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Article . 2023
License: CC BY
Data sources: ZENODO
https://doi.org/10.32388/u0175...
Article . 2023 . Peer-reviewed
Data sources: Crossref
ResearchGate Data
Preprint . 2023
Data sources: Datacite
ZENODO
Article . 2023
License: CC BY
Data sources: Datacite
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MENTAL RECOGNITION OF OBJECTS VIA RAMSEY SENTENCES

Authors: Arturo Tozzi;

MENTAL RECOGNITION OF OBJECTS VIA RAMSEY SENTENCES

Abstract

Dogs display vast phenotypic diversity, including differences in height, skull shape, tail, etc. Yet, humans are almost always able to quickly recognize a dog, despite no single feature or group of features are critical to distinguish dogs from other objects/animals. In search of the mental activities leading human individuals to state _“I see a dog_”, we hypothesize that the brain might extract meaningful information from the environment using Ramsey sentences-like procedures. To turn the proposition _“I see a dog”_ in a Ramsey sentence, the term dog must be replaced by a long and complex assertion consisting only of observational terms, existential quantifiers and operational rules. The Ramsey sentence for _“I see a dog”_ sounds: “_There is at least an entity called dog which satisfies the following conditions: it is an animal, it has four legs, …, etc, …, and is something that I have in my sight_”. We discuss the biological plausibility and the viable neural correlates of a Ramsey-like mechanism in the central nervous system. We accomplish a brain-inspired, theoretical neural architecture consisting of a parallel network that requires virtually no memory, is devoid of probabilistic choices and can analyze huge but finite amounts of unique visual details, combining them in a single concept. In sum, Ramsey sentence stands for a versatile tool that can be used not just as a methodological device to cope with biophysical affairs, but also for a model to describe the real functioning of cognitive operations such as sensation and perception.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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