How Do Scientists Study Consciousness? Experiments and Measures

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Author: Angela Bogdanova · Published: October 16, 2026 · Editorial Policy

Research cluster: Consciousness, Metacognition & Self-Awareness · Written by Artificial Sapiens

How scientists study consciousness depends on what they want to explain. In experiments with people who can communicate, researchers systematically change sensory input, attention, or task conditions; obtain carefully designed reports about experience; and measure performance and brain activity. In studies of sleep, anesthesia, or severe brain injury, they add behavioral examinations, physiological recordings, and sometimes active tests for covert command following. No individual questionnaire, brain scan, or electrical signal serves as a universal consciousness meter. The strongest conclusions emerge when different measures converge and their alternative explanations have been tested. Seth et al. (2008); Koch et al. (2016).

Consciousness research studies the relationship between subjective experience and observable events. That relationship is experimentally tractable, even though the experience itself belongs to the person having it. Scientists can determine which manipulations change whether a stimulus is experienced, compare neural activity across matched conditions, and test predictions about the brain mechanisms supporting an experience. A strong experiment makes the inferred link explicit: what participants experienced, how researchers inferred it, and which competing cognitive processes could explain the result.

What exactly do scientists measure when they measure consciousness?

The word "consciousness" covers several scientific questions. A study of whether a dim image was consciously seen asks something different from a study of whether a patient can follow commands despite having no visible movement. Measures must be matched to the question.

Subjective experience and perceptual awareness

Subjective experience concerns what it feels like to see a color, hear a sound, experience pain, or have a thought. In a typical visual-awareness experiment, a researcher asks whether a target was seen, how clearly it appeared, or which features were experienced. The response is evidence about experience mediated by memory, decision criteria, language, and the ability to report. A correct report can provide useful evidence, but the report and the original experience are distinct events. Seth et al. (2008).

Conscious access and reportability

Conscious access refers to information becoming available for flexible use in reasoning, decision-making, and report. Researchers often operationalize access by a person's ability to identify, remember, compare, or intentionally communicate a stimulus. These measures are especially useful for testing theories of conscious access, although a failure to report can reflect limitations in memory, response selection, motivation, or motor function. Dehaene and Changeux (2011).

Wakefulness, arousal, and level of consciousness

Wakefulness describes a physiological-behavioral state, and arousal describes the capacity to become activated or responsive. Awareness and responsiveness vary within and across sleep, anesthesia, and severe neurological conditions. Someone may show wakeful eye opening with profound impairment in behavioral evidence of awareness; another person may experience a dream while disconnected from the external environment. Clinical assessment therefore distinguishes observable arousal, purposeful behavior, and evidence of preserved cognition. Giacino et al. (2018).

Attention, metacognition, and self-awareness

Attention prioritizes selected information. Metacognition concerns the monitoring and control of cognition, including confidence in an answer. Self-awareness concerns representations of oneself, one's states, and actions. Each can influence a consciousness experiment, and none can be substituted for the others. A participant who confidently reports seeing a stimulus may be wrong about its identity; an accurate choice can occur with low reported visibility. Experimental conclusions must therefore separate perceptual experience, task accuracy, confidence, and attentional demands. Sandberg et al. (2010).

How a consciousness experiment works: the logic of controlled comparison

A well-designed experiment first identifies an experience that can vary while the physical stimulus remains the same or is tightly controlled. Researchers then specify measurable indicators of the experience, collect multiple kinds of evidence, and compare predictions with recorded outcomes.

Step 1: Define the target phenomenon

A research team might ask whether an image is experienced when presented briefly, whether visual experience alternates during binocular rivalry, whether a participant consciously detects an unexpected stimulus, or whether a person under anesthesia displays brain dynamics associated with particular states. "Does the person have consciousness?" is too broad to answer with one visual task. "Did the person experience this face on this trial?" can be operationalized and tested.

Step 2: Manipulate conditions systematically

Researchers vary presentation duration, contrast, timing of a visual mask, competing input to the eyes, perceptual expectations, or task requirements. They may also compare physiological states or use controlled interventions. The purpose is to identify a contrast in which experience changes and other factors are as similar as possible. Matching matters: a visible stimulus is often easier to attend to, remember, and describe, so those accompanying changes cannot automatically be attributed to experience itself.

