The interplay of recurrent excitation and short-term plasticity enables nonlinear transient amplification, an ideal mechanism for selective amplification, pattern completion, and pattern separation in recurrent neural networks.

Temporal continuity-induced plasticity in individual neurons of inferior temporal cortex builds neural representations that underlie robust core object recognition behavior.

Chronic excitation of the Caenorhabditis elegans oxygen-sensing neurons alters calcium homeostasis to accelerate the decline of neural plasticity with age.

A biologically plausible model of myelin plasticity demonstrates how oligodendrocytes can selectively adjust conduction delays in axon bundles to allow robust communication between brain regions through long-range synchronization.

Analysis and modelling of sensorimotor neural activity shows how ongoing plasticity and appropriately tuned weights can cope with substantial ongoing changes in the neural code.

Inhibitory synaptic plasticity provides a flexible and biologically plausible circuit mechanism to detect the novelty of bottom-up stimuli and to generate stimulus-specific adaptation.

Gradient-descent synaptic plasticity applied to neuroscience categorization tasks captures the behaviour of common neural activity measures (category and context selectivity, correlation, asymmetry) reported in experiments, and makes novel experimental predictions.

Multi-modal imaging, genetic and behavioral findings in humans and mice revealed that metabotropic glutamate receptors of subtype 5 contribute to the molecular machinery keeping track of sleep need and coping with physiological and behavioral consequences of sleep loss, pointing to novel targets for improved wakefulness and sleep.

A recurrent network using a simple, biologically plausible learning rule can learn the successor representation, suggesting that long-horizon predictions are computations that are easily accessible in neural circuits.

Hippocampal learning in dentate gyrus follows a U-shaped function, with moderate, but not high or low, overlap between representations leading to differentiation of neural patterns.