Understanding Minds in Real-World Environments: Toward a Mobile Cognition Approach

Abstract

There is a growing body of evidence that important aspects of human cognition have been marginalized, or overlooked, by traditional cognitive science. In particular, the use of laboratory-based experiments in which stimuli are artificial, and response options are fixed, inevitably results in findings that are less ecologically valid in relation to real-world behavior. In the present review we highlight the opportunities provided by a range of new mobile technologies that allow traditionally lab-bound measurements to now be collected during natural interactions with the world. We begin by outlining the theoretical support that mobile approaches receive from the development of embodied accounts of cognition, and we review the widening evidence that illustrates the importance of examining cognitive processes in their context. As we acknowledge, in practice, the development of mobile approaches brings with it fresh challenges, and will undoubtedly require innovation in paradigm design and analysis. If successful, however, the mobile cognition approach will offer novel insights in a range of areas, including understanding the cognitive processes underlying navigation through space and the role of attention during natural behavior. We argue that the development of real-world mobile cognition offers both increased ecological validity, and the opportunity to examine the interactions between perception, cognition and action—rather than examining each in isolation.

Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG

“…Cognitive processes are different between rest and movement conditions (e.g., vision for action vs. vision for recognition, Goodale et al, 1991, or the interference of cognitive effort and gait stability, Al-Yahya et al, 2011) and the motor system even closely interacts with sensory processing (Schafer and Marcus, 1973). Accordingly the ecological validity of cognitive neuroscience research depends to a significant degree on the ability of studying the brain during natural motion (Ladouce et al, 2017). Even subtle motion, however, may distort signal quality.…”

Identifying key factors for improving ICA-based decomposition of EEG data in mobile and stationary experiments

“…Gramann et al, 2010;De Sanctis et al, 2014;Ehinger et al, 2014;Gehrke et al, 2018;Djebbara et al, 2019) and in the real world, which increases our understanding of human brain dynamics accompanying embodied cognitive processes as well as the impact of real world environments (e.g. Debener et al, 2012;Wascher et al, 2014;Ladouce et al, 2017;Protzak and Gramann, 2018;Wunderlich and Gramann, 2018). While these experimental protocols provide new insights into the neural activity subserving cognition in more realistic and natural settings, they present new challenges.…”

Body-World Coupling, Sensorimotor Mechanisms, and the Ontogeny of Social Cognition

“…This modeling can be achieved through tools derived from network science and/or machine learning techniques (Vespignani, 2011;Boonstra et al, 2015;Sekara et al, 2016;Shine et al, 2016;Avena-Koenigsberger et al, 2017;Aguilera, 2018;Parada and Rossi, 2018). Furthermore, implementing scalable experimental paradigms (Parada, 2018;Matusz et al, 2019;Shamay-Tsoory and Mendelsohn, 2019) and generating novel hypotheses of interacting brain/body systems functioning during natural cognition (De Jaegher et al, 2010Di Paolo and De Jaegher, 2012;Gramann et al, 2014;Ladouce et al, 2017;Parada, 2018;Parada and Rossi, 2018) are among the most outstanding challenges for the 4E-cognition research program. We believe that the incorporation of a mechanistic framework facilitates meeting those challenges and advancing a deeper understanding of cognitive phenomena, social, and otherwise.…”