The brain's balancing act: Adjusting its neural noise to optimise performance

Neural noise is an unavoidable byproduct of brain function. Rather than noise being merely an unavoidable limitation, accumulating evidence suggests it may serve a functional role in maintaining optimal neural processing. Some theoretical accounts suggest that the brain may modulate its noise level to achieve this; however, experimental and computational evidence that illustrates this dynamic nature of neural noise is limited. Here, we investigated whether the brain aims to optimise its neural noise levels in response to task demands using a visual letter identification task with varying stimulus contrast. Computational modelling predicted conditions where counterintuitive increases in neural noise should lead to optimal performance. We tested this prediction experimentally, estimating neural noise using an N-pass paradigm. Results revealed that lower stimulus contrasts (i.e., more difficult perceptual conditions) were associated with higher neural noise, suggesting that the brain adapts and modulates its internal variability depending on sensory demands to enhance performance. Overall, our results support the notion that the brain's neural noise is contextually flexible and may serve an adaptive role, which reflects the brain's ability to adapt to changing perceptual demands.