Conscious Detection Research Articles

Attentional capture mediates the emergence and suppression of intrusive memories.

Intrusive memories hijack consciousness and their control may lead to forgetting. However, the contribution of reflexive attention to qualifying a memory signal as interfering is unknown. We used machine learning to decode the brain's electrical activity and pinpoint the otherwise hidden emergence of intrusive memories reported during a memory suppression task. Importantly, the algorithm was trained on an independent attentional model of visual activity, mimicking either the abrupt and interfering appearance of visual scenes into conscious awareness or their deliberate exploration. Intrusion of memories into conscious awareness were decoded above chance. The decoding accuracy increased when the algorithm was trained using a model of reflexive attention. Conscious detection of intrusive activity decoded from the brain signal was central to the future silencing of suppressed memories and laterforgetting. Unwanted memories require the reflexive orienting of attention and access to consciousness to be suppressed effectively by inhibitory control.

Brain-Computer Interfaces for Awareness Detection, Auxiliary Diagnosis, Prognosis, and Rehabilitation in Patients with Disorders of Consciousness.

In recent years, neuroimaging studies have remarkably demonstrated the presence of cognitive motor dissociation in patients with disorders of consciousness (DoC). These findings accelerated the development of brain-computer interfaces (BCIs) as clinical tools for behaviorally unresponsive patients. This article reviews the recent progress of BCIs in patients with DoC and discusses the open challenges. In view of the practical application of BCIs in patients with DoC, four aspects of the relevant literature are introduced: consciousness detection, auxiliary diagnosis, prognosis, and rehabilitation. For each aspect, the paradigm design, brain signal processing methods, and experimental results of representative BCI systems are analyzed. Furthermore, this article provides guidance for BCI design for patients with DoC and discusses practical challenges for future research.

The cost of attentional reorienting on conscious visual perception: an MEG study.

How do attentional networks influence conscious perception? To answer this question, we used magnetoencephalography in human participants and assessed the effects of spatially nonpredictive or predictive supra-threshold peripheral cues on the conscious perception of near-threshold Gabors. Three main results emerged. (i) As compared with invalid cues, both nonpredictive and predictive valid cues increased conscious detection. Yet, only predictive cues shifted the response criterion toward a more liberal decision (i.e. willingness to report the presence of a target under conditions of greater perceptual uncertainty) and affected target contrast leading to 50% detections. (ii) Conscious perception following valid predictive cues was associated to enhanced activity in frontoparietal networks. These responses were lateralized to the left hemisphere during attentional orienting and to the right hemisphere during target processing. The involvement of frontoparietal networks occurred earlier in valid than in invalid trials, a possible neural marker of the cost of re-orienting attention. (iii) When detected targets were preceded by invalid predictive cues, and thus reorienting to the target was required, neural responses occurred in left hemisphere temporo-occipital regions during attentional orienting, and in right hemisphere anterior insular and temporo-occipital regions during target processing. These results confirm and specify the role of frontoparietal networks in modulating conscious processing and detail how invalid orienting of spatial attention disrupts conscious processing.

Perceived timing of cutaneous vibration and intracortical microstimulation of human somatosensory cortex

BackgroundIntracortical microstimulation (ICMS) of somatosensory cortex can partially restore the sense of touch. Though ICMS bypasses much of the neuraxis, prior studies have found that conscious detection of touch elicited by ICMS lags behind the detection of cutaneous vibration. These findings may have been influenced by mismatched stimulus intensities, which can impact temporal perception. ObjectiveEvaluate the relative latency at which intensity-matched vibration and ICMS are perceived by a human participant. MethodsOne person implanted with microelectrode arrays in somatosensory cortex performed reaction time and temporal order judgment (TOJ) tasks. To measure reaction time, the participant reported when he perceived vibration or ICMS. In the TOJ task, vibration and ICMS were sequentially presented and the participant reported which stimulus occurred first. To verify that the participant could distinguish between stimuli, he also performed a modality discrimination task, in which he indicated if he felt vibration, ICMS, or both. ResultsWhen vibration was matched in perceived intensity to high-amplitude ICMS, vibration was perceived, on average, 48 ms faster than ICMS. However, in the TOJ task, both sensations arose at comparable latencies, with points of subjective simultaneity not significantly different from zero. The participant could discriminate between tactile modalities above chance level but was more inclined to report feeling vibration than ICMS. ConclusionsThe latencies of ICMS-evoked percepts are slower than their mechanical counterparts. However, differences in latencies are small, particularly when stimuli are matched for intensity, implying that ICMS-based somatosensory feedback is rapid enough to be effective in neuroprosthetic applications.

