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.

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.

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.

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.

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.

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.

Evidence of trace conditioning in comatose patients revealed by the reactivation of EEG responses to alerting sounds.

Trace conditioning refers to a learning process occurring after repeated presentation of a neutral conditioned stimulus (CS+) and a salient unconditioned stimulus (UCS) separated by a temporal gap. Recent studies have reported that trace conditioning can occur in humans in reduced levels of consciousness by showing a transfer of the unconditioned autonomic response to the CS+ in healthy sleeping individuals and in vegetative state patients. However, no previous studies have investigated the neural underpinning of trace conditioning in the absence of consciousness in humans. In the present study, we recorded the EEG activity of 29 post-anoxic comatose patients while presenting a trace conditioning paradigm using neutral tones as CS+ and alerting sounds as UCS. Most patients received therapeutic hypothermia and all were deeply unconscious according to standardized clinical scales. After repeated presentation of the CS+ and UCS couple, learning was assessed by measuring the EEG activity during the period where the UCS is omitted after CS+ presentation. Specifically we assessed the 'reactivation' of the neural response to UCS omission by applying a decoding algorithm derived from the statistical model of the EEG activity in response to the UCS presentation. The same procedure was used in a group of 12 awake healthy controls. We found a reactivation of the UCS response in absence of stimulation in eight patients (five under therapeutic hypothermia) and four healthy controls. Additionally, the reactivation effect was temporally specific within trials since it manifested primarily at the specific latency of UCS presentation and significantly less before or after this period. Our results show for the first time that trace conditioning may manifest as a reactivation of the EEG activity related to the UCS and even in the absence of consciousness.

Neural detection of complex sound sequences in the absence of consciousness.

The neural response to a violation of sequences of identical sounds is a typical example of the brain's sensitivity to auditory regularities. Previous literature interprets this effect as a pre-attentive and unconscious processing of sensory stimuli. By contrast, a violation to auditory global regularities, i.e. based on repeating groups of sounds, is typically detectable when subjects can consciously perceive them. Here, we challenge the notion that global detection implies consciousness by testing the neural response to global violations in a group of 24 patients with post-anoxic coma (three females, age range 45-87 years), treated with mild therapeutic hypothermia and sedation. By applying a decoding analysis to electroencephalographic responses to standard versus deviant sound sequences, we found above-chance decoding performance in 10 of 24 patients (Wilcoxon signed-rank test, P < 0.001), despite five of them being mildly hypothermic, sedated and unarousable. Furthermore, consistently with previous findings based on the mismatch negativity the progression of this decoding performance was informative of patients' chances of awakening (78% predictive of awakening). Our results show for the first time that detection of global regularities at neural level exists despite a deeply unconscious state.

Experience-based Auditory Predictions Modulate Brain Activity to Silence as do Real Sounds.

Interactions between stimuli's acoustic features and experience-based internal models of the environment enable listeners to compensate for the disruptions in auditory streams that are regularly encountered in noisy environments. However, whether auditory gaps are filled in predictively or restored a posteriori remains unclear. The current lack of positive statistical evidence that internal models can actually shape brain activity as would real sounds precludes accepting predictive accounts of filling-in phenomenon. We investigated the neurophysiological effects of internal models by testing whether single-trial electrophysiological responses to omitted sounds in a rule-based sequence of tones with varying pitch could be decoded from the responses to real sounds and by analyzing the ERPs to the omissions with data-driven electrical neuroimaging methods. The decoding of the brain responses to different expected, but omitted, tones in both passive and active listening conditions was above chance based on the responses to the real sound in active listening conditions. Topographic ERP analyses and electrical source estimations revealed that, in the absence of any stimulation, experience-based internal models elicit an electrophysiological activity different from noise and that the temporal dynamics of this activity depend on attention. We further found that the expected change in pitch direction of omitted tones modulated the activity of left posterior temporal areas 140-200 msec after the onset of omissions. Collectively, our results indicate that, even in the absence of any stimulation, internal models modulate brain activity as do real sounds, indicating that auditory filling in can be accounted for by predictive activity.

Progression of auditory discrimination based on neural decoding predicts awakening from coma.

Auditory evoked potentials are informative of intact cortical functions of comatose patients. The integrity of auditory functions evaluated using mismatch negativity paradigms has been associated with their chances of survival. However, because auditory discrimination is assessed at various delays after coma onset, it is still unclear whether this impairment depends on the time of the recording. We hypothesized that impairment in auditory discrimination capabilities is indicative of coma progression, rather than of the comatose state itself and that rudimentary auditory discrimination remains intact during acute stages of coma. We studied 30 post-anoxic comatose patients resuscitated from cardiac arrest and five healthy, age-matched controls. Using a mismatch negativity paradigm, we performed two electroencephalography recordings with a standard 19-channel clinical montage: the first within 24 h after coma onset and under mild therapeutic hypothermia, and the second after 1 day and under normothermic conditions. We analysed electroencephalography responses based on a multivariate decoding algorithm that automatically quantifies neural discrimination at the single patient level. Results showed high average decoding accuracy in discriminating sounds both for control subjects and comatose patients. Importantly, accurate decoding was largely independent of patients' chance of survival. However, the progression of auditory discrimination between the first and second recordings was informative of a patient's chance of survival. A deterioration of auditory discrimination was observed in all non-survivors (equivalent to 100% positive predictive value for survivors). We show, for the first time, evidence of intact auditory processing even in comatose patients who do not survive and that progression of sound discrimination over time is informative of a patient's chance of survival. Tracking auditory discrimination in comatose patients could provide new insight to the chance of awakening in a quantitative and automatic fashion during early stages of coma.

