Phenotypes to remember: Evolutionary developmental memory capacity and robustness

Area of Science:

• Evolutionary developmental biology
• Computational neuroscience
• Systems biology

Background:

• Growing recognition of evolutionary learning's role in development.
• Analogous formalisms in genetic regulatory networks (GRNs) and neural networks (NNs).
• Potential for cross-disciplinary knowledge transfer between GRNs and NNs.

Purpose of the Study:

• Investigate the formation and persistence of developmental memories from past phenotypes.
• Analyze how memory capacity scales with network size.
• Determine if memory storage follows Hebbian-like rules.
• Assess the robustness of these developmental memories against network perturbations.

Main Methods:

• Modeling genetic regulatory and neural networks using analogous formalisms.
• Simulating the formation and persistence of developmental memories.
• Analyzing memory scaling with network size.
• Testing memory robustness against perturbations (graceful degradation).

Main Results:

• Developmental memories, termed "devo-engrams," can form and persist in these networks.
• Memory capacity shows scaling relationships with network size.
• Evidence suggests Hebbian-like rules may underlie memory storage.
• Devo-engrams exhibit graceful degradation, indicating robustness.

Conclusions:

• The analogy between NNs and GRNs is functionally significant, enabling knowledge transfer.
• Developmental memories offer a potential mechanism for evolutionary learning.
• These findings may help explain rapid evolutionary changes like phenotypic radiations.