American and European Guidelines on Disorders of Consciousness: Ethical Challenges of Implementation.

American and European Guidelines on Disorders of Consciousness: Ethical Challenges of Implementation.

The Predictive Role of Low Spatial Frequencies in Automatic Face Processing: A Visual Mismatch Negativity Investigation.

Visual processing is thought to function in a coarse-to-fine manner. Low spatial frequencies (LSF), conveying coarse information, would be processed early to generate predictions. These LSF-based predictions would facilitate the further integration of high spatial frequencies (HSF), conveying fine details. The predictive role of LSF might be crucial in automatic face processing, where high performance could be explained by an accurate selection of clues in early processing. In the present study, we used a visual Mismatch Negativity (vMMN) paradigm by presenting an unfiltered face as standard stimulus, and the same face filtered in LSF or HSF as deviant, to investigate the predictive role of LSF vs. HSF during automatic face processing. If LSF are critical for predictions, we hypothesize that LSF deviants would elicit less prediction error (i.e., reduced mismatch responses) than HSF deviants. Results show that both LSF and HSF deviants elicited a mismatch response compared with their equivalent in an equiprobable sequence. However, in line with our hypothesis, LSF deviants evoke significantly reduced mismatch responses compared to HSF deviants, particularly at later stages. The difference in mismatch between HSF and LSF conditions involves posterior areas and right fusiform gyrus. Overall, our findings suggest a predictive role of LSF during automatic face processing and a critical involvement of HSF in the fusiform during the conscious detection of changes in faces.

Clarifying the effect of facial emotional expression on inattentional blindness

Conscious perception often fails when an object appears unexpectedly and our attention is focused elsewhere (inattentional blindness). While various factors have been identified that modulate the likelihood of this failure of awareness, the semantic value of facial emotional expression of the unexpected stimulus is not clear. A total of 457 participants performed a static or a dynamic inattentional blindness paradigm with one of three face icons as the unexpected stimulus. Whereas we only found an effect of frowning faceś semantic value on its conscious detection in the static paradigm, we found in both paradigms a substantial effect of frowning as well as happy faceś semantic value on their conscious identification. Thus, we assume that the semantic value of unexpected stimuli, based on facial emotional expressions, controls attentional prioritization and influences inattentional blindness. Furthermore, we argue that every finding in inattentional blindness research should be considered in its respective context.

Oculomotor freezing indicates conscious detection free of decision bias.

The appearance of a salient stimulus rapidly and automatically inhibits saccadic eye movements. Curiously, this "oculomotor freezing" response is triggered only by stimuli that the observer reports seeing. It remains unknown, however, whether oculomotor freezing is linked to the observer's sensory experience or their decision that a stimulus was present. To dissociate between these possibilities, we manipulated decision criterion via monetary payoffs and stimulus probability in a detection task. These manipulations greatly shifted observers' decision criteria but did not affect the degree to which microsaccades were inhibited by stimulus presence. Moreover, the link between oculomotor freezing and explicit reports of stimulus presence was stronger when the criterion was conservative rather than liberal. We conclude that the sensory threshold for oculomotor freezing is independent of decision bias. Provided that conscious experience is also unaffected by such bias, oculomotor freezing is an implicit indicator of sensory awareness.NEW & NOTEWORTHY Sometimes a visual stimulus reaches awareness, and sometimes it does not. To understand why, we need objective, bias-free measures of awareness. We discovered that a reflexive freezing of small eye movements indicates when an observer detects a stimulus. Furthermore, when we biased observers' decisions to report seeing the stimulus, the oculomotor response was unaltered. This suggests that the threshold for conscious perception is independent of the decision criterion and is revealed by oculomotor freezing.

Insular dichotomy in the implicit detection of emotions in human faces.

The functional roles of the insula diverge between its posterior portion (PI), mainly connected with somato-sensory and motor areas, and its anterior section (AI) connected with the frontal, limbic, and cingulate regions. We report intracranial recordings of local field evoked potentials from PI, AI, and the visual fusiform gyrus to a full array of emotional faces including pain while the individuals' attention was diverted from emotions. The fusiform gyrus and PI responded equally to all types of faces, including neutrals. Conversely, the AI responded only to emotional faces, maximally to pain and fear, while remaining insensitive to neutrals. The two insular sectors reacted with almost identical latency suggesting their parallel initial activation via distinct functional routes. The consistent responses to all emotions, together with the absence of response to neutral faces, suggest that early responses in the AI reflect the immediate arousal value and behavioral relevance of emotional stimuli, which may be subserved by "fast track" routes conveying coarse-spatial-frequency information via the superior colliculus and dorsal pulvinar. Such responses precede the conscious detection of the stimulus' precise signification and valence, which need network interaction and information exchange with other brain areas, for which the AI is an essentialhub.

