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Understanding Information Dynamics in Biological Systems: A Multi-Level Interaction Framework

This analysis explores the vast landscape of information within biological systems, highlighting the disparity between molecular information storage in the human body and the genome's capacity. It examines the roots of innate knowledge, the relationship between genes and behavior, and the impact of various interactions across levels—from molecular and cellular interactions to brain systems and environmental influences. Through the lens of chick imprinting, the study elucidates the dynamics of learning and attention systems, proposing a connectionist model to explain information processing through mechanisms such as inhibition, excitation, and hysteresis.

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Understanding Information Dynamics in Biological Systems: A Multi-Level Interaction Framework

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Presentation Transcript

  1. Interactions all the way down a Friedrich & Assadollahi

  2. Problem of Information Calow, 1976: • The human body contains about 5x1028 bits of information in its molecular arrangement, but the human genome only contains about 105 bits of information. => Where does the information come from?

  3. Problem of Information • How domain- and representation-specific is innate knowledge? • How direct is the link between gene and behaviour?

  4. Interactions • Molecular and and cellular interactions at the lowest level • Brain systems on the intermediate level • The whole individual and the environment on the highest level

  5. Brain systems interaction Chick imprinting: Imprinting is the process by which newly hatched birds become attached to the first conspicious object they see. • Predisposition to attend toward head and neck region of objects that possess configurations of features found in hens. • Learning system in the forehead (Intermediate and Medial Hyperstriatum Ventrale, IMHV) for imprinting.

  6. Brain systems interaction Three possible forms of interation: • None • Attention system activates learning • Attention system acts as a filter

  7. Connectionist Model o inhibition, > excitiation => hysteresis.

  8. Connectionist Model Uses hysteresis for movement independent representation5

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