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.
Using the AppNL-G-F rat model, this study reveals that while Alzheimer's disease impairs explicit spatial remapping in the hippocampus, preserved learning capacity is supported by the refinement of implicit temporal coding and enhanced neural reactivation during sharp wave ripples.
This study establishes a novel spectro-omic framework that demonstrates how distinct spectrolaminar rhythms across the macaque cortex are significantly predicted by underlying spatial transcriptomic programs, revealing that deep-layer glutamatergic architecture supports low-frequency processes while superficial inhibitory and metabolic signatures drive high-frequency activity.
This study demonstrates that the gut microbiota-derived metabolite queuosine, which modifies tRNAs, is essential for promoting neuronal arborization, reducing inhibitory synaptic density, and enhancing spontaneous calcium activity, thereby revealing its critical role in regulating neuronal development and network function.
This study proposes a unified computational framework that integrates cellular and synaptic constraints to demonstrate how deep brain stimulation effects on neuronal activity are determined by the intrinsic properties, architectural organization, and downstream circuit motifs of stimulated nuclei, thereby offering a mechanistic basis for optimizing clinical stimulation parameters.
This paper presents a preliminary in vivo study in rats demonstrating that a high dV/dt voltage-step method can detect and analyze high-frequency transient current components in deep brain tissue, revealing spectral differences between catecholaminergic regions and cortical tissue that support the technique's further development.
This study utilizes a The Virtual Brain-based computational model fitted to developmental fMRI data to demonstrate that cortical inhibitory upregulation, particularly within frontoparietal and default mode networks, is a key driver of distinct human neuromaturational trajectories.
This fMRI study demonstrates that distinct subregions of the angular gyrus and precuneus support different phases of perspective-guided autobiographical memory retrieval, with the precuneus facilitating preparatory perspective selection and the angular gyrus sustaining perspective maintenance during reconstruction, thereby shaping specific subjective memory qualities like vividness and emotional intensity.
This study demonstrates that perceptual filling-in is modulated by the functional properties of early visual cortex, specifically the oblique effect and orientation-tuned surround suppression, thereby supporting a two-stage model where the competition between figure boundary and background representations determines the onset and duration of the phenomenon.
This study demonstrates that a single session of motor cortical stimulation induces long-lasting analgesia in chronic pain by triggering NMDA- and mu-opioid receptor-dependent neural plasticity in the rostral ventromedial medulla, a mechanism that can be enhanced by transiently boosting endogenous opioid signaling.
This study demonstrates that Temporal Mapper, a topological data analysis tool, effectively captures the complex, fine-grained postural dynamics of interacting domestic ferrets, revealing that social interactions are characterized by smaller, more widespread, and consistently sequenced unstable states compared to non-social activities.