Missed signals in the congruency between visual distracting cues and auditory goals

Previously, auditory-visual paradigms have been studied when the person is reading a text and receives a distractive sound stimulus. In this study, attention to sound stimulus is evaluated while receiving distractive visual stimuli. The present study questioned whether the difference between visual and auditory meaning would be considered a high or a low cognitive load. Therefore, in this study, we explored the congruency of visual and auditory stimulus, the gender of the voice, the gender of the individual participating, and others as variables, by using information gathered from 1000 events. The results revealed that the omissions made by the participant are influenced by the audio/image inequality. More omissions were analized using information gathered from 1000 events. The results revealed that the omissions made by the observed when the number presented in audio was different from that presented in the image (p = 0.001), thus showing a linear correlation (r =-0.54, p > 0.01). The interpretation of these omissions was complementary to the findings by Wolfe and colleagues (Wolfe, Horowitz & Kenner, 2005), who explored at least 2000 events per participant and where the distractive element was an auditory bottom-up. In this way, the number of omissions that appeared in only 1000 events of the auditory top-down type occurred because such omissions are caused by the bottom-up visual events-where the difference of 120.6 ms between congruency and incongruence could be explained according to the findings of Lavie & Cox (1997) of 40 ms, of high working memory (Lavie, 2005) of about 60 ms, plus the gap between audio and image, which could be considered about 20 ms. © 2018 Association for Computing Machinery

Variaciones de los tiempos de reacción frente a cambios de perspectiva y tamaño de los estímulos 2D y 3D en atención selectiva

Frente a un estímulo objetivo, las personas procesan mediante la atención selectiva antes de realizar toma de decisiones. Si ese estímulo sufre algún cambio en su configuración 2D o 3D, ¿en qué casos una persona reacciona más rápido o más lento? La presente investigación evaluó la influencia de los cambios en las características de los estímulos en experimentos de tiempos de reacción en tareas de atención visual en videojuegos creados en Unity 3D. Para estudiar esas características, se realizó una comparación entre dos experimentos de videojuegos. El primer experimento se dividió en dos bloques: uno mostraba estímulos en 2D y otro en 3D. Se recolectó el tiempo de reacción de los participantes frente a esos estímulos y se obtuvo que el tiempo de reacción fue mayor en 3D en 28.33 ms. En el segundo experimento se incrementaron los bloques (de dos a ocho) para explicar las diferencias de los tiempos de reacción obtenidas en el primer experimento sea por el tamaño o el ángulo relativo que otorga una diferente perspectiva geométrica de presentación de los estímulos en 3D, para lo cual se modificaron algunas características de los estímulos del primer experimento. Los resultados después de comparar los distintos escenarios muestran que la modificación de las características tiene una influencia en la atención selectiva, pues los tiempos de reacción del primer experimento varían en comparación a los del segundo experimento dependiendo del cambio realizado (entre 65 y 67 ms de diferencia para 2D y entre 53 y 77 ms para 3D). En la discusión, se analiza el ámbito de los estímulos en 2D y 3D en el neuromarketing o el deporte ante los cambios de tamaño y ángulo de la cámara. En ambos escenarios, el presente trabajo sugiere evaluar para cada caso la modificación en sus presentaciones o herramientas en un consiguiente incremento del tiempo de reacción de los potenciales usuarios o equivalentemente en un nivel bajo de atención.When facing a goal-stimulus, people have a certain degree of attention. Therefore, when stimulus has changes in 2D or 3D configuration, in which cases one would react faster or slower? The present research evaluated the influence of the changes in the characteristics of the stimuli in reaction time experiments in visual attention tasks in videogames made in Unity 3D. For this, a comparison was made between two videogame experiments. The first videogame experiment was divided into two blocks that showed stimuli a block in 2D videogame and another in 3D videogame respectively to the participants and collected their reaction times against these stimuli. The second videogame experiment increase the number of blocks (from two to eight) to explain the differences in the reaction times obtained in the first experiment either by the size or the relative angle of 3D presentation of the stimuli, for which some characteristics of the blocks of the first experiment. The results, after comparing the different scenarios, have shown that the modification of the characteristics changed selective attention, because the reaction times of the first experiment vary in comparison to those of the second experiment depending on the change made (between 65 and 67 ms of difference for 2D and between 53 and 77 ms for 3D). On the discussion, one can question the commercial spheres of 2D stimuli in the so-called neuromarketing or sports. In both scenarios, the present work suggests evaluating for each case changes in their presentations or tools in a consequent control the reaction time of potential users, and this translates into a level of attention control

