1527 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 specific dominant mutations in α-tubulin can rescue tau-induced neurodegeneration in *C. elegans* by altering global microtubule properties rather than by reducing tau aggregation or phosphorylation, suggesting that targeting microtubule function offers a viable therapeutic strategy for tauopathies even in the presence of pathological tau.
This study demonstrates that human decision-makers employ flexible, adaptive rules to terminate evidence accumulation in response to varying task conditions, thereby optimizing the trade-off between speed and accuracy to maximize reward rates in a manner consistent with rationally bounded normative principles.
This study demonstrates that semantic novelty modulates fixation-related neural activity across frontal and visual cortical areas in both humans and non-human primates, providing evidence that the brain integrates semantic information across saccades via top-down predictive mechanisms.
By combining bilateral whisker-based texture-matching tasks with cortex-wide calcium imaging in mice, this study reveals that behavioral strategy (active versus passive) dictates the specific cortical location of interhemispheric information transfer, with active mice routing information through barrel cortices and passive mice utilizing the posterior lateral association cortex.
This study identifies that a reduction in cross-hemispheric connectivity and an increase in lateral asymmetry within the beta1 frequency band, observed one week after starting antidepressant treatment, serve as potential early neurophysiological indicators of treatment response in patients with major depressive disorder.
This study demonstrates that intravenous administration of a PHP.eB serotype adeno-associated virus (AAV) to deliver an amyloid-β antibody expression vector effectively reduces Aβ plaques, improves cognitive function, and reverses neuroinflammation and myelin deficits in Alzheimer's disease mouse models without causing brain microhemorrhage or liver damage.
This study presents a systematic, data-driven workflow to develop and validate a comprehensive, general-purpose biophysical model of hippocampal CA1 pyramidal neurons that accurately replicates diverse electrophysiological features and demonstrates the necessity of explicitly modeling dendritic spines for capturing nonlinear synaptic integration.
This paper presents an automated calcium imaging pipeline that successfully characterizes and quantifies compound-specific effects on astrocyte activity across mouse and human monocultures and astrocyte-neuron cocultures, demonstrating its utility for screening drug candidates and modeling disease pathology.
This study reveals that while 3-year-olds can detect audiovisual synchrony, the ability to efficiently segregate a target speaker in a multisensory "cocktail party" scenario undergoes a qualitative shift between ages 5 and 6, driven by the maturation of dynamic gaze control strategies that organize visual sampling in relation to auditory information.
This paper proposes and validates a multi-task battery approach for functional brain mapping that outperforms traditional single-contrast localizers by providing more consistent, reliable, and sensitive individual region localization and parcellation, supported by a data-driven task selection strategy and an open-source toolbox.