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Aaron Schurger

6 papers in the library · 25 citations · publishing 2019-2026

Papers

Studying unconscious processing: Contention and consensus.

The Behavioral and brain sciences July 22, 2025 François Stockart, Maor Schreiber, Pietro Amerio et al. 20 citations

The scope of unconscious processing remains hotly debated, driven by diverse methods for manipulating and measuring perceptual awareness. Through dialogue among researchers with varied theoretical backgrounds, ten recommendations and nine outstanding issues are provided for designing experimental paradigms, analyzing data, and reporting results. These guidelines aim to evoke discussion about norms in studying unconscious processes and help researchers make informed decisions. While some recommendations may not align with existing approaches and will likely evolve, they are intended to foster a more convergent understanding of the extent and limits of unconscious processing.

On a confusion about there being two types of consciousness.

Trends in cognitive sciences December 17, 2025 Liad Mudrik, Nathan Faivre, Michael Pitts et al. 5 citations

A major controversy in consciousness science divides sensory and cognitive theories. Reexamining Block's 1995 distinction between phenomenal consciousness (P) and access consciousness (A), the authors argue that P and A are not two different types of consciousness but two necessary conditions for consciousness. This conceptual shift helps resolve unresolved questions about neural mechanisms, functions of consciousness, and its relationship with attention. The proposal motivates selective unification across different classes of theories.

A caveat regarding the unfolding argument: implications of plasticity.

Neuroscience of consciousness January 1, 2026 Vikas N O'Reilly-Shah, Alessandro Maria Selvitella, Aaron Schurger

The unfolding argument claims that causal structure cannot matter for consciousness because any recurrent neural network can be replaced by a feedforward network with the same input-output behavior. This paper shows a boundary condition: when a network has rapid plasticity—weights that change quickly based on history—the equivalence fails. Mathematical proofs demonstrate that such systems encode information in ways a static feedforward network cannot capture, including history-dependent dynamics, complex temporal encoding, and perturbational instability. The results do not prove that recurrence or plasticity is necessary for consciousness, but they show that the unfolding argument does not block empirical tests of whether these properties matter.

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.

Hard criteria for empirical theories of consciousness

Cognitive neuroscience July 14, 2020 Adrien Doerig, Aaron Schurger, M. Herzog

Consciousness research has produced many competing theories, ranging from computational to quantum approaches, more than in other natural sciences. This abundance may stem from a lack of clear criteria for how empirical data should constrain such theories. The authors argue consciousness is empirically well-defined and propose a checklist of criteria that empirical theories of consciousness must address. They review 13 influential theories against these criteria, revealing their relative strengths and weaknesses from a strictly empirical perspective.

The unfolding argument: Why IIT and other causal structure theories cannot explain consciousness.

Consciousness and Cognition July 1, 2019 Adrien Doerig, Aaron Schurger, K. Hess et al.

Theories that identify consciousness with specific causal structures in the brain, such as those requiring feedback loops, are either false or unscientific. Using theorems from computation theory, the authors demonstrate that causal structure theories—including Information Integration Theory (IIT) and Recurrent Processing Theory (RPT)—cannot be empirically tested because any causal structure can be realized by systems that lack consciousness. This undermines the claim that feedforward systems are never conscious and feedback systems always are. The argument suggests that consciousness research should focus instead on functional explanations, such as global workspace or higher-order theories, which are compatible with diverse neural implementations.