Hierarchical approaches to understanding consciousness.
Neural Networks November 2007 DOI: 10.1016/j.neunet.2007.09.009 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Argues that a scientific theory of consciousness should follow the physical sciences' model of hierarchical descriptions, enabling mapping between high-level and detailed levels, and that understanding when to shift levels is fundamental. Proposes a form for such a theory and critiques alternative approaches for their limitations. |
Abstract
There has been much discussion on what a scientific theory of consciousness would look like, and even whether such a theory is possible. Some common misunderstandings of the nature of theories (e.g., in the physical sciences) have confused the discussion of theories concerning consciousness. Theories in the physical sciences establish hierarchies of descriptions that relate high-level descriptions of macro-level phenomena to detailed-level descriptions at a micro level. Detailed descriptions are usually more accurate but information-dense and therefore often beyond human comprehensibility (unless limited to tiny segments of a macro-level phenomenon). High-level descriptions are usually much less information-dense but more approximate. The ability to map between levels of description, and in particular the understanding of when a shift from a higher-level to a more detailed description is needed to achieve a desired degree of accuracy, is fundamental to an effective theory in any field. The form of such a theory of consciousness is sketched, and the limitations of some alternative approaches described.
Citations in the library
Cites 4
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