Unsupervised classification of brain-wide axons reveals the presubiculum neuronal projection blueprint

• Published in: Nature communications Vol. 15; no. 1; pp. 1555 - 14
• Main Authors: Wheeler, Diek W., Banduri, Shaina, Sankararaman, Sruthi, Vinay, Samhita, Ascoli, Giorgio A.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 20.02.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/1386; 631/378/3920; Ammon's horn; Animals; Axon guidance; Axons; Axons - physiology; Brain; Classification; Cortex (motor); Divergence; Functional morphology; Hippocampus - physiology; Humanities and Social Sciences; Hypothalamus; Mesencephalon; Mice; multidisciplinary; Neurons; Neurons - physiology; Parahippocampal Gyrus; Presubiculum; Science; Science (multidisciplinary); Telencephalon; Thalamus
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-024-45741-x

We present a quantitative strategy to identify all projection neuron types from a given region with statistically different patterns of anatomical targeting. We first validate the technique with mouse primary motor cortex layer 6 data, yielding two clusters consistent with cortico-thalamic and intra-telencephalic neurons. We next analyze the presubiculum, a less-explored region, identifying five classes of projecting neurons with unique patterns of divergence, convergence, and specificity. We report several findings: individual classes target multiple subregions along defined functions; all hypothalamic regions are exclusively targeted by the same class also invading midbrain and agranular retrosplenial cortex; Cornu Ammonis receives input from a single class of presubicular axons also projecting to granular retrosplenial cortex; path distances from the presubiculum to the same targets differ significantly between classes, as do the path distances to distinct targets within most classes; the identified classes have highly non-uniform abundances; and presubicular somata are topographically segregated among classes. This study thus demonstrates that statistically distinct projections shed light on the functional organization of their circuit. The classification of different types of neurons has been a long-standing challenge in neuroscience. Here, the authors present a strategy to quantify all statistically distinct axonal patterns from a brain region based on their anatomical targeting, with this projection-driven neuron classification informing the functional architecture of the circuit.