Functionalist Emergentist Materialism: A Pragmatic Framework for Consciousness
Amedeo D’Angiulli, Kiranpreet K Sidhu
Imagination, Cognition and Personality June 1, 2025 DOI: 10.1177/02762366251316255 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Proposes that functionalist emergentist materialism (FEM) resolves theoretical disputes about consciousness by treating the hard problem as an evolutionary solution, and integrates with Damasio's tripartite theory to produce a pragmatic test for consciousness. |
Abstract
It is often challenging to fully justify why it is preferable to think and conduct research about consciousness following a particular theory as opposed to another. This may be especially true in disciplines within Psychology, Cognitive Science, and Neuroscience which may be pressured to follow radical reductionism to physics or chemistry. The present approach was developed through teaching a cohort of approximately 2000 undergraduate and graduate students for over fifteen years. It involves a pragmatic tutorial of the major traditions in philosophical thinking, dissecting the explanatory power of each theory and logically resolving their differences in a unitary novel framework called functionalist emergentist materialism (FEM). This proposed epistemic approach dissolves many theoretical issues. Notably, it becomes possible to make sense of the “hard problem” as an evolutionary solution. We apply and integrate this approach with one of the most comprehensive neuroscientific theories, Damasio's tripartite of consciousness, and extract a pragmatic test for recognizing conditions in which an organism is conscious. FEM aligns with contemporary evolutionary thinking and current scientific standards.
Citations in the library
Cited by 2
- Origins and Evolution of Imagination, From Australopithecus to Modern-Day Deep Learning. Wiley Interdisciplinary Reviews: Cognitive Science 2026
- Beyond the brain: a computational MRI-derived neurophysiological framework for robotic conscious capacity. Neuroscience & Biobehavioral Reviews December 1, 2025
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and 5 more in the library