Why brain recordings look simpler than they might be

Researchers compared the dimensionality (effective complexity) of real neural population recordings to predictions from randomly connected networks with measurement constraints built in. Random networks matched observed dimensionality when realistic factors like finite recording time and behavioral context switches were included. The finding suggests current experiments can't yet distinguish truly simple circuits from tangled ones—but analyzing how neural patterns rotate between behaviors could do better.