Event segmentation in temporal data streams is a key challenge in cognitive
architectures, with applications in robotics, video analytics, natural language
processing, and many other areas. This work presents an innovative event seg-
mentation model inspired by neuroscience and psychology, two branches of
cognitive science. The model emulates the temporal segmentation processes of the
human brain during visual perception. The model integrates perceptual processes
with hierarchical attention mechanisms to detect transitions between events in
