Combinatorial quantification of distinct neural projections from retrograde tracing

Abstract

Comprehensive quantification of neuronal architectures underlying anatomical brain connectivity remains challenging. We introduce a method to identify distinct axonal projection patterns from a source to a set of target regions and the count of neurons with each pattern. A source region projecting to n targets could have 2ⁿ-1 theoretically possible projection types, although only a subset of these types typically exists. By injecting uniquely labeled retrograde tracers in k target regions (k < n), one can experimentally count the cells expressing different color combinations in the source region. The neuronal counts for different color combinations from n-choose-k experiments provide constraints for a model that is robustly solvable using evolutionary algorithms. Here, we demonstrate this method’s reliability for 4 targets using simulated triple injection experiments. Furthermore, we illustrate the experimental application of this framework by quantifying the projections of male mouse primary motor cortex to the primary and secondary somatosensory and motor cortices.

Comprehensive quantification of neural architectures underlying brain circuitry remains challenging. Here, the authors present a practical method to quantitatively identify nerve cells with specific axonal projections from retrograde anatomical injections.