Constraints on Information Processing
Constraints on Information Processing
In this lesson, you will learn about how constraints can help us understand how the brain works.
Topics covered in this lesson
- Examples of modelling.
- What makes a good model - should ask a question, be simple (find the right abstractions), should be possible to falsify.
- Shannon's information and entropy.
- Reverse engineering.
- Examples of amplification, low pass filtering in biological circuits.
- Biological limits and constraints on processing - energy density, noise.
- Analogue signal quality and information rate.
- Shannon's information rate.
- Biological "cost per bit" vs signal rate. Information cost vs cell size.
- Reversible computation.
- Efficiency of chemical computation vs electrical computation.
- Benefits of electrical computation: many-to-one integration, speed.
- Phylogenetic constraints.
Prerequisites
Familiarity with concepts of entropy, free energy
Back to the course