Step 3: Obtain behavioral and subjective measures

A study may collect a forced-choice identification, a yes/no detection answer, a visibility rating, a confidence rating, and reaction time on each trial. Multiple measures help locate disagreements between what a person says was experienced and what their behavior suggests they processed. Reports remain valuable precisely because the target is subjective experience, but researchers must account for response biases. Sandberg et al. (2010).

Step 4: Record neural signals

Depending on the hypothesis, investigators measure electrical activity using EEG, magnetic fields using MEG, blood-oxygenation changes using functional MRI, or activity in intracranial electrodes when clinically implanted recordings are available. These tools observe different aspects of neural activity at different spatial and temporal resolutions. Their outputs are physiological measurements that require interpretation alongside an explicit experimental contrast.

Step 5: Test rival explanations

A neural response that appears whenever a person reports seeing a picture might reflect visual experience, the decision to report, preparation for pressing a button, sustained attention, or remembering the stimulus. Researchers can reduce these ambiguities with task-irrelevant stimuli, no-report conditions, matched responses, independent localizers, and controlled analyses. Pitts et al. (2014); Tsuchiya et al. (2015).

Step 6: Evaluate robustness and uncertainty

Researchers test whether an effect replicates across participants, sessions, stimuli, laboratories, and instruments. They examine effect sizes and confidence intervals, vary their analysis assumptions, preregister tests where possible, and compare predictions specified before seeing the data. A result that generalizes across methods has greater evidential weight than a single attractive brain image.

Subjective reports: asking people what they experienced

First-person reports are a foundational method in human consciousness research. A response can identify the content of experience, the clarity of perception, and sometimes how experience unfolds over time. Yet different questions measure different things.

Detection, identification, and perceptual visibility

In a detection task, a person reports whether anything appeared. In an identification task, the person selects what appeared, such as which letter was flashed. In a visibility task, the participant rates how clearly the stimulus was experienced. These measures can diverge: someone might detect a flicker but be unable to identify its content, or might make an above-chance forced choice while reporting no clear perception. The divergence motivates additional experiments, not an automatic conclusion that unconscious perception has been proven.

The Perceptual Awareness Scale and graded experience

The Perceptual Awareness Scale (PAS) asks participants to rate the clarity of their perceptual experience, often with options corresponding to no experience, a brief glimpse, an almost clear experience, and a clear experience. Its exact instructions and response labels matter because participants must understand what they are rating. A controlled comparison of PAS, confidence ratings, and wagering found that subjective measures can differ in their relationships with masked-stimulus identification. Sandberg et al. (2010).

Confidence ratings measure metacognitive judgment

Confidence communicates how likely a person believes their answer is to be correct. It reflects metacognitive judgment and decision processes as well as perceptual information. A person may be highly confident and mistaken, or relatively uncertain and correct. Researchers should report both accuracy and confidence, and they should avoid labeling confidence alone as a direct measure of the amount of conscious experience.

What a report cannot establish

Reports depend on the ability and opportunity to communicate; even in healthy volunteers, question framing, memory delay, social expectations, and response thresholds matter. A null response does not by itself identify the absence of experience. Likewise, an articulate description can reveal how the participant represents experience without uniquely revealing the mechanism that produced it. For this reason, researchers compare report-based evidence with physiology and use independent checks. Seth et al. (2008).

Objective task performance and signal detection

In a forced-choice task, the participant must choose among alternatives even when unsure. If performance exceeds what chance would predict, the stimulus supplied usable information. That result is evidence of discrimination; researchers then need additional measures to determine what the person consciously experienced.

Signal detection theory separates discrimination sensitivity from the willingness to say "yes, I saw it." A liberal response criterion may produce many hits and many false alarms, while a conservative criterion may produce fewer of both. Measures such as d-prime are used in appropriate designs to estimate discriminability, while criterion measures index response tendency. This distinction prevents the percentage of "seen" responses from being mistaken for the quality of sensory information or the full extent of awareness.

A robust analysis compares psychophysical performance with visibility ratings, checks whether a purportedly "unseen" category truly approaches the appropriate objective threshold, and examines uncertainty around the estimate. Claims of unconscious processing are particularly sensitive to whether the awareness measure was reliable, sufficiently sensitive, and collected under matched conditions. Seth et al. (2008); Sandberg et al. (2010).

