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Neuroscience of Consciousness

ISSN 2057-2107

158 papers in the library · 2,675 citations · publishing 2015-2026

Papers

Stroboscopically induced visual hallucinations: historical, phenomenological, and neurobiological perspectives.

Neuroscience of Consciousness January 1, 2025 Trevor Hewitt, Ioanna Amaya, Romy Beauté et al.

Exposure to rapid, bright stroboscopic light has been known for over 200 years to induce vivid visual hallucinations of color and geometric shapes. This narrative review summarizes the history of research on stroboscopic light stimulation (SLS), its recreational and lay-therapeutic uses, the phenomenology of the experiences it produces, and current understanding of potential neural mechanisms. Despite progress, fundamental questions remain about the full characterization of its phenomenology, its precise physiological origins, the conditions under which it leads to altered states of consciousness, and possible clinical applications.

Neural correlates of unconscious processing in functional magnetic resonance imaging: does brain activity contain more information than can be consciously reported?

Neuroscience of Consciousness January 1, 2025 Joaquim Streicher, Sascha Meyen, Volker H Franz et al.

A common method for studying unconscious processing compares participants' ability to consciously detect a stimulus with an indirect measure of processing, such as reaction time or brain activity. If the direct measure shows no awareness but the indirect measure shows a significant effect, researchers conclude the stimulus was processed unconsciously. However, this reasoning rests on a statistical fallacy: the sensitivities of the two measures are never directly compared. Reanalyzing 80 experimental conditions from 16 fMRI studies, only eight provided evidence for unconscious processing when sensitivities were properly compared. This suggests that the scope of unconscious processing—both its capacity and the brain areas involved—has been overestimated.

Qualia structures collapse for geometric shapes, but not faces, when spatial attention is withdrawn.

Neuroscience of Consciousness January 1, 2025 Elise G Rowe, Ken Takeda, Masafumi Oizumi et al.

Top-down attention affects not just whether we see something, but how we see it—the quality of conscious experience, or qualia. Using a dual-task paradigm, participants rated similarity of stimulus pairs in the periphery for rotated letters, bisected disks, and greyscale faces. Similarity ratings served as a proxy for qualia structures, analyzed with dimension reduction and optimal transport alignment. Attention withdrawal collapsed qualia structures for letters and disks, but alignment accuracy remained high for face qualia structures under both full and poor attention. This relational judgment approach extends previous binary categorization methods and offers a novel way to study qualia structures.

Meta-representations as representations of processes.

Neuroscience of Consciousness January 1, 2025 Ryota Kanai, Ryota Takatsuki, Ippei Fujisawa

A refined computational interpretation of meta-representations in higher-order theories (HOT) of consciousness is proposed, focusing on process-level representations rather than mere transformations of first-order states. Meta-representations are argued to represent the computational processes that generate first-order representations, building on the Radical Plasticity Thesis. As a proof-of-concept, "meta-networks" were constructed using autoencoders of first-order neural networks within deep learning architectures, where latent spaces embedding first-order networks correspond to meta-representations. Applied to neural networks trained on visual and auditory datasets, these meta-representations successfully captured qualitative aspects by separating visual and auditory networks in the meta-representation space. This formulation offers an empirically testable hypothesis that brain regions may represent processes transforming one representation into another, potentially underlying the ability to describe qualia.

Content–state dimensions characterize different types of neuronal markers of consciousness

Neuroscience of Consciousness July 12, 2024 P. Pérez, D. Manasova, B. Hermann et al.

A framework is introduced that characterizes neuronal markers of consciousness along two dimensions: how well they distinguish conscious from non-conscious states (x-axis) and how well they distinguish different conscious contents (y-axis). Using electroencephalography markers of connectivity, complexity, and spectral summaries, the framework is applied to healthy participants during a nap and patients with disorders of consciousness for the state dimension, and to healthy participants in visual awareness and auditory local-global paradigms for the content dimension. Separate clusters of markers with correlated and anticorrelated dynamics emerge, highlighting the complex relationship between the state and content of consciousness and the need to consider them together.

