RESUMEN
The objective of the present work was to identify electroencephalographic (EEG) components in order to distinguish between braking and accelerating intention in simulated car driving. To do so, we collected high-density EEG data from thirty participants while they were driving in a car simulator. The EEG was separated into independent components that were clustered across participants according to their scalp map topographies. For each component, time-frequency activity related to braking and acceleration events was determined through wavelet analysis, and the cortical generators were estimated through minimum norm source localisation. Comparisons of the time-frequency patterns of power and phase activations revealed that theta power synchronisation distinguishes braking from acceleration events 800â¯ms before the action and that phase-locked activity increases for braking 800â¯ms before foot movement in the theta-alpha frequency range. In addition, source reconstruction showed that the dorso-mesial part of the premotor cortex plays a key role in preparation of foot movement. Overall, the results illustrate that dorso-mesial premotor areas are involved in movement preparation while driving, and that low-frequency EEG rhythms could be exploited to predict drivers' intention to brake or accelerate.
Asunto(s)
Conducción de Automóvil/psicología , Tiempo de Reacción/fisiología , Aceleración , Adulto , Automóviles , Simulación por Computador , Electroencefalografía/métodos , Femenino , Humanos , Intención , Masculino , Corteza Motora/fisiología , Análisis Espacio-Temporal , Adulto JovenRESUMEN
We discuss transport measurements through graphene Andreev interferometers exhibiting reentrance of the superconducting proximity effect. We observe that at high gate voltage (VBG) the energy dependence of the Andreev conductance oscillations exhibits a scaling in agreement with theoretical expectations, which breaks down at low VBG, when the Fermi energy approaches the charge neutrality point. The phenomenon is a manifestation of single particle dephasing that increasingly limits the propagation of superconducting correlations away from the superconductor-graphene interface. Our work addresses the interplay between microscopic decoherence and superconductivity, and shows that graphene provides a useful experimental platform to investigate unexplored regimes and phenomena in the superconducting proximity effect.