The membrane nonlinearities of the dendritic arbor of striatal cholinergic interneurons conspire with the spatial distribution of its excitatory inputs to preferentially boost thalamic inputs.

Dendrites combine the inputs that they receive from other neurons using calculations that have been optimized for those particular input patterns.

In feedforward networks with random connectivity, connection motifs underlying the detection of short clusters and activity sequences are likely to converge on a subset of postsynaptic neurons purely by chance.

NMDA receptors mediate prominent supralinear summation of clustered excitatory inputs to the dendrites of neurogliaform and oriens-lacunosum moleculare interneurons of the hippocampus, showing that these cells perform sub-cellular computations.

Accurate direction-selective information is present within small sections of the dendrites, raising the possibility that single dendrites utilize parallel processing schemes to process motion information.

In motor cortex pyramidal neurons, diverse task-related signals are distributed throughout the dendritic arbor and compartmentalized by dendritic distance and branching.

The formation and refinement of prediction error circuits relies on an experience-dependent balance of excitation and inhibition in canonical microcircuits.

The frontal associative cortex promotes fear learning by non-linearly integrating Gaussian noise in between conditioning trials with the help of basolateral amygdala inputs.

Retinal physiology and anatomy and visual behavior reveal how sensory circuits in the retina can shape an organism’s eye movements over a range of ethologically relevant stimulus conditions.