Linking detailed cellular biophysics to macroscopic neural behavior

Determine how detailed biophysical processes at the neuronal level combine to generate complex macroscopic behaviors in neural systems, including in relatively simple organisms, thereby clarifying how cellular-level dynamics give rise to emergent network- and organism-level function.

Background

The paper contrasts detailed biophysical neuron models with coarse-grained population and network-level models, emphasizing that while the former capture cellular processes, they involve many parameters that are difficult to measure and often display degeneracy, complicating bottom-up inference.

This modeling gap motivates a core unresolved question: how do the rich, heterogeneous cellular mechanisms—ion channels, dendritic and axonal properties, and synaptic dynamics—aggregate to yield the complex behaviors observed at larger scales, even in comparatively simple nervous systems? Bridging this micro-to-macro link is central for understanding neural function and informing principled coarse-graining.

References

Though detailed biophysical models are useful for studying cellular processes, it remains unclear how these detailed processes combine to generate the range of complex macroscopic behaviors observed, even in relatively simple organisms.

— Towards principles of brain network organization and function  (2408.02640 - Kulkarni et al., 2024) in Section 3: Modelling small groups of neurons

Whether rodents would display a capability for this level of higher order cognition is debatable, but it is implausible that simpler neural systems such as insects or in vitro neural cultures could display these traits.

— If the brain were so simple: Information-based drivers of intelligence and their interaction through an n-body-inspired framework  (2610.11142 - Kagan et al., 8 Oct 2026) in Section 1, subsection “Questions about FEP, information enthalpy, and neural criticality”

It is unclear how such mechanisms could unfold from classical neural-field models, \citep[e.g.,][]{amariDynamicsPatternFormation1977, wilsonExcitatoryInhibitoryInteractions1972}, or from the ubiquitous integrate-and-fire models \citep[e.g.,][]{Lapicque1907}.

— Excitability across scales: a unifying EI model  (2610.13275 - Burger et al., 9 Oct 2026) in Conclusion