Deep learning and predictive coding architectures commonly assume that inference in
neural networks is hierarchical. However, largely neglected in deep learning and predictive …

Trial history biases and lapses are two of the most common suboptimalities observed during
perceptual decision-making. These suboptimalities are routinely assumed to arise from …

A key challenge in neuroscience is understanding how neurons in hundreds of
interconnected brain regions integrate sensory inputs with prior expectations to initiate …

Perception is known to cycle through periods of enhanced and reduced sensitivity to
external information. Here, we asked whether such slow fluctuations arise as a noise-related …

Perceptual decisions should depend on sensory evidence. However, such decisions are
also influenced by past choices and outcomes. These choice history biases may reflect …

Active reinforcement learning enables dynamic prediction and control, where one should not
only maximize rewards but also minimize costs such as of inference, decisions, actions, and …

Adaptive behavior requires integrating prior knowledge of action outcomes and sensory
evidence for making decisions while maintaining prior knowledge for future actions. As …

When a simple model-free strategy does not provide sufficient outcomes, an inference-
based strategy estimating a hidden task structure becomes essential for optimizing choices …

Many studies have suggested that the neocortex operates as a global network of functionally
interconnected neurons, indicating that any sensory input could shift activity distributions …

When observers have prior knowledge about the likely outcome of their perceptual
decisions, they exhibit robust behavioural biases in reaction time and choice accuracy …