Consciousness Detection on Injured Simulated Patients Using Manual and Automatic Classification via Visible and Infrared Imaging.

In a disaster scene, triage is a key principle for effectively rescuing injured people according to severity level. One main parameter of the used triage algorithm is the patient’s consciousness. Unmanned aerial vehicles (UAV) have been investigated toward (semi-)automatic triage. In addition to vital parameters, such as heart and respiratory rate, UAVs should detect victims’ mobility and consciousness from the video data. This paper presents an algorithm combining deep learning with image processing techniques to detect human bodies for further (un)consciousness classification. The algorithm was tested in a 20-subject group in an outside environment with static (RGB and thermal) cameras where participants performed different limb movements in different body positions and angles between the cameras and the bodies’ longitudinal axis. The results verified that the algorithm performed better in RGB. For the most probable case of 0 degrees, RGB data obtained the following results: Mathews correlation coefficient (MMC) of 0.943, F1-score of 0.951, and precision-recall area under curve AUC (PRC) score of 0.968. For the thermal data, the MMC was 0.913, F1-score averaged 0.923, and AUC (PRC) was 0.960. Overall, the algorithm may be promising along with others for a complete contactless triage assessment in disaster events during day and night.

Response: Commentary: Distrust, False Cues, and Below-Chance Deception Detection Accuracy: Commentary on Stel et al. (2020) and Further Reflections on (Un)Conscious Lie Detection From the Perspective of Truth-Default Theory.

Response: Commentary: Distrust, False Cues, and Below-Chance Deception Detection Accuracy: Commentary on Stel et al. (2020) and Further Reflections on (Un)Conscious Lie Detection From the Perspective of Truth-Default Theory.

Update on neuroimaging in disorders of consciousness.

Neuroimaging has acquired a prominent place in the assessment of disorders of consciousness (DoC). Rapidly evolving technologies combined with state-of-the-art data analyses open new horizons to probe brain activity, but selecting appropriate imaging modalities from the plethora of available techniques can be challenging for clinicians. This update reviews selected advances in neuroimaging that demonstrate clinical relevance and translational potential in the assessment of severely brain-injured patients with DoC. Magnetic resonance imaging and high-density electroencephalography provide measurements of brain connectivity between functional networks, assessments of language function, detection of covert consciousness, and prognostic markers of recovery. Positron emission tomography can identify patients with preserved brain metabolism despite clinical unresponsiveness and can measure glucose consumption rates in targeted brain regions. Transcranial magnetic stimulation and near-infrared spectroscopy are noninvasive and practical tools with promising clinical applications. Each neuroimaging technique conveys advantages and pitfalls to assess consciousness. We recommend a multimodal approach in which complementary techniques provide diagnostic and prognostic information about brain function. Patients demonstrating neuroimaging evidence of covert consciousness may benefit from early adapted rehabilitation. Translating methodological advances to clinical care will require the implementation of recently published international guidelines and the integration of neuroimaging techniques into patient-centered decision-making algorithms.

Calibration in Consciousness Science

To study consciousness, scientists need to determine when participants are conscious and when they are not. They do so with consciousness detection procedures. A recurring skeptical argument against those procedures is that they cannot be calibrated: there is no way to make sure that detection outcomes are accurate. In this article, I address two main skeptical arguments purporting to show that consciousness scientists cannot calibrate detection procedures. I conclude that there is nothing wrong with calibration in consciousness science.

The Quest for Covert Consciousness: Bringing Neuroethics to the Bedside.

