80 had a favourable outcome. Power spectra comparison between favourable and unfavourable outcome in the training set yielded significant differences at 5.2-13.2 Hz and above 21 Hz. Outcome prediction based on power at 5.2-13.2 Hz was accurate in training and test sets. Overall, power spectra predicted patients' outcome with maximum specificity and positive predictive value: 1.00 (95% with CI: 0.94-1.00 and 0.89-1.00, respectively). The combination of power spectra and reactivity yielded better accuracy and sensitivity (0.81, 95% CI: 0.71-0.89) than prediction based on power spectra alone. CONCLUSIONS: On the first day of coma following cardiac arrest, low power spectra values around 10 Hz, typically linked to impaired cortico-thalamic structural connections, are highly specific of unfavourable outcome. Peaks in this frequency range can predict long-term outcome.

Electromyographic reactivity measured with scalp-EEG contributes to prognostication after cardiac arrest.

AIM: To assess whether stimulus-induced modifications of electromyographic activity observed on scalp EEG have a prognostic value in comatose patients after cardiac arrest. METHODS: 184 adult patients from a multi-centric prospective register who underwent an early EEG after cardiac arrest were included. Auditory and somatosensory stimulation was performed during EEG-recording. EEG reactivity (EEG-R) and EMG reactivity (EMG-R) were retrospectively assessed visually by board-certified electroencephalographers, and compared with clinical outcome (cerebral performance category, CPC) at three months. A favorable functional outcome was defined as CPC 1-2, an unfavorable outcome as CPC 3-5. RESULTS: Both EEG-R and EMG-R were predictors for good outcome (EEG-R accuracy 72% (95%-CI 66-79), sensitivity 86% (78-93), specificity 60% (50-69); EMG-R accuracy 65% (58-72), sensitivity 61% (51-75), specificity 69% (60-78)). When reactivity was defined as EEG-R and/or EMG-R, the accuracy was 73% (67-70), the sensitivity 94% (90-99), and the specificity 53% (43-63). CONCLUSION: Taking EMG into account when assessing reactivity of EEG seems to reduce false negative predictions for identifying patients with favorable outcome after cardiac arrest.

Practice-induced functional plasticity in inhibitory control interacts with aging.

Inhibitory control deficits represent a key aspect of the cognitive declines associated with aging. Practicing inhibitory control has thus been advanced as a potential approach to compensate for age-induced neurocognitive impairments. Yet, the functional brain changes associated with practicing inhibitory control tasks in older adults and whether they differ from those observed in young populations remains unresolved. We compared electrical neuroimaging analyses of ERPs recorded during a Go/NoGo practice session with a Group (Young; Older adults) by Session (Beginning; End of the practice) design to identify whether the practice of an inhibition task in older adults reinforces already implemented compensatory activity or reduce it by enhancing the functioning of the brain networks primarily involved in the tasks. We observed an equivalent small effect of practice on performance in the two age-groups. The topographic ERP analyses and source estimations revealed qualitatively different effects of the practice over the N2 and P3 ERP components, respectively driven by a decrease in supplementary motor area activity and an increase in left ventrolateral prefrontal activity in the older but not in the young adults with practice. Our results thus indicate that inhibition task practice in older adults increases age-related divergences in the underlying functional processes.

Somatosensory and auditory deviance detection for outcome prediction during postanoxic coma.

OBJECTIVE: Prominent research in patients with disorders of consciousness investigated the electrophysiological correlates of auditory deviance detection as a marker of consciousness recovery. Here, we extend previous studies by investigating whether somatosensory deviance detection provides an added value for outcome prediction in postanoxic comatose patients. METHODS: Electroencephalography responses to frequent and rare stimuli were obtained from 66 patients on the first and second day after coma onset. RESULTS: Multivariate decoding analysis revealed an above chance-level auditory discrimination in 25 patients on the first day and in 31 patients on the second day. Tactile discrimination was significant in 16 patients on the first day and in 23 patients on the second day. Single-day sensory discrimination was unrelated to patients' outcome in both modalities. However, improvement of auditory discrimination from first to the second day was predictive of good outcome with a positive predictive power (PPV) of 0.73 (CI = 0.52-0.88). Analyses considering the improvement of tactile, auditory and tactile, or either auditory or tactile discrimination showed no significant prediction of good outcome (PPVs = 0.58-0.68). INTERPRETATION: Our results show that in the acute phase of coma deviance detection is largely preserved for both auditory and tactile modalities. However, we found no evidence for an added value of somatosensory to auditory deviance detection function for coma-outcome prediction.

EEG Correlates of Preparatory Orienting, Contextual Updating, and Inhibition of Sensory Processing in Left Spatial Neglect.

