Browse our latest Neuroscience articles

Artificial neural networks can faithfully recapitulate realistic neuronal behavior with dramatically accelerated simulation runtimes, empowering accessible large-scale realistic network simulations.

Retinal ganglion cell axons release the morphogen sonic hedgehog which signals through astrocytes to induce the migration of inhibitory interneurons into the developing visual thalamus.

Core associative learning phenomena that are observed in studies of eyeblink conditioning are also observed in sensorimotor adaptation, pointing to a common framework for these distinct cerebellar-dependent motor learning processes.

C. elegans nematodes can assess faithfully the threat that H₂O₂ poses by coupling the induction of their H₂O₂ defenses to the perception of high temperature—an inherent enhancer of the reactivity of H₂O₂.

An atypical configuration of mitochondrial electron transport chain proteins may underlie the exquisite sensitivity of the carotid body to small decreases in oxygen availability.

The digital 3D-atlas maker will help ascribing neuronal birthdate and neuronal differentiation times upon gene disruption in zebrafish avatars for human diseases, and will allow the integration of the information generated in other laboratories.

Inhibition of the zona incerta by central amygdala neurons expressing PKCδ contributes to injury-induced peripheral hypersensitivity in a mouse model of neuropathic pain.

Context factors such as experimental task and model parameterization can significantly impact modeling results, such that across tasks, the same participants show different fitted parameter values, and parameters capture different cognitive processes across tasks.

Late cataract-treated individuals learn to recalibrate vision for action in the months to years after sight restoration surgery, demonstrating that this ability can develop even in the absence of early pattern vision.

A theoretical model that uses maximally informative spectrotemporal features to classify vocalizations, trained solely on natural guinea pig vocalizations, predicts guinea pig behavioral performance in classifying natural as well as spectrotemporally manipulated vocalizations.