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Andrew M. Haun

12 papers in the library · 341 citations · publishing 2017-2026

Papers

Why Does Space Feel the Way it Does? Towards a Principled Account of Spatial Experience

Entropy November 27, 2019 Andrew M. Haun, Giulio Tononi 158 citations

Experience feels the way it does for a reason, and spatial experience offers a promising starting point for investigation because it is more accessible to introspection than qualities like color or pain. Much of experience is spatial, from bodily sensations to the visual world, which appears as an extended canvas. To feel extended, this canvas must consist of countless spots related through connection, fusion, and inclusion, with each spot having a location, size, boundary, and distance from others. The authors propose an account based on integrated information theory (IIT), showing that a simulated grid-like network of units yields a cause-effect structure that explains main properties of spatial experience. This suggests spatial experience is supported by brain areas with grid-like connectivity, and changes in connectivity should warp experienced space.

Are we underestimating the richness of visual experience?

Neuroscience of Consciousness January 1, 2017 Andrew M. Haun, Giulio Tononi, Christof Koch et al. 97 citations

Some researchers claim that perceptual experience is impoverished—that people perceive and remember very little visual information. However, the evidence indicates that this view is mistaken and that visual phenomenology is actually immensely rich. To accurately assess perceptual content, experiments should go beyond simple binary forced-choice tasks and instead analyze broader reports of experience. Adopting such methods will reveal the genuine richness of experience and its underlying neural basis.

Consciousness and the fallacy of misplaced objectivity.

Neuroscience of Consciousness January 1, 2021 Francesco Ellia, Jeremiah Hendren, Matteo Grasso et al. 61 citations

Subjective experience can be objectively explained in physical terms by moving beyond cognitive functions and understanding how experience is structured. Integrated information theory provides a framework to account for both the essential properties of every experience and the specific properties that make particular experiences feel the way they do, avoiding the fallacy that only objective properties should be explained by science.

Of maps and grids.

Neuroscience of Consciousness January 1, 2021 Matteo Grasso, Andrew M. Haun, Giulio Tononi 20 citations

A grid-like neural network representing posterior cortical areas can perform the same fixation function as a map-like pretectal circuit, but only the grid-like network's cause-effect structure, as analyzed by Integrated Information Theory, accounts for the subjective experience of space as extended. Standard functional analysis explains what the model does—encoding, decoding, and triggering eye movements—but cannot explain why a human fixating a stimulus would also see it at a location. The map-like network, lacking lateral connections, is functionally equivalent yet cannot account for the phenomenal properties of space.

The unfathomable richness of seeing.

Trends in Cognitive Sciences July 3, 2025 Andrew M. Haun, Giulio Tononi 5 citations

Visual experience is unfathomably rich, not sparse. Seeing involves three levels: high-level object and scene categorizations, mid-level feature groupings, and a fundamental spatial field of spots and their relations. Seeing objects requires seeing the groupings that compose them, and seeing groupings requires seeing the spatial field that grounds them. Even the basic feeling of spatial extendedness implies rich phenomenal structure. Much of what we see cannot be used, reported, or remembered, yet we see it.

Integrated information and predictive processing theories of consciousness: An adversarial collaborative review.

Neuroscience and Biobehavioral Reviews August 1, 2026 Andrew W. Corcoran, Andrew M. Haun, Reinder Dorman et al.

Three theories of consciousness—Integrated Information Theory, Neurorepresentationalism, and Active Inference—are compared and contrasted in a structured adversarial collaboration. The review presents each theory's core claims, the phenomena they explain, their explanatory approaches, and methodological strategies. It outlines key hypotheses to be tested across multi-site experiments, discusses observations that would support or challenge each theory, and describes how data from disparate experiments can be formally integrated to quantify evidential support. The work also provides meta-scientific insights into the mechanics of adversarial collaboration and theory-testing, including how theories may be evaluated by the scientific progress they deliver.

