Quantifying dynamical high-order interdependencies from the O-information: an application to neural spiking dynamics

We address the problem of efficiently and informatively quantifying how multiplets of variables carry information about the future of the dynamical system they belong to. In particular we want to identify groups of variables carrying redundant or synergistic information, and track how the size and the composition of these multiplets changes as the collective behavior of the system evolves. In order to afford a parsimonious expansion of shared information, and at the same time control for lagged interactions and common effect, we develop a dynamical, conditioned version of the O-information, a framework recently proposed to quantify high-order interdependencies via multivariate extension of the mutual information. We thus obtain an expansion of the transfer entropy in which synergistic and redundant effects are separated. We apply this framework to a dataset of spiking neurons from a monkey performing a perceptual discrimination task. The method identifies synergistic multiplets that include neurons previously categorized as containing little relevant information individually

Network Latency in On-Line Gaming: An Engineering or a Psychological Problem?

Ongoing research attempts to find engineering-based solutions to the problem of network latency in multiplayer computer games. However, few studies have been conducted to examine the end-users' experience of latency from a psychological perspective. The current study examines the roles of network latency and game complexity on the subjective experience of participants playing a specially designed computer game. Results suggest that participants prefer complex over simple games, regardless of the level of latency experienced. These findings suggest the possibility of a psychological solution to some of the negative effects of network latency. It is suggested that by manipulating Relational Complexity, it may be possible to maintain a satisfactory gaming experience in the presence of latency

Quantifying dynamical high-order interdependencies from the O-information : an application to neural spiking dynamics

We address the problem of efficiently and informatively quantifying how multiplets of variables carry information about the future of the dynamical system they belong to. In particular we want to identify groups of variables carrying redundant or synergistic information, and track how the size and the composition of these multiplets changes as the collective behavior of the system evolves. In order to afford a parsimonious expansion of shared information, and at the same time control for lagged interactions and common effect, we develop a dynamical, conditioned version of the O-information, a framework recently proposed to quantify high-order interdependencies via multivariate extension of the mutual information. The dynamic O-information, here introduced, allows to separate multiplets of variables which influence synergistically the future of the system from redundant multiplets. We apply this framework to a dataset of spiking neurons from a monkey performing a perceptual discrimination task. The method identifies synergistic multiplets that include neurons previously categorized as containing little relevant information individually

Estrategias de promoción y fidelización del cliente en la Clínica Estética San Martin de Porres, Chimbote, 2022

La presente investigación tuvo como objetivo determinar la relación entre las Estrategias de Promoción y la Fidelización del Cliente en la Clínica Estética San Martin de Porres, Chimbote, 2022. El método fue de tipo aplicada, diseño no experimental y enfoque cuantitativo. La población estuvo conformada por 240 y una muestra de 69 clientes. Para la el procedimiento de recolección se usó el análisis exploratorio, evaluando las variables estrategias de promoción y fidelización del cliente, con el instrumento cuestionario, que consto de 15 preguntas para la primera variable y 11 preguntas para la segunda variable, de acuerdo a la escala de Likert. Los resultados para el procesamiento de datos se usó el programa estadístico SPSS V.25. Concluyendo que existe relación entre las variables de Estrategias de Promoción y Fidelización del Cliente en la Clínica Estética San Martin de Porres, Chimbote, 2022, con Rho de Spearman de 0,619 y donde su Sig. Bilateral es 0,000. Y por medio de la regla (Sig. 0.000 ≤ 0.05). Se puede concluir que se rechaza la hipótesis nula y acepta la hipótesis alterna

Near-infrared spectrometry for the measurement of central nervous system activation: a brief demonstration of an emerging behavioral assessment tool

Behavior analysts are familiar with the use of electrodermal activity as a dependent measure of central nervous system activation. In addition, behavior analysts have increasingly turned to direct measures of brain activation, such as electroencephalography and event-related potentials. Recent developments in the field of bioengineering, however, have produced a new and exciting brain-activation recording device known as near infrared spectrometry, or NIRS. The current paper reports a demonstration of its use in a traditional respondent conditioning paradigm. Specifically, a male volunteer was exposed to a conditioning paradigm designed to produce both an eliciting stimulus for fear and a relief stimulus. Conditioning effects were assessed using electrodermal activation as well as blood volume changes in the frontal lobe, recorded by NIRS. The results of the demonstration show that both electrodermal and NIRS measures can successfully identify conditioning effects without necessarily tracking each other on a trial-by-trial basis. It is suggested that NIRS is an inexpensive, non-invasive technique for the assessment of learning and behavior at the neural level

The Unfolding of the Relational Operant: A Real-time Analysis Using Electroencephalography and Reaction Time Measures

The current study attempted to capture in real time the unfolding of the relational operant using electroencephalography (EEG) and reaction time measures. Participants were exposed to relational pretraining to establish the contextual cues of Same and Opposite for two arbitrary stimuli. These cues were then used to establish a series of contextually controlled discriminations in order to create a simple relational network among a series of arbitrary stimuli. During the test for derived relations of Same and Opposite, EEG and reaction time measures were recorded for each individual test task during the acquisition of a stable derived relational response pattern. Participants were then exposed to an identical set of relational training and testing tasks with the important difference that an entirely different set of stimuli was used. EEG and reaction time measures were again recorded during the relational test phase. Results showed that reaction times decreased for all subjects across successive test tasks and from the first to the second stimulus set. EEG data also suggested that there was increasingly less higher cognitive activity during the derivation of successive stimulus relations within and across stimulus sets. Taken together these findings provide support for the idea that derived relational responding can be viewed as an operant activity that both develops and generalizes