Feature interference underlies a neuronal basis for the behavioral cost of task uncertainty

Humans and animals have an impressive ability to juggle multiple tasks in a constantly changing environment. This flexibility, however, worsens performance under uncertain task conditions. Here we combined monkey electrophysiology, human psychophysics and artificial neural network modeling to investigate the neuronal mechanisms underlying this performance cost. We developed a behavioral paradigm to measure and influence participants' decision-making and perception in two distinct perceptual tasks. Our data reveal that both humans and monkeys, unlike an artificial neural network trained for the same tasks, make less accurate perceptual decisions when the task is uncertain. By comparing this neural network trained to produce correct choices with another network trained to replicate the participants' choices, we hypothesize that the cost of task uncertainty comes from feature interference. Through behavioral, physiological and causal experiments, we show that, under uncertain conditions, feature interference causes errors by inducing stronger representations of irrelevant features and entangled neuronal representations of different features. Our results suggest that cognitive capacity limitations may stem from interference between neural representations of different stimuli, tasks or memories.