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Vecchiato, G.

Publications and source records attributed to Vecchiato, G..

2 recordsLinked to original sources

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, the movement of the inhabitants and their interactions has been too often neglected, failing to provide a unifying view of architectures 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 EEG was recorded to assess the neural responses to the avatars 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 paralleling increased subjective arousal reports and fixation times on the avatars head. Source localization highlighted a contribution of the right 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 proving how the space and social cognition interplay is rooted in common neural substrates. This study demonstrates that the manipulation of mere architectural space is sufficient to influence human behavior in social interactions. Significance StatementIn the last thirty years the motor system has been recognized as a fundamental neural machinery for spatial and social cognition, making worthwhile the investigation of the interplay between architecture and social behavior. Here, we show that the motor system participates in the others body expression processing in two stages: the earliest influenced by the dynamic architectural experience, the latter modulated by the actual physical characteristics. These findings highlight the existence of motor neural substrates common to spatial and social cognition, with the architectural space exerting an early and possibly adapting effect on the later social experience. Since mere architectural forms influence human behavior, a proper spatial design could thus facilitate everyday social interactions.

neuroscience↗

Hybrid EEG-EMG system to detect steering actions in car driving settings

Understanding mental processes in complex human behaviour is a key issue in the context of driving, representing a milestone for developing user-centred assistive driving devices. Here we propose a hybrid method based on electroencephalographic (EEG) and electromyographic (EMG) signatures to distinguish left from right steering in driving scenarios. Twenty-four participants took part in the experiment consisting of recordings 128-channel EEG as well as EMG activity from deltoids and forearm extensors in non-ecological and ecological steering tasks. Specifically, we identified the EEG mu rhythm modulation correlates with motor preparation of self-paced steering actions in the non-ecological task, while the concurrent EMG activity of the left (right) deltoids correlates with right (left) steering. Consequently, we exploited the mu rhythm de-synchronization resulting from the non-ecological task to detect the steering side by means of a cross-correlation analysis with the ecological EMG signals. Results returned significant cross-correlation values showing the coupling between the non-ecological EEG feature and the muscular activity collected in ecological driving conditions. Moreover, such cross-correlation patterns discriminate left from right steering with an earlier dynamic with respect to the single EMG signal. This hybrid system overcomes the limitation of the EEG signals collected in ecological settings such as low reliability, accuracy and adaptability, thus adding to the EMG the characteristic predictive power of the cerebral data. These results are a proof of concept of how it is possible to complement different physiological signals to control the level of assistance needed by the driver.

neuroscience↗