Different Markov chains modulate visual stimuli processing in a Go-Go experiment in 2D, 3D and augmented reality

The introduction of Augmented Reality (AR) has attracted several developments, although the people’s experience of AR has not been clearly studied or contrasted with the human experience in 2D and 3D environments. Here, the directional task was applied in 2D, 3D, and AR using simplified stimulus in video games to determine whether there is a difference in human answer reaction time prediction using context stimulus. Testing of the directional task adapted was also done. Research question: Are the main differences between 2D, 3D, and AR able to be predicted using Markov chains? Methods: A computer was fitted with a digital acquisition card in order to record, test and validate the reaction time (RT) of participants attached to the arranged RT for the theory of Markov chain probability. A Markov chain analysis was performed on the participants’ data. Subsequently, the way certain factors influenced participants RT amongst the three tasks time on the accuracy of the participants was sought in the three tasks (environments) were statistically tested using ANOVA. Results: Markov chains of order 1 and 2 successfully reproduced the average reaction time by participants in 3D and AR tasks, having only 2D tasks with the variance predicted with the current state. Moreover, a clear explanation of delayed RT in every environment was done. Mood and coffee did not show significant differences in RTs on a simplified videogame. Gender differences were found in 3D, where endogenous directional goals are in 3D, but no gender differences appeared in AR where exogenous AR buttons can explain the larger RT that compensate for the gender difference. Our results suggest that unconscious preparation of selective choices is not restricted to current motor preparation. Instead, decisions in different environments and gender evolve from the dynamics of preceding cognitive activity can fit and improve neurocomputational models

Data_Sheet_1_Different Markov chains modulate visual stimuli processing in a Go-Go experiment in 2D, 3D, and augmented reality.pdf

The introduction of Augmented Reality (AR) has attracted several developments, although the people’s experience of AR has not been clearly studied or contrasted with the human experience in 2D and 3D environments. Here, the directional task was applied in 2D, 3D, and AR using simplified stimulus in video games to determine whether there is a difference in human answer reaction time prediction using context stimulus. Testing of the directional task adapted was also done.Research question: Are the main differences between 2D, 3D, and AR able to be predicted using Markov chains?Methods: A computer was fitted with a digital acquisition card in order to record, test and validate the reaction time (RT) of participants attached to the arranged RT for the theory of Markov chain probability. A Markov chain analysis was performed on the participants’ data. Subsequently, the way certain factors influenced participants RT amongst the three tasks time on the accuracy of the participants was sought in the three tasks (environments) were statistically tested using ANOVA.Results: Markov chains of order 1 and 2 successfully reproduced the average reaction time by participants in 3D and AR tasks, having only 2D tasks with the variance predicted with the current state. Moreover, a clear explanation of delayed RT in every environment was done. Mood and coffee did not show significant differences in RTs on a simplified videogame. Gender differences were found in 3D, where endogenous directional goals are in 3D, but no gender differences appeared in AR where exogenous AR buttons can explain the larger RT that compensate for the gender difference. Our results suggest that unconscious preparation of selective choices is not restricted to current motor preparation. Instead, decisions in different environments and gender evolve from the dynamics of preceding cognitive activity can fit and improve neurocomputational models.</p