Plato, in his Allegory of the Cave, contemplates a group of people who have lived their entire lives facing a wall of a cave and whose impressions of the world are constrained to perceptual experiences of shadows cast on the wall by entities that are never directly observed. Since time immemorial, conscious states of others have been like Platonic shadows, inferred only imperfectly and indirectly through close observation of behaviors. Although for centuries philosophers and neuroscientists have sought to bring us closer to understanding consciousness, an influx of neurotechnologies now enables clinicians and researchers to potentially improve detection of consciousness and prediction of its recovery.1 Innovations in neuroimaging and electrophysiologic techniques now may permit detection of states of consciousness not readily discernible by bedside examination, known as covert consciousness or cognitive motor dissociation.2 The discovery of covert consciousness raises distinctive issues surrounding both the diagnosis and prognosis of persons with disorders of consciousness (DoC), highlighting the need for caution during the acute phase of neuroprognostication and exposing gaps in knowledge about the epidemiology and phenomenology of covert consciousness. These innovations represent a possible step forward from philosophical and scientific traditions that relied on behavioral observations to detect consciousness. In turn, these breakthroughs prompt reconsideration of standard approaches to the evaluation of persons with DoC and necessitate appraisal of how clinicians should communicate results of novel techniques with indeterminate meanings to surrogates. Proactive integration of neuroethical insights in clarifying responsible ends to which these technologies should be directed is essential for addressing these timely challenges. This article proposes an ethical framework to help the clinical and research community consider how to use these emerging neurotechnologies responsibly, calls for careful consideration of the consequences of searching for covert consciousness in practice, and highlights critical avenues for further study of how the finding of covert consciousness might help predict goal-concordant functional recovery.

Consciousness Detection in a Complete Locked-in Syndrome Patient through Multiscale Approach Analysis.

Completely locked-in state (CLIS) patients are unable to speak and have lost all muscle movement. From the external view, the internal brain activity of such patients cannot be easily perceived, but CLIS patients are considered to still be conscious and cognitively active. Detecting the current state of consciousness of CLIS patients is non-trivial, and it is difficult to ascertain whether CLIS patients are conscious or not. Thus, it is important to find alternative ways to re-establish communication with these patients during periods of awareness, and one such alternative is through a brain–computer interface (BCI). In this study, multiscale-based methods (multiscale sample entropy, multiscale permutation entropy and multiscale Poincaré plots) were applied to analyze electrocorticogram signals from a CLIS patient to detect the underlying consciousness level. Results from these different methods converge to a specific period of awareness of the CLIS patient in question, coinciding with the period during which the CLIS patient is recorded to have communicated with an experimenter. The aim of the investigation is to propose a methodology that could be used to create reliable communication with CLIS patients.

Neural divergence and convergence for attention to and detection of interoceptive and somatosensory stimuli

Body awareness is constructed by signals originating from within and outside the body. How do these apparently divergent signals converge? We developed a signal detection task to study the neural convergence and divergence of interoceptive and somatosensory signals. Participants focused on either cardiac or tactile events and reported their presence or absence. Beyond some evidence of divergence, we observed a robust overlap in the pattern of activation evoked across both conditions in frontal areas including the insular cortex, as well as parietal and occipital areas, and for both attention and detection of these signals. Psycho-physiological interaction analysis revealed that right insular cortex connectivity was modulated by the conscious detection of cardiac compared to somatosensory sensations, with greater connectivity to occipito-parietal regions when attending to cardiac signals. Our findings speak in favour of the inherent convergence of bodily-related signals and move beyond the apparent antagonism between exteroception and interoception.

The role of visual feedback in detecting and correcting typing errors: A signal detection approach

• Three experiments manipulating visual feedback while typing single words. • Error detection moderately impacted by visual feedback removal. • Error correction relying heavily on visual feedback. • Positional information helpful, but letter identity essential for corrections. • Application of signal detection theory to multichannel language monitoring. This study examined the role of external information in monitoring language production. In a typing-to-dictation task, participants were deprived of all or part of visual feedback. Data were analyzed using signal detection theory (SDT) applied to a multi-component monitoring framework. Results showed that removing the visual information affected the correction of typing errors more than their conscious detection (Exps 1, 2). Reinstating partial visual information (positional information) increased correction rates but not to the level of full visual information, independently of the probability of error detection (Exps 2, 3). Analysis of SDT parameters showed that while manipulating visual information affected the informativeness of the signal for both correction and conscious detection of errors, participants treated this change differently in the two tasks. We discuss the implications of the results, and more generally, the utility of SDT, for theories of monitoring and control in language production.

