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 identifies and characterizes a distinct dopaminergic A13 nucleus within the human zona incerta using histology and MRI, establishing its anatomical boundaries and unique molecular and connectivity profile to provide a foundation for future translational research.
This study demonstrates that individual differences in 3D mental rotation ability are positively associated with 2D rotation performance and are specifically linked to enhanced recruitment of neural visual-spatial cortical representations, as evidenced by stronger Rotation-Related Negativity (RRN) responses in high-performing individuals.
This study demonstrates that distinct yet spatially intermixed neural populations in the left human temporal lobe encode speech representations shaped by past, future, and surrounding context, revealing that beyond-word context is crucial for integrating abstract linguistic information.
This paper demonstrates through computational modeling and two independent studies that mood disturbances bias confidence in reward-based decision-making not by directly altering self-belief, but by distorting the gradual accumulation of reward learning signals, a mechanism that is amplified in individuals with elevated hypomanic traits.
This study introduces a low-dimensional generative neural engine based on a Deep Markov Model that successfully bridges neural activity and behavior, providing mechanistic evidence to reject the Independent Race Model in favor of an interactive dynamical framework where shared neural manifold geometry dictates reaction time distributions.
This study validates human post-mortem brain organotypic slice cultures as a viable platform for investigating myelin damage in multiple sclerosis, demonstrating that these slices maintain structural integrity for up to 13 days and can be used to induce focal demyelination and subtle destabilization through targeted drug delivery.
This paper introduces MASCAF, a free, open-source, and topologically robust pipeline that uses mean-curvature flow skeletonization to fit cable models to complex 3D neuronal surface meshes, successfully addressing the previously unsupported challenge of reconstructing looped structures like toric spines for high-resolution neural simulations.
This study identifies a somatotopically organized spinal circuit, where ascending dI3 neurons map the trunk's two-dimensional space onto specific motor pools to control reflexive skin twitches that help mammals remove irritants.
This paper introduces a wiring-agnostic deep-learning framework that successfully decodes interpretable, geometrically separable neural codes for metabolic state, sensory modality, and stimulus valence from whole-brain Drosophila calcium imaging data without requiring anatomical annotation or connectivity information.
This study reveals that specific growth trajectories of hippocampal subregions, particularly the right hippocampal head, and total sleep duration during early childhood are significant predictors of episodic memory performance in early school age.