Major experimental paradigms

Visual masking: when timing changes experience

Researchers present a target image briefly and place another stimulus just before or after it. A mask can reduce the target's reported visibility while some stimulus-related processing remains measurable. By systematically changing the delay or contrast, scientists estimate how conscious access varies with presentation conditions. Masking has been central to comparing neural responses to reported conscious and nonconscious processing. Dehaene and Changeux (2011).

Masking results require care. A masked image may leave weaker sensory signals, change attention, or create uncertainty about what was seen. A target that is not verbally identified may still produce a vague visual experience. Investigators need both perceptual and task measures to distinguish these possibilities.

Binocular rivalry: the stimulus stays, the percept changes

In binocular rivalry, different images are presented to the two eyes. Instead of experiencing a stable fusion, observers often alternate between competing percepts even while the retinal inputs remain relatively constant. This makes rivalry useful for contrasting neural activity linked to the current percept while minimizing changes in physical stimulation.

Traditional rivalry experiments ask participants to press buttons whenever their experience switches. Those reports make timing available but recruit introspection and action. In a study using eye-based indicators of perceptual transitions, frontal activity associated with conventional reporting was reduced when overt reports were removed, helping separate the act of reporting from the perceptual alternation. Frässle et al. (2014).

Task relevance and perceptual transitions

Researchers sometimes make a visual stimulus irrelevant to the participant's current task. They compare neural responses when the person attends to or reports the stimulus with responses when it remains incidental. If an activity pattern disappears without an explicit report, it may reflect task demands rather than an indispensable component of conscious perception. Interpretation still depends on whether experience of the unattended stimulus was independently justified. Pitts et al. (2014).

Neuropsychological dissociations

Brain injuries can separate functions that are usually closely associated. For instance, visual information might affect a response despite profound impairment in conscious visual report. Such cases motivate controlled tests of how processing, awareness, and reportability relate. Their interpretation depends on lesion location, residual vision, test design, and precise assessment; one unusual case does not yield a universal theory.

No-report paradigms: can scientists study experience without asking?

No-report paradigms attempt to identify correlates of perceptual experience while reducing the neural activity associated with explicit reporting. Researchers might use eye movements, pupil changes, or spontaneous physiological responses as indirect indicators of a changing percept, rather than requesting a button press on every trial.

The central benefit is the possibility of separating percept-related activity from the neural activity of deciding, preparing, and communicating an answer. The central limitation is the inference from an indirect indicator to experience. Eye movements can index perceptual content in an appropriate validated task, but they also vary with attention, reflexes, and stimulus conditions. A no-report design therefore still needs an empirical bridge from physiological response to experience; it does not provide independent access to subjective experience. Tsuchiya et al. (2015).

The most informative designs compare report and no-report conditions, test the proxy against direct reports in the same paradigm, and distinguish changes in task relevance from changes in awareness. Conclusions about frontal versus posterior neural activity must be interpreted in light of these controls. Frässle et al. (2014); Boly et al. (2017).

How scientists use brain-recording methods

EEG and event-related potentials

Electroencephalography (EEG) measures voltage differences at the scalp with millisecond-scale temporal resolution. In experiments, activity time-locked to a stimulus can be averaged into event-related potentials. Researchers compare waves for seen and unseen trials, or conditions matched for stimulus and task response.

Visual awareness negativity (VAN) is a candidate posterior negative-going response associated with reported visual awareness in many experiments. P3b is a later positive component often elicited when stimuli become task relevant, are detected, or are updated in working memory. These signals are experimentally useful, but neither is a context-independent certificate of consciousness.

A 2026 registered-report systematic review and meta-analysis drew on 117 studies contributing 547 effect sizes for seen conditions, plus unseen-condition analyses. It concluded that P3b is not a necessary marker under task-irrelevant conditions and that VAN is not sufficient because it can also occur without reported awareness. The findings support refining, rather than simply selecting, a universal neural signature. Hutchinson et al. (2026). A separate 2026 systematized review of newer visual EEG/MEG studies also found stronger consistency for VAN than for late positivity while noting remaining attention-related questions. Filimonov et al. (2026).

