Multiparametric Classification of Pure-tone Responses Distinguishes Neurons in Inferior Colliculus Subdivisions

recordings. Here, we tested whether recordings can be assigned to CNIC or CtxIC using only response properties in awake and anesthetized mice. We constructed frequency response areas (FRAs) from pure tone responses and extracted tuning and firing metrics. Individual FRA features could not reliably localize recordings. In contrast, a random forest classifier combining FRA-derived features accurately localized recordings to CNIC or CtxIC across states. These findings demonstrate that while IC subdivisions differ only subtly along individual response parameters, appropriate multiparametric approaches can enable robust classification. More broadly, our results illustrate how biologically meaningful distinctions may be revealed by combining weakly informative features, an approach that can be applied across diverse brain regions and modalities.