A novel model of divergent predictive perception

Neuroscience of Consciousness February 12, 2024 Reshanne R Reeder, Giovanni Sala, Tessa M Van Leeuwen

A novel theoretical model proposes that divergent experiences like hallucinations and synaesthesia arise from an imbalance between reliance on prior knowledge and sensory confidence. Maladaptive high-level priors (beliefs) with low sensory confidence can cause reality discrimination issues (psychosis), while maladaptive low-level priors (sensory expectations) with high sensory confidence can cause atypical sensory sensitivities (synaesthesia). Mental imagery ability, ranging from aphantasia to hyperphantasia, determines whether these experiences manifest with sensory or nonsensory characteristics. The model predicts that three factors—maladaptive priors, sensory confidence, and imagery ability—must be accounted for to predict divergent perceptual experiences in clinical and general populations.

Where is the ghost in the shell?

Neuroscience of Consciousness January 1, 2024 Veith Weilnhammer

New evidence shows that applying transcranial magnetic stimulation to the parietal cortex does not alter bistable perception, challenging some theories about the neural correlates of consciousness. This finding suggests that the parietal cortex may not be directly involved in generating conscious perceptual switches, prompting a reconsideration of where and how to search for the brain mechanisms underlying conscious experience.

Tracking rivalry with neural rhythms: multivariate SSVEPs reveal perception during binocular rivalry.

Neuroscience of Consciousness January 1, 2024 Ruben Laukkonen, Evan Lewis-Healey, Luca Ghigliotti et al.

A novel multivariate spatial filter called Rhythmic Entrainment Source Separation can extract steady-state visual evoked potentials from EEG data to quantify perceptual switch rates during binocular rivalry without requiring self-reports. This method may be valuable for studying consciousness in contexts where self-reports are problematic or impossible. The analyses also indicate that no-report conditions may affect attention deployment and thereby neural correlates, an important consideration for consciousness research.

The influence of feature-based attention and response requirements on ERP correlates of auditory awareness.

Neuroscience of Consciousness January 1, 2024 Dmitri Filimonov, Andreas Krabbe, Antti Revonsuo et al.

Aware auditory experiences are linked to a specific brain signal, the auditory awareness negativity (AAN), which remains unchanged whether listeners pay attention to sounds or must respond to them. In contrast, a later brain signal, the late positivity (LP), is influenced by both attention and the requirement to respond. These findings suggest that AAN is a genuine neural correlate of auditory consciousness, while LP reflects higher-level processing that may depend on a global workspace.

Toward a universal theory of consciousness

Neuroscience of Consciousness January 1, 2024 Ryota Kanai, Ippei Fujisawa

The paper introduces 'Universality' as a desirable property for theories of consciousness, borrowed from physics, where fundamental laws apply consistently everywhere. Universality requires that a theory can determine whether any fully described dynamical system is conscious or non-conscious, based on intrinsic properties rather than external interpretation. Most current theories lack this property, as they focus on neural correlates of consciousness in brain-centric systems. The authors argue that functionalist theories could become universal by specifying mathematical formulations of their concepts. While neurobiological and functionalist theories remain useful, a universal theory is needed to fully explain why certain systems possess consciousness.

The exclusionary approach to consciousness

Neuroscience of Consciousness October 5, 2023 Marlo Paßler

An alternative method for studying the neural correlates of consciousness (NCCs) is proposed, called the exclusionary approach. Instead of comparing conscious and unconscious trials near the threshold of perception, this approach relies on the assumption that subjective reports are reliable under normal conditions. By keeping consciousness stable while manipulating other factors like reports, tasks, stimulation, or attention, researchers can exclude certain neural activities as candidate NCCs. This yields less contentious results and provides hard criteria for theories of consciousness. The approach does not require new paradigms but can incorporate existing studies. It complements, rather than replaces, the standard identification approach.

Piecing together the puzzle of emotional consciousness

Neuroscience of Consciousness January 1, 2023 Tahnée Engelen, R. Mennella

The paper presents a balanced overview of cognitive and precognitive approaches to emotional consciousness, examining how different theories explain the experiential quality of feeling an emotion. It reviews the evidence supporting these theories, noting methodological challenges unique to studying emotional consciousness and what can be learned from research on perceptual consciousness. The authors identify three key experimental contrasts necessary for investigating neural correlates of emotional consciousness, each with its own limitations. They conclude by highlighting promising avenues that may help overcome current impasses and advance collaborative understanding of emotional consciousness.

