Illustrating a neural model of logic computations: The case of Sherlock Holmes' old maxim

TL;DR

This paper explores how neural modules in the brain might naturally perform modal logical computations, explaining why humans accept Holmes' maxim as a logical truth.

Contribution

It proposes a neural model that accounts for human understanding of logical propositions expressed in natural language, specifically illustrating the cognitive basis of Holmes' maxim.

Findings

Neural modules can perform modal logical computations.

Humans accept Holmes' maxim due to neural processing.

The model explains the cognitive basis of logical reasoning in language.

Abstract

Natural languages can express some logical propositions that humans are able to understand. We illustrate this fact with a famous text that Conan Doyle attributed to Holmes: 'It is an old maxim of mine that when you have excluded the impossible, whatever remains, however improbable, must be the truth'. This is a subtle logical statement usually felt as an evident truth. The problem we are trying to solve is the cognitive reason for such a feeling. We postulate here that we accept Holmes' maxim as true because our adult brains are equipped with neural modules that naturally perform modal logical computations.