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William Marshall

14 papers in the library · 246 citations · publishing 2016-2026

Papers

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Intrinsic Cause-Effect Power: The Tradeoff Between Differentiation and Specification.

Entropy (Basel, Switzerland) April 4, 2026 William G. P. Mayner, William Marshall, Giulio Tononi

Integrated information theory (IIT) starts from the existence of consciousness and characterizes its essential properties: every experience is intrinsic, specific, unitary, definite, and structured. IIT then formulates existence and its essential properties operationally in terms of cause-effect power of a substrate of units. Here, we address IIT's operational requirements for existence by...

DOI: 10.3390/e28040410 (opens in new tab) Full text (opens in new tab) Complexity Consciousness Differentiation Integrated information +1

Intrinsic units: identifying a system's causal grain.

Neuroscience of Consciousness 2026 William Marshall, Graham Findlay, Larissa Albantakis et al.

Integrated information theory (IIT) aims to account for the quality and quantity of consciousness in physical terms. According to IIT, a substrate of consciousness must be a system of units (e.g. synapses, neurons, minicolumns, etc.) that is a maximum of intrinsic, specific, unitary cause-effect power, quantified by integrated information ([Formula: see text]). The grain of each unit must be...

DOI: 10.1093/nc/niag013 (opens in new tab) Full text (opens in new tab) Causal emergence Computational modeling Consciousness Integrated information +1

Increasing power for detecting awareness: a new approach to test group level objective performance.

Neuroscience of Consciousness 2026 Shaked Lublinsky, Itay Yaron, William Marshall et al.

Demonstrating reliable unconscious effects is notoriously challenging, and the scope of unconscious processing remains debated. Establishing unconscious effects requires two critical pieces of evidence: first, that the stimulus of interest was processed, and second, that participants were not consciously aware of that stimulus. Here, we focus on the second requirement which has faced criticism...

DOI: 10.1093/nc/niag039 (opens in new tab) Full text (opens in new tab) Chance level performance Consciousness Detection task Discrimination task +1

Intrinsic cause-effect power: the tradeoff between differentiation and specification

arXiv Preprint Archive October 4, 2025 William G. P. Mayner, William Marshall, Giulio Tononi preprint

Integrated information theory (IIT) starts from the existence of consciousness and characterizes its essential properties: every experience is intrinsic, specific, unitary, definite, and structured. IIT then formulates existence and its essential properties operationally in terms of cause-effect power of a substrate of units. Here we address IIT's operational requirements for existence by...

Dissociating Artificial Intelligence from Artificial Consciousness

arXiv Preprint Archive December 5, 2024 Graham Findlay, William Marshall, Larissa Albantakis et al. preprint

Developments in machine learning and computing power suggest that artificial general intelligence is within reach. This raises the question of artificial consciousness: if a computer were to be functionally equivalent to a human, being able to do all we do, would it experience sights, sounds, and thoughts, as we do when we are conscious? Answering this question in a principled manner can only...

Full text (opens in new tab) Cs.ai Cs.cy Q-bio.nc

Progressing, not regressing: A possible solution to the problem of regression to the mean in unconscious processing studies.

Psychonomic Bulletin & Review February 2024 Itay Yaron, Yoav Zeevi, Uri Korisky et al.

How convincing is current evidence for unconscious processing? Recently, a major criticism suggested that some, if not much, of this evidence might be explained by a mere statistical phenomenon: regression to the mean (RttM). Excluding participants based on an awareness assessment is a common practice in studies of unconscious processing, and this post hoc data selection might lead to false...

DOI: 10.3758/s13423-023-02326-x (opens in new tab) Full text (opens in new tab) Consciousness Power Reliability Unconscious processing

Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical terms.

PLoS Computational Biology October 17, 2023 Larissa Albantakis, Leonardo S. Barbosa, Graham Findlay et al.

