Feature interference as a neuronal basis for the behavioural 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 behavioural 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. We generated a mechanistic hypothesis by comparing this neural network trained to produce correct choices with another network trained to replicate the participants’ choices. We hypothesized, and confirmed with further behavioural, physiological, and causal experiments, that the cost of task uncertainty and flexibility comes from what we term feature interference. Under uncertain conditions, interference between different tasks causes errors because it results in stronger representations of irrelevant features and entangled neuronal representations of different features. Our results suggest a tantalizing, general hypothesis: that cognitive capacity limitations, both in health and disease, stem from interference between neural representations of different stimuli, tasks, or memories.