Predicting oculomotor behaviour from correlated populations of posterior parietal neurons

Oculomotor function critically depends on how signals representing saccade direction and eye position are combined across neurons in the lateral intraparietal (LIP) area of the posterior parietal cortex. Here we show that populations of parietal neurons exhibit correlated variability, and that using these interneuronal correlations yields oculomotor predictions that are more accurate and also less uncertain. The structure of LIP population responses is therefore essential for reliable read-out of oculomotor behaviour. Cortical brain signals are often studied by predicting sensory inputs and behaviours from ensembles of neurons, but the uncertainty of these predictions is poorly understood. Graf and Andersen show that the level of uncertainty is reduced when populations of cortical neurons exhibit correlated variability.