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

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.Los lenguajes naturales pueden expresar algunas proposiciones lógicas que los humanos pueden entender. Ilustramos esto con un famoso texto que Conan Doyle atribuye a Holmes: "Una vieja máxima mía dice que cuando has eliminado lo imposible, lo que queda, por muy improbable que parezca, tiene que ser la verdad”. Esto es una sutil declaración lógica que usualmente se siente evidentemente verdadera. El problema que tratamos de resolver es la razón cognitiva de tal sentimiento. Postulamos que aceptamos la máxima de Holmes como verdadera porque nuestros cerebros adultos están equipados con módulos neurales que ejecutan naturalmente cómputos de la lógica modal

Detecting order-disorder transitions in discourse : implications for schizophrenia

Abstract Several psychiatric and neurological conditions affect the semantic organization and content of a patient's speech. Specifically, the discourse of patients with schizophrenia is frequently characterized as lacking coherence. The evaluation of disturbances in discourse is often used in diagnosis and in assessing treatment efficacy, and is an important factor in prognosis. Measuring these deviations, such as “loss of meaning” and incoherence, is difficult and requires substantial human effort. Computational procedures can be employed to characterize the nature of the anomalies in discourse. We present a set of new tools derived from network theory and information science that may assist in empirical and clinical studies of communication patterns in patients, and provide the foundation for future automatic procedures. First we review information science and complex network approaches to measuring semantic coherence, and then we introduce a representation of discourse that allows for the computation of measures of disorganization. Finally we apply these tools to speech transcriptions from patients and a healthy participant, illustrating the implications and potential of this novel framework

Thoughts about disordered thinking: measuring and quantifying the laws of order and disorder

Peer ReviewedPostprint (author's final draft

Illustrating a neural model of logic computations: the case of Sherlock Holmes’ old maxim

Los lenguajes naturales pueden expresar algunas proposiciones lógicas que los humanos pueden entender. Ilustramos esto con un famoso texto que Conan Doyle atribuye a Holmes: «Una vieja máxima mía dice que cuando has eliminado lo imposible, lo que queda, por muy improbable que parezca, tiene que ser la verdad”. Esto es una sutil declaración lógica que usualmente se siente evidentemente verdadera. El problema que tratamos de resolver es la razón cognitiva de tal sentimiento. Postulamos que aceptamos la máxima de Holmes como verdadera porque nuestros cerebros adultos están equipados con módulos neurales que ejecutan naturalmente cómputos de la lógica modal.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 true. 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 perform naturally modal logical computations.

Illustrating a neural model of logic computations: the case of Sherlock Holmes’ old maxim

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 true. 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 perform naturally modal logical computations. ; Los lenguajes naturales pueden expresar algunas proposiciones lógicas que los humanos pueden entender. Ilustramos esto con un famoso texto que Conan Doyle atribuye a Holmes: "Una vieja máxima mía dice que cuando has eliminado lo imposible, lo que queda, por muy improbable que parezca, tiene que ser la verdad”. Esto es una sutil declaración lógica que usualmente se siente evidentemente verdadera. El problema que tratamos de resolver es la razón cognitiva de tal sentimiento. Postulamos que aceptamos la máxima de Holmes como verdadera porque nuestros cerebros adultos están equipados con módulos neurales que ejecutan naturalmente cómputos de la lógica modal