Separating weak integrated information theory into inspired and aspirational approaches.

Neuroscience of Consciousness January 1, 2023 Angus Leung, Naotsugu Tsuchiya

A commentary on Mediano et al.'s distinction between strong and weak versions of integrated information theory (IIT) argues that the category of weak IIT is too broad. The authors propose splitting it into 'aspirational-IIT', which seeks to empirically test IIT by compromising on its proposed measures, and 'IIT-inspired' approaches, which borrow high-level concepts from IIT while discarding the mathematical framework derived from its introspective, first-principles method. This sharper taxonomy clarifies how different research programs relate to IIT's core commitments.

On the non-uniqueness problem in integrated information theory.

Neuroscience of Consciousness January 1, 2023 Jake R. Hanson, Sara I. Walker

Integrated Information Theory (IIT) 3.0, a leading theory of consciousness, defines a mathematical measure Φ meant to quantify consciousness. This work demonstrates that Φ is not well-defined because its value is non-unique. An algorithm that computes all possible Φ values for a given system, strictly following the theory's definition, reveals that published Φ values are arbitrarily selected from many equally valid alternatives. Crucially, both high and low Φ values can be predicted simultaneously for the same system, making it impossible to decide whether that system is conscious under the current formulation of IIT.

Towards causal mechanisms of consciousness through focused transcranial brain stimulation

Neuroscience of Consciousness January 1, 2023 Marek Havlík, J. Hlinka, M. Klírová et al.

The science of consciousness has largely relied on identifying neural correlates of conscious experience, but this approach has not yet yielded a mechanistic understanding. Advances in brain stimulation techniques, such as geodesic transcranial electric neuromodulation, now make it possible to move beyond correlation and toward causal explanations. By directly altering neural activity, researchers can test hypotheses about the mechanisms that generate conscious states, overcoming the limitations of purely observational methods. This shift promises to advance the empirical study of consciousness.

When do parts form wholes? Integrated information as the restriction on mereological composition.

Neuroscience of Consciousness January 1, 2023 Kelvin J. McQueen, Naotsugu Tsuchiya

The composition question asks under what conditions material objects form a whole. Existing answers are either vague or face counterexamples, leading many philosophers to accept that composition either never occurs or always occurs. This paper introduces integrated information theory (IIT), a theory of consciousness, and argues that it provides a precise, non-trivial answer: composition occurs when integrated information is maximized. The IIT restriction avoids the problems of vagueness and counterexamples that plague other proposals. An appendix explains how to calculate parts and wholes using a simple system.

About the compatibility between the perturbational complexity index and the global neuronal workspace theory of consciousness

Neuroscience of Consciousness January 1, 2023 M. Farisco, J. Changeux

The global neuronal workspace theory (GNWT) and the perturbational complexity index (PCI) are largely compatible frameworks for understanding conscious processing. GNWT holds that consciousness depends on long-range connections between cortical regions, enabling amplification, global propagation, and integration of brain signals. PCI, though developed within integrated information theory, aligns with this core idea. Some limited incompatibilities and apparent differences exist, but the paper concludes the two are fundamentally compatible, with certain points requiring further examination.

Time-consciousness in computational phenomenology: a temporal analysis of active inference

Neuroscience of Consciousness January 1, 2023 Juan Diego Bogotá, Z. Djebbara

Time is central to both science and daily life, yet computational models of consciousness usually treat time as a sequence, not a continuous flow. This creates a problem for computational phenomenology, which combines phenomenology with computational modeling. By analyzing the active inference framework's temporal structure, the authors show that an integrated continuity of time can be achieved by merging Husserlian temporality with sequential time. A Markov blanket of the present moment integrates past and future moments of both subjective temporality and objective time asynchronously. The authors conclude that active inference qualifies as a computational model for phenomenological investigations regarding time.

The Self-Simulational Theory of temporal extension.

