Open University of Catalonia

About: Open University of Catalonia is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Collaborative learning & Educational technology. The organization has 1943 authors who have published 4646 publications receiving 64200 citations. The organization is also known as: Universitat Oberta de Catalunya & UOC.

Spatial attention and conscious perception: the role of endogenous and exogenous orienting

Abstract: Attention has often been considered to be a gateway to consciousness (Posner, Proceedings of the National Academy of Sciences of the United States of America, 91(16), 7398–7403, 1994). However, its relationship with conscious perception (CP) remains highly controversial. While theoretical models and experimental data support the role of attention in CP (Chica, Lasaponara, Lupianez, Doricchi, & Bartolomeo, NeuroImage, 51, 1205–1212, 2010; Dehaene, Changeux, Naccache, Sackur, & Sergent, Trends in Cognitive Sciences, 10, 204–211, 2006; Mack & Rock, Inattentional blindness, 1998), recent studies have claimed that at least some forms of attention—endogenous or top-down spatial attention—are neither sufficient nor necessary for CP (Koch & Tsuchiya, Trends in Cognitive Sciences, 11, 16–22, 2007). In the present experiments, we demonstrate the importance of exogenously triggered attention for the modulation of CP. Weak or null effects were instead observed when attention was triggered endogenously. Our data are discussed in the framework of recent neuropsychological models (Dehaene et al., Trends in Cognitive Sciences, 10, 204–211, 2006), postulating that activity within reverberating frontoparietal networks, as colocalized with spatial--orienting systems, is the brain correlate of consciously processed information.

Interpreting CNN Models for Apparent Personality Trait Regression

Abstract: This paper addresses the problem of automatically inferring personality traits of people talking to a camera. As in many other computer vision problems, Convolutional Neural Networks (CNN) models have shown impressive results. However, despite of the success in terms of performance, it is unknown what internal representation emerges in the CNN. This paper presents a deep study on understanding why CNN models are performing surprisingly well in this complex problem. We use current techniques on CNN model interpretability, combined with face detection and Action Unit (AUs) recognition systems, to perform our quantitative studies. Our results show that: (1) face provides most of the discriminative information for personality trait inference, and (2) the internal CNN representations mainly analyze key face regions such as eyes, nose, and mouth. Finally, we study the contribution of AUs for personality trait inference, showing the influence of certain AUs in the facial trait judgments.

Does a Crisis Change News Habits? A Comparative Study of the Effects of COVID-19 on News Media Use in 17 European Countries

Abstract: Exogenous shocks like the COVID-19 pandemic unleashes multiple fundamental questions about society beyond public health. Based on the classical concept of ‘need for orientation’ and the literature ...