Naturalistic driving imposes rapidly changing visuomotor demands that modulate cognitive state. Whereas much driving research maps eye metrics to experimenter-defined categories, we pursue bottom-up recovery of ecologically emergent eye–cognition coupling. We examined whether pupil-centered eye dynamics and vehicle control measures are jointly organized into a structure consistent with on-road workload constructs. Eleven licensed drivers completed urban drives in an instrumented car while wearing a glasses-based eye tracker. We decomposed joint eye–vehicle time series with independent component analysis (ICA), yielding an interpretable workload component on which luminance-corrected pupil size and speed/steering instability both loaded, consistent with prior findings. In contrast, a higher saccade-to-fixation ratio also loaded on this component, diverging from the centrally anchored gaze typically observed under secondary-task load. Beyond establishing feasibility, these results provide a basis for unsupervised discovery of previously unrecognized patterns in joint eye–behavior coupling, with direct implications for driver monitoring and safety systems.

The computational modelling of the primary auditory cortex (A1) has been less fruitful than that of the primary visual cortex (V1) due to the less organized properties of A1. Greater disorder has recently been demonstrated for the tonotopy of A1 that has traditionally been considered to be as ordered as the retinotopy of V1. This disorder appears to be incongruous, given the uniformity of the neocortex; however, we hypothesized that both A1 and V1 would adopt an efficient coding strategy and that the disorder in A1 reflects natural sound statistics. To provide a computational model of the tonotopic disorder in A1, we used a model that was originally proposed for the smooth V1 map. In contrast to natural images, natural sounds exhibit distant correlations, which were learned and reflected in the disordered map. The auditory model predicted harmonic relationships among neighbouring A1 cells; furthermore, the same mechanism used to model V1 complex cells reproduced nonlinear responses similar to the pitch selectivity. These results contribute to the understanding of the sensory cortices of different modalities in a novel and integrated manner.