1825 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 paper introduces a publicly available MATLAB module for EEG bad-channel detection that combines multi-feature thresholding with co-occurrence-based clustering to identify and group artifactual channels through an interpretable, human-in-the-loop review process, serving as a quality-control step prior to ICA.
This study validates a novel TECPR2 knock-in mouse model that recapitulates key disease phenotypes and demonstrates that neonatal AAV9-mediated gene therapy effectively restores sensory-motor function and mitigates neuropathology, offering a promising therapeutic strategy for the currently untreatable TECPR2-related disorder.
This study demonstrates that aesthetic preferences exhibit robust cross-domain consistency across art, faces, and scenes, suggesting they are driven by a domain-general latent structure mediated by shared neurophysiological pathways rather than stimulus-specific factors.
This paper introduces "GlycoShuttles," a modular platform utilizing mucin-binding proteins to traverse the blood-brain barrier via the cerebrovascular glycocalyx, thereby enabling efficient delivery of diverse therapeutics to the brain and demonstrating efficacy in mouse models of dementia.
This study demonstrates that in a Wolfram syndrome mouse model, progressive synaptic alterations in the retina's inner plexiform layer, driven by early presynaptic failure, occur prior to overt axonal degeneration and represent the earliest detectable cause of vision loss.
This study demonstrates that auditory-motor learning operates across multiple timescales, where rapid, context-sensitive adjustments to auditory predictions occur implicitly during exploration, while slower, persistent modifications to motor inferences require sustained, goal-directed training.
This study demonstrates that vestibular function loss in patients with vestibular schwannomas is significantly associated with the degeneration of sensory hair cells (specifically type I) and damage to calyx endings within the vestibular sensory epithelium, suggesting that the tumor's deleterious impact on the epithelium mediates functional decline.
Using a computational model of the *C. elegans* nervous system, this study reveals that while electrical synapses shape functional communities that segregate locomotion circuits, other behaviors emerge from the synchronized activity of distributed functional communities, demonstrating how structural connectivity underpins the dynamic relationship between neural function and behavior.
This study demonstrates that during multi-finger force production, fast random walk processes and slow drifts interact within and orthogonal to the solution space to balance performance exploration and stability, with visual feedback playing a more critical role than explicit task formulation in structuring this stability.
The paper introduces SynThIA, an open-source, Python-based tool with a user-friendly interface that enables high-throughput, accurate quantification of multi-partite synapses using up to four markers, thereby addressing a critical gap in the systematic analysis of complex synaptic structures.