Protocol for investigating the warping of spatial experience across the blind spot to contrast predictions of the Integrated Information Theory and Predictive Processing accounts of consciousness.

PLoS One January 1, 2026 Clement Abbatecola, Bernard Marius ’t Hart, Belén M. Montabes De la Cruz et al.

The subjective experience of space around the visual blind spot is investigated to test three theories of consciousness: Integrated Information Theory (IIT), Predictive Processing Active Inference (AI), and Predictive Processing Neurorepresentationalism (NREP). IIT predicts that the blind spot region, lacking feedforward input from one eye, should contribute differently to perceived spatial quality. The Predictive Processing accounts argue that internal models accommodate structural deviations based on sensory evidence. Participants evaluate distances, areas, and illusory motion with or without the blind spot involved. Psychometric models quantify bias and precision in perceived versus objective space. Simulated results correspond to each theory's predictions, and challenges for dissemination are discussed.

Integrated information and predictive processing theories of consciousness: An adversarial collaborative review

arXiv Preprint Archive August 30, 2025 Andrew W. Corcoran, Andrew M. Haun, Reinder Dorman et al.

Three major theories of consciousness—Integrated Information Theory, Neurorepresentationalism, and Active Inference—are compared and contrasted in the context of a structured adversarial collaboration designed to test their competing predictions. The review presents each theory's core claims, the phenomena they explain, their explanatory styles, and methodological strategies. It outlines key hypotheses to be tested across multi-site experiments, discusses observations that would support or challenge each theory, and describes how data from disparate experiments can be formally integrated to provide a quantitative measure of evidential support. The work also offers meta-scientific insights into adversarial collaboration and theory-testing.

More than just front or back: Parietal-striatal-thalamic circuits predict consciousness level

bioRxiv Preprint Server April 7, 2020 Mohsen Afrasiabi, Michelle J. Redinbaugh, Jessica M. Phillips et al. preprint

Simultaneous recordings from frontal, parietal, striatal, and thalamic regions in macaques during wakefulness, sleep, and anesthesia, along with deep-brain thalamic stimulation, show that parietal cortex, striatum, and thalamus contribute more to the level of consciousness than frontal cortex. This supports Integrated Information Theory over Global Neuronal Workspace Theory and Higher-order Theories, but Integrated Information Theory does not account for subcortical structures like the striatum. The authors propose that thalamo-striatal circuits have a cause-effect structure that generates integrated information.

Conscious Perception as Integrated Information Patterns in Human Electrocorticography.

eNeuro January 1, 2017 Andrew M. Haun, Masafumi Oizumi, Christopher K Kovach et al.

A pattern of integrated information—a measure inspired by integrated information theory—corresponds to what a person consciously sees, whereas broader information measures such as mutual information and entropy do not. Intracranial recordings from six neurosurgical patients showed that, in object-sensitive brain areas, the hierarchical causal structure of neural interactions matched the subjects' conscious percepts when they viewed faces or objects under conditions that dissociate perception from the physical stimulus (continuous flash suppression and backward masking). Unsupervised classification confirmed that integrated information patterns, but not other information measures, clustered according to the subjects' visual experiences. The findings suggest that locally integrated information plays a key role in the neural basis of conscious object perception.

A reply to “the unfolding argument”: Beyond functionalism/behaviorism and towards a truer science of causal structural theories of consciousness

Naotsugu Tsuchiya, Thomas Andrillon, Andrew M. Haun preprint

A theory of consciousness must address both the causal structure of a system and the structure of subjective experience (phenomenal structure). Doerig et al. argue that theories based on physical brain structure are unscientific and prefer input-output descriptions, which the authors critique as extreme methodological behaviorism. The authors clarify ambiguities in Doerig et al.'s argument, reject three of their four premises, and explain how causal structure theories of consciousness can be empirical and falsifiable. They propose that consciousness science should derive phenomenal structure from reports and search for isomorphism between physical and phenomenal structures.