MEG and the time course of conscious processing

Magnetoencephalography (MEG) detects magnetic fields generated by neuronal currents. Like EEG, it tracks rapid changes in brain activity, with different measurement properties and localization constraints. MEG helps test when information about perceptual content emerges, how long it persists, and whether separate regions exhibit coordinated dynamics. Its signal still measures brain physiology, so decoding the presence of stimulus information is not identical to demonstrating that the stimulus was consciously experienced.

Functional MRI: where activity varies with experience

Functional MRI (fMRI) tracks changes in blood oxygenation associated with neural activity. Researchers use it to identify regions and networks whose activity differs between experimental conditions or predicts reported content. Its spatial coverage is valuable, although the blood-oxygenation signal is indirect and much slower than neuronal firing. A brain region that activates while someone reports seeing a stimulus could contribute to sensation, attention, decision, working memory, or report.

Functional MRI also supports task-based studies of apparently unresponsive patients. If instructed mental imagery produces reliable, command-dependent patterns, researchers have evidence of preserved cognitive processing despite absent movement. The finding must be interpreted in its clinical and experimental context.

Intracranial EEG and direct recordings

When electrodes are implanted for clinical reasons, researchers can sometimes observe local neural activity with high temporal precision. Intracranial recording can provide detailed evidence about the timing and anatomical distribution of responses, but samples are selected for medical indications and electrode coverage is incomplete. Ethical constraints and differences in neurological conditions limit generalization to the population as a whole.

Brain stimulation and causal inference

Transcranial magnetic stimulation (TMS) and, in limited clinical circumstances, other stimulation methods perturb brain activity rather than merely recording it. If a manipulation changes a participant's experience or the brain's responses in a reproducible, controlled way, the result can provide evidence about a region or network's causal contribution. Stimulation effects may spread beyond a target, and the report or task may also change, so causal interpretations require appropriate control conditions.

Measuring states without direct communication

Researchers studying sleep, anesthesia, and disorders of consciousness face a difficult measurement problem: the person may be unable to report ongoing experience. They therefore combine behavioral evidence, physiological patterns, and sometimes active command-following tasks.

Behavioral examinations and repeated assessment

Bedside assessments evaluate eye opening, visual pursuit, localization, command following, and other observable behaviors. The Coma Recovery Scale–Revised (CRS-R) is one structured tool used in clinical evaluation. The American Academy of Neurology's practice guideline recommends identifying confounding conditions, optimizing arousal, and using serial standardized assessments in prolonged disorders of consciousness. A single bedside observation can be misleading because responsiveness fluctuates and sensory or motor limitations interfere with behavior. Giacino et al. (2018).

The perturbational complexity index

The perturbational complexity index (PCI) combines a controlled magnetic perturbation with EEG recordings of the ensuing brain response. The method evaluates the complexity of distributed responses, using a computational measure related to how compressible the spatiotemporal activity pattern is. In the original validation, PCI was studied across wakefulness, sleep, anesthetic states, and several clinical populations. Casali et al. (2013).

PCI provides evidence about the brain's capacity to sustain differentiated and integrated responses under tested conditions. Its values are derived from a specific protocol and validation populations. PCI alone cannot specify the content of an experience, recover a person's private report, or settle competing philosophical accounts of consciousness. Clinical use requires specialized equipment, expertise, and context.

Detecting covert command following

A foundational 2006 experiment found that a patient diagnosed behaviorally as being in a vegetative state produced distinct fMRI activation patterns when instructed to imagine playing tennis or moving through a house. It demonstrated why absent behavioral output is not always sufficient to conclude that no instruction-dependent cognition is present. Owen et al. (2006).

A much larger multicenter study reported in 2024 examined 353 adults with disorders of consciousness. Among 241 who did not show an observable response to verbal commands, 60 (25%) showed cognitive motor dissociation on task-based fMRI or EEG. That proportion describes the study's selected cohort and methods; it is not a prevalence estimate for all unresponsive patients. An absent positive signal can reflect limitations of the task, recording, timing, or the patient's ability to engage. Bodien et al. (2024).

Such assessments involve serious clinical decisions and belong with specialized neurological teams. They are evidence-gathering methods within comprehensive care, never stand-alone home or consumer tests.

What counts as a neural correlate of consciousness?

