1296 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 reveals that the transmembrane protein Flower orchestrates astrocyte fitness in neurodegeneration through a bifurcated mechanism where its N-terminal domain drives extracellular vesicle-mediated elimination of less-fit neighbors, while its C-terminal "win" isoform ensures cell-intrinsic survival and neuroprotection under stress.
This study demonstrates that early cerebral small vessel disease is characterized by distinct disruptions in neurovisceral integration and emotional processing across neural, physiological, and behavioral levels, independent of traditional cardiovascular risk factors and cognitive decline.
This study demonstrates that movement and decision vigor are governed by separate, independent time-cost signals rather than a single global utility, with their apparent coordination arising only when both processes are influenced by a shared temporal history.
This preregistered fMRI study reveals that while striatal sensitivity to shared rewards typically predicts brain responses to reciprocated trust, this relationship is significantly altered by depressive symptoms and social closeness, with depression reversing the expected neural patterns in close relationships.
This study demonstrates that across multiple Drosophila species, olfactory behaviors are driven by a selective preference for the most statistically distinctive and ecologically informative volatile components within complex natural host odour blends.
By analyzing longitudinal multimodal data, this study reveals that while individual stroke patients' functional connectome fingerprints stabilize within three weeks, they undergo prolonged system-specific reorganization that ultimately drives recovery, with these early functional signatures serving as predictive biomarkers for long-term cognitive impairment.
This study presents openly available, high-resolution voxelwise normative models of brain morphometry derived from over 58,000 scans to capture individual heterogeneity across the lifespan, demonstrating their utility in identifying replicable, personalized brain alterations in both preterm birth and rare genetic neurodegenerative disorders.
By analyzing longitudinal histopathology data in a mouse model of Parkinson's disease, this study reveals that -synuclein propagation follows rise-and-fall trajectories rather than simple accumulation, identifying a low-dimensional vulnerability axis where regions with stronger decline dynamics possess higher monoaminergic composition and proteostatic gene expression.
This study demonstrates that N3 and REM sleep enhance the translation of neural responses (specifically the late positive potential) into accurate emotional memory, while revealing that PTSD is associated with diminished neural differentiation between negative and neutral stimuli and that women exhibit poorer memory for negative stimuli compared to men.
This paper presents a fully automated, cloud-scalable, and open-source pipeline that utilizes machine learning and rule-based algorithms to standardize, correct structural anomalies, and accurately relabel dendritic trees in large-scale 3D neural reconstructions, thereby enhancing the accuracy, efficiency, and reproducibility of neuroanatomical data quality control.