Scientists Discover Why Your Brain Has Fast and Slow Zones
This brain rule could lead to faster, more energy-efficient computers and AI.
Neurobiological circuits may be energy efficient in part because different subsystems do different jobs, and a major difference between subsystems is the time scale on which they vary. The authors argue that temporal smoothness constraints imply a division of labor: slow subsystems ought to represent slowly varying stimulus features, and fast subsystems ought to represent quickly varying features.
They formulate a novel efficient coding model to investigate this claim and exactly solve for the optimal division of labor. They find that slower subsystems ought to represent more slowly varying temporal features, and they also find surprising mathematical structure: optimal codes have subsystems that represent orthogonal temporal features and correspond to the eigenfunctions of a Sturm-Liouville problem.
- The brain saves energy by having slow regions handle slow information and fast regions handle fast information.
- A new mathematical model shows this division is optimal when energy is limited.
- This could inspire energy-efficient computers and AI, reducing costs and environmental impact.
Why It Matters
This could lead to electronics that use less power, saving you money and helping the planet.