1841 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 in *Xenopus* tadpoles, unilateral olfactory nerve injury triggers a rapid, dopamine-mediated compensatory mechanism that enhances contralateral synaptic output to maintain bilateral balance in the olfactory map, independent of inflammatory responses.
By integrating single-nucleus sequencing and high-resolution spatial transcriptomics of human lumbar spinal cord tissue, this study establishes a comprehensive molecular map defining 34 neuronal classes, revealing sex-specific glial differences, and characterizing the electrophysiological properties of dorsal horn neurons.
This paper presents a connectome-constrained Jansen-Rit framework that reliably infers local neural parameters and low-dimensional dynamical biomarkers from whole-brain activity, offering a biophysically grounded approach to understanding cortical gain control and ensemble stability relevant to disorders like schizophrenia.
This study demonstrates that ovarian steroids and sex chromosomes regulate astrocyte-mediated myelin clearance in the female brain, a mechanism that protects against traumatic brain injury-induced memory deficits.
This study demonstrates that artificial intelligence models can effectively distinguish preschoolers with language delays from those without by analyzing brief, naturalistic speech vocalizations, offering a scalable and promising tool for early language screening.
This study demonstrates that in individuals with ADHD traits, faster individual alpha frequency and flatter aperiodic neural spectra jointly drive a compressed sense of time characterized by narrower temporal binding windows and reduced reliance on perceptual priors, revealing distinct oscillatory and aperiodic pathways underlying atypical temporal processing.
By analyzing cycle-by-cycle alpha burst features in source-localized resting-state EEG, this study resolves the paradoxical alpha power findings in Fragile X syndrome by revealing distinct dysrhythmic patterns—such as prolonged periods and elevated amplitudes—that correlate with clinical symptoms and suggest underlying interneuron dysfunction.
Using 7T fMRI, this study reveals that speech production relies on feature-specific neural representations across cortical and cerebellar regions, where distinct areas encode articulatory versus phonatory timing, and a unique alignment between the operculum and cerebellum likely supports the refinement of speech motor plans.
Using 7T fMRI and a refined modeling approach to overcome limitations in stimulus coverage, this study maps the fine-grained functional architecture of human fingertip representations in primary somatosensory cortex, revealing a specific spatial organization and large population receptive field sizes consistent with primate data.
Using EEG and multivariate pattern analysis, this study reveals that learned attentional suppression of salient singleton distractors is driven by a rapid, top-down representational inversion of their neural signals approximately 200 ms after search onset, which transforms bottom-up saliency into suppression signals to facilitate goal-directed visual search.