Architectural experience influences the processing of others' body expressions.

The interplay between space and cognition is a crucial issue in Neuroscience leading to the development of multiple research fields. However, the relationship between architectural space and the movement of the inhabitants and their interactions has been too often neglected, failing to provide a unifying view of architecture's capacity to modulate social cognition broadly. We bridge this gap by requesting participants to judge avatars' emotional expression (high vs. low arousal) at the end of their promenade inside high- or low-arousing architectures. Stimuli were presented in virtual reality to ensure a dynamic, naturalistic experience. High-density electroencephalography (EEG) was recorded to assess the neural responses to the avatar's presentation. Observing highly aroused avatars increased Late Positive Potentials (LPP), in line with previous evidence. Strikingly, 250 ms before the occurrence of the LPP, P200 amplitude increased due to the experience of low-arousing architectures, reflecting an early greater attention during the processing of body expressions. In addition, participants stared longer at the avatar's head and judged the observed posture as more arousing. Source localization highlighted a contribution of the dorsal premotor cortex to both P200 and LPP. In conclusion, the immersive and dynamic architectural experience modulates human social cognition. In addition, the motor system plays a role in processing architecture and body expressions suggesting that the space and social cognition interplay is rooted in overlapping neural substrates. This study demonstrates that the manipulation of mere architectural space is sufficient to influence human social cognition.

Kicking in or kicking out? The role of the individual motor expertise in predicting the outcome of rugby actions.

In sports, understanding others' actions represents a fundamental skill that allows players to predict the outcome of teammates' and opponents' actions and counteract them properly. While it is well known that motor expertise sets better premises for predicting the result of an observed sports action, it remains untested whether this principle applies to a team where players cover different positions that imply different motor repertoires. To test this hypothesis, we selected rugby as a paradigmatic example in which only one or two players out of 22 train and perform placed kicks. We administered a placed kick outcome prediction task to three groups of participants, namely, rugby kickers, rugby non-kickers, and controls, thus spanning over different combinations of motor expertise and visual experience. Kickers outperformed both their non-kicking teammates and controls in overall prediction accuracy. We documented how the viewpoint of observation, the expertise of the observed kicker, and the position of the kick on the court influenced the prediction performance across the three groups. Finally, we revealed that within rugby players, the degree of motor expertise (but not the visual experience) causally affects accuracy, and such a result stands even after accounting for the level of visual experience. These findings extend the role of motor expertise in decoding and predicting others' behaviors to sports teammates, among which every member is equipped with a position-specific motor repertoire, advocating for new motor training procedures combining the gestures to-be-performed with those to-be-faced.

Measuring arousal and valence generated by the dynamic experience of architectural forms in virtual environments.

The built environment represents the stage surrounding our everyday life activities. To investigate how architectural design impacts individuals' affective states, we measured subjective judgments of perceived valence (pleasant and unpleasant) and arousal after the dynamic experience of a progressive change of macro visuospatial dimensions of virtual spaces. To this aim, we developed a parametric model that allowed us to create 54 virtual architectural designs characterized by a progressive change of sidewalls distance, ceiling and windows height, and color of the environment. Decreasing sidewalls distance, ceiling height variation, and increasing windows height significantly affected the participants' emotional state within virtual environments. Indeed, such architectural designs generated high arousing and unpleasant states according to subjective judgment. Overall, we observed that valence and arousal scores are affected by all the dynamic form factors which modulated the spaciousness of the surrounding. Showing that the dynamic experience of virtual environments enables the possibility of measuring the emotional impact of macro spatial architectural features, the present findings may lay the groundwork for future experiments investigating the effects that the architectural design has on individuals' mental state as a fundamental factor for the creation of future spaces.

The Avatar's Gist: How to Transfer Affective Components From Dynamic Walking to Static Body Postures.

Dynamic virtual representations of the human being can communicate a broad range of affective states through body movements, thus effectively studying emotion perception. However, the possibility of modeling static body postures preserving affective information is still fundamental in a broad spectrum of experimental settings exploring time-locked cognitive processes. We propose a novel automatic method for creating virtual affective body postures starting from kinematics data. Exploiting body features related to postural cues and movement velocity, we transferred the affective components from dynamic walking to static body postures of male and female virtual avatars. Results of two online experiments showed that participants coherently judged different valence and arousal levels in the avatar's body posture, highlighting the reliability of the proposed methodology. In addition, esthetic and postural cues made women more emotionally expressive than men. Overall, we provided a valid methodology to create affective body postures of virtual avatars, which can be used within different virtual scenarios to understand better the way we perceive the affective state of others.

Quantifying the Effect of Demixing Approaches on Directed Connectivity Estimated Between Reconstructed EEG Sources.

Electrical activity recorded on the scalp using electroencephalography (EEG) results from the mixing of signals originating from different regions of the brain as well as from artifactual sources. In order to investigate the role of distinct brain areas in a given experiment, the signal recorded on the sensors is typically projected back into the brain (source reconstruction) using algorithms that address the so-called EEG "inverse problem". Once the activity of sources located inside of the brain has been reconstructed, it is often desirable to study the statistical dependencies among them, in particular to quantify directional dynamical interactions between brain areas. Unfortunately, even when performing source reconstruction, the superposition of signals that is due to the propagation of activity from sources to sensors cannot be completely undone, resulting in potentially biased estimates of directional functional connectivity. Here we perform a set of simulations involving interacting sources to quantify source connectivity estimation performance as a function of the location of the sources, their distance to each other, the noise level, the source reconstruction algorithm, and the connectivity estimator. The generated source activity was projected onto the scalp and projected back to the cortical level using two source reconstruction algorithms, linearly constrained minimum variance beamforming and 'Exact' low-resolution tomography (eLORETA). In source space, directed connectivity was estimated using multi-variate Granger causality and time-reversed Granger causality, and compared with the imposed ground truth. Our results demonstrate that all considered factors significantly affect the connectivity estimation performance.