Decoding of temporal intervals and predictive errors in neural signals. |
Interactions between expectations and sensory information are an important part of percptual processing. There are known evidences of how such interactions are reflected on neural correlates and how they modulate human senses like vision and audition. Evidences alike for time perception are scarse. Some models of perceptual processing propose that the difference between prediction about sensory stimulation and stimulation actually received, the predictive error, is a key element in neural processing. Some works have identified dynamic representations of the predictive error in neural patterns of sensorial processing. Studies investigating the presence of a similar mechaninsm for timing are lacking. This project proposes the use of experiments with EEG acquisition and methods of multivariate pattern analysis to investigate: (1) if time intervals are represented in neural signal patterns, (2)