Philosophy and the Mind Sciences
December 22, 2025
M. Päßler, Adrien Doerig
Conscious experiences are defined by their relationships to one another, and these relationships are mirrored by brain structures. However, simply matching brain patterns to mental patterns is not enough to explain what a conscious experience is about. The brain's downstream processes must actively use those patterns in a way that preserves their structure and influences behavior. Purely anatomical or overly broad causal brain structures fail this test, but activation patterns can succeed when embedded in the right computational context. This means that local structuralist theories, which ignore how brain activity is used by subsequent processing, are incomplete. Any adequate structuralist account of consciousness must incorporate computational context.
The Behavioral and brain sciences
June 25, 2026
Michael H Herzog, Adrien Doerig
Fleming and Michel link consciousness to sensory horizons, model-based computations, reality monitoring, and decision termination, but these functions can operate without consciousness, potentially making consciousness epiphenomenal. Like other current theories, this approach places excessive explanatory weight on a limited set of factors.
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.
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.