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Exclusion of participants in tasks with a learning element can introduce substantial bias and needs to be carefully considered and transparently reported and justified.

Computational and theoretical analyses offer novel and unexpected insight into how complex, naturally occurring odor mixtures are parsed and normalized at the very first stage of olfaction.

Different features of an odor can be represented in mouse olfactory cortex using the particular ensemble of responsive neurons to represent odor identity and the synchrony of the ensemble activity to represent odor intensity.

Experimental determination of residue contacts from mutational data allows model discrimination and identification of in vivo functional conformations of proteins.

Neural sensory representations impose an inductive bias over the space of learning tasks, allowing some tasks to be learned by a downstream neuron more sample-efficiently than others.

Sensory representation in the primary olfactory area is rapidly modulated when mice switch between easy and difficult discrimination tasks, optimising the sensory representation for the task at hand.

Distinct lateral inhibitory circuits affect spiking in olfactory bulb mitral and tufted cells differently, which ultimately allows each cell type to best discriminate between similar odors in separate concentration ranges.

Human participants fail to discriminate between odor sequences that activate the same neurons at different orders, pointing against a substantial role for neuron activation time in the odor code.

Birds that see ultraviolet light tune the sensitivity of their short-wavelength photoreceptors with colored filters to maximize the number of colors they can see.

The processing of light and dark contrast information for detecting impending visual threats within grasshopper neurons reveals new mechanisms of information processing in the brain.