Scaffolding layered control architectures through constraint closure: insights into brain evolution and development.

Area of Science:

• Systems Neuroscience
• Evolutionary Biology
• Developmental Neuroscience

Background:

• Mammalian brain organization is a layered control architecture.
• Evolutionary emergence and developmental construction of this system remain unclear.
• Constraint closure is a general characteristic of living systems, involving subsystems constraining each other at different timescales.

Purpose of the Study:

• To develop a new formalism for constraint closure applicable to multi-layered systems.
• To analyze brain organization using this formalism, focusing on physiological regulation and visual orienting.
• To explore how layered brain architectures scaffold themselves across multiple timescales.

Main Methods:

• Developed a new mathematical formalism for constraint closure.
• Generalized a previous model of within-lifetime and between-lifetime dynamics.
• Applied the formalism to analyze physiological regulation and visual orienting in the brain.

Main Results:

• Demonstrated how constraint closure can be generalized to multi-layered systems.
• Showcased the capacity of layered brain architectures to self-scaffold across timescales.
• Highlighted how cortical and sub-cortical processes mutually constrain each other's organization and evolution.

Conclusions:

• Constraint closure provides a unifying framework for understanding brain organization, development, and evolution.
• Layered brain architectures exhibit self-organizing properties across diverse timescales.
• The interplay between different brain levels is crucial for functional organization and adaptation.