Neuroscience of Consciousness January 1, 2023 Jan Erik Bellingrath

Subjective experience always unfolds in time, but it also includes a sense of the immediate past and future, forming what William James called the 'specious present.' This paper proposes a new theory—the Self-Simulational Theory of temporal extension—which explains how the subjective experience of a temporal 'now' arises from a difference between actual and counterfactual self-representations. The theory is presented conceptually and formalized using information theory in a neuronally realistic framework. Convergent evidence from studies of temporal experience, altered states of consciousness, and mental illness supports the theory, which can account for systematic variations in how long the present moment feels across different conditions. The work has implications for the neuroscience of consciousness and understanding mental illness.

The functions of consciousness in visual processing

Neuroscience of Consciousness January 1, 2023 Dylan Ludwig

Consciousness contributes a cluster of functions to visual processing, including increased capacities for semantically processing complex visual stimuli, increased spatiotemporal precision, and increased capacities for representational integration over large spatiotemporal intervals. This position, called functional pluralism, argues that consciousness occupies a variety of different functional roles across different task domains, individuals, and species. The analysis consolidates research from across the cognitive sciences to compare visual system capabilities with and without conscious awareness, yielding functional markers that may guide future research in philosophy and science of consciousness, some of which are not captured by global workspace theory or information integration theory.

Toward the unknown: consciousness and pain

Neuroscience of Consciousness January 1, 2023 R. Ambron

Pain is a conscious sensation that can be studied more tractably than general consciousness. Three neural systems are required: the somatosensory system relays injury information to the thalamus, where awareness of injury arises without painfulness; the affective system modulates pain intensity; and the cognitive system directs attention. Imaging reveals two essential cortical circuits for pain and attention in the anterior cingulate cortex, activated when high-frequency input induces long-term potentiation at synapses on pyramidal neuron apical dendrites, involving AMPA and NMDA receptors and type-1 adenylate cyclase. The apical dendrites form a network where serious injury input produces a local field potential. The author proposes experiments in mouse models to test whether this local field potential is necessary and sufficient for pain consciousness.

Determining states of consciousness in the electroencephalogram based on spectral, complexity, and criticality features

Neuroscience of Consciousness April 1, 2022 Nike Walter, T. Hinterberger

Meditation states produce distinct patterns of brain activity measurable by nonlinear complexity and critical dynamics. Highly proficient meditators were measured with EEG during three meditation conditions (thoughtless emptiness, presence monitoring, focused attention) and compared to resting and reading. Compared to eyes-closed rest, emptiness and focused attention showed higher entropy and fractal dimension, while long-range temporal correlations decreased across all meditation conditions. The critical exponent was lowest for focused attention and reading. Gamma-band activity, global power spectral density, and sample entropy best discriminated among states (accuracy 0.83–0.98, 0.78–0.96, and 0.86–0.90 respectively). Meditation states can be quantified by neuronal complexity, long-range temporal correlations, and power law distributions in neuronal avalanches.

Consciousness explained or described?

Neuroscience of Consciousness January 21, 2022 Aaron Schurger, M. Graziano

Consciousness is inherently subjective, making it difficult to study with objective scientific methods. The search for neural correlates of consciousness (NCCs) has been a productive workaround, focusing on brain activity reliably linked to conscious experience. However, this approach was never meant to explain consciousness, only to sidestep the challenge. The authors argue that most modern accounts of consciousness are not true theories but rather laws that describe what they cannot explain, analogous to Newton's description of gravity. They contend that attention schema theory is an exception, qualifying as an explanatory theory that goes beyond mere description.

Does integrated information theory make testable predictions about the role of silent neurons in consciousness?

Neuroscience of Consciousness January 1, 2022 Gary Bartlett

Tononi et al.'s integrated information theory of consciousness claims that conscious experiences are generated by both active and inactive neurons, leading to two startling predictions: disabling already inactive neurons can alter a subject's conscious experience, and a subject with a completely silent brain (all neurons inactive but not disabled) can still have a conscious experience. This article argues that neither prediction is testable. After clarifying the distinction between active, inactive (silent), and inactivated (disabled) neurons, the author shows that even ignoring practical difficulties, any test would be set up under conditions where a subject's response could not reasonably be interpreted as evidence of consciousness or a change in consciousness.