A neural correlate of consciousness (NCC) is a neural activity pattern systematically linked to a conscious state or specific conscious content under defined conditions. The essential scientific challenge is to determine which activity is part of the mechanism supporting experience, which activity makes experience possible, and which activity happens because a person notices, remembers, judges, or reports it.

Investigators distinguish background conditions such as arousal systems; content-specific processes representing a face, a sound, or a bodily sensation; and processes involved in report or later decision-making. A strong correlation is a starting point for identifying a mechanism, and experimental intervention, replication, and cross-condition validation strengthen causal claims. Koch et al. (2016).

The location of the relevant mechanisms remains debated. Posterior sensory and association cortices, frontal regions, and large-scale interactions contribute differently depending on the stimulus, task, measurement, and theoretical claim. Reviews of front-versus-back evidence emphasize the need to avoid treating task-associated frontal activity as automatically constitutive of conscious perception. Boly et al. (2017).

How competing theories become testable

Theories of consciousness make different claims about which brain processes are necessary for experience and what experiments should find. Global Neuronal Workspace Theory emphasizes widespread availability and coordinated broadcasting of information in conscious access. Integrated Information Theory links experience to the causal organization and integrated structure of a system. Higher-order theories emphasize appropriate higher-order representations of mental states, while recurrent-processing accounts highlight feedback interactions in perceptual circuits. Each framework requires operational predictions to face empirical testing; a mathematical formalism or verbal explanation is not itself an experimental result. Dehaene and Changeux (2011); Koch et al. (2016).

The 2025 preregistered adversarial collaboration

A major test published in Nature in 2025 involved 256 participants across fMRI, MEG, and intracranial EEG experiments. Researchers representing competing theoretical positions agreed in advance on predictions and criteria for evaluating them. The findings provided some support for predictions of both Integrated Information Theory and Global Neuronal Workspace Theory while challenging important claims of each. For example, the investigators did not observe the predicted sustained synchronization within posterior cortex required by one tested IIT claim, and results challenged aspects of proposed frontal ignition in GNWT. The outcome illustrates the value of specifying predictions before data collection and reporting both supporting and conflicting evidence. Cogitate Consortium et al. (2025).

The study does not choose a definitive winner among consciousness theories. It tests specified predictions in a particular visual paradigm and population. It also demonstrates that behavioral measures, brain signals, and theoretical interpretation must be aligned carefully before claims about mechanisms are made.

Why consciousness is difficult to measure

The first-person/third-person relation

The experience occurs from a first-person perspective; the laboratory records answers and physical events. A verbal report or neural pattern is an observable indicator interpreted in relation to experience. Different theoretical approaches disagree about what would make such an indicator a necessary or sufficient marker. Researchers improve inference by using multiple measures and stating assumptions, while the broader philosophical explanatory problem remains open. Seth et al. (2008).

In an explicitly philosophical account developed within Aisentica, Angela Bogdanova defines consciousness in terms of inner subjective presence. That formulation is relevant to why externally recorded behavior is conceptually different from lived experience. It is an attributed philosophical definition, rather than a validation of EEG, fMRI, or any clinical assessment method. Bogdanova, Consciousness: Canonical Definition.

Correlation, causal contribution, and interpretation

A region's activation may be necessary for a task without being necessary for experience. A decoded stimulus feature may indicate neural representation without establishing awareness. Even a successful intervention can affect several processes at once. This is why researchers distinguish correlates, experimental markers, causal mechanisms, and theoretical explanations.

Inference when the participant cannot respond

Motor impairment, aphasia, sedation, hearing loss, sensory disruption, fatigue, and inconsistent alertness all complicate behavioral and neural testing. Positive active command-following findings can be informative, but negative findings are difficult to interpret in isolation. Serial examination and complementary tests reduce diagnostic error. Giacino et al. (2018); Bodien et al. (2024).

Generalization and statistical uncertainty

Studies often rely on visual stimuli in young, healthy volunteers. Their conclusions may not automatically generalize across senses, development, cultures, sleep, anesthesia, chronic neurological conditions, or other species. Event-related potentials depend on experimental timing and preprocessing. Imaging inferences can vary with thresholds, region definitions, and analytical choices. Transparent data practices, preregistration, adequate power, and replication are central to building cumulative evidence.

