Bridging Conflicting Views on Eye Position Signals: A Neurocomputational Approach to Perisaccadic Perception

Saccades are an integral component of visual perception, yet the accuracy and role of eye position signals in the brain remain unclear. The classical model of perisaccadic perception posits that the dorsal visual system combines an imperfect eye position signal with visual input, leading to systematic perisaccadic mislocalizations under specific experimental conditions. However, neurophysiological studies of eye position information have produced seemingly conflicting results. One team of researchers observed the eye position signal directly in gain-field neurons in the lateral intraparietal area (LIP) and found them incompatible with the classical model. In contrast, another team reported evidence for an eye position signal consistent with the classical model, even showing that accurate eye position can be decoded from neural activity. We modeled two subpopulations of neurons in LIP receiving input from two different sources, one representing the corollary discharge containing predictive presaccadic signals, the other representing a slowly updating proprioceptive eye position signal. By decoding eye position from the neural activity of these subpopulations, we observed the model containing sufficient information to allow the decoder to accurately predict and track the perisaccadic eye position. Our findings reconcile the apparent contradiction between the different neurophysiological studies by providing a unified framework for understanding eye position signals in perisaccadic perception. Our results suggest that a combination of a late-updating proprioceptive signal and a predictive corollary discharge is sufficient for accurately decoding eye position.