Studies with event-related potentials have highlighted deficits in the early phases of orienting to left visual targets in right-brain-damaged patients with left spatial neglect (N+). However, brain responses associated with preparatory orienting of attention, with target novelty and with the detection of a match/mismatch between expected and actual targets (contextual updating), have not been explored in N+. Here in a study in healthy humans and brain-damaged patients of both sexes we demonstrate that frontal activity that reflects supramodal mechanisms of attentional orienting (Anterior Directing Attention Negativity, ADAN) is entirely spared in N+. In contrast, posterior responses that mark the early phases of cued orienting (Early Directing Attention Negativity, EDAN) and the setting up of sensory facilitation over the visual cortex (Late Directing Attention Positivity, LDAP) are suppressed in N+. This uncoupling is associated with damage of parietal-frontal white matter. N+ also exhibit exaggerated novelty reaction to targets in the right side of space and reduced novelty reaction for those in the left side (P3a) together with impaired contextual updating (P3b) in the left space. Finally, we highlight a drop in the amplitude and latency of the P1 that over the left hemisphere signals the early blocking of sensory processing in the right space when targets occur in the left one: this identifies a new electrophysiological marker of the rightward attentional bias in N+. The heterogeneous effects and spatial biases produced by localized brain damage on the different phases of attentional processing indicate relevant functional independence among their underlying neural mechanisms and improve the understanding of the spatial neglect syndrome.SIGNIFICANCE STATEMENT Our investigation answers important questions: are the different components of preparatory orienting (EDAN, ADAN, LDAP) functionally independent in the healthy brain? Is preparatory orienting of attention spared in left spatial neglect? Does the sparing of preparatory orienting have an impact on deficits in reflexive orienting and in the assignment of behavioral relevance to the left space? We show that supramodal preparatory orienting in frontal areas is entirely spared in neglect patients though this does not counterbalance deficits in preparatory parietal-occipital activity, reflexive orienting, and contextual updating. This points at relevant functional dissociations among different components of attention and suggests that improving voluntary attention in N+ might be behaviorally ineffective unless associated with stimulations boosting the response of posterior parietal-occipital areas.

How Do You Feel? Subjective Perception of Recovery as a Reliable Surrogate of Cognitive and Functional Outcome in Cardiac Arrest Survivors.

OBJECTIVES: To show that subjective estimate of patient's condition is related to objective cognitive and functional outcome in cardiac arrest survivors. DESIGN: Longitudinal cohort study. SETTING: ICU and Neuropsychology Service in two hospitals in Switzerland. PATIENTS: Fifty survivors included from a prospective cohort of 138 patients admitted at the ICU for cardiopulmonary arrest. INTERVENTIONS: Comprehensive cognitive and functional evaluation at 6 months follow-up. MEASUREMENTS AND MAIN RESULTS: Subjectively, 70% of survivors reported satisfactory recovery and 29% reported no complaints. Objectively, 76% were classified as good neurologic outcome (Cerebral Performance Category 1), 26% as having no symptoms (modified Rankin Scale 0), and 38% as upper good recovery (Glasgow Outcome Scale Extended 1). Cognitive assessment detected substantial cognitive impairment in 26%, primarily concerning processing speed, language, long-term memory, and executive functions. Subjective complaints severity correlated significantly with objective cognitive impairment (rS = 0.64; p < 0.001). Finally, patients reporting unsatisfactory recovery displayed lower functional scores than those reporting satisfactory recovery (e.g., quality of life satisfaction: 64% vs 81%; Z = 2.18; p = 0.03) and more cognitive impairment (three vs one cognitive domains impaired; Z = -3.21; p < 0.001), concerning in particular learning and long-term verbal and visual memory. CONCLUSIONS: Long-term subjective and objective outcome appears good in the majority of cardiac arrest survivors. Specific functional and cognitive impairments were found in patients reporting unsatisfactory recovery. Subjective recovery was strongly correlated with objective assessment.

Cardio-audio synchronization drives neural surprise response.

Successful prediction of future events depends on the brain's capacity to extract temporal regularities from sensory inputs. Neuroimaging studies mainly investigated regularity processing for exteroceptive sensory inputs (i.e. from outside the body). Here we investigated whether interoceptive signals (i.e. from inside the body) can mediate auditory regularity processing. Human participants passively listened to sound sequences presented in synchrony or asynchrony to their heartbeat while concomitant electroencephalography was recorded. We hypothesized that the cardio-audio synchronicity would induce a brain expectation of future sounds. Electrical neuroimaging analysis revealed a surprise response at 158-270 ms upon omission of the expected sounds in the synchronous condition only. Control analyses ruled out that this effect was trivially based on expectation from the auditory temporal structure or on differences in heartbeat physiological signals. Implicit neural monitoring of temporal regularities across interoceptive and exteroceptive signals drives prediction of future events in auditory sequences.

Auditory discrimination improvement predicts awakening of postanoxic comatose patients treated with targeted temperature management at 36°C.

BACKGROUND: Outcome prognostication in postanoxic comatose patients is more accurate in predicting poor than good recovery. Using electroencephalography recordings in patients treated with targeted temperature management at 33°C (TTM 33), we have previously shown that improvement in auditory discrimination over the first days of coma predicted awakening. Given the increased application of a 36°C temperature target (TTM 36), here we aimed at validating the predictive value of auditory discrimination in the TTM 36 setting. METHODS: In this prospective multicenter study, we analyzed the EEG responses to auditory stimuli from 60 consecutive patients from the first and second coma day. A semiautomatic decoding analysis was applied to single patient data to quantify discrimination performance between frequently repeated and deviant sounds. The decoding change from the first to second day was used for predicting patient outcome. RESULTS: We observed an increase in auditory discrimination in 25 out of 60 patients. Among them, 17 awoke from coma (68% positive predictive value; 95% confidence interval: 0.46-0.85). By excluding patients with electroencephalographic epileptiform features, 15 of 18 exhibited improvement in auditory discrimination (83% positive predictive value; 95% confidence interval: 0.59-0.96). Specificity of good outcome prediction increased after adding auditory discrimination to EEG reactivity. CONCLUSION: These results suggest that tracking of auditory discrimination over time is informative of good recovery independent of the temperature target. This quantitative test provides complementary information to existing clinical tools by identifying patients with high chances of recovery and encouraging the maintenance of life support.