1795 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 baseline mu-opioid receptor availability predicts individual differences in neural activation during emotion regulation, with higher receptor levels associated with stronger initial responses to emotional stimuli and effective modulation of these responses through cognitive reappraisal.
The BRIAN framework demonstrates that incorporating diffusion-derived orientation priors into streamline modelling significantly improves the geometric reproduction of the MRI-visible glioblastoma core compared to isotropic spread, although using advanced multi-shell SHORE reconstruction did not yield further benefits over standard single-tensor models in this specific validation context.
This study reveals that the evolutionary expansion of glutamate/GABA co-release in the lateral habenula enables diverse temporal difference-like computations, thereby supporting sophisticated reinforcement learning and intelligent decision-making across vertebrates.
This study of 87 children reveals that while the Visual Word Form Area (VWFA) is smaller in individuals with dyslexia, its precise anatomical location relative to brain structure and white matter tracts does not differ from typical readers nor correlate with reading ability.
This study demonstrates that internally generated mental imagery in the human parietal cortex adheres to a cognitive topography where the spatial location of neural activity relative to primary sensory regions and intrinsic connectivity profiles dictates whether the imagery is modality-specific or multisensory.
This study demonstrates that SETD1A deficiency causes region-specific brain dysfunction linked to schizophrenia and identifies the LSD1 inhibitor TAK-418 as a therapeutic agent capable of rescuing associated synaptic and behavioral phenotypes by restoring H3K4me3 levels.
This study demonstrates that biallelic NRXN1 deletion disrupts human neural induction by rewiring the H3K27me3 landscape and altering chromatin accessibility, leading to spliceosome dysregulation and epigenetic priming toward non-neural, mesenchymal fates rather than canonical neural lineages.
This study demonstrates that short-term synaptic depression within a hierarchical, multiregional recurrent neural network can simultaneously explain the generation of mismatch negativity and P300-like responses, as well as their amplification by attention, by linking synaptic-scale mechanisms to brain-wide representations of salient stimuli.
Using supervised learning on Human Connectome Project data, this study demonstrates that functional connectivity patterns can accurately distinguish between left and right brain hemispheres, although these patterns cannot reliably predict an individual's handedness.
This paper introduces a nonlinear error-in-variables regression framework that quantifies the fidelity of internal neural representations by modeling neural activity as a function of latent variables that deviate from measured sensory and behavioral data, successfully recovering hidden dynamics and condition-dependent representational changes in both synthetic and real neural recordings.