Browse our latest Neuroscience articles

The large range of timescales empirically observed in neural circuits can be naturally explained when neural assemblies of heterogeneous size are recurrently coupled, empowering the neural circuits to efficiently process complex time-varying input signals.

Unipolar brush cells subtypes, classified by their excitatory or inhibitory response to glutamate, form circuits with one another that may enhance the capacity of the cerebellum to transform input signals.

Potassium presumably binds to the Na1 site in LeuT, playing a role in inwardly rectifying the transport of substrates.

Mouse superior colliculus is involved in figure detection based on differences in contrast and texture orientation and phase.

Improved cell-type-specific genetic drivers for the study of learning and memory and other complex behaviors in Drosophila are provided and validated.

Large-scale modeling of the mouse brain revealed that working memory is modular and determined by long-range cell type-specific connections, thereby providing a framework to interpret brain-wide recordings during cognition.

Spatially-resolved transcriptomics and single-nucleus RNA-sequencing are applied to the human locus coeruleus to characterize the gene expression profiles of norepinephrine (NE) neurons and other cell populations in this critical brain region, with all data made publicly available.

While minimizing the report-related motor confounding, event-related potential (ERP), high-frequency power, and functional connectivity of the local field potential (LFP) activity in human prefrontal cortex were enhanced under the emergence of visual awareness.

Mice learn a categorization task faster when exposed to task-relevant stimuli outside training, supporting neural-network models in which unsupervised learning first captures the statistical structure of inputs before classifying them.