A Mathematical Perspective Over the Mind-Body Reduction Problem
Bibliographic Data
| ID | 4238044 |
|---|---|
| Authors | Daniel Uptmoor Pauly (0000-0002-5472-8246, Universidade do Vale do Rio dos Sinos, corresponding author) |
| Year | 2022 |
| Volume | 1 |
| Issue | 45 |
| Pages | 230-247 |
| Publication date | 2022-06-23 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Revista Ideação (JOURNAL) |
| Journal identifiers | ISSN: 1415-4668 • E-ISSN: 2359-6384 |
| Publisher | Universidade Estadual de Feira de Santana (PUBLISHER • BR) |
| DOI | 10.13102/ideac.v1i45.7509 |
| OpenAlex | W4283387308 |
| Language | EN |
| References cited | 8 |
Is mental phenomena reducible to body phenomena? Reductive Analytical Method (RAM) have algebraic roots. "To reduce" translates, in a Cartesian sense, to the action of isolating independent variables. If RAM were dismissed, multiple variable problems would either: require more time and resources; be prohibitively difficult or unsolvable. Arguably, this bears truth to the majority of hard science's problems. Recent cognitive and neuro imagery studies included mental phenomena to RAM's scope, defying the tradition. Information Theory (IT) provides quantitative methods for the information contained: in the whole; in the sum of its parts; and in their relation. Justifying why it seems useful in evaluating RAM. According to IT: no set's information can be greater than the information in the sum of its parts; RAM only provides a partial account of neuronal dynamics. The negative and affirmative answers to the mind-body reduction question are, respectively: quantifying the whole as "greater than the sum of its parts"; extrapolating RAM's scope. Both answers seem to imply some mathematical claims, but, if our IT interpretations are correct, lack the mathematical ground. Novel and Traditional research methods have tried untangling the mind. Methods accounting for mind's tangled nature may contribute to debate as well
Cognitive science · Epistemology · Mathematical economics · Cognitive Science and Mapping · Computer Science · Mathematics · Philosophy · Psychology · Artificial Intelligence
| Citation velocity | historical |
|---|---|
| Highly cited | No |