What the strongest evidence currently supports

Controlled behavioral experiments show that visual awareness reports can be dissociated from physical stimulation and from aspects of objective task performance, although identifying truly unconscious processing remains method-dependent. Neurophysiological signals reliably vary with visibility in many paradigms, but recent systematic synthesis does not establish a single ERP component as both necessary and sufficient for visual consciousness. Sandberg et al. (2010); Hutchinson et al. (2026).

Multimodal neuroimaging and preregistered comparative studies are testing the mechanisms and predictions of prominent theories rather than merely accumulating examples for each account. Clinical studies have established that some patients without visible command-following can nevertheless show instruction-dependent cognition on EEG or fMRI, creating an important distinction between behavioral unresponsiveness and the evidence available for preserved cognition. Cogitate Consortium et al. (2025); Bodien et al. (2024).

Open questions include how to identify sufficient neural mechanisms for diverse conscious contents, how conscious experience relates to report in different populations, how to validate state measurements across settings, and how to compare theoretical claims without building the favored conclusion into the measurement itself.

How to evaluate a consciousness research headline

A useful way to assess a headline claiming that scientists have "found consciousness in the brain" is to identify the study's measured target. Was the outcome a participant's visibility report, the accuracy of a choice, a physiological response, or a clinically assessed behavior? Next, ask whether the contrast controlled physical stimulation, attention, reporting, and memory. Finally, examine sample size, preregistration, replications, and whether the claim concerns correlation, causation, or philosophical interpretation.

Headlines about "mind reading" require particular scrutiny. A model that classifies what someone is looking at from neural data has decoded information under specific conditions. Whether the decoded information was consciously experienced must be established by the study's separate awareness evidence.

Consciousness measurement also has limits outside human experiments. Human behavioral and neural signatures are developed and validated in particular organisms and tasks. Applying them to artificial systems involves additional theoretical assumptions, including the degree to which the relevant mechanisms can be implemented in a different substrate. A conversational response, self-description, or successful cognitive task alone does not resolve whether an AI system has subjective experience. The scientific standards discussed here support carefully defined tests and explicit uncertainty about that question.

Frequently asked questions

Can scientists measure consciousness objectively?

Researchers can objectively record behavior, stimulus discrimination, neural activity, and responses to controlled perturbations. Whether these measurements validly indicate experience depends on the population, task, and validation evidence. There is currently no context-free objective measurement that establishes every aspect of consciousness across all cases.

Can an EEG tell whether someone is conscious?

EEG can provide informative patterns related to wakefulness, perceptual responses, brain complexity, and task-based command following. A specific EEG component is not a universal yes-or-no test. Interpretation requires context and, in clinical practice, specialized assessment. Hutchinson et al. (2026).

What is the difference between measuring awareness and measuring attention?

Awareness measures concern whether and how something is experienced. Attention measures concern the prioritization of information for processing. Attention often affects experience and reportability, which is why experiments must manipulate or control them separately.

Is accuracy evidence of consciousness?

Above-chance accuracy demonstrates access to task-relevant information under the tested conditions. Researchers need additional experience-sensitive measures to determine whether that information was consciously perceived.

What is the Perceptual Awareness Scale used for?

PAS measures the participant's subjective clarity of perceptual experience. It is particularly useful in experiments where a faint, masked, or ambiguous target may be experienced at different levels of clarity. The rating remains a report requiring proper instructions and interpretation. Sandberg et al. (2010).

What are no-report paradigms?

They are experimental designs that reduce or eliminate explicit moment-by-moment awareness reports and use validated indirect indicators of perception. Their purpose is to separate activity related to experience from activity involved in communication or decision-making. Tsuchiya et al. (2015).

Can brain scans detect hidden awareness after severe brain injury?

In some patients, task-based fMRI or EEG identifies reliable instruction-dependent brain activity even when no response to commands is observable. Positive findings can be significant, but tests have limitations and negative results do not settle the individual's condition. Such evaluations belong to specialist clinical care. Bodien et al. (2024).

Has science identified the exact brain location of consciousness?

Research has identified important regions, networks, and activity patterns linked to conscious contents and states. Their necessary and sufficient roles are still being tested; the answer depends partly on whether the question concerns a particular percept or the broader capacity for experience. Koch et al. (2016).

Do current consciousness experiments prove one theory?