This paper presents Integrated Information Theory (IIT) 4.0. IIT aims to account for the properties of experience in physical (operational) terms. It identifies the essential properties of experience (axioms), infers the necessary and sufficient properties that its substrate must satisfy (postulates), and expresses them in mathematical terms. In principle, the postulates can be applied to any...

DOI: 10.1371/journal.pcbi.1011465 (opens in new tab) Full text (opens in new tab) Brain Consciousness Models, neurological Information theory

System Integrated Information

Entropy February 11, 2023 William Marshall, Matteo Grasso, William G. P. Mayner et al. 19 citations

Integrated information theory (IIT) starts from consciousness itself and identifies a set of properties (axioms) that are true of every conceivable experience. The axioms are translated into a set of postulates about the substrate of consciousness (called a complex), which are then used to formulate a mathematical framework for assessing both the quality and quantity of experience. The...

IIT, half masked and half disfigured.

Behavioral and Brain Sciences March 23, 2022 Giulio Tononi, Melanie Boly, Matteo Grasso et al.

The target article misrepresents the foundations of integrated information theory (IIT) and ignores many essential publications. It, thus, falls to this lead commentary to outline the axioms and postulates of IIT and correct major misconceptions. The commentary also explains why IIT starts from phenomenology and why it predicts that only select physical substrates can support consciousness....

Mechanism Integrated Information

Entropy March 18, 2021 Leonardo S. Barbosa, William Marshall, Larissa Albantakis et al. 74 citations

The Integrated Information Theory (IIT) of consciousness starts from essential phenomenological properties, which are then translated into postulates that any physical system must satisfy in order to specify the physical substrate of consciousness. We recently introduced an information measure (Barbosa et al., 2020) that captures three postulates of IIT-existence, intrinsicality and...

DOI: 10.3390/e23030362 (opens in new tab) Consciousness Mechanism biology Integrated information theory Measure data warehouse +6

Evaluating Approximations and Heuristic Measures of Integrated Information.

Entropy (Basel, Switzerland) May 24, 2019 André Sevenius Nilsen, Bjørn Erik Juel, William Marshall

Integrated information theory (IIT) proposes a measure of integrated information, termed Phi (Φ), to capture the level of consciousness of a physical system in a given state. Unfortunately, calculating Φ itself is currently possible only for very small model systems and far from computable for the kinds of system typically associated with consciousness (brains). Here, we considered several...

Differentiation Analysis of Continuous Electroencephalographic Activity Triggered by Video Clip Contents.

Journal of Cognitive Neuroscience August 2018 Armand Mensen, William Marshall, Shuntaro Sasai et al.

While viewing a video clip, we experience a wide variety of contents, from low-level features of the images to high-level ideas such as the storyline. Each change in our experience must be supported by some corresponding change in neurophysiological activity. Differentiation analysis, which quantifies the differences in brain activity by measuring the distances between observed brain states,...

Can the macro beat the micro? Integrated information across spatiotemporal scales

Neuroscience of Consciousness 2016 Erik Hoel, Larissa Albantakis, William Marshall et al. 153 citations

Causal interactions within complex systems such as the brain can be analyzed at multiple spatiotemporal levels. It is widely assumed that the micro level is causally complete, thus excluding causation at the macro level. However, by measuring effective information—how much a system’s mechanisms constrain its past and future states—we recently showed that causal power can be stronger at macro...

Integrated Information and State Differentiation.

Frontiers in Psychology 2016 William Marshall, Jaime Gomez-Ramirez, Giulio Tononi

Integrated information (Φ) is a measure of the cause-effect power of a physical system. This paper investigates the relationship between Φ as defined in Integrated Information Theory and state differentiation ([Formula: see text]), the number of, and difference between potential system states. Here we provide theoretical justification of the relationship between Φ and [Formula: see text], then...

DOI: 10.3389/fpsyg.2016.00926 (opens in new tab) Full text (opens in new tab) Animats Cause-effect power Consciousness Integrated information theory +1