Oliver Schmitt, Peter Eipert, Rafael Tappe Maestro, Marie Bellmann, Stefanie Haase, Paulina Morawska, Vishnu Prathapan
Understanding how nervous systems are wired requires methods that provide direct evidence of anatomical connectivity. For more than half a century, tract-tracing approaches based on axonal transport have served as the primary experimental standard for mapping neuronal pathways across central, peripheral, autonomic, and enteric nervous systems. Despite their central role in circuit neuroscience and connectomics, tract-tracing methods differ widely in transport mechanisms, uptake pathways, visualization strategies, and synaptic specificity, leading to variability in the type and strength of connectivity evidence they provide. Here we present a comprehensive, historically informed synthesis of tract-tracing methodologies grounded in the manual curation of more than 8200 research articles spanning multiple methodological generations. Rather than organizing techniques by tracer nomenclature or chemical identity, we classify tracing approaches according to biologically stable properties, including directionality of transport, cellular uptake mechanisms, transsynaptic capability, and detection modalities. This framework clarifies which anatomical inference-monosynaptic projections, collateral branching, or polysynaptic pathways-can be supported by different experimental designs and survival conditions. We further discuss how tracer-specific biases, collateralization, and detection sensitivity shape the reliability of connectivity claims and how these factors propagate into large-scale connectomic reconstructions. To address limitations of conventional region-to-region connectivity representations, we introduce complementary connectional entities capturing collateral and pathway structure, enabling integration of heterogeneous tracing evidence. By linking methodological properties to evidential scope, this review provides a principled basis for interpreting historical and contemporary tract-tracing data, supports transparent evidence grading in connectome construction, and clarifies how anatomical tracing can be integrated with network-level analyses of brain organization.