A Brain-Computer Interface (BCI) refers to a system that enables direct communication between an individual’s brain activity and a computer or mechanical device. One of the fundamental principles of BCIs is the ability to modulate neural activity through external stimuli in order to influence the user’s cognitive state. Among the various types of stimuli that can be considered, dynamic textures are particularly attractive due to their rich spatiotemporal properties and their ability to engage visual perception mechanisms.

In this work, we focus on the problem of designing and controlling dynamic textures used as visual stimuli in a BCI context. We first propose a stochastic dynamic texture model based on a parametric frequency-domain representation, capable of generating a wide variety of visual stimuli. We then formulate the BCI problem as a closed-loop control system in which the texture parameters are adjusted according to measurements of brain activity in order to steer the cognitive response toward a desired objective. Finally, we demonstrate the relevance of this approach through an application in attentional vision, where the generated textures serve as visual stimuli to modulate and analyze attention mechanisms.