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 paper presents a factorised spatiotemporal ensemble deep learning framework that achieves high-accuracy, non-invasive lobar-level localisation of the seizure onset zone from routine interictal and ictal scalp EEG, offering a fast and interpretable tool to expedite presurgical evaluation for drug-resistant focal epilepsy.
This study utilizes an integrative imaging-transcriptomic approach to demonstrate that GD3 synthase deficiency in mice leads to distinct, regionally specific brain structural and microstructural alterations detectable by multiparametric MRI, which correlate with normative gene expression patterns related to lipid metabolism, glial function, and energy homeostasis.
This study demonstrates that acute anterior thalamic deep brain stimulation for epilepsy produces reproducible scalp EEG signatures across multiple sessions, characterized primarily by enhanced gamma power and a shift in aperiodic spectral parameters.
This study employs a multiverse analysis of 5,184 analytic pipelines to demonstrate that while methodological choices affect the magnitude of gastric-brain coupling, the phenomenon remains robust and consistent across healthy participants at the group level, primarily manifesting in the alpha, theta, and beta frequency bands over medial and left-lateral electrodes.
This study demonstrates that inducing brief neuronal silent periods in awake mice via flickering light stimulation prevents endoplasmic reticulum stress responses and gene upregulation typically caused by sleep deprivation, while paradoxically increasing subsequent sleep pressure, thereby revealing that cortical network dynamics can dissociate molecular stress signatures from electrophysiological markers of sleep need.
This study of 85 older adults reveals that the weakened entorhinal hexadirectional signal associated with aging is driven by temporal instability in grid-like coding rather than the absence of representations, with this instability significantly predicting deficits in object-location memory.
This paper presents a scalable, modality-agnostic graph-based framework using supervised Random Forest classification on morphological and topological features to automatically distinguish penetrating arteries from veins in whole-mouse vasculature datasets, achieving high accuracy and enabling quantitative analysis for blood flow simulation and cerebrovascular research without the need for manual labeling.
This study demonstrates that while repetitive suprathreshold paired-pulse TMS targeting net excitation fails to induce offline changes, stimulation targeting long-interval intracortical inhibition (LICI) produces sustained reductions in corticospinal excitability lasting up to 40 minutes.
This fMRI study resolves the debate on a common magnitude system by demonstrating that while spatial, temporal, and numerical representations partially overlap in the right frontotemporoparietal cortex during target encoding, their functional coordination and neural distinctiveness dynamically reconfigure across cognitive phases, particularly during reproduction and metacognitive evaluation.
This study establishes a new epigenetic framework demonstrating that brain aging reshapes, rather than dismantles, cell-type-specific regulatory logic by revealing that the relationship between DNA methylation, hydroxymethylation, and gene expression depends on modification type, genomic context, sequence specificity, and gene length.