Structured spontaneous activity through delta oscillation-based discrete states in the medaka telencephalon

Spontaneous neural activity shapes brain states, which are associated with various behaviors, yet its organization in the teleost telencephalon is poorly understood. We characterized intrinsic neural activity dynamics in medaka (Oryzias latipes) by recording 32-site local field potentials in the lateral (Dl) and medial (Dm) dorsal telencephalon under anesthesia. We segmented delta-band (1-4 Hz) signals into 3-s episodes and computed pairwise correlation matrices for each episode. We embedded them via principal component analysis and identified brain states from the correlation patterns using k-means. State occupancy was biased rather than uniform, and temporal dynamics were structured; the episode-to-episode distances were shorter than those for shuffled surrogates, and the transitions preferentially recurred within the same state. These results indicate that, even under reduced sensory drive, the medaka telencephalon self-organizes into stable and preferred network configurations with structured propagation, echoing conserved principles of spontaneous activity across vertebrates. Our framework advances understanding of intrinsic brain function in teleosts and provides a platform for future studies in conscious animals.