Competition between neurons for postsynaptic ephrin-B3 controls distribution of a limited pool of synapses and defines a novel trans-synaptic mechanism enabling neurons to set the number of synapses they receive.
The BB model explains spatial cognition in terms of interactions between specific neuronal populations, providing a common computational framework for the human neuropsychological and in vivo animal electrophysiological literatures.
Structural and functional analysis of axonal-axonal reciprocal connections between dopamine neurons and Kenyon cells provides insight into the brain computations for normal associative olfactory learning.
Expression of Drosophila bitter receptors in taste neurons produced increased, decreased, or novel responses, supporting a model in which the response profile is determined by activation, inhibition, or competition among receptors.
Building on recent findings that central sensory processing allocates resources according to the informativeness of statistical features (Hermundstad et al., 2014), we identify visual area V2 as the site of the relevant computations for local image statistics, thus providing a common underpinning for diverse aspects of its neuronal selectivity.
Computational simulations and mathematical derivations reveal why the response of neural populations to external modulation is sometimes reversed with respect to what intuition would lead to believe in cortical circuits with multiple types of inhibitory neurons.
Computational modeling predicts that sleep replay plays a protective role against catastrophic forgetting by revealing synaptic mechanisms allowing overlapping populations of neurons to store multiple interfering memories.