Speaker
Description
Rodent vision has traditionally been considered simple and dominated by low-level feature extraction. This view has been recently challenged by evidence of a hierarchical visual system in rats, functionally analogous to the primate ventral stream, in which higher-order areas show reduced sensitivity to low-level attributes (e.g., luminance) and increased invariance to geometric transformations (e.g., translations, rotations). However, these findings were derived almost entirely from simplified parametric stimuli, leaving open whether the same organization holds under naturalistic stimulation.
We addressed this gap by performing extracellular recordings along the rat “ventral stream” during fast stimulation with 992 natural images spanning 62 ImageNet categories. For each reliably responsive unit, we computed neural predictivity layer-by-layer using convolutional neural networks (CNNs) under distinct training regimes (untrained, supervised, L2-robustified), applying the same pipeline to public macaque and mouse datasets for cross-species comparison.
As expected, macaque hierarchy was recapitulated by network depth, while no such correspondence emerged in the mouse. The rat occupied an intermediate position: network predictivity across depth aligned with cortical hierarchy, but the progression was less sharply delineated than in the macaque, while remaining distinguishable from the flat mouse profile. Information imbalance analysis corroborated this conclusion, showing the signature of a functional processing hierarchy resembling the one of macaques and CNNs, more than mouse visual areas did. However, decoding category information revealed that this hierarchical organization coexists with a persistent encoding of luminance across the rat hierarchy, decreasing but not disappearing with depth.
Together, these results indicate that hierarchical visual processing in the rat extends to naturalistic images, yielding a graded, intermediate organization in which low-level statistics remain partially entangled with higher-order representations, unlike the degree of feature abstraction seen in primate inferotemporal cortex.
| Preferred Presentation | No specific preference |
|---|