1313 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 demonstrates that while both deterministic and probabilistic tractography methods detect expected white matter degeneration in Alzheimer's disease, they yield substantially different bundle-specific results, highlighting the critical need for cross-method validation to ensure robust interpretation of tractometry findings.
This study demonstrates that the baseline activity of V1 fast-spiking interneurons, rather than pyramidal neurons, serves as the neural mechanism linking pupil-linked arousal to the inverted-U relationship with engaged behavioral states during perceptual decision-making in both mice and humans.
This study of a South African birth cohort reveals that perinatal HIV exposure in uninfected children is associated with persistent alterations in immune development and neurometabolites, which correlate with reduced language skills and disrupted neuroimmune pathways critical for school readiness.
This paper introduces "invertmeeg," a unified Python library and comprehensive benchmark that evaluates 106 EEG inverse solvers across diverse source configurations, revealing that while no single solver dominates all scenarios, flexible subspace and hybrid methods generally perform best overall.
This study introduces a unified hierarchical GAMLSS framework that outperforms existing ComBat-based methods in harmonizing large-scale, multi-cohort neuroimaging data by effectively removing technical batch effects while preserving complex biological signals and providing normative deviation scores across diverse, non-Gaussian distributions.
This paper presents the first complete, empirically derived three-dimensional metric field for color discrimination in RGB space, based on systematic measurements from eight observers that reveal a smooth, consistent, and anisotropic structure of perceptual color differences.
This study identifies Atto 643 carboxy as a highly specific far-red fluorescent probe that selectively labels astrocytes in both in vivo and acute brain slice preparations while minimizing the oligodendrocyte and neuronal cross-reactivity commonly observed with the widely used dye sulforhodamine 101 (SR101).
This study introduces a novel eye-tracking framework to reveal that statistical learning in noisy environments relies less on error-driven updates and more on conservative, repetition-based strategies that prioritize model stability.
This study demonstrates that in the predatory nematode *Pristionchus pacificus*, the conserved mechanosensory protein MEC-2 is essential for aversive touch responses but dispensable for prey detection due to its specific absence in the IL2 neurons that mediate the latter behavior, highlighting how the partitioning of sensory components enables functional specialization.
This paper presents a macaque retina simulator that generates biologically plausible spike trains for distinct retinal ganglion cell types based on realistic anatomical and physiological parameters, thereby providing essential input for developing and testing computational models of the primate visual cortex.