The creativity of cells: aneural irrational cognition.

aneural cognition associative learning biosemiotics creativity irrationality molecular mimicry

Journal

The Journal of physiology
ISSN: 1469-7793
Titre abrégé: J Physiol
Pays: England
ID NLM: 0266262

Informations de publication

Date de publication:
01 Oct 2023
Historique:
received: 27 06 2023
accepted: 11 09 2023
medline: 1 10 2023
pubmed: 1 10 2023
entrez: 1 10 2023
Statut: aheadofprint

Résumé

Evidence of cognition in aneural cells is well-establish in the literature. This paper extends the exploration of the mechanisms of cognition by considering whether or not aneural cells may be capable of irrational cognition, making associations based on coincidental similarities and circumstantial factors. If aneural cells do harness such semiosic qualities, as with higher-level creativity, this might be how they are able to overcome old algorithms and invent tools for new situations. I will look at three examples of irrational learning in aneural systems in terms of semiotics: (1) generalisation in the immune system, based on viral molecular mimicry, whereby immune cells attack the self, which seems to be an overgeneralisation of an icon sign based on mere similarity, not identity, (2) the classical conditioning of pea plants to trope toward wind as a sign of light, which seems to be an association of an index sign based on mere temporal proximity, and (3) a pharmaceutical intervention to prevent pregnancy, using a conjugate to encrypt self with non-self, which seems to be an example of symbol use. We identify irrational cognition easily when it leads to 'wrong' outcomes, but, if it occurs, it may also lead to favourable outcomes and 'creative' solutions.

Identifiants

pubmed: 37777982
doi: 10.1113/JP284417
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2023 The Authors. The Journal of Physiology © 2023 The Physiological Society.

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Auteurs

Victoria N Alexander (VN)

Dactyl Foundation, New York, NY, USA.

Classifications MeSH