Pupil dilation during orienting of attention and conscious detection of visual targets in patients with left spatial neglect

Right Brain-Damaged patients (RBD) with left spatial neglect (N+), are characterised by deficits in orienting and re-orienting attention to stimuli in the contralesional left side of space. In a recent ERPs study with visual stimuli (Lasaponara et al., 2018) we have pointed out that the pathological attentional bias of N+ is matched with exaggerated novelty reaction and contextual updating of targets in the right ipsilesional space and reduced novelty reaction and contextual updating of targets in the left contralesional space. To characterise further the attentional performance of N+, here we measured Pupil Dilation (PDil), which is a reliable marker of noradrenergic-locus coeruleus activity and response to unexpected events/rewards. Compared to Neutral and Valid targets, N+ patients displayed a pathological reduction of PDil in response to infrequent Invalid targets in the left side of space, while in Healthy Controls (HC) and RBD without neglect (N-) the same targets enhanced PDil with respect to Neutral and frequent Valid targets. Invalid targets in the right side of space enhanced PDil in all experimental groups. Interestingly, both N- and N+ showed a consistent number of target omissions both in the left and right side of space. With respect to seen targets, N- showed reduced PDil in response to unseen targets both in the left and right side of space. In contrast, N+ had reduced PDil in response to unseen targets in the left side of space though not in the right side, where seen and unseen targets evoked comparable levels of PDil. These results disclose, for the first time, the PDil correlates of spatial attention in left spatial neglect and suggest that the pathological attentional bias suffered by N+ might enhance the autonomic responses reflected in PDil to unseen ipsilesional stimuli. This enhancement can contribute to biasing contextual updating and predictive coding of stimuli in the ipsilesional space, thus worsening the pathological attentional bias of N+.

Is It Implicit Detection or Perception During Change Blindness?

PurposeImplicit detection differs from implicit perception. The former includes implicit registration, localisation, identification and comparison of an object. Implicit comparison is not necessary for implicit perception, and should not involve the identification or localisation of objects. While many studies have reported evidence of implicit detection in change blindness, they may, in fact, have only observed implicit perception. In this study, we aimed to find out whether there is implicit detection or perception during the change blindness period.MethodsIn Experiments 1 and 2, we used a simple change detection paradigm, coupled with a speeded attribute discrimination task. Reaction times (RTs) and accuracy of the participants were measured for the speeded attribute discrimination task. We compared differences in RT and accuracy of the invalid and congruent cue trials to find evidence for implicit detection. Invalid trials referred to stimuli where the appearance of the cue does not change, whereas congruent trials involved cued objects with the same attributes as that of the change object. In Experiment 3, a one-shot change detection experiment was conducted, where subjects were required to report whether the objects were the same or different as quickly as possible. We compared the differences in RTs between trials in which the stimulus exhibited a change but participants reported “same” (change blindness trails) and trials in which the stimulus exhibited no change and participants reported “same” (baseline trials), to find evidence for implicit perception.ResultsIn Experiments 1 and 2, the difference in accuracy and RTs under invalid and congruent conditions was not significant. We did not observe a validity effect as evidence for implicit localisation or a congruency effect as evidence for identification. In Experiment 3, the RTs were longer in the change blindness relative no-change trials, which indicated that there was implicit perception.ConclusionThe results of this study showed that there was no evidence supporting implicit detection in colour or orientation as a single or a combination of features. However, we report evidence for implicit perception during the change blindness period. Change may be implicitly perceived, but not located or identified before there is conscious detection.

Study on the effect of nontarget types on name based auditory event-related potentials.

Exploring the brain response to stimuli of healthy people in passive state is helpful to understand the brain response mechanism of unresponsive people. Event-related potential (ERP) can reflect the time synchronization of potentials, which is a feasible objective electrophysiological index reflecting the functional status of the brain. In this paper, we used the subjects' own name (SON) as target stimuli and compared with the nontarget stimuli (others' name) of Three Chinese Characters (3CC) and Two Chinese Characters (2CC) with the same stimuli duration (600ms) and inter stimuli interval (500ms-800ms）. Thirteen healthy subjects attended in this study with four conditions ( [active, passive]×[3CC, 2CC] ). We compared the ERP waveforms, the behavior performance, and the classification of four different conditions. ERP results show that the P300 amplitude of conditions with 3CC nontargets is higher than that of conditions with 2CC nontargets. Behavioral results show that the grand accuracy is 97% when the nontargets are 3CC, while the grand accuracy is only 94% when the nontargets are 2CC. The reaction time is also different from the two nontargets (605ms with 3CC vs 635ms with 2CC). Classification results illustrate that in active condition, the accuracy rate is 82.1% when the nontarget is 3CC, and that is 80.9% in passive condition, which are 4.2% and 6.4% higher than the accuracy rate under 2CC cases in both active and passive conditions. This study can provide a scheme for grading diagnosis of consciousness detection, and further applying to clinical evaluation.Clinical Relevance- This study can provide a better paradigm basis for clinical evaluation of unresponsive patients (such as disorder of consciousness, DOC) and may become an effective auxiliary means for clinical rating scales.