During learning, the brain modifies synapses to improve behaviour. In the cortex, synapses
are embedded within multilayered networks, making it difficult to determine the effect of an …

Synaptic plasticity, the activity-dependent change in neuronal connection strength, has long
been considered an important component of learning and memory. Computational and …

The anatomy of the mammalian visual system, from the retina to the neocortex, is organized
hierarchically. However, direct observation of cellular-level functional interactions across this …

Understanding spoken language requires transforming ambiguous acoustic streams into a
hierarchy of representations, from phonemes to meaning. It has been suggested that the …

For many years, the dominant theoretical framework guiding research into the neural origins
of perceptual experience has been provided by hierarchical feedforward models, in which …

In predictive coding, experience generates predictions that attenuate the feeding forward of
predicted stimuli while passing forward unpredicted “errors.” Different models have …

Primates have evolved diverse cognitive capabilities to navigate their complex social world.
To understand how the brain implements critical social cognitive abilities, we describe …

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

Research on predictive processing models has focused largely on two specific algorithmic
theories: Predictive Coding for perception and Active Inference for decision-making. While …

Brain function relies on the coordination of activity across multiple, recurrently connected
brain areas. For instance, sensory information encoded in early sensory areas is relayed to …