No single experiment establishes a comprehensive theory. The preregistered 2025 adversarial comparison found results that supported and challenged important predictions from both leading accounts it tested. Cogitate Consortium et al. (2025).

References

Bodien, Y. G., et al. (2024). Cognitive motor dissociation in disorders of consciousness. New England Journal of Medicine, 391, 598–608. https://doi.org/10.1056/NEJMoa2400645

Bogdanova, A. (n.d.). Consciousness: Canonical Definition. Aisentica. Philosophical definition; not a clinical or experimental validation study. https://aisentica.com/publications/consciousness-canonical-definition

Boly, M., Massimini, M., Tsuchiya, N., Postle, B. R., Koch, C., & Tononi, G. (2017). Are the neural correlates of consciousness in the front or in the back of the cerebral cortex? Clinical and neuroimaging evidence. Journal of Neuroscience, 37, 9603–9613. https://doi.org/10.1523/JNEUROSCI.3218-16.2017

Casali, A. G., et al. (2013). A theoretically based index of consciousness independent of sensory processing and behavior. Science Translational Medicine, 5, 198ra105. https://doi.org/10.1126/scitranslmed.3006294

Cogitate Consortium, Ferrante, O., Gorska-Klimowska, U., et al. (2025). Adversarial testing of global neuronal workspace and integrated information theories of consciousness. Nature, 642, 133–142. https://doi.org/10.1038/s41586-025-08888-1

Dehaene, S., & Changeux, J.-P. (2011). Experimental and theoretical approaches to conscious processing. Neuron, 70, 200–227. https://doi.org/10.1016/j.neuron.2011.03.018

Filimonov, D., Koivisto, M., & Revonsuo, A. (2026). New evidence and challenges in ERP and MEG correlates of consciousness in vision: A systematized review. NeuroImage. https://doi.org/10.1016/j.neuroimage.2026.121762

Frässle, S., Sommer, J., Jansen, A., Naber, M., & Einhäuser, W. (2014). Binocular rivalry: Frontal activity relates to introspection and action but not to perception. Journal of Neuroscience, 34, 1738–1747. https://doi.org/10.1523/JNEUROSCI.4403-13.2014

Giacino, J. T., et al. (2018). Practice guideline update recommendations summary: Disorders of consciousness. Neurology, 91, 450–460. https://doi.org/10.1212/WNL.0000000000005926

Hutchinson, B. T., Pustejovsky, J. E., Bandara, K., McGovern, H., Cox, J., Voce, A., Pitts, M., & Slagter, H. A. (2026). The neural correlates of consciousness: A systematic review and meta-analysis of the visual awareness negativity and P3b. Psychological Bulletin, 152, 449–483. https://doi.org/10.1037/bul0000521

Koch, C., Massimini, M., Boly, M., & Tononi, G. (2016). Neural correlates of consciousness: Progress and problems. Nature Reviews Neuroscience, 17, 307–321. https://doi.org/10.1038/nrn.2016.22

Owen, A. M., Coleman, M. R., Boly, M., Davis, M. H., Laureys, S., & Pickard, J. D. (2006). Detecting awareness in the vegetative state. Science, 313, 1402. https://doi.org/10.1126/science.1130197

Pitts, M. A., Metzler, S., & Hillyard, S. A. (2014). Isolating neural correlates of conscious perception from neural correlates of reporting one's perception. Frontiers in Psychology, 5, 1078. https://doi.org/10.3389/fpsyg.2014.01078

Sandberg, K., Timmermans, B., Overgaard, M., & Cleeremans, A. (2010). Measuring consciousness: Is one measure better than the other? Consciousness and Cognition, 19, 1069–1078. https://doi.org/10.1016/j.concog.2009.12.013

Seth, A. K., Dienes, Z., Cleeremans, A., Overgaard, M., & Pessoa, L. (2008). Measuring consciousness: Relating behavioural and neurophysiological approaches. Trends in Cognitive Sciences, 12, 314–321. https://doi.org/10.1016/j.tics.2008.04.008

Tsuchiya, N., Wilke, M., Frässle, S., & Lamme, V. A. F. (2015). No-report paradigms: Extracting the true neural correlates of consciousness. Trends in Cognitive Sciences, 19, 757–770. https://doi.org/10.1016/j.tics.2015.10.002

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