1541 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 behavior-informed modeling framework that integrates continuous measurements of running speed and head motion into functional ultrasound imaging analysis, effectively disentangling motion-related confounds from neural signals to enable reliable brain-wide mapping during naturalistic, high-motion behaviors in awake mice.
This paper proposes a computational framework combining information-theoretic and network science principles to demonstrate that population-level neural phenomena like oscillations and avalanches are genuine emergent properties driven by network-level interactions, with distinct temporal characteristics supported by both in-vivo data and in-silico simulations.
This study identifies reduced cortical N100 amplitudes in contact sport athletes compared to non-contact athletes as an objective EEG biomarker of early auditory cortical dysfunction resulting from repetitive sub-concussive head impacts, linking these neural changes to real-world speech perception deficits.
This study reveals that satellite glial cells secrete Fibulin-2 to modulate Kv4-mediated potassium currents in sensory neurons, thereby reducing neuronal excitability and pain sensitivity, while its absence leads to heightened mechanical, heat, and cold hypersensitivity.
This study demonstrates that a ResNet+BiLSTM hybrid deep network, enhanced with SHAP and LIME explainable AI techniques, can accurately distinguish children with autism from neurotypical subjects using EEG and ERP biomarkers while providing transparent insights into the model's decision-making process.
This paper demonstrates that a local predictive, error-driven learning rule enables recurrent neural networks to naturally form orthogonal task manifolds, thereby preserving previously learned dynamics and solving the problem of catastrophic forgetting in continual skill learning.
By integrating neurostimulation, neuroimaging, and experience sampling across five studies, this paper resolves the paradox of angular gyrus activation patterns by demonstrating that its engagement is driven not by semantic concreteness per se, but by a continuum of memory-guided cognitive demands, including abstraction, information buffering, and automaticity.
This study utilizes multi-omic profiling of iPSC-derived neurons to demonstrate that the MAPT V337M mutation disrupts axonogenesis and unexpectedly reduces tau phosphorylation through p38 MAPK signaling, revealing early molecular mechanisms underlying tau-related neurodegeneration.
This study reveals that the MAPT S305I mutation causes a distinct, four-layer tau filament fold stabilized by the Ile substitution and associated with argyrophilic grain disease-like pathology, highlighting unique structural mechanisms that contribute to disease heterogeneity beyond known splicing defects.
This study demonstrates that while hippocampal reactivation of memory traces in sensory cortices does not guarantee conscious recall, the successful projection of these memories into awareness is predicted by rhythmic fluctuations in the alpha band and a concurrent decrease in total sensory alpha power.