1287 papers
Neuroscience explores the intricate machinery of the brain and nervous system, seeking to understand how we think, feel, and move. From the microscopic dance of individual neurons to the complex networks that shape our memories and behaviors, this field peels back the layers of our biological selves to reveal the origins of consciousness and disease.
At Gist.Science, we bring these discoveries directly from bioRxiv, the leading preprint server for biological sciences, to a broader audience. We process every new neuroscience preprint as it is uploaded, transforming dense academic manuscripts into clear, plain-language explanations alongside detailed technical summaries. This ensures that both curious readers and specialists can stay current with the latest breakthroughs before they are formally published.
Below are the latest neuroscience papers we have processed from bioRxiv, offering fresh insights into the workings of the mind.
This study identifies a genetically defined parabrachial Ntsr1 neuron population projecting to the ventromedial hypothalamus that, when activated, suppresses food intake and promotes anxiety-like behaviors, thereby mediating the inhibition of feeding during threatening situations.
This study identifies reproducible human reward imaging phenotypes (sign-tracking and goal-tracking) that exhibit differential sensitivity to dopamine D2/D3 receptor modulation, providing a neuroimaging basis for stratifying patients and predicting responses to dopaminergic agents.
This study characterizes the post-embryonic neurodevelopment of *C. elegans*, revealing that its brain connectome maintains a weakly connected, hierarchical structure with a conserved core backbone and rich club organization that progressively strengthens through asymmetric synapse addition and centralization of input hubs.
This study demonstrates that restoring CD73 expression specifically in mouse blood-brain barrier endothelial cells protects against ischemic stroke by converting pro-inflammatory ATP into anti-inflammatory adenosine, thereby reducing infarct volume and mortality while promoting an inflammation-resolving immune response.
By modeling large-scale brain-state dynamics against a cognitively normal aging reference, this study demonstrates that Alzheimer's disease and mild cognitive impairment exhibit progressively greater deviations in transition entropy, supporting a single absolute-deviation score as a compact and interpretable biomarker for distinguishing pathological neurodegeneration from healthy aging.
This study identifies the ESCRT-0 protein Hrs as a dynamic, bidirectional regulator of synaptic strength that senses neuronal activity to modulate AMPA receptor currents and Ca2+-dependent signaling, thereby influencing synaptic plasticity and preventing neurodegenerative protein accumulation.
This study demonstrates that exposing fixed pigeon brains to gadolinium-based contrast agents during the rehydration phase alone is sufficient to achieve stable relaxation parameters and reliable diffusion-weighted imaging, offering a simplified and reproducible protocol for ex vivo avian neuroimaging.
Using the complete *Drosophila* adult brain connectome, this study reveals that mixed-polarity synapses are widespread and highly structured, with their distribution predictable by neuronal complexity and playing a critical role in shaping non-canonical and reciprocal circuit motifs.
This study presents an automated framework that combines deep-learning-based segmentation of digital holographic microscopy images with graph-theoretical analysis to quantitatively characterize the organization and maturation of neuronal networks, achieving high accuracy in classifying developmental stages through label-free imaging.
SpikeCleaner is a semi-automated algorithm that standardizes the labeling of unit quality (Good, Multi-Unit Activity, or Noise) following automated spike sorting by integrating physiological and timing metrics, achieving 97% agreement with expert curators to enable scalable, high-quality curation of large-scale neuronal datasets.