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C. Pennartz

2 papers in the library · publishing 2022-2024

Papers

Assessing the commensurability of theories of consciousness: On the usefulness of common denominators in differentiating, integrating and testing hypotheses.

Consciousness and Cognition February 27, 2024 K. Evers, M. Farisco, C. Pennartz

The paper examines how diverse current theories of consciousness are and whether they share common ground. It argues that logical and empirical commensurability—the ability to compare theories along specific dimensions—is necessary for identifying shared features. Comparing a subset of neuroscience-based theories reveals no single unifying model; theories that appear similar on one dimension may differ on another. The authors propose using multiple probing questions to assess overall similarities and differences between theories. Despite conflicting background definitions of consciousness, they conclude that a shared methodological approach to studying brain-consciousness relationships could eventually allow different theories to be integrated and merged, overcoming the current fragmentation.

What is neurorepresentationalism? From neural activity and predictive processing to multi-level representations and consciousness.

Behavioural Brain Research June 1, 2022 C. Pennartz

Conscious experience is a multimodal, situational survey—a best-guess representation of body and environment built by the brain. Five hallmarks characterize it: multimodal richness, situatedness, unity, dynamics, and intentionality. Consciousness serves a biological function, enabling goal-directed, planned behavior rather than reflexes or habits. Predictive processing models help explain the neural mechanisms, but the Hard Problem—why such activity yields phenomenal experience—remains. The author proposes that multi-level representations emergently give rise to spatially wide superinferences corresponding to experience. Neurorepresentationalism is compared with other neural theories, and its implications for assessing consciousness in animals, AI, and unresponsive patients are discussed.