This 2016 US/Italy article was written from the perspective of regenerative bioengineering:
“Higher levels beyond the molecular can have their own unique dynamics that offer better (e.g. more parsimonious and potent) explanatory power than models made at lower levels. Biological systems may be best amenable to models that include information structures (organ shape, size, topological arrangements and complex anatomical metrics) not defined at the molecular or cellular level but nevertheless serving as the most causally potent ‘knobs’ regulating the large-scale outcomes.
Top-down models can be as quantitative as the familiar bottom-up systems biology examples, but they are formulated in terms of building blocks that cannot be defined at the level of gene expression and treat those elements as bona fide causal agents (which can be manipulated by interventions and optimization techniques). The near-impossibility of determining which low-level components must be tweaked in order to achieve a specific system-level outcome is a problem that plagues most complex systems.
The current paradigm in biology of exclusively tracking physical measurable and ignoring internal representation and information structures in patterning contexts quite resemble the ultimately unsuccessful behaviourist programme in psychology and neuroscience. For example, even if stem cell biologists knew how to make any desired cell type from an undifferentiated progenitor, the task of assembling them into a limb would be quite intractable.
The current state of the art in the field of developmental bioelectricity is that it is known, at the cellular level, how resting potentials are transduced into downstream gene cascades, as well as which transcriptional and epigenetic targets are sensitive to change in developmental bioelectrical signals. What is largely missing however is a quantitative understanding of how the global dynamics of bioelectric circuits make decisions that orchestrate large numbers of individual cells, spread out over considerable anatomical distances, towards specific pattern outcomes.”
Regenerative research is gathering evidence for goal-directed memory and learning that doesn’t meet current definitions. For example:
“A tail grafted to the flank of a salamander slowly remodels to a limb, a structure more appropriate for its new location, illustrating shape homeostasis towards a normal amphibian body plan. Even the tail tip cells (in red) slowly become fingers, showing that the remodelling is not driven by only local information.”
The reviewers compared their findings to several existing research and real-world-operations domains. Other models may also benefit from the concepts of:
“Quantitative, predictive, mechanistic understanding of goal-directed morphogenesis.”
I came across this article as a result of its citation in The Body Electric blog post.
“Levin drops a hint that there are photo-sensitive drugs that can control ion gates that can be used to translate a projected geometric image into a pattern of membrane potentials. He argues that the patterns encode ‘blueprints’ rather than a ‘construction manual’ based on the fact that the program is adaptive in the face of physical barriers and disruptions.”
https://royalsocietypublishing.org/doi/full/10.1098/rsif.2016.0555 “Top-down models in biology: explanation and control of complex living systems above the molecular level”