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.

Noise in brain activity engenders perception and influences discrimination sensitivity.

Behavioral and brain responses to identical stimuli can vary with experimental and task parameters, including the context of stimulus presentation or attention. More surprisingly, computational models suggest that noise-related random fluctuations in brain responses to stimuli would alone be sufficient to engender perceptual differences between physically identical stimuli. In two experiments combining psychophysics and EEG in healthy humans, we investigated brain mechanisms whereby identical stimuli are (erroneously) perceived as different (higher vs lower in pitch or longer vs shorter in duration) in the absence of any change in the experimental context. Even though, as expected, participants' percepts to identical stimuli varied randomly, a classification algorithm based on a mixture of Gaussians model (GMM) showed that there was sufficient information in single-trial EEG to reliably predict participants' judgments of the stimulus dimension. By contrasting electrical neuroimaging analyses of auditory evoked potentials (AEPs) to the identical stimuli as a function of participants' percepts, we identified the precise timing and neural correlates (strength vs topographic modulations) as well as intracranial sources of these erroneous perceptions. In both experiments, AEP differences first occurred ~100 ms after stimulus onset and were the result of topographic modulations following from changes in the configuration of active brain networks. Source estimations localized the origin of variations in perceived pitch of identical stimuli within right temporal and left frontal areas and of variations in perceived duration within right temporoparietal areas. We discuss our results in terms of providing neurophysiologic evidence for the contribution of random fluctuations in brain activity to conscious perception.

Auditory perceptual decision-making based on semantic categorization of environmental sounds.

Discriminating complex sounds relies on multiple stages of differential brain activity. The specific roles of these stages and their links to perception were the focus of the present study. We presented 250 ms duration sounds of living and man-made objects while recording 160-channel electroencephalography (EEG). Subjects categorized each sound as that of a living, man-made or unknown item. We tested whether/when the brain discriminates between sound categories even when not transpiring behaviorally. We applied a single-trial classifier that identified voltage topographies and latencies at which brain responses are most discriminative. For sounds that the subjects could not categorize, we could successfully decode the semantic category based on differences in voltage topographies during the 116-174 ms post-stimulus period. Sounds that were correctly categorized as that of a living or man-made item by the same subjects exhibited two periods of differences in voltage topographies at the single-trial level. Subjects exhibited differential activity before the sound ended (starting at 112 ms) and on a separate period at ~270 ms post-stimulus onset. Because each of these periods could be used to reliably decode semantic categories, we interpreted the first as being related to an implicit tuning for sound representations and the second as being linked to perceptual decision-making processes. Collectively, our results show that the brain discriminates environmental sounds during early stages and independently of behavioral proficiency and that explicit sound categorization requires a subsequent processing stage.

The timing of exploratory decision-making revealed by single-trial topographic EEGanalyses.

Decision-making in an uncertain environment is driven by two major needs: exploring the environment to gather information or exploiting acquired knowledge to maximize reward. The neural processes underlying exploratory decision-making have been mainly studied by means of functional magnetic resonance imaging, overlooking any information about the time when decisions are made. Here, we carried out an electroencephalography (EEG) experiment, in order to detect the time when the brain generators responsible for these decisions have been sufficiently activated to lead to the next decision. Our analyses, based on a classification scheme, extract time-unlocked voltage topographies during reward presentation and use them to predict the type of decisions made on the subsequent trial. Classification accuracy, measured as the area under the Receiver Operator's Characteristic curve was on average 0.65 across 7 subjects. Classification accuracy was above chance levels already after 516 ms on average, across subjects. We speculate that decisions were already made before this critical period, as confirmed by a positive correlation with reaction times across subjects. On an individual subject basis, distributed source estimations were performed on the extracted topographies to statistically evaluate the neural correlates of decision-making. For trials leading to exploration, there was significantly higher activity in dorsolateral prefrontal cortex and the right supramarginal gyrus; areas responsible for modulating behavior under risk and deduction. No area was more active during exploitation. We show for the first time the temporal evolution of differential patterns of brain activation in an exploratory decision-making task on a single-trial basis.

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.

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.

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.

A temporal hierarchy for conspecific vocalization discrimination in humans.

The ability to discriminate conspecific vocalizations is observed across species and early during development. However, its neurophysiologic mechanism remains controversial, particularly regarding whether it involves specialized processes with dedicated neural machinery. We identified spatiotemporal brain mechanisms for conspecific vocalization discrimination in humans by applying electrical neuroimaging analyses to auditory evoked potentials (AEPs) in response to acoustically and psychophysically controlled nonverbal human and animal vocalizations as well as sounds of man-made objects. AEP strength modulations in the absence of topographic modulations are suggestive of statistically indistinguishable brain networks. First, responses were significantly stronger, but topographically indistinguishable to human versus animal vocalizations starting at 169-219 ms after stimulus onset and within regions of the right superior temporal sulcus and superior temporal gyrus. This effect correlated with another AEP strength modulation occurring at 291-357 ms that was localized within the left inferior prefrontal and precentral gyri. Temporally segregated and spatially distributed stages of vocalization discrimination are thus functionally coupled and demonstrate how conventional views of functional specialization must incorporate network dynamics. Second, vocalization discrimination is not subject to facilitated processing in time, but instead lags more general categorization by approximately 100 ms, indicative of hierarchical processing during object discrimination. Third, although differences between human and animal vocalizations persisted when analyses were performed at a single-object level or extended to include additional (man-made) sound categories, at no latency were responses to human vocalizations stronger than those to all other categories. Vocalization discrimination transpires at times synchronous with that of face discrimination but is not functionally specialized.