Classification in pattern recognition. New tools to adapt a system to its environment

This paper presents a new theoretic tool based on Information Theory, the main interest of which is to acutely evaluate the classification tools . The particular nature of real-world objects recognition involves us to design systems based on multi-points of view approaches . The fusion stage has to adapt itself to the environment . We show that neural networks allow to learn the fusion function, optimized to the data and the structure of the composite system . The performance of a composite recognition system is closed to the partition of the available information on each classification tools . A Genetic algorithm is designed to adapt the parameters space partition with the set of classification tools among the quality of the composite system, genetic algorithm .Cet article présente un nouvel outil théorique fondé sur la Théorie de l'information afin de réaliser une évaluation d'un outil de classement plus fine que les mesures classiques. Nous travaillons dans le cadre de la Reconnaissance d'objets naturels complexes et compliqués. La nature même du problème incite à travailler à l'aide d'une approche multi-points de vue décisionnels, fusionnés de façon adaptative. Nous montrons que les réseaux connexionnistes permettent l'apprentissage d'une fonction de fusion optimisée selon la nature du problème et la structure du Système de Reconnaissance. Nous montrons aussi que la répartition de l'information sur chaque outil de classement contribue à une meilleure reconnaissance. Une approche de type génétique est alors conçue pour adapter la partition de l'espace des paramètres relativement à l'ensemble des outils disponibles

Needing to connect: The effect of self and others on young people's involvement with their mobile phones

The present research was a preliminary examination of young Australians’ mobile phone behaviour. The study explored the relationship between, and psychological predictors of, frequency of mobile phone use and mobile phone involvement conceptualised as people’s cognitive and behavioural interaction with their mobile phone. Participants were 946 Australian youth aged between 15 and 24 years. A descriptive measurement tool, the Mobile Phone Involvement Questionnaire (MPIQ), was developed. Self-identity and validation from others were explored as predictors of both types of mobile phone behaviour. A distinction was found between frequency of mobile phone use and mobile phone involvement. Only self-identity predicted frequency of use whereas both self-identity and validation from others predicted mobile phone involvement. These findings reveal the importance of distinguishing between frequency of use and people’s psychological relationship with their phone and that factors relating to one’s self-concept and approval from others both impact on young people’s mobile phone involvement

Altering alpha-frequency brain oscillations with rapid analog feedback-driven neurostimulation.

Oscillations of the brain's local field potential (LFP) may coordinate neural ensembles and brain networks. It has been difficult to causally test this model or to translate its implications into treatments, because there are few reliable ways to alter LFP oscillations. We developed a closed-loop analog circuit to enhance brain oscillations by feeding them back into cortex through phase-locked transcranial electrical stimulation. We tested the system in a rhesus macaque with chronically implanted electrode arrays, targeting 8-15 Hz (alpha) oscillations. Ten seconds of stimulation increased alpha oscillatory power for up to 1 second after stimulation offset. In contrast, open-loop stimulation decreased alpha power. There was no effect in the neighboring 15-30 Hz (beta) LFP rhythm or on a neighboring array that did not participate in closed-loop feedback. Analog closed-loop neurostimulation might thus be a useful strategy for altering brain oscillations, both for basic research and the treatment of neuro-psychiatric disease

Altering alpha-frequency brain oscillations with rapid analog feedback-driven neurostimulation

Oscillations of the brain’s local field potential (LFP) may coordinate neural ensembles and brain networks. It has been difficult to causally test this model or to translate its implications into treatments, because there are few reliable ways to alter LFP oscillations. We developed a closed-loop analog circuit to enhance brain oscillations by feeding them back into cortex through phase-locked transcranial electrical stimulation. We tested the system in a rhesus macaque with chronically implanted electrode arrays, targeting 8–15 Hz (alpha) oscillations. Ten seconds of stimulation increased alpha oscillatory power for up to 1 second after stimulation offset. In contrast, open-loop stimulation decreased alpha power. There was no effect in the neighboring 15–30 Hz (beta) LFP rhythm or on a neighboring array that did not participate in closed-loop feedback. Analog closed-loop neurostimulation might thus be a useful strategy for altering brain oscillations, both for basic research and the treatment of neuropsychiatric disease.MIT-MHG Strategic Initiative (grant)Massachusetts Institute of Technology. Undergraduate Research Opportunities ProgramPaul E. Gray FellowshipBrain & Behavior Research Foundation (MH109722 -01)Dauten Family Foundation (Bipolar Fund at Harvard University)Massachusetts Institute of Technology. Picower Innovation FundMIT Bose Fellowship Progra