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    Constraints on Information Processing

    Difficulty level

    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.

    Familiarity with concepts of entropy, free energy