Quantify required neurobiological factors for accurate brain models

Determine the extent to which each enumerated neurobiological factor—glial cells, neuromodulatory peptides and hormones, ion concentrations, pH, synaptic connectivity, neuronal cell types, synaptic activity, gap junctions, neuronal and synaptic plasticity, diffusion of signaling molecules, protein conformations, local membrane composition, and parallel recording of external stimuli and behaviors—must be represented to achieve accurate computational models of brain function and behavior.

Background

The report highlights a wide range of biological mechanisms that may influence neural computation, spanning extracellular milieu, cellular and synaptic properties, and molecular-scale processes. Despite extensive progress in measurement and modeling, the authors emphasize that the minimum necessary level of detail for these factors remains unresolved.

Clarifying the contribution of each factor is essential to guide both data acquisition priorities and model design, ensuring that emulations are neither over- nor under-parameterized relative to what is required for accuracy.

References

We do not yet know how much each of these factors will be required for accurate models of the brain.

— State of Brain Emulation Report 2025  (2510.15745 - Zanichelli et al., 17 Oct 2025) in Introduction

Second, further investigation is needed into the behavioural dynamics of artificial neurotransmitters beyond the formulations proposed in this work. This includes a number of fundamental research questions: how many distinct neurotransmitter signals are sufficient; how multiple neurotransmitters interact or co-modulate learning dynamics; and under what conditions such signals should be activated or suppressed during training.

— Position Paper: Neurotransmitters as a Missing Dimension in Artificial Neural Networks  (2609.20083 - Li et al., 17 Sep 2026) in Section “Open Challenges and direction”

While an unknown (n) number of drivers could play a role here and across multiple biophysical systems, below we illustrate the concept by discussing the 3 concepts emphasized in this paper so far: effects across information enthalpy maximization, free-energy minimization and a drive to remain in a critical regime while processing information.

— 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 5, subsection “The interaction of systems across timescales supports adopting n-body-inspired system modeling”