The human brain uses a phase code to temporally segregate overlapping, competing memories along the phase cycle of the theta rhythm.

When exposed to sound sequences, humans compute biased transition probabilities between elements, extract the underlying network structure, and even generalize missing data.

The brain has a central cortico-striatal learning circuit that suppresses ongoing pain after injury when actively learning about things that could remove the cause of the pain.

Changes in neural response dynamics observed with visual learning provide a novel means to dissect synaptic plasticity and its interplay with slow negative feedback via firing rate adaptation.

Single unit recordings in monkeys and biophysical modelling demonstrate that local inhibitory-controlled metastable neural states specify the temporal organization of cognitive functions in frontal areas.

To accurately represent object position in real time, the human visual system predictively encodes the location of moving objects, compensating for the time required for transmission and processing of information.

Computational modeling demonstrates that population dynamics of neural calcium activity following stimulus offset are consistent with a network mechanism based on recurrent interactions.